Spin-driven enantioselective regulation of cyclooxygenase-2 activity for rheumatoid arthritis therapy via chiral gold nanohelices

Domain: physics
Published: 2026-04-10
Editorial outcome: major_revision

Abstract
Electron-spin dynamics represent an additional dimension in enzymatic catalysis, where most regulatory strategies focus on modulating active-site chemistry. Here, we present a spintronic approach that employs chiral gold nanohelices (Lh- Au) as electron spin polarizers to enantiospecifically modulate cyclooxygenase-2 (COX-2) activity for rheumatoid arthritis intervention. Exploiting the chirality-induced spin selectivity (CISS) effect inherent to both COX-2 and Au, we demonstrate that left-handed Au (Lh- Au) enhances, whereas right-handed Au (Rh- Au) suppresses COX-2 catalytic efficiency via spin-dependent electron transfer at the chiral nanoparticle-enzyme interfaces. To achieve targeted modulation in complex biological settings, we engineer molecularly imprinted Au ( Au@MIP) for selectively regulating COX-2 in inflammatory cells and collagen-induced arthritis murine model (male DBA/1J mice). Treatment with Rh- Au@MIP significantly reduces prostaglandin E secretion and mitigates joint inflammation, achieving therapeutic efficacy comparable to conventional COX-2 inhibitors. Our findings introduce electron spin polarization as an orthogonal mechanism for enzymatic regulation, offering a bioelectronic strategy for inflammation-targeted therapy.

Introduction
Regulating enzyme activity is a central mechanism for controlling diverse biological processes and has underpinned numerous therapeutic strategies1–4. Current approaches primarily target substrate access to enzyme active sites via small-molecule screening, which have yielded many successes but remain laborious, time-consuming and often enzyme-specific5–8. These limitations motivate to search for orthogonal regulatory strategies that transcend traditional chemical modulation. Electron transfer, a critical step in many enzymatic reactions, and its rate strongly influences catalytic efficiency9–12. Enhancing electron transport rate has been widely reported to improve the catalytic efficiency13–15. Spin-polarized electrons, with spins aligned parallelly, exhibit reduced scattering and longer coherence lifetimes, enabling more efficient transport with higher activity15–18. Therefore, manipulation of electron spin polarization may offer a non-classical and potentially generalizable strategy for modulating enzyme activity.

Chiral materials provide an alternative paradigm in generating highly spin-polarized electrons because of chirality-induced spin selectivity (CISS)19–25 (Fig. 1a). When electrons propagate across two adjacent chiral systems with matching CISS profiles, spin orientation is preserved, leading to efficient transport. In contrast, a mismatch in CISS necessitates spin-flipping, which consumes additional energy and disrupt electron flow (Fig. 1b). Given the intrinsic chirality of enzymes, modulating electron spin polarization at the nano-bio interface may enable to regulate enzymatic activity in a chirality-dependent manner26–30. Indeed, injecting spin-polarized photons to enzymes using circularly polarized light (CPL) has been shown to enantioselectively change phosphoglycerate kinase activity31. Therefore, it suggests that chiral nanomaterials could serve as programmable spin polarizers to modulate the spin-polarized state of electrons for enzyme activity regulation.

Here, we explore this concept using cyclooxygenase-2 (COX-2), a chiral heme-peroxidase that catalyzes the oxidation of arachidonic acid (AA) to prostaglandin E (PGE ), a key mediator of inflammation and validated therapeutic target in rheumatic arthritis (RA)32–34. We synthesized chiral gold nanohelices ( Au) — left-handed (Lh- Au) and right-handed (Rh- Au) — to enantioselectively modulate COX-2 activity via spin-selective electron transport: Lh- Au enhanced the COX-2 activity owing to the identical CISS to COX-2, while Rh- Au inhibited it because of the opposite CISS to COX-2. This stereospecific effect is attributed to the spin-selective compatibility between COX-2 and Au enantiomers. To enable targeted enzyme modulation in complex biological settings, we further engineered molecular imprinted Au ( Au@MIP), which selectively binds COX-2 and enriches chiral interface interactions. In activated macrophages and collagen-induced arthritis (CIA) mouse model, Rh- Au@MIP treatment significantly reduces PGE production and alleviates inflammation, showing efficacy comparable to conventional COX-2 inhibitors (Fig. 1c). Our work establishes electron-spin polarization as an additional dimension of enzymatic regulation, offering a spintronic biointerface platform for precision modulation of inflammatory enzymes. It also broadens the conceptual toolkit for bioelectronic therapeutics and sheds light on spin–chirality coupling in biological catalysis.

Results
Activity of COX-2 regulated by spin-polarized electrons
Spin-polarized electrons exhibit enhanced catalytic efficiency owing to reduced scattering and prolonged active lifetime15,17,18,35,36. To examine whether COX-2 activity can be modulated by electron spin, we measured cyclic voltammetry (CV) of arachidonic acid (AA) oxidation on a custom electrochemical setup (Fig. 2a). A ferromagnetic Ni plate, coated first with Au nanoparticles to improve conductivity and enzyme loading, served as the working electrode. Applying an external magnetic field (MF) through the Ni substrate spin-polarizes the injected electrons, with polarity (north vs. south) determining the electron-spin orientation16,37,38. In the absence of MF (w/o MF), the CV curve exhibited an asymmetric profile with a cationic oxidation peak current at ~1.28 V (E ) with a corrected peak current (I ) of 2.03 ± 0.08 μA but without any obvious corresponding anionic reduction peak, indicating the irreversibility of the oxidation of AA (Fig. 2b-2c). Under MF with the north pole of magnet facing to the working electrode (MF-N), I decreased to 1.07 ± 0.27 μA, whereas under the south pole orientation (MF-S), I increased to 2.52 ± 0.22 μA (Fig. 2b-2d). These opposite shifts confirm that COX-2 catalytic activity is sensitive to the spin polarization of the incoming electrons. To determine whether the observed MF dependent effects on AA oxidation arise from COX-2-mediated spin-selective electron transport, rather than a direct influence of spin-polarized electrons on AA itself, we performed control CV measurements on Ni electrodes coated with gold nanoparticles but without COX-2 modification (Fig. S1a). The CV curve in w/o MF showed an I of 1.85 ± 0.12 μA, and both values of I under MF-N and MF-S decreased, but did not show the bidirectional modulation observed in the COX-2-coated system (Fig. S1b-S1d), which is probably because the Lorentz force under MF increases the transmission dissipation of electrons and inhibits the oxidation of AA39. Therefore, the introduction of COX-2 as a catalyst for AA oxidation altered the electric response to MF, with inhibition under MF-N and promotion under MF-S, a typical feature of CISS effect of chiral molecules, as evidenced by the circular dichroism (CD) spectra of COX-2 (Fig. 2e). To further validate intrinsic spin selectivity, we modeled electron transport through COX-2 as an α-helical protein and computed spin-resolved conductances using a tight-binding Hamiltonian40. (Fig. 2f). The calculated spin-up conductance (G ) and spin-down one (G ) diverge substantially across the whole energy spectrum, yielding highly large spin polarization (Fig. 2g-2h). This behavior arises from the chiral structure induced spin-orbit coupling, and holds for different α-helical protein of various sequences (Fig. S2), indicating that electrons of one specific spin orientation will preferentially transmit through COX-2. Taken together, these results confirm that the COX-2 catalytic activity in AA oxidation is enantioselectively modulated by the spin state of injected electrons (Fig. 2i-2j). The AA oxidation by COX-2 has been studied to occur via two active domains: cyclooxygenase (COX) site embedded in short α-helical segments containing Tyr385 and Trp387, and the heme-containing peroxidase (POX) site, via an intramolecular electron transfer process41, 42. The catalytic cycle starts at the POX site, where heme Fe3+ is oxidized by peroxide (ROOH) to form radical Intermediate I (Fe4+=O Por•+), which extracts one electron from Tyr 385 via Trp387, producing Tyr385• that abstracts a hydrogen atom from AA to form AA•. AA• then reacts with O to yield Prostaglandin G (PGG ). PGG , as a peroxide, donates an electron back to regenerate POX heme Fe3+, being reduced to Prostaglandin H (PGH ), which is subsequently isomerized to PGE (Fig. 2i and 2j). Since the α-helical segments bridge the internal electron transport between the COX and POX sites, providing the possible structural basis for spin polarized electrons to modulate COX-2 catalytic efficiency via CISS effect.

CISS effect of Au to generate spin-polarized electrons
To explore the potential of Au as spin polarizers, we synthesized Lh- Au, Rh- Au, and racemic (RAC- Au) nanohelices by helical overgrowth on Au nanorods using L-, D-, and RAC-cysteine as chiral inducing agents43–47. Transmission electron microscope (TEM) images showed that Lh-, Rh- and RAC- Au with comparable dimensions in length (L), transverse width (W) and helical pitch (P) (Lh- Au: L = 93.6 ± 12.2 nm, W = 32.7 ± 2.5 nm, P = 21.3 ± 2.2 nm; Rh- Au: L = 96.9 ± 11.2 nm, W = 30.8 ± 3.1 nm, P =22.7 ± 3.7 nm; RAC- Au: L = 87.9 ± 13.3 nm, W = 28.4 ± 2.4 nm, P = 24.5 ± 2.5 nm) (Fig. 3a-3c). And all three Au variants shared similar zeta potentials of +20~+22 mV (Fig. S3) and a localized surface plasmon resonance (LSPR) maximum absorption at 760 nm (Fig. 3d). However, their chiroptical responses revealed pronounced differences. CD spectra revealed mirror-image signals for Lh- Au and Rh- Au, with characteristic Cotton effects at 530 nm and 729 nm, while RAC- Au exhibited negligible CD signals (Fig. 3e). The corresponding anisotropy g-factors of Lh- Au and Rh- Au were identical in magnitude but opposite in sign, with a maximum value of |0.005|, suggesting strong and enantiomer-specific interaction with circularly polarized light (Fig. 3f).
According to the CISS mechanism, chiral structures can preferentially transmit electrons of a specific spin orientation, functioning as spin filters. To test this, we deposited each Lh- Au, Rh- Au or RAC- Au onto a ferromagnetic Ni plate to form working electrodes and recorded CV profiles of the robust redox couple of Fe(CN) 4- to Fe(CN) 3- under MF (Fig. 3g). In this configuration, electrons are injected from the Ni surface toward Au, the transport efficiency of spin-polarized electrons from Ni electrode to Au will strongly depend on the CISS effect of Au. Under w/o MF, all Au variants exhibited similar CV profiles (Fig. S4). However, when with MF, clear chirality-dependent shifts appeared in the CV curves of Lh- Au and Rh- Au, and these shifts changed to opposite directions with MF reverted (Fig. 3h and 3i). In contrast, RAC- Au showed no significant changes with or without MF (Fig. 3j), resembling the behavior of achiral Au nanospheres (Fig. S5). It indicates that spin-polarized electrons induced by MF-S can selectively traverse Lh- Au (spin matched), while those induced by MF-N cannot traverse Lh- Au (spin mismatched). For Rh- Au, the situation is opposite (Fig. 3k). These bidirectional CV shifts unambiguously demonstrate that Lh- Au and Rh- Au generate spin-polarized electrons with opposite spin orientations.
To substantiate these findings, we developed a theoretical model simulating electron transport through Au-like helical geometry, which was constructed by etching a helical groove from achiral gold cylinders and the cross sections at different positions of the remaining Au resemble major sectors of different notch orientations (Fig. S6 and 3l-3n). The calculated spin-resolved conductance results showed that, for Lh- Au and Rh- Au, G with spin-up electrons injected was different from G with spin-down electrons are injected, and G with spin-unpolarized electrons injected fell between them (Fig. 3o and 3p). While for RAC- Au, no observable difference existed between G and G (Fig. 3q). These numerical results demonstrate that both Lh- Au and Rh- Au exhibit strong but opposite spin selectivity, where the spin polarization was reversed between Lh- Au and Rh- Au (Fig. 3r). Further current (I) calculation also revealed the similar behaviors of I , I and I of Au (Fig. 3s-3u), as demonstrated in their G , G and G . Moreover, the spin selectivity of Lh- Au and Rh- Au is robust against variations in helical pitch, radius, and structural defects (Fig. S7-S12), revealing pronounced spin polarization of both systems in the presence of geometric or surface irregularities, ionic screening, or surface functionalization with different substances. These theoretical results align well with the experimental data shown in Fig. 3h-3j, confirming that both Lh- Au and Rh- Au function as effective spin polarizers, generating spin-polarized electrons with opposite orientations depending on chirality.

Enantioselective modulation of COX-2 by Au
Building on our demonstration that COX-2 activity is sensitive to electron spin and that Au can generate spin-polarized electrons, we tested whether Au enantiomers could directly modulate COX-2 catalysis. We first employed a resorufin-based fluorescence assay, in which signal intensity scales linearly with COX-2 activity. Incubation of COX-2 with Lh- Au increased activity modestly to 105.2 ± 5.0% relative to enzyme alone (set to 100%), whereas Rh- Au and RAC- Au reduced activity to 52.0 ± 2.5% and 62.3 ± 3.0%, respectively (Fig. 4a and 4b). These results demonstrate clear enantioselective modulation of COX-2 activity by Au. To corroborate the fluorescence findings, we immobilized COX-2 directly on each Au variants, forming Lh- Au@COX-2, Rh- Au@COX-2 and RAC- Au@COX-2 respectively, and measured the CV profiles of AA oxidation on a Pt electrode (Fig. S13). Consistent with the fluorescence data: Lh- Au@COX-2 increased I from 2.07 ± 0.1 μA (COX-2 alone) to 2.38 ± 0.13 μA, whereas Rh- Au@COX-2 and RAC- Au@COX-2 reduced I to 1.42 ± 0.06 μA and 1.61 ± 0.07 μA, respectively (Fig. 4c-4d and S14). Furthermore, we experimentally and theoretically studied the modulation of COX-2 activity with varied enantiomeric excess (ee) of Au. The results revealed an approximately linear correlation between the relative modulation of Au on COX-2 and ee (Fig. S15), demonstrating that the Au can regulate COX-2 activity in an enantioselective and quantitatively predictable manner. And the theoretical results consistently showed good linear relationship between current and ee values (Fig. S16). Together, these complementary assays confirm that Au exert enantioselectivity in modulation of COX-2 activity that Lh- Au enhances, while Rh- Au and RAC- Au suppress enzyme catalysis.

Mechanistic dissection: Cooperative CISS-driven electron transport underlines the enantioselective modulation of Au to COX-2 activity
Chiral nanomaterials can influence enzyme activity through three possible mechanisms: (i) nanozymatic property28,48-50, (ii) active site change27,51,52, or (iii) electron transfer29,31. To pinpoint which mechanism drives the enantioselective regulation of Au to COX-2 activity, we performed the following studies: first, we studied the possible mechanism (i), the nanozymatic property of Au. For the electrochemical studies without COX-2, CV curves of AA oxidation obtained with electrodes coated with Lh-, Rh- or RAC- Au all showed enhanced I , which was independent on the Au chirality albeit of different enhancement times (Fig. S17), indicating that all Au variants exhibit weak COX-2-like enzymatic properties. Since this enhancement did not depend on the chirality of Au, we exclude intrinsic nanozymatic activity (mechanism i) as responsible for enantioselective regulation of COX-2 activity.
Regarding mechanism (ii), in which Au enantiomers may enantioselectively interact with the active sites of COX-2, or mechanism (iii), in which Au enantioselectively change the electron transport process, we investigated the influence of MF on Au@COX-2 catalyzed oxidation of AA by measuring CV curves, as only the electron transport process instead of the interaction with the active site of COX-2 will be changed by MF. Therefore, a nonmagnetic Pt plate instead of magnetic Ni plate was cast by Lh- Au@COX-2, Rh- Au@COX-2 and RAC- Au@COX-2 to form the working electrodes with MF applied (Fig. 4e and S18). Using non-magnetic electrodes ensures that any MF-dependent response arises from CISS-induced spin polarization within the Au@COX-2 system, rather than from spin-polarized injection by the electrode. Since MF can perturb spin transport through the Peierls phase to alter electron spin evolution and transport efficiency53-54, it allows us to selectively probe CISS-mediated electron transport while excluding active-site effects. The CV curves showed that for all these Au@COX-2, the application of MF-N suppressed the AA oxidation, while MF-S promoted it to a certain degree (Fig. S19 and 4f-4i). As RAC- Au lacks the CISS effect, the influence of MF on RAC- Au@COX-2 likely originates from the CISS effect of COX-2. While RAC- Au@COX-2 showed inhibited COX-2 activity, it may relate to the passivation of active sites due to the adsorption of Au (Fig. 4d, 4h-4i), although such adsorption caused negligible changes in the secondary structure of COX-2 (Fig. S20-S21). Therefore, it turns out that mechanism (ii) is excluded from the enantioselective regulation of COX-2 activity, while mechanism (iii) is implicated.
To further elucidate the underlying mechanism, we simulated the electron transport by injecting unpolarized electrons from a nonmagnetic electrode into Au@COX-2 constructs and the conductance was calculated for electrons ejected from all the terminals of these COX-2. (Fig. 4j). Spin-resolved conductance calculations revealed that for all these Au@COX-2, G > G across a broad energy range, and the conductance without MF G fell between G and G (Fig. S22). Further calculations on the current-voltage characteristics of all these Au@COX-2 were plotted in Fig. 4k-4m, showing that I was the largest, followed by I and I (Fig. 4n), demonstrating the electron transport efficiency varied with MF directions for various Au@COX-2. All above results further confirm the critical role of the mechanism (iii) in enantioselective regulation of COX-2 activity.
Taken together, Au influences COX-2 activity through three additive contributions: (i) the nanozymatic enhancement of Au, which is weak and achiral (Fig. S17); (ii) active-site passivation by surface adsorption of Au, yielding chirality-independent inhibition (Fig. 4h); (iii) cooperative CISS filtering at the Au-COX-2 interface, which contributes to the enantioselective regulation of COX-2 activity (Fig. 4i and 4n). Notably, although nanozymatic activity (mechanism i) and active-site passivation (mechanism ii) clearly contributes to overall activity modulation, it does not account for the chirality-dependent differences between Lh- Au and Rh- Au. Remarkably, spin-polarized electron transfer via CISS can modulate the passive inhibition by Au adsorption. Thus, the relative contributions of the three mechanisms were quantified for each Au sample via a simple sum model and are presented in the radar plot (Fig. 4o). This visualization highlights how CISS selectively modulates COX-2 activity beyond the additive effects of catalytic activity and active-site passivation, providing a quantitative framework for the enantioselective regulation.

Cellular inflammation regulation
Inhibiting the expression and activity of COX-2 has been proven effective in alleviating inflammation34,52. Given that Au can enantioselectively modulate COX-2 activity via spin-polarized electron transfer, to assess the biomedical potential of our spintronic platform, Au was utilized to regulate COX-2 activity on inflammatory cells with lipopolysaccharide (LPS)-activated Raw 264.7 macrophages (Fig. 5a). To improve the specific recognition of COX-2 and minimize the non-specific interaction with various biomolecules, Au was molecularly imprinted against COX-2 through dopamine-based molecule imprinting process, forming Au@MIP (Lh- Au@MIP, Rh- Au@MIP and RAC- Au@MIP), with TEM images shown in Fig. 5b-5d, hydrodynamic sizes at the range of 111.0~118.9 nm (Fig. S23), and zeta potentials of -10.1 ~ -13.5 mV (Fig. S24). Both experiments and theoretical simulations demonstrate that Au coated with the MIP ( Au@MIP), maintains high spin selectivity comparable to that of the pristine Au without the MIP (Fig. S25-S26). All these Au@MIP exhibited minimal cytotoxicity against LPS-stimulated RAW 264.7 cells as assessed by CCK assay (Fig. S27). Cy5.5-labeled Lh- Au@MIP, Rh- Au@MIP and RAC- Au@MIP (Lh- Au@MIPCy5.5, Rh- Au@MIPCy5.5 and RAC- Au@MIPCy5.5) were efficiently internalized by inflammatory cells without significant difference, as confirmed by confocal fluorescence microscopy and flow cytometry (Fig. 5e-5f and S28). Subsequently, the expression and activity of COX-2 were assessed by western blot (Fig. 5g and 5h) and PGE enzyme-linked immunosorbent assay (ELISA), respectively (Fig. 5i). LPS stimulation significantly increased the expression of COX-2 (Fig. 5g), confirming the presence of inflammation in inflammatory cells. Treatment with Lh- Au@MIP increased the expression of COX-2 to 118.3%, whereas treatments with Rh- Au@MIP and RAC- Au@MIP reduced the expression to 18.4 and 41.7%, respectively. Celecoxib, a known COX-2 inhibitor, reduced the expression of COX-2 to 7.1%, in terms of COX-2 activity (Fig. 5h). Consistently, following LPS stimulation, the secretion of PGE increased to 334.0 ± 20.4 pg mL-1, compared to 50.10 ± 1.9 pg mL-1 without LPS stimulation (Fig. 5i). Further treatment with Lh- Au@MIP slightly increased PGE level to 345.7 ± 39.6 pg mL-1, while treatments with Rh- Au@MIP and RAC- Au@MIP decreased the levels to 98.0 ± 1.8 and 163.9 ± 12.3 pg mL-1, respectively. As a positive control, treatment with celecoxib decreased PGE level to 126.4 ± 13.7 pg mL-1. Notably, Rh- Au@MIP showed a lower PGE level than celecoxib, while the statistical analysis resulted in a P value>0.05 possibly due to the limited sample size. Additionally, the expression of CD86, a surface mark indicative of inflammatory responses, was evaluated by flow cytometry. LPS stimulation could increase the CD86-expressed cells to 65.2% compared to 12.3% without LPS stimulation (Fig. 5j). This percentage increased to 79.9% by further treatment with Lh- Au@MIP but decreased to 47.8 and 60.0% following treatments with Rh- Au@MIP and RAC- Au@MIP, respectively. Furthermore, the typical inflammatory cytokines (TNF-α and IL-1β) were assessed by ELISA (Fig. S29 and S30). Treatment with Lh- Au@MIP notably increased the levels of both cytokines, while treatments with Rh- Au@MIP and RAC- Au@MIP reduced these levels, similar to the effect of celecoxib. These findings collectively demonstrate that Au@MIP can enantioselectively regulate the inflammation of macrophages.
To uncover how Au@MIP variants reprogram macrophage inflammation at the molecular level, we performed integrated proteomic and untargeted metabolomic profiling of LPS-stimulated cells treated with Lh-, Rh-, or RAC- Au@MIP or celecoxib. Hierarchical clustering analysis of AA metabolism-associated proteins and metabolites was conducted to identify distinct regulatory patterns across the treatment groups. The hierarchical clustering heatmap of AA metabolism-associated proteins revealed that LPS induced robust upregulation of PTGS2 (COX-2), PTGES, PLA2G6, PTGES2, and PLA2G4A, indicating activation of the pro-inflammatory cascade (Fig. 5k). Both celecoxib and Rh- Au@MIP markedly suppressed these pro-inflammatory proteins, whereas Lh- Au@MIP mirrored the LPS response and RAC- Au@MIP produced an intermediate profile with PTGS2, PTGES2, and PLA2G4A downregulated while PTGES and PLA2G6 remained upregulated. Consistently, metabolomic clustering heatmap showed that LPS stimulation led to a pronounced AA depletion and elevated pro-inflammatory eicosanoids, including PGE₂, PGA1, PGA2, PGD1, PGJ2, 15-PGJ2, PGF1A, PGFM, LTB , and 20-HETE. Rh- Au@MIP restored eicosanoid levels to those seen with celecoxib, Lh- Au@MIP sustained their elevation, and RAC- Au@MIP partially normalized the profile (Fig. 5l). Collectively, these data confirm that Rh- Au@MIP exerted anti-inflammatory effects similar to celecoxib by downregulating AA metabolising enzymes and pro-inflammatory lipid mediators.

Rheumatic arthritis therapy in vivo
Building on the potent enantioselective COX-2 activity regulation with Au observed in vitro, we evaluated the therapeutic potential of Au@MIP in collagen-induced arthritis (CIA) mouse model. 6-8-week-old male DBA/1J mice were immunized to establish CIA induced RA model, in which typical RA symptoms, including erythema and swelling in limb, were observed54-56. To detect the targeting ability of Au@MIP to the inflammatory joints where COX-2 is highly overexpressed, the metabolism profiles of Au@MIP were studied using an in vivo fluorescence imaging system, where intravenously injected Cy5.5-labeled Au@MIP ( Au@MIPCy5.5) accumulated at joints and ankles at 4 h post-injection, peaking at 12 h and dissipating at 48 h. In comparison, Au@DOPCy5.5, which was Cy5.5-labeled and dopamine-coated Au NPs but without molecular imprinting against COX-2, showed weak fluorescence signal at 6-24 h post-injection, while Cy5.5-labeled dopamine (DopCy5.5) showed no signal at the inflammatory sites (Fig. 6a and S31). Pharmacokinetic analysis further revealed that Lh- Au@MIP, Rh- Au@MIP, and RAC- Au@MIP exhibited elimination half-lives (t ) of 23.41 h, 26.98 h, and 22.39 h, respectively, with corresponding mean retention times (MRT) of 35.78 h, 38.18 h, and 33.77 h (Fig. S32). These results indicate favorable circulation stability and moderate systemic persistence, allowing sufficient time for effective accumulation at inflamed joints while minimizing long-term retention and systemic burden. At 12 h post-injection, Ex vivo fluorescence images of major organs (heart, liver, spleen, lung and kidney) and limbs showed that all the Au@MIPCy5.5, Au@DOPCy5.5 and DOPCy5.5 significantly accumulated at liver and kidney, consistent with systemic nanoparticle clearance. Notably, Au@MIPCy5.5 exhibited substantially greater accumulation in inflamed limbs than Au@DOPCy5.5 and DopCy5.5 (Fig. 6b and S33), indicating that while passive EPR may contribute to joint localization, the enhanced and prolonged retention of Au@MIP is primarily driven by active COX-2 recognition mediated by the MIP coating.
Thus, to investigate the therapeutic effect of Au@MIP, RA mice were divided into 5 groups receiving PBS, celecoxib, Lh- Au@MIP, Rh- Au@MIP and RAC- Au@MIP, respectively, through intravenous injection every other day for consecutive 12 days (Fig. 6c). During the treatment, RA severity was evaluated by the thickness and erythema of the ankle or paw of the mice and scored56–57. Rh- Au@MIP group showed the continuous and significant decrease in the thickness and erythema of the paw, and RAC- Au@MIP group showed moderate improvement, but the Lh- Au@MIP group had minimal effects similar to PBS group. (Fig. 6d-6f and Fig. S34). At the end of treatment, the paws of mice were collected for further evaluation of the therapeutic effects by micro-CT imaging, histological analysis and immunohistochemical analysis. Micro-CT images showed that Rh- Au@MIP effectively impeded the bone erosion in the small joints of paws and ankles, and remarkably reduced the bone porosity of ankle joints and metatarsophalangeal joints, and Lh- Au@MIP and RAC- Au@MIP partially alleviated the bone damage, whereas PBS resulted in severe bone destruction (Fig. 6g). The pathological sections of bone joints revealed that severe inflammation (Fig. 6h, hematoxylin and eosin (H&E) staining), narrow articular cavity, formation of pannus (Fig. 6h, Masson’s Trichrome staining) and damaged cartilage (Fig. 6h, Safranin O staining) were observed in PBS group (Fig. 6h). These symptoms were mildly mitigated in the RAC- Au@MIP group. Conversely, the celecoxib and Rh- Au@MIP group exhibited marked improvements, with enlarged articular cavity, reduced inflammation and clear bone-cartilage separation. Since PGE is the direct effector of inflammation induced by COX-2 and its expression reflects the COX-2 activity, the immunohistochemical staining of PGE in the limbs indicated that Rh- Au@MIP effectively reduced the expression of PGE , similar to celecoxib (Fig. 6i). Additionally, systemic inflammatory markers, such as TNF-α and IL-1β levels in the plasma, were significantly reduced in the Rh- Au@MIP and celecoxib groups, aligning with normal levels. This further confirmed a systemic reduction in inflammation (Fig. S35-S36).
To assess the biocompatibility of Au@MIP, the body weight of RA mice was continuously monitored, showing minimal variation across groups (Fig. S37). Comprehensive blood routine and biochemical analysis revealed most hematological parameters within the normal ranges (Fig. S38). Liver function markers (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)) along with blood urea nitrogen (BUN) indicated no significant toxicity associated with Lh- Au@MIP (Fig. S39). In addition, H&E-stained sections of major organs revealed no discernible difference compared to the PBS group (Fig. S40). Collectively, these results demonstrate that Au@MIP exhibit excellent biocompatibility and promising enantioselective therapeutic efficacy in RA.

Methods
Ethical Statement
All animal studies were conducted at the Changchun Institute of Applied Chemistry, Chinese Academy of Sciences (CIAC-CAS). Experimental procedures involving animals were approved by the Committee for Animal Research of CIAC-CAS (No. 2021-08).

Materials
Chloroauric acid (HAuCl ·3H O, ≥ 47.8%), silver nitrate (AgNO , 99.99%), hydrochloric acid (HCl, 36%), sodium hydroxide (NaOH, ≥ 96%), sodium borohydride (NaBH , 96%), L-cysteine (L-Cys, 99%), D-cysteine (D-Cys, 99%), potassium ferricyanide (K Fe(CN) , 99.5%), Potassium ferrocyanide (K Fe(CN) , 99.6%), 10-Acetyl-3,7-dihydroxyphenoxazine (ADPH, 98%), cyclooxygenase (COX-2, > 90%), acetic acid (AR, 99.8%), dopamine (98%), Sodium dodecyl sulfate (SDS, 92.5-100.5%), acetone (99.5%), perchloric acid (HClO , 70-72%), ethanol (95%), sulfuric acid (H SO , ≥ 96%), hydrogen peroxide (H O , 30%), acetonitrile (99.9%), Sodium perchlorate (NaClO , 95%) were purchased from Sigma-Aldrich. Cetyltrimethylammonium bromide (CTAB, ≥ 98%) was purchased from Acros Organics. Arachidonic acid (AA, ≥ 90%), 4-Mercaptobenzoic acid (≥ 95%) and hydroquinone (HQ, 99%) were received from Aladdin. All chemicals were used as supplied by the manufacturers without additional purification.

Characterization
Electrochemical measurements were conducted using a Chi 660E electrochemical workstation (Shanghai Chenhua, China). The morphology and primary size of nanomaterials were examined by transmission electron microscope (TEM, JEOL-1400, Japan). Fluorescence emission spectra were acquired on an Agilent Cary Eclipse fluorescence spectrophotometer (USA). Hydrodynamic diameter and zeta potential of nanomaterials were detected on a Zetasizer Nano ZS90 analyzer (Malvern, UK).
Circular dichroism (CD) spectra were acquired using a circular dichroism spectroscopy (JASCO 1500, Japan). The CD spectra of COX-2 was measured with the following parameters: scan range, 180-250 nm; scanning speed, 50 nm min-1; data pitch, 0.2 nm; band width, 2 nm; 3 repeats. The CD spectra of Au were obtained with the following parameters: scan range, 200-900 nm; scanning speed, 100 nm min-1; data pitch: 0.5 nm; band width, 5 nm; 3 repeats.

Preparation of Au, Au@COX-2 and Au@MIP
Au with different chiralities including Lh- Au, Rh- Au and RAC- Au were prepared via chiral thiol-mediated overgrowth on gold nanorods (GNRs).
GNRs were prepared first as the seed for growth of Au. Lh- Au, Rh- Au and RAC- Au were synthesized by adding L-/D-/RAC-Cys during the overgrowth process, respectively. The detailed experimental procedures were described as follow:
First, Au seed was synthesized by reducing HAuCl (0.1 mL, 25 mmol L-1) with freshly prepared ice-cold NaBH (600 μL, 10 mmol L-1) in an aqueous CTAB solution (10 mL, 100 mmol L-1). The light brown seed was formed after 3 min vigorous stirring, and the solution was kept still with cap-opened at 30 °C for 3 h to allow unreacted NaBH oxidized by oxygen in air.
Second, GNRs were prepared by adding 160 μL of well-prepared seed solution into a growth solution: HQ (500 μL, 0.1 mol L-1) was added into a mixed aqueous solution of CTAB (10 mL, 100 mmol L-1), HAuCl (200 μL, 25 mmol L-1), AgNO (70 μL, 0.1 mol L-1). The reaction was taken for 12 h at 30 °C to obtain GNRs. The resulting GNRs were centrifuged twice (14000 × g, 5 min) and redispersed in an aqueous solution containing 10 mmol L-1 CTAB for further synthesis of Au.
Finally, for synthesis of Lh- Au, Rh- Au or RAC- Au, 60 μL of 10 mmol L-1 L-Cys or D-Cys or 60 μL of an equal amount mixture of L-Cys and D-Cys (30 μL each, 10 mmol L-1) was added to 10 mL of GNR aqueous solution (0.1 nmol L-1, Abs = 0.2) stabilized with 10 mmol L-1 CTAB, respectively, and sit still at 30 °C for 3 h. Then, AgNO (70 μL, 10 mmol L-1), HAuCl (56 μL, 25 mmol L-1) and ascorbic acid (32 μL, 100 mmol L-1) were quickly added sequentially and thoroughly mixed. The mixture was allowed to grow at 70 °C for 1 h, during which the solution color gradually changed from light red to bluish purple. The solution was centrifuged twice (14000 × g, 5 min) to obtain Lh- Au, Rh- Au or RAC- Au.
For preparation of Au@COX-2, 0.1 mL of 2 mg mL-1 COX-2 was added to 10 mL of 0.5 nmol L-1 Lh- Au, Rh- Au or RAC- Au (Abs = 1.0) aqueous solution, respectively, followed by ultrasonication in a water bath for 15 min and incubation at 30 °C for 12 h. Then, unbound COX-2 was removed by centrifugation (14000 × g, 5 min) to obtain Lh- Au@COX-2, Rh- Au@COX-2, RAC- Au@COX-2, respectively.
Then, for preparation of Au@MIP, Au@COX-2 synthesized by the above method was dispersed in 10 mL of deionized H O, and the pH was adjusted to 8.5 using 1 mol L-1 NaOH. Then, 500 μL of 2 mg mL-1 dopamine was added to 10 mL of Au@COX-2 dispersion under vigorous stirring to react for 2 h. After that, the dopamine-coated Au@COX-2 was centrifuged (14000 × g, 5 min) and washed five times with a 3% (v/v) acetic acid solution containing 0.1% (w/v) SDS, and then washed thoroughly with distilled water 3 times.
Cy5.5-labeled Au@MIP ( Au@MIPCy5.5, including Lh- Au@MIPCy5.5, Rh- Au@MIPCy5.5 and RAC- Au@MIPCy5.5) were prepared via electrostatic interactions between Cy5.5 and the dopamine shell. In detail, 10 μL 5 mg mL-1 Cy5.5 (DMSO) was added into 5 mL dispersion of Lh- Au@MIP, Rh- Au@MIP and RAC- Au@MIP (equivalent to 3 mg mL-1 Au), respectively. After ultrasonicated for 5 min in water bath, the mixture was sit still for 3 h for efficient modification, then followed by centrifugation (14000 × g, 5 min) for 4 times to remove unbound Cy5.5 to obtain Au@MIPCy5.5. The loading concentration of Cy5.5 on Au@MIPCy5.5 was calculated to be ~1.25 μg mL-1 by measuring the fluorescence spectra of Cy5.5, which showed obvious emission peak around 690nm.

Electrochemical Measurements Setup
The electrochemical measurements were performed in a typical three-electrode cell using an electrochemical workstation (Chi 660e, Shanghai, China). Ni or Pt plate (size 1 cm × 1 cm), an Ag/AgCl (saturated KCl) electrode, and a Pt wire were used as the working, reference, and counter electrodes, respectively. Prior to use, Ni or Pt plates were cleaned in boiling acetone and ethanol for 20 min, and then used as the working electrode to remove the oxides on surface with the potential set at -1.0 V in 1 mol L-1 HClO to run for 20 min, then washed with acetone and ethanol again. All the glassware used in the electrochemical experiments were carefully cleaned with piranha solution (H SO :H O = 7:3 (v:v)). A permanent magnet of a field strength H= 1.2 T was placed close to the working electrode for investigating the influence of MF. The field strength on the Ni or Pt surface was measured to be 0.8 T using a digital Gauss meter.

CV curves of AA oxidation without COX-2
The well cleaned Ni plate was spin coated with ~8 nm Au nanoparticles (NPs) using a vacuum spin coater (Shenzhen Kejing, VTC-100B), followed by rinsing with DI H O to remove unadsorbed Au nanoparticles. Then the Au NP-deposited Ni plate was used as the working electrode for CV measurements. Acetic acid containing 20% (w/v) acetonitrile and 0.5 mol L-1 NaClO was used as the electrolytes. After purging N for 30 min to displace the air in electrolytes, 10 mmol L-1 AA was added, and the CV curves were measured using the following parameters: initial potential, -0.4 V; final potential, 1.6 V; scan rate, 50 mV s-1. To study the influence of external MF, a permanent magnet was placed close to the Ni plate outside the electrochemical measurement cell. The MF direction was reversed by simply flipping the magnet.
All electrochemical measurements involving AA oxidation were independently repeated three times under identical conditions. Specifically, each Ni (or Pt) working electrode was prepared as a single large film and then cut into three electrodes of equal size. Freshly prepared AA solution was evenly divided for the three replicates. For each sample, only the first cycle of the cyclic voltammogram (CV) was analyzed to avoid surface passivation or accumulation effects. The original CV curves obtained from three independent experiments were averaged as the final CV curves shown. Then the positive semi-cycle of CV curves were baseline fitted and subtracted to generate background-corrected CV curves for peak current determination and comparison. Peak currents from the background-corrected positive semi-cycle of CV curves obtained from the three independent measurements were used to calculate the mean ± standard deviation (SD), which are represented as error bars in all relevant figures. This protocol was applied consistently across all AA oxidation related CV measurements unless otherwise stated.

CV measurement of AA oxidation with COX-2
Following deposition with Au NPs, the Ni plate was immersed in 2 mg mL-1 COX-2 at 4 °C with shaking for 12 h to adsorb COX-2 onto the surface, and then washed with DI H O. To check if COX-2 was successfully modified on Au NP-deposited Ni plate, the electrochemical impedance spectra (EIS) was measured before CV measurements. The measurement parameters were set to the same as that case without COX-2 modification.

CISS effect of Au
In order to better modify Au on Ni plate, the well cleaned Ni plate was first immersed in 10 mmol L-1 4-mercaptobenzoic acid at 4 °C for 12 h. After washing with DI water, the Ni plate was immersed in a 5 mg mL-1 solution of Lh- Au, Rh- Au, RAC- Au or achiral Au nanoparticles for 3 h. The EIS spectra were measured to confirm the successful deposition of Au NPs on Ni plate. Then, Au-modified Ni plate was used as the working electrode for CV measurement. 4 mmol L-1 K [Fe(CN) ] and K [Fe(CN) ] were used as the redox pair and 0.1 mol L-1 KOH was employed as the supporting electrolyte for CV curve scanning. The measurement parameters were set as: initial potential, -0.1 V; final potential, 0.5 V; scan rate, 50 mV s-1. For each condition, at least three independent experiments were conducted and the final stable CV curves for each experiment were employed for analysis.

Enantioselective regulation of Au on COX-2 activity
The well cleaned Pt plate was immersed in a solution of Lh- Au@COX-2, Rh- Au@COX-2 and RAC- Au@COX-2, respectively, at 4°C for 12 h. Then, the Lh- Au@COX-2-, Rh- Au@COX-2- or RAC- Au@COX-2-deposited Pt plate was used as the working electrode to measure the CV curves of AA oxidation. The measurement parameters were set as: initial potential, -0.4 V; final potential, 1.6 V; scan rate, 50 mV s-1. To study the influence of external MF, a permanent magnet was placed close to the Pt plate outside the electrochemical measurement cell. The MF direction was reversed by simply flipping the magnet.

Determination of enzyme activity regulation effects of Au
Au with varied ee values (100%, 80%, 40%, 20%, 0, -20%, -40%, -80%, -100%) was obtained by mixing different concentration Lh- Au and Rh- Au. Then Au ([Au0] = 100 μg•mL-1) with varied ee values were pre-incubate with 2 mg•mL-1 enzyme (COX-2, laccase or LDH) at 37 °C for 1 h. Then, the mixture of Au and enzymes were employed for enzyme activity determination with corresponding kit according to the product description. Cyclooxygenase 2 Inhibitor Screening Kit (Beyotime, Lot#S0168), micro laccase assay kit (Acmec, Lot# AC10346) and lacate dehydrogenase (LDH) activity assay kit (Acmec, Lot# AC10186) were employed for determining the activity of COX-2, laccase and LDH, respectively.

Cell culture
RAW 264.7 murine macrophages purchased from ATCC were employed for in vitro experiments and cultured in Dulbecco's Modified Eagle Medium (DMEM) containing 10% fetal bovine serum (FBS), penicillin (10 U mL-1) and streptomycin (10 μg mL-1) at 37 °C with 5% CO . Cells were passaged routinely and used during the logarithmic growth phase. To establish an inflammatory phenotype, RAW 264.7 cells were exposed to lipopolysaccharide (LPS, 100ng mL-1) for 12h prior to subsequent treatments, as specified for individual experiments.

Cytotoxicity assessment of Au@MIP
RAW 264.7 cells were seeded in 96-well plates (1×104 cells per well) and allowed to stabilize and grow overnight. Then, the medium was changed into 100 μL of fresh DMEM containing 0, 25, 50, 100, 200 μg mL-1 (calculated in [Au0]) of Lh- Au@MIP, Rh- Au@MIP or RAC- Au@MIP, respectively. After co-culture for 24 h, 10 μL cell counting kit 8 (CCK8, Beyotime, Shanghai, China) reagent was added into each well for 2 h of incubation at 37 °C. Then, the 96-well plates were used for measuring the absorbance at 450 nm by microplate reader (SpectraMax M5, Molecular Devices, USA). Wells without cells were applied as blanks.

Endocytosis and distribution of Au@MIP in macrophages
RAW 264.7 cells were seeded in 6-well plates pre-placed with coverslips (3.0 × 105 cells per well) and stimulated with 100 ng mL-1 LPS for 6 h. Then, the medium was replaced by DMEM containing Au@MIPCy5.5 (Lh- Au@MIPCy5.5, Rh- Au@MIPCy5.5 and RAC- Au@MIPCy5.5) ([Au0] = 100 μg mL-1) and co-cultured for 12 h. Then, after washing with PBS, cells were fixed by 4% (w/v) paraformaldehyde, followed by staining (FITC-labeled Wheat Germ Agglutinin (FITC-WGA) (2 μg mL-1), 15 min, for cell membrane; Hoechst 33342 (100 nmol L-1), 3 min, for nuclei). For endocytosis study, cells were harvested and analyzed by flow cytometry (BD AccuriTM C6 plus flow cytometer, USA). The data were analyzed by Flowjo v10.0. For distribution study of nanoparticles in cells, the coverslips were used for fluorescence imaging under a laser scanning microscope (Leica TCP SP8, USA).

COX-2 expression analyses
COX-2 expression levels in inflammatory cells were analyzed by western blotting. RAW 264.7 cells seeded in 6-well plates with a density of 3.0 × 105 cells per well were first stimulated with 100 ng mL-1 LPS for 6 h. Then, the medium was replaced by DMEM containing Lh- Au@MIP, Rh- Au@MIP, RAC- Au@MIP ([Au0] = 100 μg mL-1) or celecoxib (100 nM), respectively, for an additional 12 h of co-culture at 37 °C. Following treatment, cells were harvested and lysed on ice with RIPA buffer (Beyotime, CAT#P0013B) containing protease inhibitors. After centrifugation (14,000 × g, 15 min), the supernatant was collected and the total protein concentration for each sample was determined using a BCA assay. Protein were loaded in equal amounts and resolved by 12% SDS-PAGE and then electronically transferred onto polyvinylidene difluoride (PVDF) membranes. Membranes were blocked with a blocking buffer (5% skimmed milk in TBST solution) for 1 h at room temperature, then incubated with a primary antibody against COX-2 (Abcam, Ab28672) at 4 °C overnight. Membranes were then washed, and incubated with horseradish peroxidase (HRP)-conjugated secondary antibody for 1 h at room temperature before enhanced chemiluminescence (ECL) imaging, which were recorded using a Tanon 2500 imaging system (Shanghai, China). The uncropped blot images are provided in the Source Data file.

Cell inflammatory phenotype determination by Flow cytometry
After cells co-cultured with Lh- Au@MIP, Rh- Au@MIP, RAC- Au@MIP ([Au0] = 100 μg mL-1) or celecoxib (100 nM) for 12 h, respectively, the cell pellets were collected by centrifugation (1000 × g, 5 min) and then stained with antibodies of FITC-anti-F4/80, PE-anti-CD86, and APC-anti-CD206 (BioLegend, Cat# 123107, 105007, 141708) according to the instructed conditions. Flow cytometric analysis was then conducted using a flow cytometer (Accuri C6 Plus, BD Biosciences, USA). Cells were first gated on forward scatter (FSC) versus side scatter (SSC) to exclude debris and doublets, ensuring analysis of viable single cells. A total of 10,000 FITC-positive events were randomly collected for each sample. FITC+ cells were subsequently analyzed for fluorescence intensity in the PE and APC channels to determine the proportion of CD86+ (M1-like) and CD206+ (M2-like) macrophages. Fig. S42 refers to the PBS group exemplifies the gating strategy for all samples.

Cytokines PGE , TNF-α and IL-1β quantification by ELISA
After the indicated treatments, culture supernatants from RAW 264.7 cells were collected and clarified by centrifugation to remove cellular debris. The concentrations of PGE , TNF-α, and IL-1β were quantified using commercially available ELISA kits (PGE : Abcam, Ab287802; TNF-α: BioLegend, 430901; IL-1β: BioLegend, 575109). Absorbance signals were recorded using a microplate reader, and cytokine levels were calculated based on standard curves measured for each assay.

Proteomics and untargeted metabolomics analysis
RAW 264.7 cells subjected to the same treatments as described in Section 1.12 were harvested by centrifugation (1000 × g, 5 min) and washed with PBS for twice. Cell pellets were stored at −80 °C until further proteomic and untargeted metabolomic analysis.
For proteomics, frozen cell pellets were ice lysed using RIPA buffer containing protease and phosphatase inhibitors. Protein concentrations were then measured using a BCA assay. For each sample, 100 μg protein was digested via the filter-aided sample preparation (FASP) protocol. The resulting peptides were desalted and vacuum-dried. Peptides analysis was conducted on a Thermo Scientific Orbitrap Astral mass spectrometer. Separation was achieved on a C18 analytical column (150 μm × 15 cm, Evosep) with a linear gradient of 5–35% acetonitrile for 120 min with a flow rate of 300 nL min-1. Raw data were processed using Proteome Discoverer™ Software 2.4 against the UniProt mouse protein database. The false discovery rate was controlled below 1% at both peptide and protein levels, with a precursor mass tolerance of 20 ppm and fragment mass tolerance of 0.02 Da. Label-free quantification (LFQ) was used for relative protein quantification. To focus on inflammation-related pathways mediated by arachidonic acid (AA) metabolism, differentially expressed proteins (DEPs) were identified by a fold change ≥1.5 and p-value < 0.05 (t-test). AA metabolism-related proteins were then curated by cross-referencing DEPs with known pathway databases, including: KEGG Pathway: mmu00590 (Arachidonic acid metabolism); Reactome Pathway: “Arachidonic acid metabolism” and “Biosynthesis of eicosanoids”; Gene Ontology (GO) terms related to: “arachidonic acid metabolic process” (GO:0019369) and “eicosanoid biosynthetic process” (GO:0006690). The final list included key enzymes such as PTGS2, PTGS, PTGES, PTGES2, PLA2G4A, PLA2G6, PTGS1/2, PTGES, PTGES2, and ALOX5 family members involved in AA processing. The expression profiles of these AA metabolism-related proteins in different groups were then subjected to hierarchical clustering analysis.
For metabolomics, cell pellets were extracted in pre-chilled methanol:acetonitrile:water (2:2:1, v/v/v), vortexed, and subjected to three freeze–thaw cycles. After centrifugation (14,000 × g, 15 min, 4 °C), the supernatants were collected, vacuum-dried, and reconstituted in 80% methanol. Metabolite profiling was acquired using an ultra-high-performance liquid chromatography UHPLC system coupled to a Thermo Q Exactive HF-X mass spectrometer. Chromatographic separation was performed using a HSS T3 column under both positive and negative ionization modes. Raw data were processed using Progenesis QI (Waters Corp.) for peak alignment, deconvolution, and normalization. Metabolite identification was achieved by matching MS/MS spectra to public databases including HMDB, METLIN, and KEGG. Metabolites associated with AA metabolism were identified based on KEGG annotations and manual curation of key intermediates and eicosanoids, including: arachidonic acid (AA), PGE₂, PGA1, PGA2, PGD2, PGJ2, 15d-PGJ2, PGF2α, LTB , and 20-HETE. Then the expression data of the curated AA-associated metabolites in different groups were used for subsequent hierarchical clustering analysis.
Both proteomic and metabolomic clustering heatmaps were generated using the Bioinformatics Online Platform (https://www.bioinformatics.com.cn, last accessed: Dec 10, 2024). Prior to clustering, all values were Z-score normalized across samples. Hierarchical clustering was obtained using Euclidean distance and complete linkage method; color gradients were used to represent relative abundance (blue: low, red: high).

Animal
DBA/1J mice (male, 6-8 weeks old) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd.. Only male mice were used in this study to align with the well-established protocols for the CIA-induced RA model. All animals were maintained under a specific pathogen-free conditions at around 20 °C, with 40–60% relative humidity, on a 12 h light/12 h dark cycle and with free access to food and water.

Establishment of CIA-induced RA mouse model
Male DBA/1J mice (~15 g, 6-8 weeks old) were employed for building the RA model by CIA method. Briefly, each DBA/1J mouse was subcutaneously immunized by injection of 100 μL of homogeneously emulsified mixture of 50 μL of type II bovine collagen (2 mg mL-1) and 50 μL of Freunds’ Complete Adjuvant (CFA) containing mycobacterium tuberculosis (2 mg mL-1) at the base of the tail. On Day 21, 100 μL homogeneously emulsified mixture of 50 μL type II bovine collagen (2 mg mL-1) and 50 μL Freunds’ Incomplete Adjuvant (IFA) containing mycobacterium tuberculosis (2 mg mL-1) was subcutaneously administered into the mice at the base of the tail as a booster injection to induce arthritis. On Day 28, mice with red and swelled paws and joints were observed, suggesting the successful establishment of CIA mouse model.

Biodistribution analysis
Biodistribution of Au@MIP in RA mice was investigated using Cy5.5-labeled Au@MIP ( Au@MIPCy5.5). DopCy5.5 and Au@DopCy5.5 were also prepared for comparison. In detail, for DopCy5.5, 5 mg dopamine hydrocholoride powder was added to 10 mL H O with pH pre-adjusted to 8.5 under vigorous stirring, after reaction for 1h, 20 μL of 5mg mL-1 Cy5.5 dissolved in DMSO was quickly added, and continued to react for 2 h, and the obtained greyish solution was centrifuged in 14000 × g for 30 min to settle down the dopamine nanoparticles (DopCy5.5). Au@DopCy5.5 was prepared using the similar protocol to Au@MIPCy5.5 but skipping the step of COX-2 adsorption. Lh- Au was dispersed in 10 mL of deionized H O, and the pH was adjusted to 8.5 using 1 mol L-1 NaOH. Then, 500 μL of 2 mg mL-1 dopamine was added under vigorous stirring and allowed to react for 2 h. Then the dopamine-coated Au ( Au@Dop) obtained by centrifugation (14000 × g, 5 min) for 3 times and redispersed in deionized H O, and the concentration of Au@Dop was adjusted to ~15 nM (equivalent to 3 mg mL-1 Au). Then, 10 μL of 5 mg mL-1 Cy5.5 (DMSO) was added into 5 mL dispersion of Lh- Au@Dop, and followed by 5 min ultrasonication in water bath and sit still for 3 h before centrifugation (14000 × g, 5 min) for 4 times to remove unbound Cy5.5 to obtain Au@DopCy5.5.
RA mice were intravenously injected with 100 μL of DopCy5.5, Lh- Au@DopCy5.5, Lh- Au@MIPCy5.5, Rh- Au@MIPCy5.5, RAC- Au@MIPCy5.5 (equivalent to 3 mg mL-1 Au or 1.25 μg mL-1 Cy5.5), and then the mice were imaged on an in vivo fluorescence imaging system (VISQUE InVivo Smart-LF, Viewworks, Korea) at 0, 2, 4, 6, 12, 24, 36 and 48 h post injection. For ex vivo imaging, mice were similarly treated as described above, and at 12 h post-injection, mice were euthanized and the major organs (heart, liver, spleen, lung and kidney) and limbs were harvested for fluorescence imaging.

Therapeutic treatment
RA mice were randomly divided into five groups (n = 5 per group) and intravenously administered with 100 μL of PBS, Lh- Au@MIP, Rh- Au@MIP, RAC- Au@MIP ([Au0] = 3 mg mL-1, 20 mg kg-1), and celecoxib (100 nmol L-1) every other day for two weeks. During the treatment, the hind paw thickness of each mouse was monitored using a digital caliper, and arthritis severity was assessed using a clinical scoring system. Four paws of each mouse were scored every other day (score: 0, normal with no paw swelling or erythema; 1 , slight erythema and swelling; 2, moderate swelling with edema; 3 , pronounced edema and reduced joint mobility; 4, severe edema and joint stiffness). The maximum possible score for each mouse was 16.

Micro-CT imaging
After 12 days of treatment under different conditions, the hind limbs of RA mice were collected and fixed using 4% (w/v) paraformaldehyde. The collected hind limbs were scanned in 12 μm isotropic resolution and analyzed by a 3D Cone Beam Nemo Micro-CT (NMC-200, PINGSENG, China). 3D reconstructions of the tissues were conducted with FDK algorithm using the Avatar software (version 1.7.2, PINGSENG, China).

Histopathological analysis of joints
After 12 days of treatment under different conditions, limb tissues of RA mice were collected at the end of two weeks of treatment, fixed in 4% (w/v) paraformaldehyde, followed by decalcification with 10% (w/v) EDTA for three weeks. Then, the embedded tissue blocks were sectioned into 30 μm-thickness slices for H&E, Masson, and Safranin O/Fast Green staining. And representative images were obtained using an optical microscopy (Mshot MF53-M, China).

Immunochemical analysis of PGE in arthritis
At the end of 12 days of treatment under different conditions, the hind limbs of mice in all groups were collected, fixed with 4% (w/v) paraformaldehyde, and embedded in paraffin for sectioning into 10 μm-thick slices. Prior to antibody staining, heat-mediated antigen retrieval was applied in citrate buffer solution for 10 min under the microwave, then endogenous peroxidase activity was quenched using 3% (v/v) hydrogen peroxide solution for 10 min in the dark. Sections were then incubated with 3% (w/v) bovine serum albumin (BSA) in PBS buffer for 10 min to minimize non-specific binding, followed by incubation with a PGE -specific primary antibody (Antibodies-online, CAT# AA281384) at 4 °C overnight. After thorough washing, HRP-conjugated secondary antibody was applied to incubate at room temperature for 10 min, and immunoreactivity was visualized using diaminobenzidine (DAB) as the chromogenic substrate, with hematoxylin counterstaining. Stained sections were dehydrated in ethanol and xylene, mounted with neutral balsam, and examined under an optical microscopy (Mshot MF53-M, China).

Cytokines measurement in serum
After 12 days of treatment under different conditions, blood samples were retrieved from the retro-orbital plexus of RA and normal mice, respectively, and then centrifuged at 500 × g for 10 min to separate the serum, which was used for detection of the concentrations of the pro-inflammatory cytokines TNF-α and IL-1β using specific ELISA kits according to the manufacturer’s instructions.

Biocompatibility Analysis
After 12 days treatment, blood and major organs (heart, liver, spleen, lung and kidney) were collected. Blood samples were used for hematological and biochemical analysis and key parameters including liver function markers (ALT, AST) and kidney function markers (creatinine, blood urea nitrogen) were measured. Major organs were fixed in 4% (w/v) paraformaldehyde, embedded in paraffin and sectioned into 5 μm-thickness slices for H&E staining. Representative images were captured using an optical microscope (Mshot MF53-M, China).

Statistical Analysis
All quantitative data are presented as mean ± standard deviation (SD) and GraphPad Prism (v8.0) was used for all Statistical analyses. One-way analysis of variance (ANOVA) with Tukey’s post hoc test was applied for comparisons among multiple experimental groups. A two-sided p < 0.05 was considered statistically significant. All experiments were independently repeated at least three times, with the specific number of replicates (n) indicated in the figure legends.

Theoretical Calculation
Theoretical models of COX-2, Au and Au@COX-2 were respectively constructed and positioned between two electrodes to investigate their spin-selective electron transport properties. Spin-resolved conductance spectra and current–voltage (I–V) characteristics were calculated using a model Hamiltonian framework. The electronic transport behavior of each system was analyzed by applying the Landauer–Büttiker formalism in conjunction with the non-equilibrium Green’s function (NEGF) method. Full details on model construction, Hamiltonian formulation, and parameter selection are provided in the Supplementary Information.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript introduces a conceptually novel strategy for regulating enzyme activity through electron spin polarization, mediated by chirality-induced spin selectivity (CISS) effect of chiral gold nanohelices (CAu). The authors demonstrate that CAu with different handedness (Lh vs. Rh) exhibit enantiospecific control of cyclooxygenase-2 (COX-2) catalytic activity through spin-aligned or mismatched electron transport pathways. This strategy surpasses conventional regulatory approaches, such as nanozyme activity regulation or active-site interference regulation. Notably, the spin-dependent modulation is validated in both cellular and animal models of rheumatoid arthritis (RA), highlighting its therapeutic relevance.\n\nAlthough the CISS effect has been reported in physical systems, its direct application to the regulation of biomolecular function remains largely unexplored. To the best of my knowledge, this is the first study to leverage electron spin polarization for the regulation of a biological enzyme, and to successfully translate this modulation into therapeutic outcomes. The findings are supported by comprehensive electrochemical analyses, theoretical modeling, and in vitro/in vivo experimental assessments. Overall, the manuscript represents a pioneering integration of spin physics with redox enzyme modulation, with significant implications for both mechanistic enzymology and biomedical engineering. I recommend its publication pending minor revisions to address the following points.\n\n1.The mechanistic contributions require further clarification and quantification. In Figure 4O, the authors outline three mechanisms underlying COX-2 modulation: (i) nanozyme activity, (ii) active site blocking, and (iii) CISS-driven electron transport. However, the rationale behind the reported contribution percentages of each mechanism is not clearly explained. Please clarify how these contributions were quantitatively determined. Providing a detailed explanation would strengthen the mechanistic interpretation and credibility of the conclusions.\n2.Although Figure S8 suggests weak and chirality-independent catalytic activity from CAu, the enhancement of COX-2 activity by Lh-CAu (~5%) may still partially stem from this effect. Can the authors rule out this contribution more explicitly?\n3.In vivo imaging (Fig. 6A-B) and RA scoring (Fig. 6D-F) demonstrate a pronounced therapeutic benefit of Rh-CAu@MIP. Although the therapeutic effect of Rh-CAu@MIP in RA mice is attributed to spin-mediated COX-2 inhibition, other contributing factors (such as nanoparticle biodistribution and MIP-induced pharmacokinetics) could also play a role. Could this observed therapeutic efficacy be explained by passive enhanced permeability and retention (EPR) rather than spin-selective regulation? The authors are encouraged to discuss whether the preferential accumulation at inflamed joints is primarily driven by COX-2 recognition through the molecularly imprinted polymer (MIP), or whether it is largely a consequence of passive EPR effects. A clearer distinction between these mechanisms would strengthen the interpretation of in vivo efficacy.\n4.Given that the MIP coating alters the surface chemistry and dielectric environment of the nanoparticles, the authors should discuss whether this coating could attenuate or modulate the spin-polarized electron transport of CAu.\n5.The authors employ a simplified α-helical model to simulate spin-dependent electron transport through COX-2 (Fig. 2E–G and 4J–N). While this approach is widely used in CISS studies, COX-2 is a large multidomain enzyme featuring complex tertiary structure and multiple electron relay sites. Could the authors clarify whether the α-helix approximation is representative of the specific domains involved in COX-2’s catalytic electron transfer? It would be helpful to specify whether the known redox-active residues or cofactor-associated helices were considered in the model design.\n6.The theoretical model of chiral gold nanohelices (CAu) presented in Fig. 3K–T relies on idealized helical structures with smooth surfaces and regular pitch. However, synthesized CAu particles exhibit a distribution of geometries and surface irregularities, and are often functionalized with surfactants or ligands (e.g., CTAB or dopamine). Have the authors assessed how variations in helical pitch, radius, or structural defects might influence spin polarization and conductance? It would be informative to include a brief parametric sensitivity analysis.\n7.While COX-2 serves as an excellent proof-of-concept model for RA therapy, the manuscript would benefit from a more in-depth discussion of the broader applicability of this approach. Could this CISS-based strategy be extended to other oxidoreductases? It is suggested to include a brief discussion on the potential generalizability of electron spin polarization for modulating diverse redox enzymes in the Discussion section.\n8.Figures 3 and 4 contain extensive graphs and information. While they are important for mechanism clarification, it is strongly suggested to add schematic arrows or visual cues highlighting the “spin alignment versus mismatch” pathways, which will improve the readability and comprehension.", "reviewer_2": "In this study, the authors investigated the effect of chiral gold nanohelices (cAu) on COX-2 activity and enhanced its targeting capability through molecularly imprinted polymers (MIPs), thereby improving its translational potential. This work introduces a conceptual shift: enzyme activity can be modulated not solely through static structural engagement, but via the spin dynamics of electron flow at the molecular level. However, the manuscript still has the following issues:\n\n1．The study demonstrated the activity of COX-2 regulated by spin-polarized electrons through electrochemical CV curves (Figs. 2B-C) and theoretical calculations (Figs. 2E-G). However, it did not incorporate circular dichroism (CD) spectroscopy or molecular dynamics simulations to analyze potential conformational changes in COX-2 upon cAu binding.\n2. The theoretical calculations (Figs. 2E-G, 3K-M) employed a tight-binding model to simulate electron transport, but were conducted under the assumption of a vacuum environment, thereby neglecting critical biointerface factors such as protein surface hydration layers or ionic screening effects.\n3．While the results section (Figs. 4H-I) identified spin mismatch as the primary cause of activity inhibition, the potential contribution of conformational perturbation was not conclusively ruled out.\n4. The study appears more conjectural in nature, employing an overly idealized model that lacks theoretical simulations to elucidate the fundamental mechanism by which spin polarization direction regulates electron transfer pathways. While the work demonstrates innovation in material design, its core findings suffer from insufficient quantitative analysis. Although the observed phenomena are revealed, the research fails to delve deeper into critical parameters such as material composition ratios and enantiomeric excess of chiral structures that could significantly impact enzymatic activity.\n5.In Figure 4B, the inhibitory effect of cAu on COX-2 activity is weaker than that of celecoxib. What advantages do cAu materials offer over traditional rheumatoid arthritis drugs?\n6.Regarding the mechanism of COX-2 inhibition, a major difference between Rh-cAu@MIP / RAC-cAu@MIP and celecoxib is that the latter directly binds to the active site of COX-2, whereas the former does not, which could affect drug resistance. It is recommended to include relevant validation of resistance development.\n7.Sections 1 and 2 only elaborate on the mechanism by which cAu modulates COX-2 activity, but fail to explain how cAu affects COX-2 protein expression as shown in Figure 5G.\n8.In Figures 4B and 5H, both COX-2 activity and protein levels in the celecoxib group are lower than those in the Rh-cAu@MIP and RAC-cAu@MIP groups. However, in Figure 5I, the PGE₂ level in the celecoxib group is paradoxically higher than in the other two groups. This discrepancy requires further clarification.\n9.Does intravenous injection of MIP-modified cAu pose any risks of immunogenicity or long-term instability?\n10.The layout and formatting of Figures 5 and 6 are disorganized and need improvement.\n11.Has the potential for long-term retention or toxicity of the nanomaterials used in this study been fully evaluated in vivo? Although the preliminary biocompatibility results appear favorable, have any extended-duration or multiple-dose toxicity assessments been conducted?\n12. Figure 6H – Histology – some of these images do not look like they are sectioned from the same location making comparison difficult to judge.", "reviewer_3": "In this article, the authors investigate the construction of chiral nanohelix-enzyme assemblies with the goal of employing the chiral-induced spin-selectivity (CISS) effect to modulate the oxidation of arachidonic acid, which mediates inflammation and has applications in the treatment of rheumatoid arthritis. Beyond this specific therapeutic context, modulation of enzyme activity using CISS offers an important means of controlling a wide range of biological processes that can complement conventional chemical approaches. By attaching the cyclooxygenase-2 (COX-2) enzyme to chiral gold nanohelices, enzyme activity could be favored or suppressed depending on their enantiomorphic form which leads to homo- or heterochiral assemblies, as demonstrated using electrochemical measurements, studies on cellular inflammation, and in vivo mouse models.\n\nBroadly, I find the central argument regarding the influence of CISS on the pairings of COX-2 with either left- or right-handed Au nanohelices to be reasonably solid, although there are many details that still require attention, particularly with regards to the influence of external magnetic fields. The authors establish beyond reasonable doubt with circular dichroism spectra that the enzyme and nanohelices are chiral, and that the symmetric spectra of the latter indicate an absence of structural differences between left- and right-handed nanohelices that might lead to misinterpretation of confounding factors as effects of CISS. The authors also plausibly demonstrate that left-handed helices form a homochiral pairing with COX-2 (facilitating electron transfer) and right-handed helices form heterochiral structures (impairing ET), a fact that is supported by both the electrochemical and biological experiments. Overall, the core argument of the manuscript appears largely to be sound, but major revisions will be needed before I recommend its acceptance for publication.\n\nA prominent concern is the role of the magnetic field in the nanohelix-COX-2 assemblies. The results of the electrochemical experiments in sections 2 and 3 are straightforward to understand, since electron spins are injected via the magnetic nickel electrode, wherein the magnetic field is necessary to favor upward- or downward pointing-spins. However, in Figure 4, the magnetic field still achieves significant modulation of the current despite the use of a non-magnetic electrode. Since the usual purpose of a magnetic field in these experiments is to polarize the injected electron spins by splitting the spin sub-bands of the electrode, this effect is precluded in this suite of experiments, and some other interaction must be invoked to describe the magnetic field dependence. The authors should think carefully about other magnetochiral effects and how they might manifest in complicated molecules such as COX-2, particularly since the behavior of the nanohelix-enzyme assemblies seems to mirror the behavior of COX-2 alone, raising the possibility that the latter may also be dominated by non-CISS effects. (This might be easy to probe by performing analogous experiments to those in Figure 2 using a Pt electrode in place of Ni.)\n\nAdditionally, the electrochemical experiments in general are analyzed at such a rudimentary level that I find them only somewhat convincing. Use of the raw peak current measured at the AA oxidation feature as the main metric leaves the analysis vulnerable to unrelated confounding factors that also contribute to the current (e.g., double layer discharge), and this background clearly changes from sample to sample in ways that do not seem straightforward to interpret. The authors should, at minimum, attempt to fit the peaks using a suitable lineshape (pseudo-Voigt function, for instance) after subtracting off the background (a simple linear background would be acceptable, in my opinion). A more sophisticated line of analysis would be to perform the cyclic voltammetry measurements using a range of voltage scan rates, and use Marcus theory to estimate the rate constant. (Recent examples of this approach in similar systems can be found in Langmuir 2023, 39, 1414-1424 and J Phys. Chem. B. 2023, 127, 6462-6469.) This latter approach may not be straightforward due to the irreversibility of the oxidation, but the authors should at least estimate the peak current with the background subtracted to confirm the validity of their analysis.\n\nMore specific comments expanding on these and other points are provided below:\n\nFigure 1: A more detailed explanation of the figure, either in the caption, or in the main text, would be helpful. It took me some time, for instance, to understand that the blue and gold symbols in panels A and B were electrons, rather than opposite enantiomorphs of chiral nanoparticles decorating a larger structure such as a nanorod or a chiral molecule. I figured it out eventually, but an explicit legend denoting gold symbols as spin-up electrons and blue symbols as spin-down electrons would remove some of the friction in this process. Also, the chirality of the molecule in A and B should be indicated; it may even be worthwhile to include a fifth row containing the molecule’s opposite enantiomer to clarify that CISS works the same way for molecules as for nanorods. Finally, the chiral molecule appears to contain a right-handed helix, but has favorable electron transport in conjunction with the left-handed nanorod and poor transport with the right-handed one, when the opposite behavior would be expected. The diagram should be updated to convey the more physically accurate behavior (i.e., CISS favors transport in homochiral systems and retards it in heterochiral systems).\n\nFigures 2A-C and S1, Associated Discussion: I don’t fully understand the sentence “To exclude the influence of spin-polarized electrons on AA oxidation, we repeated CV measurements on the gold nanoparticle-coated Ni plate electrode without COX-2 modification.” Isn’t the whole point of the experiment in Figure 2 to probe the influence of spin-polarized electrons, as mediated by COX-2? And since the experiment is performed on a Ni electrode with an external magnetic field, spin-polarized electrons will be present. So this should be discussed a little bit differently, to validate the hypothesis that no other parts of the system are contributing to the CISS effect, besides the expected contribution from the chiral enzyme. Furthermore, while the data in Figure 2A-C broadly seem to support the authors’ argument, I have some concerns:\n- What do the error bars represent, and how were they calculated (standard deviation, confidence interval, # of samples)? This question extends to all figures where error bars are presented.\n- It is worrisome that the magnetic field still appears to affect the current measured in the control samples in Figure S1. The authors’ explanation regarding the Lorentz force may be correct, but this would not seem to explain why the attenuation in oxidation changes when the magnet is flipped, which appears to be both statistically significant (depending on the meaning of the error bars) and perhaps even larger than the difference between magnetic field/no magnetic field cases. The background effects noted above may also skew the results – if the background were subtracted and the peaks refit as suggested above, would the trend remain? Also, how temporally stable are the systems during electrochemical measurements? Was the magnetic field flipped several times, and statistics taken across flips, or was it only flipped once for north vs. south, and the associated statistics collected in batches? Without this information, it is difficult to tell whether the observed differences are real or an artifact of the data collection processes.\n\nFigure 2D: the absorption spectrum of COX-2 should be presented alongside the CD spectrum to clarify the nature and origin of the relevant electronic transitions.\n\nFigure 2F, G: the meaning of the energy scale in the x-axis should be clarified; particularly, what does the zero represent? Fermi level? Valence band maximum? Something else?\n\nFigure 2H: the mechanism of AA oxidation should be explained in more detail, particularly because it appears that AA and its products interact with COX-2 interact at different times at different sites. Am I correct in understanding from the diagram that effectively the same electron obtained from the oxidation of AA later contributes to the reduction of the product PGG-2, and that both of these electron transfer processes are potentially CISS-modulated? Because there is no net exchange of electrons, one might argue that CISS shouldn’t have any net effect either, but it may be that an interesting and subtle point can be made – i.e., supposing that the electron transfer path follows a single alpha helix that is bent in a U-shape so that the oxidation and reduction sites are located in close proximity on the same “face” of the enzyme, one could argue that CISS would in fact impact both processes in a concerted way despite no net charge transfer occurring. I have no idea if what I am suggesting is even remotely faithful to the actual structure of COX-2, however. The essential point is that the authors must do a much better job of explaining the mechanism in full detail so the readers don't have to project so much imagination onto the system, and possibly draw wildly inaccurate conclusions about it, as I may have done here. For instance, what are the yellow cyclic compound and green heme-looking structures supposed to represent, and what roles do they play? What are the PGG2and PGH2 intermediates, for the benefit of readers from non-biomedical backgrounds? Many important details regarding the nature of the overall process to form the PGE2 product are missing, and it is hard to fully evaluate the scientific claims without a more thoroughly sketched description.\n\nResults Section 4: The overall logic used to discriminate active site change or passivation from electron transport modulation does not make sense to me. What is the theoretical basis for assuming that a magnetic field will affect transport when an unmagnetized electrode is used to inject electrons? Does this arise from the magnetic field-dependent phase factor in the hopping integral (as discussed in the SI), and can additional detail be provided to explore this? Or is it something else? I find it curious that the same magnetic field dependence appears in the Au nanorod-COX-2 assemblies with a non-magnetic electrode as when just COX-2 is present on a magnetic electrode, as shown in Figure 2. It seems as though there could be an effect of the magnetic field that is unrelated to polarization of the injected spins by the electrode. Does COX-2 contain heme, as Figure 2H seems to indicate? If so, might it retain exhibit some paramagnetism from the Fe atom? This might lead to additional effects beyond CISS in conventional chiral molecules. At any rate, I still don’t see how this helps discriminate electron transfer from active site passivation, and it’s not self-evident to me that applying a magnetic field couldn’t affect the way things bind to active sites. Surely there are some more incisive techniques, perhaps akin to the fluorescence quenching experiment in Figure 4A and B that might allow adsorption on these sites to be probed more directly?\n\nN.B. The theoretical simulations (as described in “Numerical methods” on page 7 of the SI) appear to calculate the conductances under north or south applied magnetic fields considering the presence of a Ni (i.e., magnetic) electrode, yielding a spin polarization parameter of μ = ±1. This is unrealistically high even for magnetically saturated nickel, for which polarization of injected spins is closer to 30% - see, for instance, J. Phys. Chem. C 2024, 128, 6438-6445, and associated references.)\n\nFigure 4O: how, precisely, are the values in the “competency diagram” calculated? The term “enzyme activity regulation” is confusing because it’s not always apparent whether you are focusing specifically on the enantioselective aspect of it, which is presumably most interesting, or on the overall activity? Overall I think this diagram is more confusing than effective, and would recommend striking it altogether."}, "author_response": "Responsetothecomments fromreviewers:\nFirst, we would like to sincerely thank all the reviewers for their critical examination of our\nmanuscript. Their comments are very helpful for revising the manuscript. We have made\nsignificant changes to address their concerns. The issues they raised, and our responses, are\noutlinedbelow.\nREVIEWERCOMMENTS\nReviewer#1(RemarkstotheAuthor):\nThis manuscript introduces a conceptually novel strategy for regulating enzyme activity through\nelectron spin polarization, mediated by chirality-induced spin selectivity (CISS) effect of chiral\ngold nanohelices(CAu).Theauthorsdemonstrate thatCAu withdifferenthandedness(Lhvs. Rh)\nexhibit enantiospecific control of cyclooxygenase-2 (COX-2) catalytic activity through\nspin-aligned or mismatched electron transport pathways. This strategy surpasses conventional\nregulatory approaches, suchas nanozyme activity regulation or active-site interference regulation.\nNotably, the spin-dependent modulation is validated in both cellular and animal models of\nrheumatoidarthritis(RA),highlightingitstherapeuticrelevance.\nAlthough the CISS effect has been reported in physical systems, its direct application to the\nregulationofbiomolecularfunctionremainslargelyunexplored.Tothebestofmyknowledge,this\nis the first study to leverage electron spin polarization for the regulation of a biological enzyme,\nand to successfully translate this modulation into therapeutic outcomes. The findings are\nsupported by comprehensive electrochemical analyses, theoretical modeling, and in vitro/in vivo\nexperimental assessments. Overall, the manuscript represents a pioneering integration of spin\nphysics with redox enzyme modulation, with significant implications for both mechanistic\nenzymology and biomedical engineering. I recommend its publication pending minor revisions to\naddressthefollowingpoints.\n1.The mechanistic contributions require further clarification and quantification. In Figure 4O, the\nauthorsoutlinethreemechanismsunderlyingCOX-2 modulation:(i)nanozyme activity,(ii) active\nsite blocking, and (iii) CISS-driven electron transport. However, the rationale behind the reported\ncontribution percentages of each mechanism is not clearly explained. Please clarify how these\ncontributions were quantitatively determined. Providing a detailed explanation would strengthen\nthemechanisticinterpretationandcredibilityoftheconclusions.\nResponse:Thanksforyourinsightfulcomment.Followingyouradvice,wehaveclarifiedhowthe\nmechanistic contributions in Fig. 4O were quantified in the revised Supplementary Materials and\nhaveredrawnFig.4Obasedonthesecalculations.\nTo help understand the quantification contribution of each mechanism to COX-2 activity,\nadditional demonstration was added at the end of section 4 (Page 7 Line 15-19), “The relative\ncontributions of the three mechanisms were quantified for each Au sample and are presented in\nC\nthe radar plot (Fig. 4O). This visualization highlights how CISS selectively modulates COX-2\nactivity beyond the additive effects of catalytic activity and active-site passivation, providing a\nquantitative framework for the enantioselective regulation.” The following quantification\n1\nprocedure was included in Supplementary Materials in Page 9 as a newly added part of\n“QuantificationofMechanisticContributionsforFig.4O”.\nQuantificationofMechanisticContributionsforFig.4O:\nTheregulationofCOX-2activitybyLh-/Rh-/RAC- Auwasmeasuredas+5%,-48%,and-38%\nC\nby the fluorescence assay kit (Fig. 4A-B), and +14.86%, -31.31%, and -22.41% by\nelectrochemical measurements (Fig. 4C-D). Since both nanozyme catalytic activity and CISS\neffects were characterized by electrochemistry (CV curves), the electrochemical data were used\nforquantitative decomposition ofthe threemechanisms: nanozyme activity (x),active site change\n(y),andCISSeffect(z).\nNanozyme activity (x): In the absence of COX-2, all three samples (Lh-/Rh-/RAC- Au)\nC\npromoteAAoxidation (Fig. S17, Fig. S8 in the original version). The calculated contributions to\nCOX-2activitywere+18.80%,+34.12%,and+28.59%,respectively.\nActive site change (y): Since RAC- Au lacks a CISS effect (z = 0), but it inhibits COX-2\nC\nactivity.Therefore,theinhibitionisattributedtoactivesiteconformationalchanges:\nyRAC- Au=(-22.41%)-(+28.59%)=-51.0%\nC\nWeassume that Lh- and Rh- Au have similar effects on active site conformation due to similar\nC\nAusurfacestructures.\nCISS effect (z): For Lh- and Rh- Au, the contribution of CISS was obtained by subtracting x\nC\nyandfromtheoverallCOX-2modulation:\nzLh- Au=+14.86%-(+18.8%)-(-51.0%)=+47.06%\nC\nzRh- Au=-31.31%-(+34.12%)-(-51.0%)=-14.43%\nC\nThis difference between zLh- Au and zRh- Au indicates that CISS matching enhances\nC C\nspin-polarizedelectrontransport,whereasCISSmismatchsuppressesit.\nTo visualize the relative contributions, the x, y, and z values for Lh-/Rh-/RAC- Au were\nC\nsummed and normalized to calculate the relative percentage contribution of each mechanism, and\npresentedasaradarplotinFig.4O.Thecalculatedcontributionsare:\nforRAC- Au,x=35.92%,y=-64.08%,z=0;\nC\nforLh- Au,x=16.09%,y=-43.64%,z=40.27%;\nC\nforRh- Au,x=34.27%,y=-51.23%,z=-14.5%.\nC\nIn the radar plot, each axis (x, y, z) represents one mechanism, with its length corresponding to\nthe calculated percentage contribution. The overall COX-2 activity modulation can be interpreted\nasthesumofthesethreecontributions.\nIn summary, for Lh-/Rh-/RAC- Au, nanozyme catalytic activity promotes COX-2 activity,\nC\nactivesite modulation inhibits COX-2 activity,andCISSeffects caneither enhanceorsuppressto\nmodulatethefinaloutcome.\nactivityregulation.\n2. Although Figure S8 suggests weak and chirality-independent catalytic activity from CAu, the\nenhancement of COX-2 activity by Lh-CAu (~5%) may still partially stem from this effect. Can\ntheauthorsruleoutthiscontributionmoreexplicitly?\nResponse: Yes. As we explained above for Fig. 4O, the modulation of COX-2 activity by Au\nC\narises from a combination of factors, including its intrinsic nanozyme activity, changes in the\nenzyme active sites upon adsorption, and the CISS effect. Fig. S8 (corresponding to Fig. S17 in\nrevised version) confirms that Lh-, Rh-, and RAC- Au all promote AA oxidation, indicating\nC\nchirality-independent catalytic activity. Notably, RAC- Au is achiral and thus exhibits no CISS\nC\neffect, yet it inhibits COX-2 activity (Fig. 4A-4D), signifying that adsorption-induced changes in\nthe active sites can lead to inhibition. For Lh- and Rh- Au, applying a magnetic field as a\nC\nperturbation to spin-polarized electron transport demonstrated that the CISS effect indeed\ncontributed to the alteration of COX-2 activity. Taken together, although the enhancement of\nCOX-2 activity by Lh- Au is very slight (~5%), these results demonstrate that the slight\nC\nenhancement observed for Lh- Au cannot be explained solely by weak chirality-independent\nC\ncatalysis,butnecessarilyinvolvescontributionsfromtheCISSeffectandactive-sitemodulation.\nIn the revised version (Page 7 Line 11-19), it was clarified as “Notably, although\nnanozymatic activity (mechanism i) and active-site passivation (mechanism ii) clearly contribute\nto overall activity modulation, it does notaccount forthe chirality-dependentdifferences between\nLh- Au and Rh- Au. Remarkably, spin-polarized electron transfer via CISS can modulate the\nC C\npassive inhibition by Au adsorption. Thus, the relative contributions of the three mechanisms\nC\nwere quantified for each Au sample via a simple sum model and are presented in the radar plot\nC\n(Fig. 4O). This visualization highlights how CISS selectively modulates COX-2 activity beyond\nthe additive effects of catalytic activity and active-site passivation, providing a quantitative\nframeworkfortheenantioselectiveregulation.”forbetterunderstanding.\n3.In vivoimaging(Fig. 6A-B) andRAscoring(Fig. 6D-F) demonstrate apronouncedtherapeutic\nbenefit of Rh-CAu@MIP. Although the therapeutic effect of Rh-CAu@MIP in RA mice is\nattributed to spin-mediated COX-2 inhibition, other contributing factors (such as nanoparticle\nbiodistribution and MIP-induced pharmacokinetics) could also play a role. Could this observed\n3\ntherapeutic efficacy be explained by passive enhanced permeability and retention (EPR) rather\nthan spin-selective regulation? The authors are encouraged to discuss whether the preferential\naccumulationatinflamedjointsisprimarilydrivenbyCOX-2recognitionthroughthemolecularly\nimprinted polymer (MIP), orwhether itis largely aconsequenceofpassive EPR effects.Aclearer\ndistinctionbetweenthesemechanismswouldstrengthentheinterpretationofinvivoefficacy.\nResponse:Thank you for your insightful comment.We agree that passive EPR may contribute to\nnanoparticle accumulation in inflamed joints. However, our data indicate that molecular\nimprinting is the predominant factor conferring targeting specificity. As shown in Fig. 6A–B,\nAu@MIPCy5.5displayedmarkedlystrongerandmoreprolongedretentioninjointscomparedwith\nC\nAu@DOPCy5.5, which lacks molecular imprinting. Quantitative analysis of organs and joint\nfluorescence intensity (Fig. R2, corresponding to Fig. S33 in revised version) was supplemented\nto further confirm this difference. Given that both Au@MIPCy5.5andAu@DOPCy5.5 share similar\nC\nphysicochemical parameters (size, surface coating) relevant to EPR, the significantly enhanced\nretentionof Au@MIPisunlikelytobeexplainedsolelybypassiveEPR.Duetospaceconstraints,\nC\nthispointwasnotexplicitlydiscussedintheoriginalsubmission.\nIn the revised version, we have added discussion to clarify this issue (Page 9 Line 15-22).\nThe original text describing in vivo imaging has been revised to:“At 12 h post-injection, Ex vivo\nfluorescenceimages ofmajor organs(heart, liver,spleen,lungandkidney) and limbsshowed that\nall the Au@MIPCy5.5, Au@DOPCy5.5and DOPCy5.5significantly accumulated at liver and kidney,\nC\nconsistent with systemic nanoparticle clearance. Notably, Au@MIPCy5.5 exhibited substantially\nC\ngreater accumulation in inflamed limbs than Au@DOPCy5.5 and DopCy5.5 (Fig. 6B and S33),\nindicatingthatwhilepassiveEPRmaycontributetojointlocalization,theenhancedandprolonged\nretention of Au@MIP is primarily driven by active COX-2 recognition mediated by the MIP\nC\ncoating.”.\nFig. R2. (corresponding to Fig. S33 in revised version) Quantitative analysis of fluorescence\nintensityoforgansandlimbshowninFig.6B.\n4. Given that the MIP coating alters the surface chemistry and dielectric environment\nof the nanoparticles, the authors should discuss whether this coating could attenuate\normodulatethespin-polarized electron transport ofCAu.\nmodifiesboththesurfacechemistryandthedielectricenvironmentofthe Au,itwasdeducedthat\nC\nthe CISS would not be attenuated much as the CISS effect mainly originating from the chiral\nhelical structure of Au. However, to further clearly prove it, we carried out additional\nC\nexperimentsandtheoreticalsimulationtoexaminewhetherthiscoatinginfluencestheCISSeffect.\nExperimentally, we deposited Lh- Au@MIP, Rh- Au@MIP, and RAC- Au@MIP onto Ni\nC C C\nelectrodes, and measured the cyclic voltammetry responses in electrolytes of 4 mmol•L-1\nK Fe(CN) / K Fe(CN) and 0.1 mol•L-1 KOH under varied magnetic field orientations. The CV\n3 6 4 6\ncurves of Au@MIP exhibited trends consistent with those observed for bare Au (Fig. 3H-3J)\nC C\nupon magnetic field modulation. For Lh- Au@MIP, MF-S increased the redox peak current,\nC\nwhereas MF-N decreased it. Rh- Au@MIPshowed the opposite response, while RAC- Au@MIP\nC C\nexhibitednegligiblechangesunderthesameconditions(Fig.R3,correspondingtoFig.S25inthe\nrevisedversion).TheseresultsindicatethattheCISSeffectispreservedafterMIPcoating,andthe\nspin-dependentelectrontransportbehaviorof Auremainsdetectable.\nC\nFig.R3.(correspondingtoFig.S25intherevisedversion)CISSeffectof\nC\nAu@MIP.TheCVcurves\nobtained from working electrode deposited by Lh-\nC\nAu@MIP (A), Rh-\nC\nAu@MIP (B) and\nRAC-\nC\nAu@MIP(C),withorwithoutMF.\nTheoretically, when Au are coated with MIP, the surface gold atoms interact directly with the\nC\nMIP rather than with the surrounding electrolytes, thereby modifying the surface chemistry and\ndielectricenvironmentof Au.Thus,intheoreticalmodeling,thisisequivalenttoalteringthelocal\nC\non-siteenergiesofthesurfacegoldatoms incontactwiththeMIP.Toillustratethiseffect,wetake\nLh- Au as an example, and emphasize that opposite spin selectivity is observed in Rh- Au. Fig.\nC C\nR4 (corresponding to Fig. S26 in the revised version) presents the conductances G , G , G ,\nN S W/O\nand the corresponding spin polarization of Lh- Au by varying the on-site energies of the surface\nC\ngold atoms from +100 meV to -100 meV. Here, G , G , and G are the conductances under\nN S W/O\nupward magnetic field (MF), downward MF, and without MF, respectively. As shown in Fig.\nR4A-4C, both the conductance profiles and magnitudes remain largely unchanged for different\non-site energies. The spin selectivity increases slightly for positive on-site energies and decreases\nfor negative ones (Fig. R4D).These results demonstrate that the spin-polarized electron transport\nin AuisrobustagainstthepresenceoftheMIPcoating.\nC\nIntherevisedmanuscript,weaddedthis statementinthemaintextofPage 7Line30-32as“Both\nexperiments and theoretical simulations demonstrate that Au coated with the MIP ( Au@MIP),\nC C\n5\nmaintains high spin selectivity comparable to that of the pristine Au without the MIP (Fig.\nC\nS25-S26).”.Fig.S25-S26wereincludedintheSupplementaryMaterials.\nFig. R4. (corresponding to Fig. S26 in the revised version) Spin-selective electron transport\nthrough Lh- Au with the on-site energies of surface gold atoms fixed to specific values.\nC\nTheoretical conductancewith the on-site energies of surface gold atomsset to (A) 100 meV,(B)\n-100meV,(C)0meV,and(D)thecorrespondingspinpolarization. , ,and represent\nthe conductances under upward magnetic field (MF), downward MF, and without MF,\nGN GS GWO/\nrespectively.Forreference,panel(C)reproducesFig.3Oofthemaintext.\n5.The authorsemploy a simplified α-helicalmodelto simulate spin-dependentelectron transport\nthrough COX-2 (Fig. 2E–G and 4J–N). While this approach is widely used in CISS studies,\nCOX-2 is a large multidomain enzyme featuring complex tertiary structure and multiple electron\nrelay sites. Could the authors clarify whether the α-helix approximation is representative of the\nspecific domains involved in COX-2’s catalytic electron transfer? It would be helpful to specify\nwhether the known redox-active residues or cofactor-associated helices were considered in the\nmodeldesign.\nResponse: Yes, COX-2 is a large multidomain enzyme with a complex tertiary structure. By\nexamining the PDB database (3HS5), COX-2 is mainly composed of α-helices, separated by\nnon-helical domains. Notably, the key redox-active residues, such as Tyr385 and Trp387, are\nlocated within α-helical domains. Since the spin selectivity originates from α-helical structures, it\nis reasonableto approximate COX-2 as asingleα-helicalprotein whensimulating spin-dependent\nelectron transmission. In addition to the homogeneous α-helical protein composed of identical\namino acids, we also investigated disordered α-helical proteins of randomly distributed amino\nacids, which is simulated by assigning random on-site energies. Interestingly, these disordered\nα-helical proteins exhibit almost the same spin selectivity as the homogeneous one, as shown in\nFig.S2oftheSupplementaryMaterials.\nrealisticproteinsegments extractedfromCOX-2, whichlocatetotheleftandright ofthecatalytic\nactive site, as shown in Fig. R5 and R6. In these simulations, the on-site energy is set as vertical\nionization energy of amino acids in aqueous solution, obtained from first-principles calculations,\nwhile fixing the long-range hopping integral (J. Phys. Chem. A 2011, 115, 2900-2912.). One can\nseethattheconductancestronglydependsontheaminoacidsequenceandwillbeincreasedwhen\nnon-helical subsegments are removed (Fig. R5A-B and Fig. R6A-B). Nevertheless, both protein\nsegments exhibit very high spin selectivity, with spin polarization exceeding 83% (black lines in\nFig. R5C and Fig. R6C), which is lower than in the main text, owing to the shorter length of\nα-helical protein studied here. Moreover, the spin polarization profiles and magnitudes are quite\nsimilar between the full protein segments and those with all non-helical subsegments removed\n(Fig.R5CandFig.R6C).Inconclusion,theseresultsdemonstratethattreatingCOX-2asasingle\nα-helicalproteinisreliable,therebyvalidatingthenumericalresultsinthemaintext.\nIn the revised manuscript, we added this statement in Page 9 Line 4-12 in the Supplementary\nMaterials.\nFig. R5. Spin-selective electron transport through a protein segment extracted from COX-2.\nTheoretical conductance of (A) the full segment and (B) the same segment with all non-helical\nsubsegments removed, and (C) the corresponding spin polarization. The sequence of segment\n(324-385) is ‘GDEQLFQTSRLILIGETIKIVIEDYVQHLSGYHFKLKFDPELLFNQQFQYQNRIASEFNTLY’,\nlocated to the left of the catalytic active site Tyr385 (‘Y’, the last amino acid), where α-helical\nregionsarehighlightedinredandnon-helicalonesinblue.\nFig. R6. Spin-selective electron transport through a second protein segment extracted from\nCOX-2.Theoreticalconductanceof(A)thefullsegmentand(B)thesamesegmentbyremovingall\nnon-helicalsubsegments, and (C) thecorresponding spin polarization. The sequence of segment\n(385-458) is ‘YHWHPLLPDTFNIEDQEYSFKQFLYNNSILLEHGLTQFVESFTRQIAGRVAGGRNVPIAVQAVAK\nASIDQSREM’, located to the right of the catalytic active site Tyr 385 (‘Y’, the first amino acid),\nwhereα-helicalregionsareshowninredandnon-helicalregionsinblue.\n7\n6. The theoretical model of chiral gold nanohelices (CAu) presented in Fig. 3K–T relies on\nidealized helical structures with smooth surfaces and regular pitch. However, synthesized CAu\nparticles exhibit a distribution of geometries and surface irregularities, and are often\nfunctionalized with surfactants or ligands (e.g., CTAB or dopamine). Have the authors assessed\nhow variations in helical pitch, radius, or structural defects might influence spin polarization and\nconductance?Itwouldbeinformativetoincludeabriefparametricsensitivityanalysis.\nResponse:Yes,inourtheoreticalsimulations, Auaremodeledasidealizedhelicalstructureswith\nC\nsmooth surfaces and regular pitch. Following the reviewer’s suggestion, we discussed the\ninfluenceofhelicalpitch,radiusandstructuraldefectsonspin-selectiveelectrontransportthrough\nAu.As described in the Supplementary Materials, Au can beconstructed via vertically stacking\nC C\nmajor sectors, where the twist angle between two neighboring sectors is and the helical pitch\nis given by , with being the stacking distance. The structural parameters of each\n∆ \nsector arecharacterized bythe outerradius , the inner radius , andthe explementary angle\n2   ∆  \n. In the following, we systematically studied how variations' in helical pitch, radius, and\n3  3\nstructural defects affect the spin-polarized electron transport in Lh- Au.\nC\n3∆ \nThe numerical results in\nFig. R7-R8 and Fig. R9-R11 are calculated by averaging over 200 and 50 independent Lh- Au\nC\nsamples,respectively.OppositespinselectivitycanbedetectedinRh- Au.\nC\nInfluenceofirregularhelicalpitchonspin-polarizedelectrontransportin Au\nC\nIrregular helical pitch may arise during the synthesis of Au when the twist angle between\nC\ncertainsuccessivemajorsectorsis ratherthan .Ifthefractionofsuchsectorsisdenotedby\n,theaveragetwistangleandaverag'ehelicalpitchareexpressedas\n∆  ∆ \n\n' 2  \n∆  = 1−   ∆  +   ∆  ,  = '. (R1)\nItisevidentfromequation(R1)thatthehelicalpitchdepend1s−on  b  ot∆h  +  a  n∆d  .Inourstudy,\na single Lh- Au sample consists of many complete turns, and the number of major' sectors with\nC   ∆ \ntwist angle may vary from one turn to another, thereby producing Lh- Au with irregular\nC\nhelicalpitch. '\n∆ \nWefirstconsiderthe caseofnon-rotated sectors with , thefraction of whichis denoted\nby . Fig. R7 shows the conductances , , ' (top panels), and the corresponding\n∆  =0\ncurrents , , (bottom panels) of Lh- Au as increases from to . Here, , ,\nC     / \nand representthe currents under upwardMF,downwardMF,and withoutMF,respectively.\n/    0 0.1    \nCorrespondingly, the average helical pitch increases from to .\n/ \ndenotestheidealLh- Auwithregularhelicalpitch,andFig.R7AandR7DreproduceFig.\nC\n=2   ∆  2   0.9∆ \n3Oand 3Sof themain text,respectively.By inspectingFig. R7A-7C,we canseethatthe overall\n=0\nconductancesareslightlydecreasedbyincreasing ,while and becomemoreseparated\naround the Fermi energy eV.As a result, the corresponding currents and are\n\nfurtherseparatedinthepresenceofnon-rotatedsectors(Fig.R7D-7F).\n=−1.0    \nWe then examine the case of over-rotated sectors with , whose fraction is , as\nillustrated in Fig. R8. In this case, the average helical pitch'decreases from ' to\n∆  =2∆   \nwhen increasesfrom to .Itclearlyappearsthattheoverallconductances\n=2   ∆ \ndecrease with increasing' , while remains different from throughout the energy\n2   1.1∆    0 0.1\n'\n\nspectrum (Fig. R8A-8C). Likewise, the currents and are also separated from each other\n(Fig.R8D-8F).Theseresultsindicatethatthespinselectivityof Auisrobustagainstvariationsin\nC\nthehelicalpitch.\nFig.R7.(correspondingtoFig.S7intherevisedversion)Spin-selectiveelectrontransportthrough\nLh-\nC\nAu with irregular helical pitch characterized by . (A-C) Theoreticalconductance and (D-F)\nthe corresponding current-voltage curves for (A, D), (B, E), and (C, F).\n\ndenotestheratioofnon-rotatedmajorsectorstothetotalnumberofmajorsectors,with\n=0 0.05 0.1  \ncorrespondingtotheidealLh- Auwithregularhelicalpitch.As increasesfrom to ,the\nC   =\naveragehelicalpitchincreasesfrom to .Thenumericalresultsare\n0   0 0.1\naveragedover200Lh-\nC\nAusamples.Forreference,panels(A)and(D)reproduceFig.3Oand3Sof\n=2   ∆  2   0.9∆ \nthemaintext,respectively.\nLh-\nC\nAuwith irregularhelicalpitchevaluatedby .(A-C)Theoreticalconductanceand(D-F)the\ncorresponding current-voltage curves for '(A, D), (B, E), and (C, F). is the\n\nratio of major sectors rotated by to 'the total number of major sectors, with '\n=0 0.05 0.1  \ndenotingtheidealLh-\nC\nAuwithregu\n2\nla\n∆\nr\n\nhelicalpitch.As increasesfrom to ,the\n\nav\n\ne'r\n=\nag\n0\ne\nhelical pitch decreases from to ' . The numerical results are\n0 0.1\naveragedover200Lh-\nC\nAusamples.Panels(A)and(D)reproduceFig.3Oand3Softhemaintext,\n=2   ∆  2   1.1∆ \nrespectively.\nInfluenceofradiusonspin-polarizedelectrontransportin Au\nC\nWenextinvestigatetheinfluenceoftheradiusonspin-selectiveelectrontransportinLh- Au,as\nC\nshown in Fig. R9. In the original simulations, the outer radius is set to and the inner\nradius to , with a ratio . This ratio is chosen because, for the synthesized\n3 =5\nAu samples', the inner-to-outer ra'dius ratio is approximately 0.6. For and\nC  3 =3  3  3 =0.6\nyieldinga similar ratio, is generally smaller than over mostof the energy spectrum'(Fig.\n3 =7  3 =4\nR9A), andthe correspondingcurrents and are well separated(Fig. R9D).When the inner\n\nradius is reduced to or , the conductances are declined, while and become\n\nfurther separated aroun'd the Fermi energy eV (Fig. R9B-9C), leading to larger\n3 =0 2    \nseparationbetween and (Fig. R9E-9F).These results demonstrate thatthespin selectivity\n=−1.0\nof Auremainspronouncedforvariousradii.\nC    \nLh-\nC\nAu with differentouterradius and innerradius . (A-C)Theoreticalconductanceand\n(D-F)thecorresponding current-voltagecurvesfor ' (A, D), (B,\n3  3\nE),and (C,F). ' '\n3 =7,  3 =4  3 =5,  3 =0\n'\nInflue  nc 3 e=of5s,t  ru3c=tur2aldefectsonspin-polarizedelectrontransportin Au\nC\nFinally,we study spin-dependent electron transport through Lh- Au by taking into account two\nC\ntypes of structural defects, i.e., surface atomic vacancies and irregular major sectors with varying\nexplementary angles. Fig. R10 presents , , , and the corresponding spin polarization\nofLh- Au for and . Here, is thefraction ofgold vacancies relative to the total\nC       /O\nnumber of surface gold atoms, and denotes the ideal Lh- Au without vacancies. By\n=0.05 0.1   C\ninspecting Fig. R10A-10B, it is clear that although the conductances are decreased by increasing\n=0\n, is distinct from . Moreover, the spin polarization is considerably enhanced by these\nsurface atomic vacancies (Fig. R10C). Fig. R11 displays , , and , together with the\n\ncorrespondingspin polarization, of Lh- Au for and . Here, representsthe ratio\nC       /O\nof major sectors with explementary angles being either or to the total number of\n=0.05 0.1  \nsectors,with correspondingtotheidealLh- Auwheretheexplementaryangleis .We\nC\n2∆  4∆ \ncanseethatboththeconductanceprofilesandmagnitudesarelargelyunchanged(Fig.R11A-11B),\n=0 3∆ \nwhile the spinpolarization is slightly increasedbyincreasing (Fig. R11C).In conclusion,the\nspinselectivityof Auisrobustagainstvariationsinthehelicalpitch,theradius,andthestructural\nC  \ndefects. Moreover, the spin filtration efficiency of Au could be significantly enhanced by\nC\nconsidering,e.g.,differentradiusandsurfaceatomicvacancies.\nthroughLh- Auwith surfaceatomic vacanciescharacterizedby .Theoretical conductancefor\nC\n(A)and (B),and(C)thecorrespondingspinpolarization. isthefractionofgold\n\nvacancies relative to the total number of surface gold atoms, with denoting the ideal\n=0.05 0.1  \nLh- Au without any vacancy. The numerical results are averaged over 50 Lh- Au samples. For\nC   =0 C\nreference,thelightyellowcurveinpanel(C)reproducestheorangecurveinFig.3Rofthemain\ntext.\nFig. R11. (corresponding to Fig. S11 in the revised version) Spin-selective electron transport\nthrough Lh- Au constructed from irregular major sectors with varying explementary angles.\nC\nTheoretical conductance for (A) and 0.1 (B), and (C) the corresponding spin\npolarization. denotes the fraction of major sectors with explementary angles being either\n=0.05\nor relative to the total number of major sectors, with corresponding to the\n2∆  C 4∆    =0\nideal Lh- Au where the explementary angle is . The numerical results are averaged over 50\nC\nLh-\nC\nAusamples.Forreference,theblackcurveinpanel(C)reproducestheorangecurveinFig.3R\n3∆ \nofthemaintext.\nIn therevised manuscript, weaddedthis discussion alongwith Fig. R7-R11in themain text of\nPage 5 Line 14-17 as “Moreover, the spin selectivity of Lh- Au and Rh- Au is robust against\nC C\nvariations in helical pitch, radius, and structural defects (Fig. S7-S12), revealing pronounced spin\npolarizationofbothsystemsinthepresenceofgeometric orsurfaceirregularities,ionicscreening,\nor surface functionalization with different substances.”, and a new section “Robustness of spin\nselectivityin Au”ofPage9andFig.S7-S11intheSupplementaryMaterials.\nC\n7. While COX-2 serves as an excellent proof-of-concept model for RA therapy, the manuscript\nwouldbenefitfromamorein-depthdiscussionofthebroaderapplicabilityofthisapproach.Could\nthis CISS-based strategy be extended to other oxidoreductases? It is suggested to include a brief\ndiscussion on the potential generalizability of electron spin polarization for modulating diverse\nredoxenzymesintheDiscussionsection.\nResponse:Weappreciatethisinsightfulsuggestion.From amechanisticstandpoint,theregulation\nof COX-2 activity via CISS-mediated electron transfer modulation implies that electron spin\n12\npolarization could, in principle, be applied to other oxidoreductases. In preliminary trials, we\ntestedLh- AuandRh- Auonseveralrepresentativeoxidoreductases,includinglaccaseandlactate\nC C\ndehydrogenase (LDH). Interestingly, laccase exhibited enantioselective modulation, with Rh- Au\nC\nenhancingandLh- Auinhibitingitscatalyticactivityinamannerproportionaltotheenantiomeric\nC\nexcess (ee), whereas LDH showed no apparent response (Fig. R12, corresponding to Fig. S41 in\nthe revised version). These findings suggest that CISS-based spin regulation may extend to other\nredox-active enzymes, albeit in an enzyme-dependent fashion. Nevertheless, as enzymatic\ncatalysis is governed by complex structural and environmental factors, it remains challenging to\nunambiguously attribute these effects solely to the CISS mechanism without further systematic\ninvestigation.\nIn the revised manuscript, the following discussion has been added in Page 11 Line 5-13:\n“Beyond COX-2, the principle of spin-selective electron transport may also apply to other\noxidoreductases that rely on multistep electron relay pathways. Preliminary experiments with\nLh- Au and Rh- Au on laccase and lactate dehydrogenase (LDH) revealed enzyme-dependent,\nC C\nenantioselective modulation of catalytic activity, indicating broader potential applicability (Fig.\nS41). However,as redoxcatalysis involves multiple coupled factors, definitive attribution of such\neffects to CISS requires systematic, enzyme-specific studies. While such exploration lies beyond\nthe present scope, our COX-2 system provides a robust framework, highlighting CISS as a\npromisinggeneralizablemechanismforredoxenzymeregulation.”\nFig.R12.(correspondingtoFig.S41intherevisedversion)Modulationoflaccase(A)andLDH(B)\nactivitywithCAuwithvariedee.\n8. Figures 3 and 4 contain extensive graphs and information. While they are important for\nmechanism clarification, it is strongly suggested to add schematic arrows or visual cues\nhighlightingthe “spinalignmentversusmismatch” pathways,whichwillimprove thereadability\nandcomprehension.\nResponse: Thanks for this constructive suggestion. To improve clarity and readability, we have\nrevised Fig. 3 (Fig. R13) by addingschematic visual cues thatdistinguish the spin-alignment and\nspin-mismatch pathways. Specifically,a newschematic (nowincludedasFig. 3K) illustrates how\nthe alignment or mismatch of spin selectivity between the ferromagnetic electrode and Au\nC\ngovernselectrontransportefficiency.ItprovidesaclearvisualrepresentationoftheCISSeffectin\nC\nWe made additional demonstration at the revised main text of Page 4 Line 35-37: “It indicates\nthat spin-polarized electrons induced by MF-S can selectively traverse Lh- Au (spin matched),\nC\nwhile those induced by MF-S cannot traverse Lh- Au (spin mismatched). For Rh- Au, the\nC C\nsituationisopposite(Fig.3K).”.\nFig.R13.TherevisedFig.3\nIn this study, the authors investigated the effect of chiral gold nanohelices (cAu) on COX-2\nactivity and enhanced its targeting capability through molecularly imprinted polymers (MIPs),\nthereby improving its translational potential. This work introduces a conceptual shift: enzyme\nactivity can be modulated not solely through static structural engagement, but via the spin\ndynamics of electron flow at the molecular level. However, the manuscript still has the following\nissues:\n1．The study demonstrated the activity of COX-2 regulated by spin-polarized electrons through\nelectrochemicalCVcurves(Figs. 2B-C)andtheoreticalcalculations(Figs.2E-G).However,itdid\nnot incorporate circular dichroism (CD) spectroscopy or molecular dynamics simulations to\nanalyzepotentialconformationalchangesinCOX-2uponcAubinding.\nResponse: We thank the reviewer for this insightful comment. Following your suggestion, we\nanalyzed the possible conformational changes of COX-2 bound by Au from both experimental\nC\nandtheoreticalperspectives.\nExperimentally, to assess whether binding to Au induces conformational changes in COX-2,\nC\nwe performed circular dichroism (CD) spectroscopymeasurements.After incubating COX-2 with\nAu, the dispersions were centrifuged twice to remove unbound protein, ensuring that the\nC\nmeasured spectra reflected the close-contact layer of COX-2 on the Au surface. For comparison,\nC\nCD spectra of free COX-2 (20 µg/mL) was also recorded. The spectrum of COX-2 alone\ndisplayed a positive peak at ~195 nm and two negative peaks at ~208 nm and ~220 nm,\ncharacteristic of α-helical secondary structures. Importantly, the CD spectra of COX-2 in the\npresenceofLh- Au,Rh- Au,orRAC- Auallexhibitedsimilarfeatureswithnegligibledifferences\nC C C\ninpeakpositionsorintensities(Fig.R14,correspondingtoFig.S20intherevisedversion).These\nresultsindicatethat Aubindingdoesnotcausesignificantalterationofthesecondarystructureof\nC\nCOX-2.\nFig. R14. (corresponding to Fig. S20 in the revised version) CD spectra of COX-2, and COX-2\nbounded to Lh-\nC\nAu, Rh-\nC\nAu, RAC-\nC\nAu (A) and the zoomed-in view in the wavelength range of\n180-300nm(B).\nTo theoretically explore the structural stability of COX-2 on gold, we carried out general\nall-atom molecular dynamics (MD) simulations when COX-2 is adsorbed on an Au substrate\n15\nrather than Au. as the latter contains too many gold atoms to perform MD simulations. The\nC\nCOX-2structureisobtainedfromthePDB(3HS5),whiletheAusubstrateischosenasanAu(111)\nslab, where the former is simulated with the CHARMM36 all-atom force field (J. Chem. Theory\nComput. 2012, 8, 3257-3273; Nat. Methods 2017, 14, 71-73.), and the latter is described by a\nface-centered cubic Lennard–Jones potential (J. Phys. Chem. C 2008, 112, 17281-17290.)]. This\nhybrid COX-2@Au system was solvated with approximately 124,000TIP3P water molecules and\nneutralized with Na+ counterions, as placed in a periodic cubic box of 16×16×18.5 nm³.\nThe MD\nsimulations were conducted using the GROMACS package at 310 K to mimic physiological\nconditions.\nAs shown in Fig. R15A (corresponding to Fig. S21 in the revised version), the backbone\nRMSD of COX-2 initially increases, revealing a rapid conformational adjustment owing to the\nVan der Waals interactions from the Au substrate. After 25 ns, the backbone RMSD fluctuates\nbetween 1.8 nm and 2.1 nm, indicating that COX-2 maintains structural stability without global\nunfoldings. The evolution of COX-2 secondary structure is presented in Fig. R15B. The helical\nstructures remain dominant domains and their number only slightly fluctuates around an\nequilibrium value throughout the simulation, indicating that adsorption on Au surface does not\ndisruptthesecondarystructureofCOX-2. Therepresentative conformationalsnapshotsofCOX-2\nat 0, 50, 100, and 150 ns are shown in Fig. R15C-15F. The COX-2 structure undergoes\nrearrangement from 0 to 50 ns due to domain rotation and partial separation relative to the Au\nsubstrate, but remains nearly unchanged thereafter, consistent with the RMSD analysis. In\nconclusion, these results confirm that the COX-2 structure remains almost the same upon\nadsorption onto the Au substrate, indicating the structural stability of COX-2 and the reliable\nsimulationsinthemaintext.\nIntherevisedmanuscript,weaddedthisstatementandFig.R14-R15inthemaintextofPage6\nLine 31-32 as “although such adsorption caused negligible changes in the secondary structure of\nCOX-2(Fig.S20andS21).”,andFig.S20-S21intheSupplementaryMaterials.\nsencondary structure change of COX-2upon adsoption on Au surface. (A)Time evolution of the\nRMSD ofthe COX-2backbonewhen adsorbed on the Au(111)surface. (B)Time evolution of the\nnumber of residues corresponding to detailed secondary structures in chain A of COX-2. And\nTypicalsnapshotsoftheCOX-2structureontheAu(111)surfaceat0ns(C),50ns(D),100ns(E),\nand150ns(F).\n2. The theoretical calculations (Figs. 2E-G, 3K-M) employed a tight-binding model to simulate\nelectron transport, but were conducted under the assumption of a vacuum environment, thereby\nneglecting critical biointerface factors such as protein surface hydration layers or ionic screening\neffects.\nResponse:Wethank the reviewer for this insightful comment. Indeed,our theoretical simulations\nhave already taken the solution environment into account. As noted, the CV measurements of\nCOX-2, Au and Au@COX-2 were performed in electrolyte environments. Under such\nC C\nconditions,aportionofelectronscanpropagatefromtheworkingelectrodeintothesolutionrather\nthanreachingthecounterelectrode,which refersto electronleakage, asdescribedin equation(4),\n(9) and (14) of the Supplementary Materials. In our theoretical modeling, this electron leakage\neffect is consistently incorporated into the numerical calculations of COX-2, Au and\nC\nAu@COX-2,therebyreproducingtheelectron-transportbehavioroccurringinbuffersolutions.\nC\nInelectrolyteenvironments,COX-2and Auaresurroundedwithvariousspecies,suchaswater\nC\nmolecules, ions, surfactants, and ligands. In such cases, the on-site energies of amino acids or\n17\nsurfacegold atoms in contactwith these substanceswillbemodified simultaneously.As shownin\nFig. S2 of the Supplementary Materials, the spin selectivity of COX-2 remains nearly unchanged\nwhen the on-site energies of amino acids are assigned as random variables. Likewise, the\nspin-polarized electron transport in Au is largely unaffected by varying the on-site energies of\nC\nsurfacegoldatoms,asweclarifiedinResponsetoComment4byReviewer#1.\nTo further demonstrate the robustness of spin-polarized electron transport in Au against\nC\nsurface adsorption effects, we considered the most disordered case, where the on-site energies of\nsurface gold atoms are randomly and uniformly distributed within the range , with\ndenotingthedisorderstrength.Wetake Lh- Auasanexample, andopposite spinselectivity is\nC\n−  /2,  /2\nobserved in Rh- Au. Fig. R16 (corresponding to Fig. S12 in the revised version) presents the\nC\n\nconductances , , , and the corresponding spin polarization of Lh-cAu for\nand meV, where, , , and represent the conductances under upward MF,\n/   =100\ndownward MF, and without MF, respectively, as defined in the main text. As shown in Fig.\n200       /O\nR16A-B, both the conductance profiles and magnitudes remain nearly unchanged compared with\nthe idealized Au without disorder (Fig. 3O of the main text). Moreover, the spin polarization\nC\nshowsnoobservable differencefordifferentdisorder strengths.These results demonstrate thatthe\nspin-polarized electrontransportin bothCOX-2 and Auremainshighly robustinthepresenceof\nC\nsurfacehydration,ionicscreeningorsurfaceadsorptioneffects,sodoesin Au@COX-2.\nC\nIntherevisedmanuscript,weaddedthisstatementandFig.R16inthemaintextofPage5Line\n14-17:“Moreover,thespinselectivityofLh- AuandRh- Auisrobustagainstvariationsinhelical\nC C\npitch, radius, and structural defects (Fig. S7-S12), revealing pronounced spin polarization of both\nsystems in the presence of geometric or surface irregularities, ionic screening, or surface\nfunctionalization with different substances.”, and in the Supplementary Materials of Page 3 as\n“Indeed,thiselectronleakageeffect,describedinequation(4)andfurtherinequation(9)and(14),\nreproduces the electron-transport behavior occurring in buffer solutions, where during CV\nmeasurements in electrolyte environments, a portion of electrons propagates from the working\nelectrode into the solution rather than reaching the counter electrode.” and Page 7 “The electron\nleakage process is described by adding additional self-energies and in the Green’s\nfunction, which is consistently incorporated into the numerical calcurlations ofrCOX-2, cAu, and\nC  Au\ncAu@COX-2.”. In addition, a new section “Robustness of spin selectivity in Au” and Fig. S12\nC\nwerealsoaddedintheSupplementaryMaterials.\nFig. R16. (corresponding to Fig. S12 in the revised version) Spin-selective electron transport\nthroughLh- Auwith disorderedon-siteenergiesofsurfacegoldatoms.Theoretical conductance\nC\nfor meV (A) and meV (B), and (C) the corresponding spin polarization.\ndenotes the disorder strength, with the on-site energies of surface gold atoms randomly and\n=100 200 \nuniformlydistributed within .Thenumerical resultsareaveragedover50Lh- Au\nC\n−  2,  2\n18\nsamples.Forreference,thelightbluecurveinpanel(C)reproducestheorangecurveinFig.3Rof\nthemaintext.\n3．Whiletheresultssection(Figs.4H-I)identifiedspinmismatchastheprimarycauseofactivity\ninhibition, the potential contribution of conformational perturbation was not conclusively ruled\nout.\nResponse: Thank you for pointing this out, and we apologize for the potential misunderstanding.\nAs shown in Fig. 4O, conformational perturbation induced by Au is indeed one of the\nC\ncontributors to COX-2 regulation. Our experiments in Figs. 4H–4I were specifically designed to\ndemonstrate that the observed enantioselectivity—namely,the enhancement ofCOX-2 activity by\nLh- Au and the inhibition by Rh- Au—stems from the CISS effect rather than from\nC C\nconformational changes. In other words, while conformational perturbation contributes to the\noverall modulation of COX-2 activity, it does not account for the chirality-dependent differences\nobserved between Lh- Au and Rh- Au. This clarification has been incorporated into the revised\nC C\nmanuscripttoavoidambiguity.\nIn the revised version, we modified the conclusion in Mechanism section in Page 7 Line\n11-14 into “Notably, although nanozymatic activity (mechanism i) and active-site passivation\n(mechanism ii) clearly contributes to overall activity modulation, it does not account for the\nchirality-dependentdifferencesbetweenLh- AuandRh- Au.”\nC C\n4. The study appears more conjectural in nature, employing an overly idealized model that lacks\ntheoretical simulations to elucidate the fundamental mechanism by which spin polarization\ndirectionregulateselectrontransferpathways.Whiletheworkdemonstratesinnovationinmaterial\ndesign, its core findings suffer from insufficient quantitative analysis. Although the observed\nphenomenaarerevealed,theresearchfailstodelvedeeperintocriticalparameterssuchasmaterial\ncomposition ratios and enantiomeric excess of chiral structures that could significantly impact\nenzymaticactivity.\nResponse: We appreciate your insightful comment. Indeed, our present work primarily\ndemonstrates at the phenomenological level that electron spin polarization can modulate enzyme\nactivity, while the microscopic mechanism governing the spin-dependent electron transfer\nbetween AuandCOX-2remainsto befurtherelucidated.Nevertheless, itiswell-establishedthat\nC\nelectron transport can proceed via non-contact tunneling, and both experimental evidence and\ntheoretical considerations support that the CISS effect critically influences electron transfer\nefficiency. This spin-dependent modulation mechanism is fundamentally distinct from\nconventionalactive-sitemediatedenzymeregulationandthusrepresentsakeyconceptualadvance\nofthisstudy.\nRegarding the influence of material composition and chirality, we fully agree that parameters\nsuch as enantiomeric excess (ee) and composition ratios can substantially affect enzymatic\nregulation.Toaddressthis, we have performed additionalexperiments andtheoretical simulations\nexamining COX-2 activity as a function of the ee values of Au samples (ee = +100%, +80%,\nC\n+40%, +20%, 0, -20%, -40%, -80%, and -100%). The CV curves of AA oxidation on\nCOX-2-modified Au electrodes with varied ee values are presented in Fig. R17A, and the\nC\ncorresponding baseline-corrected CVs are shown in Fig. R17B. The oxidation peak currents (I ,\nP\nC\non COX-2 activity (%, denoted as y). The results reveal an approximately linear correlation\nbetweenyandeewiththeequationy=0.2664x+82.612(R² =0.9208)(Fig.R17D),confirming\nthat the Au can regulate COX-2 activity in an enantioselective and quantitatively predictable\nC\nmanner.\nFig. R17. (corresponding to Fig. S15 in the revised version) Modulation of COX-2 activity with\nvaryingeeof\nC\nAu.(A)CVcurvesofAAoxidationrecordedonCOX-2modified\nC\nAuelectrodeswith\ndifferent enantiomeric excess (ee) values. (B) Corresponding positive semi-cycles after baseline\nfittingandbackgroundsubtractionoftheCVcurvesin(A).(C)Extractedoxidationpeakcurrent(I )\nP\nvaluesfrom(B)atpotentialsaround1.2V.(D)Linearcorrelationbetweentherelativemodulation\nofCOX-2activityandeevalues,demonstratingtheenantioselectiveregulationbehavior.\nTheoretical results also verified the regulation baviour of Au with varying ee., Fig. R18A\nC\ndisplaysthecurrent-voltagecurvesof Au@COX-2byrangingtheeevalueof Aufrom-100%to\nC C\n100%. It clearly appears that, for any given voltage, the current increases monotonically with\nincreasing ee (Fig. R18A). Indeed, the current at a fixed voltage of, e.g., 1.3 V, increases linearly\nwithincreasingee,asillustratedinFig.R18B.Therefore,weconcludethatthecatalyticactivityof\nCOX-2 can be considerably influenced by the ee of Au, thereby manifesting electron-spin\nC\npolarizationaseffectiveapproachinenzymaticregulation.\nC\nAu@COX-2 at different ee values of\nC\nAu in the absence of MF. (A) Theoretical current-voltage\ncurveswith eerangingfrom-100%to100%,and(B)thecurrentat1.3Vasafunctionofee.The\nverticallineinpanel(A)representsthevoltageof1.3V.\nIn the revised version, the modulation of COX-2 activity varying with ee of Au was included\nC\nin the main text in Page 5 Line 34-39: “Furthermore, we experimentally and theoretically studied\nthe modulation of COX-2 activity with varied enantiomeric excess (ee) of Au. The results\nC\nrevealed an approximately linear correlation between the relative modulation of Au on COX-2\nC\nand ee (Fig. S15) ,demonstrating that the Au can regulate COX-2 activity in an enantioselective\nC\nandquantitatively predictable manner.And the theoreticalresults consistently showedgood linear\nrelationship between current and ee values (Fig. S16).” and Fig. S15-S16 in the Supplementary\nMaterials.\n5. In Figure 4B, the inhibitory effect of cAu on COX-2 activity is weaker than that of celecoxib.\nWhatadvantagesdocAumaterialsofferovertraditionalrheumatoidarthritisdrugs?\nResponse: Thank you for your question. In this manuscript, celecoxib was used as a positive\ncontrolto validate theregulationability of Au onCOX-2 activity,and theadvantage comparison\nC\nis notthe purpose of this manuscript.The efficacyof celecoxib hasbeenwell established to show\na concentration-dependent behavior, which may lead to the development of drug resistance upon\nprolonged use. In contrast, Au can modulate COX-2 activity via multiple mechanisms as shown\nC\nin Fig. 4O, rather than direct inhibition at the catalytic pocket. This may offer an alternative\nchoice with potential advantages including reduced likelihood of resistance development and the\npossibility for precise,site-specific enzyme modulation,although no apparentdrugresistance was\nobservedwitheithercelecoxibor Au@MIPover6weeksserialpassagingexperiment(Fig.R19).\nC\nOverall, current Au provides a promising proof-of-concept for spin-based therapeutic strategies\nC\nandopenanewparadigmforrheumatoidarthritistreatments.\n6.Regarding the mechanism of COX-2 inhibition, a major difference between Rh-cAu@MIP /\nRAC-cAu@MIPandcelecoxibisthatthelatterdirectlybindstotheactivesiteofCOX-2,whereas\nthe former does not, which could affect drug resistance. It is recommended to include relevant\nvalidationofresistancedevelopment.\nResponse:Thankyouforthis valuablecomment.Asweclarified above,thisstudyprimarilyaims\nto provide a proof-of-concept strategy for COX-2 activity regulation rather than to replace\ncelecoxib. Nevertheless, we agree that drug resistance development is an important concern.\nC\nregulates enzyme activity through multiple cooperative mechanisms, including the catalytic\nactivity of Au, active-site passivation via adsorption, and electron transport modulation through\nthe CISS effect. Such multi-targeted regulation is theoretically less prone to resistance\ndevelopmentcomparedtosingle-siteinhibitors.\nTopreliminarilycomparetheresistancepotentialofcelecoxibandRh- Au@MIP,weperformed\nC\na serial passaging experiment in LPS-stimulated RAW264.7 macrophages. The half-maximal\ninhibitoryconcentrations(IC )forsuppressionofLPS-inducedPGE productionweredetermined\n50 2\nto be 48.7 nmol•L-1 for celecoxib (Fig. R19A-B) and 40.8 μg•mL-1 for Rh- Au@MIP (Fig.\nC\nR19C-D).Then,cellswere exposedto50nmol•L-1celecoxib or40μg•mL-1Rh- Au@MIPfor24\nC\nh,followedbyculture indrug-free medium for threepassage-confluencycycles.After every three\npassages (~6 days), cells were reseeded, stabilized, and re-stimulated with LPS (100 ng•mL-1) in\nthe presence of celecoxib (50 nmol•L-1) or Rh- Au@MIP (40 μg•mL-1) for 12 h, and the\nC\nsupernatants were collected for PGE quantification. This procedure was repeated for six\n2\nconsecutive cycles (Weeks 1-6). As shown in Fig. R19E, neither celecoxib nor Rh- Au@MIP\nC\nexhibited a discernible loss of inhibitory efficacy across the six-week period, indicating no\napparentresistancedevelopmentundertheseconditions.\nIn the revised version,we includedthis in Page 11Line 1-3: “The multi-mechanistic regulation\nof enzyme activity by Au may confer a theoretical advantage in resistance prevention, although\nC\nboth Rh- Au@MIP and celecoxib maintained stable efficacy in preliminary 6-week serial\nC\npassagingexperiments.”\nFig. R19. Drug resistance development of celecoxib and Rh- C Au@MIP. (A) PGE 2 concentration in\nthe supernatant of LPS-stimulated macrophages treated with varied concentrations of celecoxib\n(Cele) and (B) the corresponding function of PGE\n2\nlevel change with Cele concentration for\ncalculating IC\n50\nof Cele. (C) PGE\n2\nconcentration in the supernatant of macrophages treated with\nvaried concentrations of Rh-\nC\nAu@MIP, and (D) the corresponding function of PGE\n2\nlevel change\nwith Rh-\nC\nAu@MIP concentration for calculating IC\n50\nof Rh-\nC\nAu@MIP. (E) PGE₂ concentration\nmeasuredinmacrophagesco-incubatedwithCeleorRh- Au@MIPduringserialpassagingculture\nC\nover6weeks.\n22\n7.Sections1and2onlyelaborateonthemechanismbywhichcAumodulatesCOX-2activity,\nbut\nfailtoexplainhowcAuaffectsCOX-2proteinexpressionasshowninFigure5G.\nResponse: Thank you for this insightful comment. Although the main focus of our study is the\nregulation of COX-2 activity for inflammation modulation, it is worth noting that celecoxib and\nother COX-2 inhibitors have been reported to not only suppress COX-2 activity but also reduce\nCOX-2 protein expression through transcriptional and post-transcriptional mechanisms. Previous\nstudies showed that celecoxib treatment significantly decreased COX-2 mRNAand protein levels\ninLPS-stimulatedRAW264.7macrophages(Atherosclerosis.2019,284,50-58；OncolLett.2019,\n18(6),5793-5800.),andreducedCOX-2expressioninvivothroughinhibitionofNF-κBactivation\n(Am J Physiol Lung Cell Mol Physiol. 2010, 299, L184–L191). These findings suggest that\ninhibitionofCOX-2activitymaytriggerfeedbacksuppressionofitstranscription,asCOX-2isan\ninducible enzyme upregulated by inflammatory mediators. In our study, both Rh- Au@MIP and\nC\nRAC- Au@MIP inhibited COX-2 activity and attenuated macrophage inflammation, which may\nC\nexplaintheconcurrentreductionofCOX-2 proteinexpressionobservedin Fig.5G.Therefore,we\nincluded this analysis to compare the similarity between Au and celecoxib in inflammation\nC\nmodulation.\n8.In Figures 4B and 5H, both COX-2 activity and protein levels in the celecoxib group are lower\nthan those in the Rh-cAu@MIP and RAC-cAu@MIP groups. However, in Figure 5I, the PGE₂\nlevelinthecelecoxibgroupisparadoxicallyhigherthanintheothertwogroups.Thisdiscrepancy\nrequiresfurtherclarification.\nResponse:Thank you for noticing this. Since PGE is a downstream product ofCOX-2-catalyzed\n2\narachidonic acid metabolism, inhibition of COX-2 activity is expected to reduce PGE synthesis.\nRh- Au@MIP and RAC- Au@MIP groups(Fig. 4B and 5H), in cellular assays, PGE levels can\nC C 2\nalso be influenced by factors beyond COX-2 activity, including arachidonic acid availability,\nactivityofotherprostaglandinsynthases,andmetabolicfeedbackpathways.Thiscanleadtosmall\ndifferences that don’t perfectly match COX-2 inhibition. In our data, although the mean PGE\n2\nlevelinthecelecoxibgroupappearsslightlyhigher thanthatintheRh- Au@MIPgroup(Fig.5I),\nC\nthe difference is not statistically significant. Therefore, it remains consistent with our conclusion\nthatRh- Au@MIPreducesinflammationbyinhibitingCOX-2andloweringPGE production.\nC 2\n9. Does intravenous injection of MIP-modified cAu pose any risks of immunogenicity or\nlong-terminstability?\nResponse:Thank you for raising this important question. Our in vivo studies indicate that\nAu@MIP exhibit low immunotoxicity. Histological analysis of major organs showed no notable\ntissue damage, and Rh- Au@MIP treatment reduced serum levels of inflammatory cytokines,\nC\nsupportingminimalimmuneactivation.\nThe immunogenicity of gold nanoparticles (AuNPs) depends strongly on size, shape, surface\ncharge, coating, and dose(Chem. Soc. Rev. 2009, 38, 1759-1782.). PEGylated and polydopamine\n(PDA)-coatedAuNPshavebeenreportedtoshowlowimmunogenicity andgoodbiocompatibility\nin vivo (Chem. Soc. Rev. 2012,41, 2256-2282; ACS Nano 2022, 16(11), 18119-18132.). PDA, in\nparticular, provides ROS scavenging and anti-inflammatory effects (ACS Nano 2013, 7:9384–\n23\n9395; Bioact. Mater.2020, 5(3), 522-541.). In our system,Au@MIPwere prepared via dopamine\npolymerization-mediated entrapment of COX-2, forming a thin PDA shell that enhances both\nbiocompatibilityandstability.Moreover,ournewlyaddedpharmacokineticdataindicatedthatthe\nelimination half-lives (t ) of Lh- Au@MIP, Rh- Au@MIP, and RAC- Au@MIP were 23.41 h,\n1/2 C C C\n26.98 h, and 22.39 h, respectively, with corresponding mean retention times (MRT) of 35.78 h,\n38.18 h, and 33.77 h (Fig. R20, corresponding to Fig. S32 in the revised version). These results\nindicate rapid clearance and low potential for long-term accumulation. Together, these findings\nsuggest that MIP-modified Au nanoparticles possess good in vivo biocompatibility, low\nC\nimmunogenicity,andfavorableclearancekinetics.\nFig.R20.(correspondingtoFig.S32intherevisedversion)ThepharmacokineticsofLh-\nC\nAu@MIP,\nRh- Au@MIPandRAC- Au@MIPmeasuredbyserumAu0concentrationinatmultipletimeponits\nC C\n(5min,15min,30min,2h,4h,6h,12h,24h,48h,72h,96h)posti.vinjectionviaICP-MS.The\ninsettableshowsthepharmacokineticsparameters,includinghalf-lives(T ),areaundercurve\n1/2\n(AUC),clearrate(CL)andmeanrententiontime(MRT),forLh- Au@MIP,Rh- Au@MIPand\nC C\nRAC- Au@MIP.\nC\n10.ThelayoutandformattingofFigures5and6aredisorganizedandneedimprovement.\nResponse:WehavereorganizedFig.5(Fig.R21)andFig.6(Fig.R22)toimprovethereadability.\n11. Has the potential for long-term retention or toxicity of the nanomaterials used in this study\nbeen fully evaluated in vivo?Although the preliminary biocompatibility results appear favorable,\n26\nhaveanyextended-durationormultiple-dosetoxicityassessmentsbeenconducted?\nResponse:We appreciate the reviewer’s insightful question regarding the long-term retention and\npotentialtoxicityofthenanomaterialsusedinourstudy.\nWe performed a comprehensive biocompatibility and toxicity assessment at the end of 14 days\ntherapeutic period, which we consider a relatively long-term evaluation in the context of\npreclinicalsafety studies.These evaluations included hematologicalanalysis, serumbiochemistry,\nand histopathological examination of major organs, all of which showed no significant\nabnormalitiesorsignsofsystemictoxicity(Fig.S38-S40).Weagreethatfurtherextendedtoxicity\nstudies will provide a more comprehensive safety profile for clinical translation and will be\nconsideredinthefuturestudy.\nIn the revised version, to further confirm the clearance of Au@MIP in blood circulation, we\nC\ntested the pharmacokinetics profile of Au@MIP in serum by collecting Retro-Orbital blood for\nC\nICP-MS measurements for Au quantification post i.v. injection of Au@MIP. It showed that the\nC\nhalf-lives is 23.41h, 26.98hand22.39h,andmean retentiontime (MRT) is 35.78h, 38.18hand\n33.77 h for Lh- Au@MIP, Lh- Au@MIP and RAC- Au@MIP, respectively (Fig. S32). It means\nC C C\nthat Au@MIP show good clearance efficiency in vivo. We included this in Page 9 Line 10-15:\nC\n“Pharmacokinetic analysis further revealed that Lh- Au@MIP, Rh- Au@MIP, and\nC C\nRAC- Au@MIP exhibited elimination half-lives (t ) of 23.41 h, 26.98 h, and 22.39 h,\nC 1/2\nrespectively, with corresponding mean retention times (MRT) of 35.78 h, 38.18 h, and 33.77 h\n(Fig.S32).Theseresultsindicatefavorablecirculationstabilityandmoderatesystemicpersistence,\nallowing sufficienttime for effective accumulation at inflamed joints while minimizing long-term\nretentionandsystemicburden.”\n12.Figure6H – Histology – someoftheseimagesdonotlooklike theyaresectionedfromthe\nsamelocationmakingcomparisondifficulttojudge.\nResponse: We appreciate the reviewer’s comment. All histological sections were obtained from\nthe joint region between femur and tibia. However, severe inflammatory damage disrupted the\nnormal joint architecture in some groups, which may have created the impression of different\nsectioning sites. In addition, because of this structural disruption, the exact paraffin sectioning\nplanewasnotalwaysidenticalacrosssamples.Furthermore,theimagesintheoriginalsubmission\nwere not consistently oriented, which further increased the difficulty of comparison. Following\nyour advice, we re-sectioned the paraffin-embedded tissues and performed additional staining to\nobtainsectionsfromcomparableplanes.\nIn the revised version of Fig. 6H (Fig. R23), all images have been reoriented consistently and\npresent joint regions with similar anatomical profiles, facilitating clearer and more reliable\ncomparisonoftherapeuticoutcomes.\nInthis article,theauthorsinvestigatetheconstructionofchiralnanohelix-enzyme assemblieswith\nthe goal of employing the chiral-induced spin-selectivity (CISS) effect to modulate the oxidation\nof arachidonic acid, which mediates inflammation and has applications in the treatment of\nrheumatoid arthritis. Beyond this specific therapeutic context, modulation of enzyme activity\nusingCISS offersanimportantmeans ofcontrollinga widerange of biologicalprocessesthatcan\ncomplement conventional chemical approaches. By attaching the cyclooxygenase-2 (COX-2)\nenzyme to chiral gold nanohelices, enzyme activity could be favored or suppressed depending on\ntheirenantiomorphicformwhichleadstohomo-orheterochiralassemblies,asdemonstratedusing\nelectrochemicalmeasurements,studiesoncellularinflammation,andinvivomousemodels.\nBroadly, I find the central argument regarding the influence of CISS on the pairings of COX-2\nwith either left- or right-handed Au nanohelices to be reasonably solid, although there are many\ndetails that still require attention, particularly with regards to the influence of external magnetic\nfields. The authors establish beyond reasonable doubt with circular dichroism spectra that the\nenzymeandnanohelicesarechiral,andthatthesymmetricspectraofthelatterindicateanabsence\nof structural differences between left- and right-handed nanohelices that might lead to\nmisinterpretation of confounding factors as effects of CISS. The authors also plausibly\ndemonstrate that left-handed helices form a homochiral pairing with COX-2 (facilitating electron\ntransfer) and right-handed helices form heterochiral structures (impairing ET), a fact that is\nsupported by both the electrochemical and biological experiments. Overall, the core argument of\nthe manuscript appears largely to be sound, but major revisions will be needed before I\nrecommenditsacceptanceforpublication.\nA prominent concern is the role of the magnetic field in the nanohelix-COX-2 assemblies. The\nresults of the electrochemical experiments in sections 2 and 3 are straightforward to understand,\nsince electron spins are injected via the magnetic nickel electrode, wherein the magnetic field is\nnecessarytofavor upward-or downwardpointing-spins. However,in Figure 4,the magnetic field\nstill achieves significant modulation of the current despite the use of a non-magnetic electrode.\nSincetheusualpurposeofamagneticfieldintheseexperimentsistopolarizetheinjectedelectron\nspins by splitting the spin sub-bands of the electrode, this effect is precluded in this suite of\nexperiments, and some other interaction must be invoked to describe the magnetic field\ndependence. The authors should think carefully about other magnetochiral effects and how they\nmight manifest in complicated molecules such as COX-2, particularly since the behavior of the\nnanohelix-enzymeassembliesseemstomirrorthebehaviorofCOX-2alone,raisingthepossibility\nthat the latter may also be dominated by non-CISS effects. (This might be easy to probe by\nperforminganalogousexperimentstothoseinFigure2usingaPtelectrodeinplaceofNi.)\nAdditionally,the electrochemical experiments in general are analyzed at such a rudimentary level\nthat I find them only somewhat convincing. Use of the raw peak current measured at the AA\noxidation feature as the main metric leaves the analysis vulnerable to unrelated confounding\nfactors that also contribute to the current (e.g., double layer discharge), and this background\nclearly changes from sample to sample in ways that do not seem straightforward to interpret. The\nauthors should, at minimum, attempt to fit the peaks using a suitable lineshape (pseudo-Voigt\nfunction, for instance) after subtracting off the background (a simple linear background would be\n29\nacceptable, in my opinion).Amore sophisticated line of analysis would be to perform the cyclic\nvoltammetrymeasurements usingarangeofvoltagescanrates,anduseMarcustheorytoestimate\nthe rate constant. (Recentexamples ofthis approach in similar systems canbe foundin Langmuir\n2023, 39, 1414-1424 and J Phys. Chem. B. 2023, 127, 6462-6469.) This latter approach may not\nbe straightforward due to the irreversibility of the oxidation, but the authors should at least\nestimatethepeakcurrentwiththebackgroundsubtractedtoconfirmthevalidityoftheiranalysis.\nResponse:Thank you for this helpful suggestion. We fully agree that directly using the raw peak\ncurrent without background correction may introduce uncertainty due to capacitive contributions\nsuch as double-layer charging, which can vary among samples. As the oxidation of AA is an\nirreversible process, performing CV measurements at a series of scan rates can lead to gradual\nelectrode passivation, thereby resulting in artificially reduced currents. For this reason, our\nanalysis was limited to the first oxidation cycle of the CV curves. In addition, because the\nbackgroundcurrentvariesineachmeasurement,thelineshapeoftheCVcurvescandifferamong\nreplicates.Intheoriginalversion,wepresentedonerepresentativeCVcurvethatbestreflectedthe\ncharacteristicdifferenceamongsamplesratherthananaveragedcurve.\nFollowing your advice, in the revised version, CV curves are averaged from three independent\nexperiments. Besides, we have re-analyzed all CV data by performing baseline fitting and\nsubtraction to remove background contributions before comparing peak currents. The\nbackground-corrected CV curves (positive semi-cycle forAAoxidation) are now provided in the\nrevised Fig. 2C, Fig. S1, S14, S15, S19 and S21.After background correction, the overall trends\namongsamplesremainconsistentwiththosereportedintheoriginalversion,althoughtheabsolute\ncurrent values and associated error bars were adjusted. These results confirm that our original\nconclusionsarerobustafteraccountingforbackgroundeffects.\nMorespecificcommentsexpandingontheseandotherpointsareprovidedbelow:\nFigure 1: A more detailed explanation of the figure, either in the caption, or in the main text,\nwouldbehelpful.Ittookmesometime,forinstance,tounderstandthattheblueandgoldsymbols\nin panels A and B were electrons, rather than opposite enantiomorphs of chiral nanoparticles\ndecoratingalargerstructuresuchasananorodorachiralmolecule.Ifigureditouteventually,but\nan explicit legend denoting gold symbols as spin-up electrons and blue symbols as spin-down\nelectrons would remove some of the friction in this process.Also, the chirality ofthe molecule in\nA and B should be indicated; it may even be worthwhile to include a fifth row containing the\nmolecule’s opposite enantiomer to clarify that CISS works the same way for molecules as for\nnanorods. Finally, the chiral molecule appears to contain a right-handed helix, but has favorable\nelectron transport in conjunction with the left-handed nanorod and poor transport with the\nright-handedone,whenthe oppositebehavior wouldbeexpected.Thediagram shouldbeupdated\nto convey the more physically accurate behavior (i.e., CISS favors transport in homochiral\nsystemsandretardsitinheterochiralsystems).\nResponse: Thank you for the suggestion. In the revised version, we have added a clear legend\npanel labeling the gold and blue spheres with arrows as spin-up and spin-down electrons,\nrespectively,andannotatedotherkeyelementsinthefigureforeasierinterpretation(Fig.R24).To\nmake the CISS mechanism more intuitive, revised Fig. 1A has been simplified to illustrate\nelectron transport in achiral materials (without CISS) and in chiral materials exhibiting CISS,\n30\nwhere left- and right-handed chiral systems selectively transport electrons with opposite spin\norientations. Correspondingly, revised Fig. 1B has been refined to show two representative cases:\nefficient transport between materials with identical chirality (Spin matched system) and inhibited\ntransport between materials with opposite chirality (Spin mismatched system). We believe these\nupdatesmakethediagramphysicallyconsistentandimproveitsoverallclarity.\nFig.R24.RevisedFig.1\nFigures 2A-C and S1,Associated Discussion: I don’t fully understand the sentence “To exclude\nthe influence of spin-polarized electrons onAAoxidation, we repeated CV measurements on the\ngold nanoparticle-coated Ni plate electrode without COX-2 modification.” Isn’t the whole point\n31\nof the experiment in Figure 2 to probe the influence of spin-polarized electrons, as mediated by\nCOX-2?AndsincetheexperimentisperformedonaNielectrodewith anexternalmagneticfield,\nspin-polarized electrons will be present. So this should be discussed a little bit differently, to\nvalidate the hypothesis that no other parts of the system are contributing to the CISS effect,\nbesides the expected contribution from the chiral enzyme. Furthermore, while the data in Figure\n2A-Cbroadlyseemtosupporttheauthors’ argument,Ihavesomeconcerns:\nResponse: We thank the reviewer for this astute observation. We agree that our original phrasing\nwas unclear and may have implied that we aimed to eliminate the influence of spin-polarized\nelectronsaltogether,whichcontradictsthecentralgoaloftheexperiment.\nActually,thepurposeofthecontrolexperimentusingtheNielectrodewithoutCOX-2(Fig.S1)\nwasnottoexcludetheinfluenceofspin-polarizedelectronsperse,butrathertodeterminewhether\nspin-polarized electronsalone,withoutenzymatic mediation,coulddirectlyaffecttheoxidationof\narachidonicacid(AA). SinceAAoxidationcanoccurelectrochemically intheabsenceofCOX-2,\nitisnecessarytoclarifywhethertheobservedmagneticfieldeffectsinthemainexperiments(Fig.\n2A-2C) truly arose from spin-dependent modulation of the catalytic activity of COX-2, and not\nfromsomeintrinsicmagneticorelectrochemicalpropertyoftheAAitselfortheelectrode.\nThe results in Fig. S1 showed that in the absence of COX-2, flipping the magnetic field\ndirectiondidnotsignificantlyaltertheAAoxidationcurrent,eventhoughspin-polarized electrons\nwere injected from the Ni electrode. This supports our conclusion that the magnetic\nfield-dependent effects observed in the presence of COX-2 are specifically due to CISS-mediated\nelectrontransfermodulationwithinthechiralenzyme.\nWe have now revised the sentence “To exclude the influence of spin-polarized electrons on AA\noxidation, we repeated CV measurements on the gold nanoparticle-coated Ni plate electrode\nwithout COX-2 modification.”into “To determine whether the observed magnetic field dependent\neffectsonAAoxidationarisefromCOX-2-mediatedspin-selectiveelectrontransport,\nratherthana\ndirect influence of spin-polarized electrons onAAitself, we performed control CV measurements\non Ni electrodes coated with gold nanoparticles but without COX-2 modification”(see Page 3,\nLine18-22).\n-What do the error bars represent, and how were they calculated (standard deviation, confidence\ninterval,#ofsamples)?Thisquestionextendstoallfigureswhereerrorbarsarepresented.\nResponse:Weappreciatethereviewer’sattentiontostatisticalclarity.AstheoxidationofAAisan\nirreversible process, all electrochemical measurements involving AA oxidation were\nindependently repeated three times under identical experimental conditions. Specifically, the\nmodified Ni electrodes were prepared as a single large film and then cut into three electrodes of\nequalsize.TheAAsolutionwasfreshlyprepared,mixedwithelectrolyte,andthenevenlydivided\nfor the three replicates. For each sample, only the first cycle of the cyclic voltammogram (CV)\nwas analyzed to avoid complications from surface passivation or accumulation effects during\nrepeatedscans.\nIn the revised version, the original CV curves obtained from three independent experiments\nwere averaged as the final CV curves shown. Then the positive semi-cyle of CV curves were\nbaseline fitted and subtracted to generate background-corrected CV curves for peak current\n32\ndeterminationandcomparison.Peakcurrentsfromthebackground-correctedpositivesemi-cyleof\nCV curves obtained from these three independent measurements were used to calculate the mean\n± standard deviation (SD), which is represented by the error bars in the figures. This protocol\nwas applied consistently across all AA oxidation related CV relevant figures unless otherwise\nstated.All these clarification have beenadded to the Methods Section in the main text ofPage 14\nLine 14-25. And the statistic analysis method is followed in the caption of each corresponding\nFigure.\n-It is worrisome that the magnetic field still appears to affect the current measured in the control\nsamples in Figure S1. The authors’ explanation regarding the Lorentz force may be correct, but\nthis would not seem to explain why the attenuation in oxidation changes when the magnet is\nflipped, which appears to be both statistically significant (depending on the meaning of the error\nbars) and perhaps even larger than the difference between magnetic field/no magnetic field cases.\nThe background effects noted above may also skew the results – if the background were\nsubtracted and the peaks refit as suggested above, would the trend remain?Also, how temporally\nstable are the systems during electrochemical measurements? Was the magnetic field flipped\nseveral times, and statistics taken across flips, or was it only flipped once for north vs. south, and\ntheassociatedstatisticscollectedinbatches?Withoutthisinformation,itisdifficulttotellwhether\ntheobserveddifferencesarerealoranartifactofthedatacollectionprocesses.\nResponse: We thank the reviewer for raising this important point. As AA oxidation is an\nirreversible process, flipping the magnetic field (MF) during a single measurement makes it\ndifficult to distinguish whether the observed current variations originate from the MF itself or\nfrom electrode passivation and reaction kinetics. Therefore, in our experiments, the MF was not\nrepeatedly flipped during one CV scan. Instead, each condition (w/o MF, MF-N, and MF-S) was\nmeasured independently in three separate experiments, and all replicates consistently showed\nsimilartrend.\nFollowing your advice, to further clarify this issue, we have reanalyzed the CV curves data by\nperforming baseline fitting and background subtraction prior to comparing peak currents. The\nreprocessed results show that the CV curve shapes remain similar among groups, and the\nstatistical difference between the control (w/o MF) and MF-applied groups (MF-N or MF-S)\nremains significant after background correction. In contrast, the difference between MF-N and\nMF-S is notstatistically significant.The updatedresults are presentedin the revised Fig. S1 (Fig.\nR25). Fig. R25B shows the averaged CV curves from three independent measurements under\neach condition, Fig. R25C presents the positive semi-cycles after baseline subtraction, and Fig.\nR25D summarizes the corresponding peak current (I ) values.These results confirm that the\nP\nobserved MF effect is reproducible and not an artifact arising from background variations or data\nprocessing.\nAA. (A) Schematic diagram of the electrochemical measurement setup for the measurement of\nCV curves of the oxidation of AA with or without MF applied. (B) Averaged CV curves obtained\nfrom three independent measurements under each condition. (C) Positive semi-cycles of the\ncorresponding CV curves after baseline fitting and background subtraction, showing the\nbackground-correctedAAoxidationfeatures.(D)ComparisonoftheI\nP\nextractedfrompanel(C).\nFigure 2D: the absorption spectrum of COX-2 should be presented alongside the CD spectrum to\nclarifythenatureandoriginoftherelevantelectronictransitions.\nResponse: Thank you for this constructive suggestion. We have now included the UV-Vis\nabsorbancespectrumofCOX-2 intherevised Fig.2(newlyrevisedasFig.2E) tofacilitate direct\ncomparison with its CD spectrum and to clarify the origin of the observed electronic transitions.\nTheUV-VisspectrumexhibitsacharacteristicSoretbandinthe380-420nmrange,corresponding\ntotheheme-relatedπ-πtransition.However,nosignificantCDresponseisobservedinthisregion,\nindicating that the heme center does not contribute strongly to the overall optical activity. The\nmain CD features appear in the 180-260 nm range, consistent with the secondary structure of the\nprotein(Fig.R26).\nFig. R26. (corresponding to Fig. 2E in the revised version), CD spectra (blue) and UV-vis\nabsorbancespectra(purple)ofCOX-2(10μg/mL)\nFigure 2F, G: the meaning of the energy scale in the x-axis should be clarified; particularly, what\ndoesthezerorepresent?Fermilevel?Valencebandmaximum?Somethingelse?\nResponse:Wethankthereviewerforthisinsightfulcomment.InFig.(2G-2H)andFig. (3O-3Q)\nof the main text, the x-axis represents the incident electron energy. In our numerical calculations,\nthe on-site energy of gold atoms is chosenas the reference point( ), and the Fermi level is\nset to eV, reflecting the electron-dominated transport characteristics of gold. The\n=0\nrelative on-site energy of amino acids can be estimated as follows. The work function of gold\n=−1.00\nfilms, the minimum energy required to remove one electron from the surface to vacuum, is\napproximately 5.30 eV. In contrast, the vertical ionization energy of amino acids, the minimum\nenergyforonevalenceelectronescapingfromamoleculetovacuum,rangesfrom6.67to8.46eV\n[J. Phys. Chem. A 115, 2900-2912 (2011)], with an average value of 7.57 eV. This indicates that\nthe itinerant electron energy in gold is roughly 2 eV higher than in amino acids.Accordingly, the\nrelativeon-siteenergyofaminoacidsisapproximatedas-2eV.WhencAuarecoupledtoCOX-2,\n34\nelectronscanpropagatefromcAutoCOX-2underequilibriumconditions,shiftingtheFermilevel\ntoward lower energy.Without loss of generality, we set the Fermi level to eVin our\nnumerical calculations to represent electron-dominated transport. We emphasize that our results\n=−1.00\nstillholdwhentheFermileveldeviatesfrom-1.00eV.\nIn the revised manuscript, we clarified this point by adding a phrase ‘as a function of the\nincidentelectronenergy,withtheon-siteenergyofcAusetasthereferencepoint(zeroenergy)’to\nthe caption of Fig. 2 in the main text, and an explanatory sentence below equation (15) in the\nSupplementaryMaterials.\nFigure 2H: the mechanism of AA oxidation should be explained in more detail, particularly\nbecause it appears that AA and its products interact with COX-2 interact at different times at\ndifferent sites.Am I correct in understanding from the diagram that effectively the same electron\nobtained from the oxidation of AA later contributes to the reduction of the product PGG-2, and\nthatbothof theseelectron transfer processes arepotentially CISS-modulated? Becausethere is no\nnet exchange of electrons, one might argue that CISS shouldn’t have any net effect either, but it\nmay be that an interesting and subtle point can be made – i.e., supposing that the electron\ntransfer path follows a single alpha helix that is bent in a U-shape so that the oxidation and\nreductionsites arelocatedincloseproximity onthesame “face” oftheenzyme, onecouldargue\nthat CISS would in fact impact both processes in a concerted way despite no net charge transfer\noccurring. I have no idea if what I am suggesting is even remotely faithful to the actual structure\nofCOX-2,however.Theessentialpointisthattheauthorsmustdoamuchbetterjobofexplaining\nthe mechanism in full detail so the readers don't have to project so much imagination onto the\nsystem, and possibly draw wildly inaccurate conclusions about it, as I may have done here. For\ninstance, what are the yellow cyclic compound and green heme-looking structures supposed to\nrepresent, and what roles do they play? What are the PGG2and PGH2 intermediates, for the\nbenefitofreadersfromnon-biomedicalbackgrounds?Manyimportantdetailsregardingthenature\nof the overall process to form the PGE2 product are missing, and it is hard to fully evaluate the\nscientificclaimswithoutamorethoroughlysketcheddescription.\nResponse: We sincerely thank you for this thoughtful comment. We agree that the original\nschematic did not sufficiently illustrate the detailed catalytic mechanism of AA oxidation by\nCOX-2,norclearlyconnecttheoxidation-reductioncyclewiththepotentialspin-selectiveelectron\ntransportpathway.\nIn the revised manuscript, we have redrawnandexpandedthe mechanisticschematic as Fig. 2I\nand 2J (Fig. R27), which provide a detailed structural and mechanistic representation of the\nCOX-2catalyticcycleandhighlightthepotentialinfluenceofCISSeffect.\nAs shown in Fig. 2I, COX-2 consists of two spatially coupled functional domains: the\ncyclooxygenase (COX) site embedded in short α-helical segments containing Tyr385 and Trp387\nandtheheme-containingperoxidase(POX)site(Biochemistry,2002,41(52),15451-15458;Chem.\nRev.2003,103(6),2239-304.).Thecatalyticcycle(Fig.2Iand2J)proceedsasfollows:\n1)Thereactionisinitiatedbyoxidationoftheheme-Fe3+centerinthePOXsitebyanendogenous\nperoxide (ROOH), generating the high-valent Intermediate I (Fe4+=O Por•+) after the loss of two\nelectrons.\n35\n2) This Intermediate I abstracts an electron through Tyr 385 via the bridge of Trp387, forming\nIntermediateIIandTyr385• attheCOXsite.\n3) Tyr385• subsequently oxidizes AA bound in the hydrophobic channel, generating the AA\nradical(AA•)andleadingtotheinsertionofO toyieldProstaglandinG (PGG ).\n2 2 2\n4) PGG , being a hydroperoxide, can then donate an electron to Intermediate II in the POX site,\n2\nregenerating the resting heme-Fe3+ state and producing Prostaglandin H (PGH ), which is\n2 2\nsubsequentlyisomerizedtoProstaglandinE (PGE ),invokinginflammatoryresponse.\n2 2\nThus, as the reviewer correctly noted, the overall catalytic cycle involves intramolecular\nelectron transfer cascade without net charge exchange between COX-2 and its surroundings.\nAlthough the internal electrin-transfer mainly occur between AA, COX and POX site, the\nneighboring residues such as Tyr348, Trp387, and Tyr504 have been revealed to significantly\ninfluence the electron-transfer kinetics and catalytic efficiency of COX-2 (Biochemistry 2006,\n45(2),523-32;Biochemistry2015,54,7309-7312.).Therefore,theα-helicalsegmentsbridgingthe\nCOX and POX domains may function as spin-selective conduits to modulate spin-polarized\nelectrontunnelingviaCISSeffect.\nIn the end of section 2 (Page 3 Line 37) in the revised manuscript, we added details on the\ncatalytic process of AA oxidation by COX-2: “TheAA oxidation by COX-2 has been studied to\noccur via two active domains: cyclooxygenase (COX) site embedded in short α-helical segments\ncontaining Tyr385 and Trp387, and the heme-containing peroxidase (POX) site, via an\nintramolecular electron transfer process40, 41. The catalytic cycle starts at the POX site, where\nheme Fe3+ is oxidized by peroxide (ROOH) to form radical Intermediate I (Fe4+=O Por•+), which\nextracts one electron from Tyr 385 viaTrp387, producingTyr385• that abstracts a hydrogen atom\nfrom AA to form AA•. AA• then reacts with O to yield Prostaglandin G (PGG ). PGG , as a\n2 2 2 2\nperoxide, donates an electron back to regenerate POX heme Fe3+, being reduced to Prostaglandin\nH (PGH ), which is subsequently isomerized to PGE (Fig. 2I and 2J). Since the α-helical\n2 2 2\nsegments bridge the internal electron transport between the COX and POX sites, providing the\npossible structural basis for spin polarized electrons to modulate COX-2 catalytic efficiency via\nCISSeffect.”\nperoxidase (POX) site, cyclooxygenase (COX) site, and α-helical residues Tyr385 and Trp387\ninvolved in intramolecular electron transfer of catalyzing AA oxidation to generate PGE .\n① and ② indicate the two electrons flow to Heme-Fe3+ in POX sites, which initially loses two\nelectrons to initialize the electron transfer process for AA oxidation. (J) Proposed catalytic\nmechanismofAAoxidationbyCOX-2,showingsequentialelectrontransfersteps(1)-(7)between\ntheCOXandPOXsites.\nResults Section 4: The overall logic used to discriminate active site change or passivation from\nelectron transport modulation does not make sense to me. What is the theoretical basis for\nassuming that a magnetic field will affect transport when an unmagnetized electrode is used to\ninject electrons? Does this arise from the magnetic field-dependent phase factor in the hopping\nintegral (as discussed in the SI), and can additional detail be provided to explore this? Or is it\nsomething else? I find it curious that the same magnetic field dependence appears in the Au\nnanorod-COX-2 assemblies with a non-magnetic electrode as when just COX-2 is present on a\nmagnetic electrode, as shown in Figure 2. It seems as though there could be an effect of the\nmagnetic field thatis unrelatedto polarizationof theinjected spinsbythe electrode.DoesCOX-2\ncontain heme, as Figure 2H seems to indicate? If so, might it retain exhibit some paramagnetism\nfrom the Fe atom? This might lead to additional effects beyond CISS in conventional chiral\nmolecules.At any rate, I still don’t see how this helps discriminate electron transfer from active\nsite passivation, and it’s not self-evident to me that applying a magnetic field couldn’t affect the\nwaythingsbindtoactivesites.Surelytherearesomemoreincisivetechniques,perhapsakintothe\nfluorescencequenching experiment in Figure 4AandB that might allow adsorption on these sites\ntobeprobedmoredirectly?\nResponse: Yes, the theoretical basis, why a MF can affect electron transport in Au@COX-2\nC\nwhen using an unmagnetized electrode, arises from the Peierls phase induced by the MF, i.e., the\nMF-dependent phase factor in the hopping integral (see the first paragraph of Page 4 in the\nSupplementary Materials). This mechanism differs fundamentally from the case shown in Fig. 2\nof the main text, where the Ni electrode becomes magnetized under an external MF and thus\nspin-polarized electrons are injected. In contrast, Fig. 4 of the main text deliberately employs\nnon-magnetic Pt electrodes to exclude any spin polarization originating from the electrodes and\nsubsequently the observed spin selectivity arises intrinsically from hybrid Au@COX-2 via the\nC\nCISS effect. Under such case of the unmagnetized electrode, spin-unpolarized electrons will be\ninjected and propagate through Au@COX-2 via multiple transport pathways. Subsequently,\nC\nquantum interference arises naturally and the current flowing through Au@COX-2 will depend\nC\nontheMFinduced-Peierlsphase.\nTo further elucidate the physical origin of this MF-dependent current, we consider a simple\nchiral system of two transport pathways (Phys. Rev. B 2016, 94, 235448; Phys. Rev. B 2020, 102,\n195406).In this case, thetransmission coefficientofthe first-order tunnelingprocessis expressed\nas:\n∆   +∆     +∆    2\n=  1+  2 \n2 2 \n=  1 +  2 +2  1  2 cos ∆   +∆     +∆    . (   )\ntransportpathways, is thenormalphasedifferencebetweenthetwopathways, is the\n1  2\ncorrespondingphasedifferenceinducedbythespin-orbit couplingeffect,and ist  hePeierls\n∆   ∆    \nphase difference induced by MF, with and . Notice that is\n∆   \nreversed for opposite MF direction and is zero in the ab↑sence of M↓F. Correspondingly, for a\n=↑,↓ ∆     =−∆     ∆   \nspecificMF,thetotaltransmissioncoefficientreads:\n↑ ↓ 2 2 ↑\nIt is  e  vi  de=nt   fr  om+  e  q  ua=tio2n  R 1 3 +that  2 the+t2ota  l 1  t 2 rancosmsis∆s  io  n+c∆oe  f  fi  ciecnotsde∆p  e  n  d  e  n  ts o.n(  b  o)th the\nmagnitude and orientation of MF.As a result, the current flowing through cAu@COX-2 depends\nonMF.\nIn the revised manuscript, we explicitly clarified the mechanism of MF-dependent current in\nAu@COX-2 (see Page 6 Line 19-24): “Using non-magnetic electrodes ensures that any\nC\nMF-dependent response arises from CISS-induced spin polarization within the Au@COX-2\nC\nsystem, rather than from spin-polarized injection by the electrode. Since MF can perturb spin\ntransport through the Peierls phase to alter electron spin evolution and transport efficiency, it\nallows us to selectively probe CISS-mediated electron transport while excluding active-site\neffects.”\nN. B. The theoretical simulations (as described in “Numerical methods” on page 7 of the SI)\nappear to calculate the conductances under north or south applied magnetic fields considering the\npresence of a Ni (i.e., magnetic) electrode, yielding a spin polarization parameter of μ = ±1. This\nis unrealistically high even for magnetically saturated nickel, for which polarization of injected\nspins is closer to 30% - see, for instance, J. Phys. Chem. C 2024, 128, 6438-6445, and associated\nreferences.)\nResponse: We thank the reviewer for this insightful comment. Yes, in our original numerical\ncalculations,thespinpolarizationoftheNielectrodewassethigherthanthetypicalvalueofabout\n30%. This discrepancy can be rationalized by considering the magnetic proximity effect (MPE)\n(Phys. Rep. 2014, 535, 61-99; https://arxiv.org/abs/2509.05588.). We take COX-2 as an example\nto elucidate this MPE. In proximity to the Ni electrode, the electronic wavefunctions of Ni can\npenetrate into the interfacial region of COX-2, inducing magnetized sites via exchange\ninteractions. Since these induced magnetic moments in COX-2 are highly localized, the effective\nspinpolarizationatthesemagnetizedsitescanexceedthatoftheNielectrode,leadingtoenhanced\nspinselectivityinspin-polarizedelectrontransport(https://arxiv.org/abs/2509.05588).\nTo further elucidate the influence of MPE on spin-polarized electron transport, Fig. R28\npresents the conductances , , and the corresponding spin polarization of COX-2, when the\nspin polarization of the magnetic electrode is fixed at . Here, and represent the\n\nconductances under upward MF and downward MF, respectively. As shown in Fig. R28A, the\n30%    \nconductance profiles closely resemble those in the main text (Fig. 2G), and is distinct from\nacross the entire energy spectrum, yielding a spin polarization of approximately 70.0% (Fig.\n\nR28B).\n\nSimilarly, Fig. R29 plots the conductances , , and , along with the corresponding\ncurrents , , and , for both Lh- Au (left panels) and Rh- Au (right panels) with the\nC       /  C\n/ \n38\nelectrode spin polarization fixed at . Here, and refer to the results obtained\nwithoutMF.TheconductanceprofilesinFig. R29A-29B arealsosimilarasthosein themain text\n30%   /    / \n(Fig.3Oand3P).And isdifferentfrom ,withthespinpolarizationachieving11.7%atthe\nFermi level, which is comparable to the value 16.1% in Fig. 3O and 3P of the main text.\n\nCorrespondingly, and remain well separated. These results demonstrate that both COX-2\nand Au maintain strong spin selectivity even when the electrode spin polarization is limited to\nC    \n30%,therebyvalidatingthenumericalresultsinthemaintext.\nFig. R28. Spin-selective electron transport through COX-2 with the spin polarization of magnetic\nelectrode fixed at . (A) Energy-dependent spin-up conductance under upward MF and\nspin-downconductance underdownwardMF,and(b)thecorrespondingspinpolarization.\n30%  \n\nFig.R29. Spin-selective electrontransportthroughLh- AuandRh- Au with thespinpolarization\nC C\n39\nof magnetic electrode fixed at . (A-B) Energy-dependent conductances , , and ,\nand (C-D) the corresponding current-voltage curves for Lh- Au (left) and Rh- Au (right).\n30% C   C     / \ndenotes the conductance without MF, and , , and are the currents under upward MF,\n/ \ndownwardMF,andwithoutMF,respectively.\n/ \nIntherevisedmanuscript,weaddedthisstatementinPage8Line5-15,andcitedthereferencesof\nPhys. Rep. 2014, 535, 61-99, https://arxiv.org/abs/2509.05588, and J. Phys. Chem. C 2024, 128,\n6438-6445,asRefs.[6-8]intheSupplementaryMaterials.\nFigure 4O: how, precisely, are the values in the “competency diagram” calculated? The term\n“enzyme activity regulation” is confusing because it’s not always apparent whether you are\nfocusingspecifically onthe enantioselective aspectofit, which is presumably most interesting, or\non the overall activity? Overall I think this diagram is more confusing than effective, and would\nrecommendstrikingitaltogether.\nResponse:Thank you for your kind suggestion. In the revised version, we have redrawn Fig. 4O\n(Fig.R1)basedontheelectrochemicalmeasurementsdataandaddedthecalculationdetailsinthe\nSupplementaryMaterials.\nQuantificationofMechanisticContributionsforFig.4O:\nTheregulationofCOX-2activitybyLh-/Rh-/RAC- Auwasmeasuredas+5%,-48%,and-38%\nC\nby the fluorescence assay kit (Fig. 4A-B), and +14.86%, -31.31%, and -22.41% by\nelectrochemical measurements (Fig. 4C-D). Since both nanozyme catalytic activity and CISS\neffects were characterized by electrochemistry (CV curves), the electrochemical data were used\nforquantitative decomposition ofthe threemechanisms: nanozyme activity (x),active site change\n(y),andCISSeffect(z).\nNanozyme activity (x): In the absence of COX-2, all three samples (Lh-/Rh-/RAC- Au)\nC\npromoteAAoxidation (Fig. S17, Fig. S8 in the original version). The calculated contributions to\nCOX-2activitywere+18.80%,+34.12%,and+28.59%,respectively.\nActive site change (y): Since RAC- Au lacks a CISS effect (z = 0), but it inhibits COX-2\nC\nactivity.Therefore,theinhibitionisattributedtoactivesiteconformationalchanges:\nyRAC- Au=(-22.41%)-(+28.59%)=-51.0%\nC\nWeassume that Lh- and Rh- Au have similar effects on active site conformation due to similar\nC\nAusurfacestructures.\nCISS effect (z): For Lh- and Rh- Au, the contribution of CISS was obtained by subtracting x\nC\nyandfromtheoverallCOX-2modulation:\nzLh- Au=+14.86%-(+18.8%)-(-51.0%)=+47.06%\nC\nzRh- Au=-31.31%-(+34.12%)-(-51.0%)=-14.43%\nC\nThis difference between zLh- Au and zRh- Au indicates that CISS matching enhances\nC C\nspin-polarizedelectrontransport,whereasCISSmismatchsuppressesit.\nTo visualize the relative contributions, the x, y, and z values for Lh-/Rh-/RAC- Au were\nC\nsummed and normalized to calculate the relative percentage contribution of each mechanism, and\npresentedasaradarplotinFig.4O.Thecalculatedcontributionsare:\nforRAC- Au,x=35.92%,y=-64.08%,z=0;\nC\nforLh- Au,x=16.09%,y=-43.64%,z=40.27%;\nC\nforRh- Au,x=34.27%,y=-51.23%,z=-14.5%.\nC\nIn the radar plot, each axis (x, y, z) represents one mechanism, with its length corresponding to\nthe calculated percentage contribution. The overall COX-2 activity modulation can be interpreted\nasthesumofthesethreecontributions.\nIn summary, for Lh-/Rh-/RAC- Au, nanozyme catalytic activity promotes COX-2 activity,\nC\nactivesite modulation inhibits COX-2 activity,andCISSeffects caneither enhanceorsuppressto\nmodulatethefinaloutcome.\nFig. R1. (Revised Fig. 4O), Radar plot of the three different mechanism contribution to COX-2\nactivityregulation.\nWe sincerely thank all three reviewers for their insightful comments and strong support\nfor the manuscript. We believe the revisions have further improved clarity, transparency,\nand data robustness.\nReviewer #1 (Remarks to the Author):\nThe authors have throughly addressed my comments raised in the last review. It can be\npublished on Nature Communications.\nResponse: We sincerely thank the reviewer for the positive evaluation and support.\nReviewer #2 (Remarks to the Author):\nI agree with the acceptance of the manuscript.\nResponse: We thank the reviewer for the supportive assessment.\nReviewer #3 (Remarks to the Author):\nIt is clear that the authors have put a considerable amount of care and thought into\naddressing the points I (as well as the other reviewers) raised. I appreciate the\nthoroughness of their responses and their willingness to refine their data analysis and\nredraw key schematics, and I think that this effort has paid off and the manuscript has\nbeen greatly improved. I am pleased to recommend the article for publication pending\na few nominal changes that arose when reviewing the Excel file containing data, noted\nbelow, and congratulate the authors on a very interesting study that promises to be\nhighly impactful.\nResponse: Thank you for the thoughtful and encouraging comments. We have carefully\naddressed each of the remaining point.\n- The spectra in Figure 4A appear to be sampled unusually coarsely, and it looks as\nthough some sort of spline interpolation has been performed to draw the smooth curves\nshown. This isn't a big issue, but the authors might consider adding markers to\ndemonstrate the points at which the fluorescence intensity data were collected.\nResponse: Thank you for this helpful suggestion. Figure 4A shows the fluorescence\nspectra obtained using a commercial COX-2 activity assay kit to evaluate the regulation\neffects of Lh- Au, Rh- Au, RAC- Au, and celecoxib. The spectra were collected under\nC C C\nthe kit-recommended parameters (excitation at 530 nm; emission in the range of 550-\n650 nm) with a data acquisition interval of 5 nm. The original spectra were plotted\ndirectly from the raw data using Excel (“scatter with smooth lines”), without applying\nspline interpolation or artificial curve fitting.\nTo improve transparency and to show that the spectra were generated from discrete\nexperimental data points rather than interpolated traces, we have revised Figure 4A to\ndisplay line curves with individual data markers. The revised figure has been updated\nin the manuscript, and “Spectra were collected in the wavelength range of 550-650 nm\nwith data interval of 5 nm.” was added in the caption part.\nFig. R1 (revised Figure 4A) Fluorescence emission spectra of resorufin (λ = 535 nm)\nex\nreflecting COX-2 enzymatic activity in the presence of AA and 10-Acetyl-3,7-\ndihydroxypenoxazin (ADPH). COX-2 was incubated with Lh- Au, Rh- Au or RAC-\nC C\nAu; celecoxib served as a positive control for COX-2 inhibition. During AA oxidation\nC\nby COX-2, ADPH is oxidized into fluorescent resorufin. Spectra were collected in the\nwavelength range of 550-650 nm with data interval of 5 nm.\n- There appear to be more CV sweeps in the data corresponding to Figures 4F-H than\nare actually shown in the figure; also in S14 and S15, and seemingly most cases in\nwhich cyclic voltammograms are plotted. The authors may wish to clarify which\nsubsection of the data provided is relevant in each of these cases.\nResponse: We appreciate this important point. We carefully re-examined all cyclic\nvoltammetry (CV) datasets. In the original data files, multiple recorded CV sweeps\nwere contained. However, as we explained in the last revision, only the first-cycle CV\ncurves were intended to be analyzed for comparison and presented in Figures 4F–H\nand Figures S14–S15, because AA oxidation is an irreversible process and the repeated\ncycling can gradually induce electrode passivation, leading to artificially decreased\ncurrent responses in subsequent scans. Therefore, to avoid confusion, in the revised\nversion of the raw data (.xls) file, we have retained only the first-cycle CV sweeps,\nwhich correspond exactly to the curves shown in the manuscript figures.\n- Figure S12C appears to be missing the curves corresponding to W parameter values\nof 100 meV and 200 meV.\nResponse: Thank you for highlighting this issue. The curves corresponding to W\nparameter values of 100 meV and 200 meV are indeed all presented in Figure S12C.\nAs the simulated spin polarization curves for W = 0, 100 meV, and 200 meV almost\noverlap, the three curves appear as a single visible line in the plotted figure. We have\nadded an explanatory note in the revised caption to clarify this overlap as “Theoretical\nconductance for W=100 meV (A) and 200 meV (B), and the corresponding spin\npolarization (C), where the spin polarization curves almost overlap.”\n- Data for the histograms in Figure 5 F and J are not given in the Excel sheet.\nResponse: Thank you for the comment. The histograms in Figures 5F and 5J were\ngenerated by processing the raw flow cytometry files (FCS) using FlowJo, where the\nfrequencies corresponding to each gated population were directly obtained from the\nsoftware, so we didn’t extract the data from the software. In the revised raw data (.xls)\nfile, we have now included the numerical values underlying Figures 5F and 5J.\n- In Figure S23, there appear to be some discrepancies between the plotted DLS\nhistograms and the data. In particular, in the plot the first peak of all three distributions\nis centered in the 10.1-nm bin, and the peak has a significant tail into the <10 nm region.\nHowever, the histograms in the data peak around 15-18 nm and do not extend into the\n<10 nm region at all. The authors should carefully review their data to resolve this\ninconsistency.\nResponse: We sincerely thank the reviewer for the careful inspection and valuable\ncomments. After rechecking the original DLS raw files, we confirmed that the\npreviously plotted histograms in Figure S23 indeed contained inconsistencies relative\nto the source data, which may arise from an unintended misalignment of the x-axis bin\npositions during the plotting process. To address this issue, we have replotted all DLS\nhistograms for Lh-, Rh-, and RAC- Au using the raw data and have replaced Figure\nC\nS23 in the revised Supplementary Information. The updated histograms now correctly\nrepresent the true peak positions of each sample.\nFig. R2 (Revised Figure S23) Size distribution of Lh- Au@MIP, Rh- Au@MIP and\nC C\nRAC- Au@MIP via dynamic light scattering measurement.\nC\nReviewer #3 (Remarks on code availability):\nFrom a cursory review of the code files, this looks reasonable - the README file\nappears to be helpful. The only thing I would suggest would be to put more comments\nwithin the script files themselves. I did not attempt to install or run the code because I\ndo not currently have access to a MATLAB license, and the authors might consider\nreleasing a version in an open-source language like Python. However, I think that the\npackage the authors provided is generally in compliance with good practices for code\navailability.\nResponse: Thank you for this constructive suggestion. We have added detailed\nexplanatory comments within all MATLAB script files. Furthermore, we have\nimplemented the full code in Python and uploaded the Python version to Figshare\n(10.6084/m9.figshare.30391330)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have throughly addressed my comments raised in the last review. It can be published on Nature Communications.", "reviewer_2": "I agree with the acceptance of the manuscript.", "reviewer_3": "It is clear that the authors have put a considerable amount of care and thought into addressing the points I (as well as the other reviewers) raised. I appreciate the thoroughness of their responses and their willingness to refine their data analysis and redraw key schematics, and I think that this effort has paid off and the manuscript has been greatly improved. I am pleased to recommend the article for publication pending a few nominal changes that arose when reviewing the Excel file containing data, noted below, and congratulate the authors on a very interesting study that promises to be highly impactful.\n- The spectra in Figure 4A appear to be sampled unusually coarsely, and it looks as though some sort of spline interpolation has been performed to draw the smooth curves shown. This isn't a big issue, but the authors might consider adding markers to demonstrate the points at which the fluorescence intensity data were collected.\n- There appear to be more CV sweeps in the data corresponding to Figures 4F-H than are actually shown in the figure; also in S14 and S15, and seemingly most cases in which cyclic voltammograms are plotted. The authors may wish to clarify which subsection of the data provided is relevant in each of these cases.\n- Figure S12C appears to be missing the curves corresponding to W parameter values of 100 meV and 200 meV.\n- Data for the histograms in Figure 5 F and J are not given in the Excel sheet.\n- In Figure S23, there appear to be some discrepancies between the plotted DLS histograms and the data. In particular, in the plot the first peak of all three distributions is centered in the 10.1-nm bin, and the peak has a significant tail into the <10 nm region. However, the histograms in the data peak around 15-18 nm and do not extend into the <10 nm region at all. The authors should carefully review their data to resolve this inconsistency."}, "author_response": "Response to Reviewers’ Comments\nWe sincerely thank all three reviewers for their insightful comments and strong support\nfor the manuscript. We believe the revisions have further improved clarity, transparency,\nand data robustness.\nReviewer #1 (Remarks to the Author):\nThe authors have throughly addressed my comments raised in the last review. It can be\npublished on Nature Communications.\nResponse: We sincerely thank the reviewer for the positive evaluation and support.\nReviewer #2 (Remarks to the Author):\nI agree with the acceptance of the manuscript.\nResponse: We thank the reviewer for the supportive assessment.\nReviewer #3 (Remarks to the Author):\nIt is clear that the authors have put a considerable amount of care and thought into\naddressing the points I (as well as the other reviewers) raised. I appreciate the\nthoroughness of their responses and their willingness to refine their data analysis and\nredraw key schematics, and I think that this effort has paid off and the manuscript has\nbeen greatly improved. I am pleased to recommend the article for publication pending\na few nominal changes that arose when reviewing the Excel file containing data, noted\nbelow, and congratulate the authors on a very interesting study that promises to be\nhighly impactful.\nResponse: Thank you for the thoughtful and encouraging comments. We have carefully\naddressed each of the remaining point.\n- The spectra in Figure 4A appear to be sampled unusually coarsely, and it looks as\nthough some sort of spline interpolation has been performed to draw the smooth curves\nshown. This isn't a big issue, but the authors might consider adding markers to\ndemonstrate the points at which the fluorescence intensity data were collected.\nResponse: Thank you for this helpful suggestion. Figure 4A shows the fluorescence\nspectra obtained using a commercial COX-2 activity assay kit to evaluate the regulation\neffects of Lh- Au, Rh- Au, RAC- Au, and celecoxib. The spectra were collected under\nC C C\nthe kit-recommended parameters (excitation at 530 nm; emission in the range of 550-\n650 nm) with a data acquisition interval of 5 nm. The original spectra were plotted\ndirectly from the raw data using Excel (“scatter with smooth lines”), without applying\nspline interpolation or artificial curve fitting.\nTo improve transparency and to show that the spectra were generated from discrete\nexperimental data points rather than interpolated traces, we have revised Figure 4A to\ndisplay line curves with individual data markers. The revised figure has been updated\nin the manuscript, and “Spectra were collected in the wavelength range of 550-650 nm\nwith data interval of 5 nm.” was added in the caption part.\nFig. R1 (revised Figure 4A) Fluorescence emission spectra of resorufin (λ = 535 nm)\nex\nreflecting COX-2 enzymatic activity in the presence of AA and 10-Acetyl-3,7-\ndihydroxypenoxazin (ADPH). COX-2 was incubated with Lh- Au, Rh- Au or RAC-\nC C\nAu; celecoxib served as a positive control for COX-2 inhibition. During AA oxidation\nC\nby COX-2, ADPH is oxidized into fluorescent resorufin. Spectra were collected in the\nwavelength range of 550-650 nm with data interval of 5 nm.\n- There appear to be more CV sweeps in the data corresponding to Figures 4F-H than\nare actually shown in the figure; also in S14 and S15, and seemingly most cases in\nwhich cyclic voltammograms are plotted. The authors may wish to clarify which\nsubsection of the data provided is relevant in each of these cases.\nResponse: We appreciate this important point. We carefully re-examined all cyclic\nvoltammetry (CV) datasets. In the original data files, multiple recorded CV sweeps\nwere contained. However, as we explained in the last revision, only the first-cycle CV\ncurves were intended to be analyzed for comparison and presented in Figures 4F–H\nand Figures S14–S15, because AA oxidation is an irreversible process and the repeated\ncycling can gradually induce electrode passivation, leading to artificially decreased\ncurrent responses in subsequent scans. Therefore, to avoid confusion, in the revised\nversion of the raw data (.xls) file, we have retained only the first-cycle CV sweeps,\nwhich correspond exactly to the curves shown in the manuscript figures.\n- Figure S12C appears to be missing the curves corresponding to W parameter values\nof 100 meV and 200 meV.\nResponse: Thank you for highlighting this issue. The curves corresponding to W\nparameter values of 100 meV and 200 meV are indeed all presented in Figure S12C.\nAs the simulated spin polarization curves for W = 0, 100 meV, and 200 meV almost\noverlap, the three curves appear as a single visible line in the plotted figure. We have\nadded an explanatory note in the revised caption to clarify this overlap as “Theoretical\nconductance for W=100 meV (A) and 200 meV (B), and the corresponding spin\npolarization (C), where the spin polarization curves almost overlap.”\n- Data for the histograms in Figure 5 F and J are not given in the Excel sheet.\nResponse: Thank you for the comment. The histograms in Figures 5F and 5J were\ngenerated by processing the raw flow cytometry files (FCS) using FlowJo, where the\nfrequencies corresponding to each gated population were directly obtained from the\nsoftware, so we didn’t extract the data from the software. In the revised raw data (.xls)\nfile, we have now included the numerical values underlying Figures 5F and 5J.\n- In Figure S23, there appear to be some discrepancies between the plotted DLS\nhistograms and the data. In particular, in the plot the first peak of all three distributions\nis centered in the 10.1-nm bin, and the peak has a significant tail into the <10 nm region.\nHowever, the histograms in the data peak around 15-18 nm and do not extend into the\n<10 nm region at all. The authors should carefully review their data to resolve this\ninconsistency.\nResponse: We sincerely thank the reviewer for the careful inspection and valuable\ncomments. After rechecking the original DLS raw files, we confirmed that the\npreviously plotted histograms in Figure S23 indeed contained inconsistencies relative\nto the source data, which may arise from an unintended misalignment of the x-axis bin\npositions during the plotting process. To address this issue, we have replotted all DLS\nhistograms for Lh-, Rh-, and RAC- Au using the raw data and have replaced Figure\nC\nS23 in the revised Supplementary Information. The updated histograms now correctly\nrepresent the true peak positions of each sample.\nFig. R2 (Revised Figure S23) Size distribution of Lh- Au@MIP, Rh- Au@MIP and\nC C\nRAC- Au@MIP via dynamic light scattering measurement.\nC\nReviewer #3 (Remarks on code availability):\nFrom a cursory review of the code files, this looks reasonable - the README file\nappears to be helpful. The only thing I would suggest would be to put more comments\nwithin the script files themselves. I did not attempt to install or run the code because I\ndo not currently have access to a MATLAB license, and the authors might consider\nreleasing a version in an open-source language like Python. However, I think that the\npackage the authors provided is generally in compliance with good practices for code\navailability.\nResponse: Thank you for this constructive suggestion. We have added detailed\nexplanatory comments within all MATLAB script files. Furthermore, we have\nimplemented the full code in Python and uploaded the Python version to Figshare\n(10.6084/m9.figshare.30391330)."}, {"round": 3, "reviewer_comments": {"reviewer_3": "I thank the authors for taking the time to address the points I raised, and in particular appreciate their willingness to translate their source code into Python. I am happy to recommend publication with no further changes."}, "author_response": ""}]

Decision letter