Next-generation inhibitors of SARS-CoV-2 M^pro overcome the deficiencies of Paxlovid

Domain: neuroscience
Published: 2026-04-04
Editorial outcome: major_revision

Abstract
It remains elusive to design peptidomimetic inhibitors of SARS-CoV-2 main protease (Mpro) refractory to multiple deficiencies of Paxlovid (ritonavir-boosted nirmatrelvir), pertaining mainly to E166X mutations-conferred drug resistance and inherent pharmacokinetic limitations to nirmatrelvir. We identify via virtual screening an iso-quinoline P1 moiety in place of the traditional γ-lactam and design iso-quinoline-containing inhibitors with high affinity for Mpro and its nirmatrelvir-resistant E166X mutants. Further optimization at P4 cultivates distinctive peptidomimetic inhibitors with drastically improved pharmacokinetic properties and significantly enhanced antiviral efficacy independent of ritonavir. Two such inhibitors, FD3-32 and FD3-36, also potent against SARS-CoV-1 and MERS-CoV Mpro, are more effective as a monotherapy regimen than Paxlovid in reducing viral loads in vivo and protecting infected male mice from acute lung injury. Here, we report the discovery of next-generation SARS-CoV-2 Mpro inhibitors that overcome the deficiencies of Paxlovid, promising efficacious antivirals critical for mitigating the current and future pandemics of coronaviruses.

Introduction
Within a short period of two decades, the world has already succumbed to three major pandemics of coronaviruses with grave human sufferings, i.e., severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) in 2003 1, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 2, and, particularly, SARS-CoV-2 that causes coronavirus disease 2019 (COVID-19) 3. Tens of millions of people have died worldwide from COVID-19 since December 2019 4, and many more patients who survived SARS-CoV-2 infection have, without timely antiviral intervention, suffered long COVID – a collection of long-lasting symptoms such as fatigue, shortness of breath, chest pain, brain fog, etc 5. The ritonavir (RTV)-boosted oral antiviral nirmatrelvir (NTV), i.e., Paxlovid, developed by Pfizer as a peptidomimetic inhibitor of SARS-CoV-2 main protease (Mpro or 3CLpro), has saved millions of lives globally, and is chiefly responsible, along with mRNA vaccination, for largely mitigating the COVID-19 pandemic.

SARS-CoV-2 Mpro is a cysteine protease that processes viral polyproteins important for the assembly and replication of the positive-sense single-stranded RNA β-coronavirus 3,6-9. Mpro operates the Cys145-His41 catalytic dyad in its active cleft to cleave protein substrates at the specific site of GlnP1-XxxP1’ 7-9; this P1-restricted substrate specificity differs from that of known human cysteine proteases 8,10, making SARS-CoV-2 Mpro an ideal drug target for antiviral therapy 10. Numerous Mpro inhibitors of different structural classes have been reported 11,12, among which NTV, a rationally designed peptidomimetic covalent inhibitor with a γ-lactam ring (formed intramolecularly between the α-amino and side-chain amide groups of Gln) at P1 position 13, and ensitrelvir (ETV), a non-covalent small-molecule inhibitor derived through structure-based virtual screening 14, are clinically proven to be highly effective antivirals for the treatment of SARS-CoV-2 infections.

Despite the huge initial success achieved by Paxlovid in mitigating the COVID-19 pandemic, two major deficiencies of the antiviral are emerging, including evolved drug resistance and adverse clinical effects posed by RTV. The γ-lactam ring at P1 is a general molecular signature of most peptidomimetic covalent inhibitors of Mpro as it supersedes Gln side chain with reduced conformational entropy and, thus, improved binding affinity for the viral protease 15,16. In fact, a network of three H-bonds formed by the P1 residue, Gln side chain or γ-lactam ring, with the three residues F140, H163 and E166 lining part of the S1 binding pocket is strictly maintained in both peptide substrate-Mpro and NTV-Mpro complexes (Figure 1a and Figure S1), structurally validating the “canonical” γ-lactam-for-Gln design strategy. When a six-membered δ-lactam ring was introduced at P1 of nirmatrelvir, a stronger H-bond formed between the lactam NH and E166 side chain carboxylate, largely responsible for several-fold enhancement of inhibitory and antiviral activity 17. While this high-fidelity H-bonding network involving the side chains of H163 Nε2 and E166 Oε2 ensures recognition specificity in both catalysis and inhibition, it invites escape mutations at these two positions for the virus to develop drug resistance. A recent study has shown that an H163A mutation completely abolishes the catalytic activity of Mpro due to mutation-induced conformational changes 18, leaving E166 all the more vulnerable to either laboratory-evolved or clinically selected mutations for potential resistance 19-22. In fact, drug-resistant variants of the virus featuring E166A or E166V mutation in Mpro, often in combination with M49L, L50F and/or L167F compensatory mutations to partially improve replicative fitness 19, exhibit much-reduced sensitivity to NTV and/or ETV due mainly to the loss of electrostatic interactions afforded by E166 side chain 19,23-27. Although the prevalence of E166X mutations is relatively low in clinical strains 21, pre-emptive and sharply focused efforts are warranted to develop peptidomimetic inhibitors of Mpro with a “non-canonical” P1 moiety to maximally circumvent drug resistance conferred by E166 mutations.

Adverse clinical effects posed by RTV are perhaps a more imminent threat to the future success of Paxlovid, which brought in for Pfizer $5.7B revenues in 2024 alone 28. RTV is an HIV-1 protease inhibitor clinically used along with other drugs for the treatment of HIV-1 infection 29,30. Coincidentally, RTV also potently inhibits cytochrome P450 3A4 (CYP3A4), an enzyme in the liver that metabolizes NTV primarily through oxidation of the γ-lactam ring 13, and P-glycoprotein (P-gp), a multidrug efflux transporter in the plasma membrane that diminishes intracellular NTV 31. While co-administration of RTV significantly improves therapeutic efficacy of NTV against SARS-CoV-2 infection by suppressing hepatic metabolism and drug efflux 32, it poses serious concerns of drug-drug interactions with multiple medications even after withdrawal of Paxlovid 33,34, thus adversely affecting the treatment of other diseases 31,34,35. For this reason, earnest efforts are ongoing to develop efficacious antiviral monotherapy against SARS-CoV-2 infection without RTV 36,37.

In this work, we initially set out to tackle evolved drug resistance to NTV through the discovery of a distinctive class of peptidomimetic inhibitors against SARS-CoV-2 Mpro and its E166X mutants. We find that iso-quinoline in place of γ-lactam ring at P1 largely overcome drug resistance instigated by E166X mutations. Additional modifications at P4 improve pharmacokinetic properties of these inhibitors, which leads in a monotherapy to enhanced in vivo antiviral efficacy compared with NTV (with or without RTV). Further, these inhibitors are potently active against Mpro from SARS-CoV-1 and MERS-CoV, promising a next generation of broad-spectrum antivirals with far reaching implications for clinical intervention of future pandemics of sarbecoviruses and merbecoviruses.

Results
Identification of pyridine/iso-quinoline derivatives at P1 via virtual library screening.
To discover an alternative class of P1 groups in replace of γ-lactam, we first validated our docking protocol using ETV as a quality control (Figure S2), followed by virtually screening of a commercial library of ~3,000,000 compounds from four Enamine collections (advanced, functional, hts and premium) against the catalytic cleft of Mpro, from which 10,847 hits were obtained after binding energy-based refinement. Hit compounds were further divided into ten clusters based on Morgan fingerprints 38 and projected into a two-dimensional (2D) chemical space for abundance and distribution (Figure 1b). The compound with the strongest binding energy from each cluster was selected (Figure S3), and its 2D chemical structure presented in Figure 1b. Nine out of these ten representative compounds contained a heterocycle P1 moiety (colored in hot pink), among which four compounds comprised the same pyridine group at P1 (Figure 1b). This finding prompted us to conduct a substructure refinement search for aromatic nitrogen heterocycles, which led to the identification of pyridine and its derivatives (2066/10847) in 19% compounds from the above 10,847 hits (Figure 1c). While pyridine and its derivatives displayed a high probability density in the 2D chemical space as monocyclic replacements for γ-lactam, iso-quinoline and its derivatives at 0.42% (46/10847) stood out as a bicyclic aromatic nitrogen heterocycle at P1 with the highest probability density. Of note, pyridine at P1 had been previously reported for some non-covalent inhibitors of Mpro, and the crystal structures of their complexes with the enzyme determined (Figure S4) 39-41. In a non-peptidic inhibitor scaffold discovered by the COVID Moonshot team, iso-quinoline in place of pyridine at P1 was found to substantially boost Mpro inhibition through expanded hydrophobic interactions 42. Unfortunately, these non-covalent inhibitors failed to achieve sufficient therapeutic exposure in vivo due to high clearance and low bioavailability 42.

To dissect the preference of Mpro for pyridine/iso-quinoline derivatives at P1, we analyzed in a molecular docking study six representative compounds from the substructure refinement search (Figure S5). As shown in Figure S5, the aromatic pyridine/iso-quinoline ring occupied the same position as γ-lactam, with its nitrogen atom (as opposed to the carbonyl oxygen atom in γ-lactam) accepting an H-bond of ~3.0 Å from H163 Nε2, while leaving F140 O and E166 Oε2 in a “unbound” state due to the lack of additional H-bond acceptors/donors as previously seen (Figure S4) 39-41. To interrogate further, we designed and synthesized 29 non-covalent inhibitors of Mpro comprising a pyridine/iso-quinoline moiety (for the S1 pocket) linked to an aromatic (for the S2 pocket) (Figure S6a). Most of these compounds exhibited dose-dependent inhibition of wild-type (WT) Mpro with low micromolar Ki values and highly similar docking modes in the catalytic cleft as predicted (Figure S6b-c and Figure S7). Importantly, iso-quinoline and its bicyclic derivatives at P1 were generally superior to pyridine and its monocyclic derivatives as evidenced by their significant differences in Ki values (Figure S6a-b). Molecular dynamics (MD) simulation studies of six representative synthetic compounds docked in the active site of Mpro confirmed the presence of a highly stable H-bond donated by H163 Nε2 to the nitrogen atom of both monocyclic (FD6-7 and FD6-8) and bicyclic derivatives (FD6-10, FD6-31, FD6-68, and FD6-69) at P1 (Figure 1d-e, Figure S8a and Figure S9). Moreover, while both types of derivatives interacted favorably with H163, H164 and M165 of Mpro, residues 140-145 collectively contributed more binding energy to the bicyclic P1 moieties than to the monocyclic counterparts (Figure 1f and Figure S8b), thereby explaining the superiority of iso-quinoline over pyridine at P1.

Structural validation by nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. We expressed 15N-labeled Mpro in E. coli (Figure S10) and determined its 2D NMR spectra in the presence and absence of some pyridine/iso-quinoline-derived inhibitors. As shown in Figure 2a-b, the 1H-15N TROSY-HSQC (transverse relaxation optimized spectroscopy-heteronuclear single quantum correlation) spectrum of either apo or inhibitor-bound Mpro displayed generally well-dispersed resonance peaks, except for the broadening of some in the center, as reported previously (Figure S11-S12) 43,44. In the absence of a more comprehensive NMR study of our Mpro with limited spectroscopic data, we only made partial assignments according to the published spectra (Figure S11-S12) 43,44. The chemical shifts assigned in this study alongside the previously reported values are listed in Table S1, accompanied by calculated combined chemical shift deviations (CCSD) as a measure of assignment reliability/ambiguity. For clarity, the assignments were further grouped and differentially colored based on the degree of resonance peak crowding and/or overlapping in Table S1. Addition of each of the four inhibitors FD6-7, FD6-10, FD6-31 and FD6-68 to Mpro at a molar ratio of 2:1 invariably induced significant alterations in chemical shifts of some resonance peaks assigned to residues in the catalytic cavity, including V42, T45, F134, G170, V171, T175, V186, and Q192 (Figure 2c-f). The resonance peaks of some residues located in the S1 pocket such as F140, L141, N142 and E166 became much sharper upon inhibitor binding (Figure S13), indicative of strengthened S1 interactions with pyridine/iso-quinoline derivatives at P1. Of note, FD6-10 with bicyclic iso-quinoline at P1 exerted a much stronger influence on both the sharpness and chemical shifts of those resonance peaks than did FD6-7 with monocyclic methylpyridine, whereas FD6-31 with iso-quinoline and FD6-68 with naphthyridine behaved largely the same (Figure 2c-d and Figure S13), thus corroborating the findings from MD simulation studies and inhibitory activity measurements.

To validate their mode of inhibition at atomic levels, we solved the crystal structure of Mpro in complex with FD6-31 at 1.96 Å resolution (Table S2). As shown in the electron density map of FD6-31 occupying the catalytic cavity of Mpro (Figure 2g), the iso-quinoline moiety embeds itself in the S1 pocket, while the chloro-phenyl group packs against the S2 pocket. As predicted, the N atom of iso-quinoline accepts an H-bond of 2.9 Å from H163 Nε2, an indispensable interaction further strengthened by an aromatic heterocycle (π-π) stacking between the imidazole and iso-quinoline rings (Figure 2h). Additional stackings form between the iso-quinoline ring and the peptide bond (amide-π) of L141-N142 as well as the side chain (sulfur-π) of C145, which, along with a crystalline water molecule (W1) bridging the phenyl moiety of iso-quinoline with N142 N via two H-bonds, contribute collectively to the preferred recognition of iso-quinoline by the S1 pocket (Figure 2h). In the S2 pocket, the chloro-phenyl moiety of FD6-31, sandwiched between the side chains of M49 and M165, packs its aromatic ring against H41 (π-π stacking), with its Cl atom in intimate contact with H41 Nδ1, M165 Cε and D187 Cβ (Figure 2i). An H-bond of 3.0 Å formed between G143 N and the carbonyl O of FD6-31, hydrophobic interactions between C145 Sγ and the heterocyclic linker of FD6-31, and a crystalline water molecule (W2)-mediated indirect contact between the carbonyl O of FD6-31 and C145 N, further stabilize the non-covalent inhibitor in the catalytic cavity of Mpro (Figure 2j). Of note, the co-crystal structure largely corroborated the docking model of the FD6-31-Mpro complex (Figure 2k), attesting to the validity of computational efforts. In fact, we further conducted refined MD simulations and computational alanine scan analysis based on the co-crystal structure of FD6-31-Mpro complex (Figure S14), and the results, while entirely consistent with the structural findings, reenforced the energetic importance of C145, H163, and the peptide bond of L141-N142. Finally, comparison of the crystal structures of Mpro in complex with NTV and with FD6-31 underscored some critically important differences between γ-lactam and iso-quinoline in the S1 pocket (Figure 2l). The former is mainly stabilized by an intricate network of triangulated H-bonds with F140 O, H163 Nε2 and E166 Oε2, whereas the latter only engages H163 Nε2 for binding (Figure 2l). Despite fewer H-bonds iso-quinoline forms, its aromaticity affords compensatory π stacking interactions absent in the binding of γ-lactam, contributing not only to its energetic preference by the S1 pocket, but more importantly, to its selection as a non-canonical P1 moiety independent of resistance-prone E166 mutations.

Structure-to-activity relationships (SAR) of peptidomimetic inhibitors with iso-quinoline at P1 against SARS-CoV-2 Mpro and three critical E166X mutants. Inspired by the above findings, we set out to test the proof-of-concept of designing peptidomimetic covalent inhibitors against wild-type (WT) and NTV-resistant Mpro through substituting iso-quinoline for γ-lactam. A fluorescence resonance energy transfer (FRET)-based enzymatic assay was employed to determine the Ki value of each inhibitor 45,46. To this end, we initially replaced γ-lactam of NTV with pyridine, yielding a weakened inhibitor (FD3-5) against WT Mpro with a Ki value of 29.0 nM, 6-fold higher than that of NTV (Ki = 5.10 nM) (Figure 3a, Figure S15 and Table S3). However, iso-quinoline replacement of γ-lactam improved inhibitory activity of FD3-6 over NTV by 40%, resulting in a Ki value of 3.08 nM (Figure 3a, Figure S15 and Table S3). This initial study functionally confirmed the superiority of iso-quinoline over pyridine, which was also verified in the scaffold of inhibitor GC376 (Figure 3a), cementing the use of iso-quinoline as an invariant P1 moiety in subsequent extensive SAR investigation aimed at further optimizing subsite interactions involving P2, P3 and P4.

A chemically synthesized 15 additional derivatives of FD3-6 (FD3-11 to FD3-28, Figure 3b) by introducing cyclo-propyl-spiro-proline in place of dimethyl-cyclo-propyl-proline moiety at P2, cyclohexyl in place of tert-butyl at P3, and 13 different groups in place of trifluoromethyl at P4. While both cyclo-propyl-spiro-proline at P2 and cyclohexyl at P3 as well as most substituents at P4 were functionally deleterious (Figure 3b), difluoro-chloromethyl (FD3-22), cyclopropyl (FD3-24) and difluoro-cyclopropyl (FD3-25) at P4 improved inhibitory activity by 2-3 folds as compared with trifluoromethyl in FD3-11 (Figure 3b). The P4 position of GC376 backbone was also interrogated through replacing benzyl (FD3-8) with indolyl derivatives, and the resultant inhibitors FD3-9, FD3-30 and FD3-31 all functionally benefited from an enlarged aromatic substitution.

Given the SAR results, the P2 and P3 moieties were reverted to those of NTV in the next round of inhibitor design, which incorporated difluoro-chloromethyl and difluoro-cyclopropyl substituents at P4, yielding compounds FD3-32 and FD3-33 (Figure 3c). FD3-32 and FD3-33 potently inhibited WT Mpro with respectively Ki values of 0.513 and 1.23 nM, roughly 5~10-fold stronger than NTV (Figure S15 and Table S3). A slight increase in the ring size at P4 from difluoro-cyclopropyl (FD3-33) to difluoro-cyclobutyl (FD3-34, Ki = 0.983 nM) marginally improved inhibitory activity (Figure 3c, Figure S15 and Table S3). Interestingly, while replacement of one fluorine atom with Cl in the trifluoromethyl group substantially increased inhibitory activity of FD3-32 over FD3-6, introduction of bromine at the same position had little effect on FD3-36.

A critical test of the proof-of-concept of the design of compounds FD3-6, FD3-32, FD3-33, FD3-34 and FD3-36 lies in their enhanced ability to inhibit E166X mutants of Mpro. We expressed in E. coli three reported E166X mutants of Mpro resistant to ETV and/or NTV (Figure S16), i.e., M49L/E166A 23, L50F/E166A/L167F 24, and L50F/E166V 24. Added to the panel of inhibitors for comparison was Ibuzatrelvir (ITV) – a next-generation monotherapeutic peptidomimetic inhibitor under clinical development by Pfizer against SARS-CoV-2 Mpro 36. As shown in Figure 3d-e, while NTV, ITV, and ETV in particular, lost much of their inhibitory activity against the M49L/E166A mutant, registering respective Ki values of 224 nM, 477 nM, and 71.3 μM, FD3-6 (8.62 nM), FD3-32 (2.18 nM), FD3-33 (1.76 nM), FD3-34 (10.6 nM) and FD3-36 (4.65 nM) all maintained potent inhibition of the enzyme with Ki values in the low nanomolar concentration range (Table S4). With respect to the NTV/ETV-resistant triple mutant L50F/E166A/L167F, although all our compounds exhibited somewhat reduced inhibition to double-digit nanomolar Ki values, they were still 15~43-fold stronger than NTV and ITV, and 168~400-fold better than ETV (Figure 3d-e and Table S4). The double mutant L50F/E166V is particularly resistant to NTV 24, which inhibited the enzyme in our assays with a Ki value of 25 μM, representing a 5000-fold reduction in inhibitory activity (Figure 3d-e and Table S4). However, our designed inhibitors FD3-32, FD3-33, FD3-34 and FD3-36 faired 23~150-folder better than NTV, with FD3-33 being the strongest (Ki = 167 nM). Taken together, these data biochemically validate the inhibitor design strategy for tackling E166 mutation-conferred drug resistance through substituting a non-canonical moiety, iso-quinoline, for the canonical γ-lactam group at P1 – an iterative process also facilitated by the optimization of P4.

The importance of H163 for Mpro inhibition by FD3-32 and FD3-36. H163 in the S1 pocket of Mpro forms via its imidazole ring a critical H-bond with the sidechain of Gln at P1 of the substrate (Figure 1a) 8, thus important for catalysis. Tran et al. previously reported that an H163A mutation completely inactivated Mpro by inducing in the active site a conformational change confined by a newly formed disulfide bridge between the catalytic thiol group of C145 and neighboring C117 18. Given that the iso-quinoline ring at P1 of our inhibitors is also H-bonded to H163 (Figure 2h), we produced an H163A mutant and characterized its inhibition by NTV, ITV, FD3-32 and FD3-36 to better understand the functional importance of H163 for Mpro inhibition (Figure S17).

As shown in Figure 3f-g, the H163A mutation markedly reduced enzymatic activity (kcat/Km) by a whopping 600-fold (Figure 3g) but did not fully obliterate it, contrasting the previous report 18. Since the catalytic activity of a cysteine protease depends much on the use of a strongly reducing agent in the assay buffer to keep the catalytic thiol group from being oxidized or forming a disulfide bond 47, this observed discrepancy may likely be attributable to differences in experimental conditions pertinent to reducibility. Importantly, the 600-fold decrease in enzymatic activity mostly came from the loss of the turnover number or kcat, but not from Km, suggesting that during catalysis H163 likely formed a much stronger H-bond with P1 Gln of the substrate in the transition state than in the ground state.

While important for catalysis, H163 was also crucial for Mpro inhibition by NTV, ITV, FD3-32 and FD3-36 as it formed the critical H-bond with the γ-lactam or iso-quinoline ring at P1 (Figure 1a and Figure 2h). As shown in Figure 3h, a huge reduction of ~4 orders of magnitude in inhibitory activity was observed for these Mpro inhibitors against the H163A mutant, registering decreases in Ki of 40,000-fold for FD3-32 and of 4,000-fold for FD3-36 (Table S4). Of note, although these Mpro inhibitors can theoretically induce mutations at position 163 conferring resistance, it is likely to be difficult for drug-resistant H163X mutants to emerge due to its greatly reduced catalytic activity or replication fitness. Nevertheless, adaptive laboratory evolution of SARS-CoV-2 in the presence of FD3-32 and FD3-36 is warranted in future studies to rigorously survey the landscape of resistance for our inhibitors to attest their ability or lack thereof to overcome additional Mpro mutations that may arise.

Mode of action of FD3-32 and FD3-33 against Mpro. Given their potent inhibitory activity against Mpro and its NTV-resistant mutants, FD3-32 and FD3-33 were selected for an in-depth study to decipher their mechanisms of inhibition at the molecular level. We characterized 15N-labelled WT Mpro in the presence and absence of the inhibitors and NTV by NMR spectroscopy. As shown in the 1H-15N TROSY-HSQC spectra (Figure 4a and Figure S18a-b), addition of FD3-32, FD3-33 or NTV to Mpro induced, as expected, notable shifts of resonance peaks assigned to the residues in the catalytic cavity (Figure 4b-c and Figure S18c-f). As was the case with non-covalent inhibitors (Figure S13), binding of FD3-32, FD3-33 or NTV to Mpro invariably sharpened resonance peaks of the residues located in the S1 pocket, including F140, L141, N142, E166 and L167 (Figure 4b-c and Figure S18c-f). However, the degree and extent of chemical shifts caused by our peptidomimetic inhibitors and NTV varied significantly, as evidenced by changes in chemical shift of the three sets of residue(s) V171 and Q192, G170 and F185, and M49 (Figure 4b-c and Figure S18c-f). These findings illustrate that FD3-32 or FD3-33, in comparison with NTV, while occupying the same orthosteric site in Mpro, differentially induced conformational perturbations not only to local residues composed of the S1 pocket, but also to adjacent residues located in a β-hairpin, an α-helix and a loop motif surrounding the S2, S3 and S4 pockets (Figure 4d). MD simulations based on the crystal structures of Mpro (apo state) and NTV-Mpro and on the docking complexes of FD3-32/FD3-33-Mpro (Figure S19) corroborated the NMR results by generating ternary phase diagrams for analysis of the mobility, as characterized by statistical dispersion of the MD ensemble, of each of those three structural elements. As shown in Figure 4e, while inhibitor binding to Mpro differentially increased the mobility of the α-helix (aa 45-51), binding of FD3-32/FD3-33 constrained the conformations of the β-hairpin (aa 166-172) and the loop (aa 185-193) more strongly than that of NTV, indicative of enhanced P1-S1 and P4-S4 interactions involving our inhibitors.

Using ESI-TOF mass spectrometry, we detected covalent complexes of Mpro formed with our peptidomimetic inhibitors upon mixing (Figure S20), validating the mechanism of covalent inhibition. We further compared NTV and FD3-33 in their ability to form covalent complexes with Mpro and its three resistant mutants, M49L/E166A, L50F/E166A/L167F and L50F/E166V, as the molar ratio of inhibitor to enzyme was progressively raised from 0.039:1 to 5:1. As shown in Figure 4f and Figure S21, the abundance of enzyme-inhibitor complex relative to free enzyme on mass spectrometry was, as expected, dependent on the concentration and potency of inhibitor, qualitatively confirming the supremacy of FD3-33 over NTV in covalent inhibition of both wild type and mutant enzymes. Of note, we could not quantify these interactions as the covalent bond of thioimidate formed by the catalytic thiol group of the enzyme and the cyano group of the inhibitor is known to be acid labile and readily breaks down reversibly under LC-MS conditions.

Drug-resistant mutations of Mpro marginally reduced the thermal stability of the enzyme as characterized by melting temperature (Tm) measured in a protein thermal shift assay 48-50 (Figure 4g), likely contributing to its impaired replicative fitness. While binding of FD3-33 and NTV to WT Mpro substantially improved the enzyme’s stability, the effect of our inhibitor was much more pronounced (Tm from 53.5 to 75 °C) than that of NTV (Tm from 53.6 °C to 65.8 °C) (Figure 4h), indicative of a stronger binding affinity of FD3-33 for WT Mpro than NTV. Similarly, while NTV binding showed rather limited influence on the stability of the three resistant mutants of Mpro with ΔTm only ranging from 0.9 °C to 3.5 °C (Figure 4h), FD3-33 binding resulted in significant Tm shifts by 12.8 °C for L50F/E166A/L167F mutant and 12.5 °C for M49L/E166A mutant (Figure 4h). The smallest Tm shift of 1.4 °C seen with L50F/E166V mutant was likely attributed to FD3-33 being the least potent inhibitor against L50F/E166V mutant than against WT Mpro and the other two mutants. Taken together, these findings fully elucidate at the molecular and structural levels the mechanisms of action by which our designed inhibitors decimate the function of Mpro and its drug-resistant mutants.

In vitro and in vivo antiviral efficacy, pharmacokinetic and safety profiles of FD3-32 and FD3-33. We first subjected our peptidomimetic inhibitors FD3-6, FD3-32, FD3-33 and FD3-34 to a cytotoxicity assay using human lung epithelial cell A549, mouse macrophage J774A.1, transformed human liver epithelial-2 (THLE-2) cell and African green monkey kidney epithelial cell Vero E6, and none of them impacted the viability of these different cell lines at the highest concentration of 50 μM tested (Figure S22). FD3-32 and FD3-33 along with NTV were subsequently evaluated in an in vitro antiviral efficacy assay using Vero E6 cells infected with SARS-CoV-2 Omicron BA.5.2 (100 TCID50). While FD3-32 and FD3-33 showed remarkable antiviral activity with respective IC50 values of 0.794 nM and 9.17 nM as determined by immunofluorescence staining of SARS-CoV-2 nucleocapsid protein (Figure 5a-b and Figure S23), NTV was drastically less active against the virus with an IC50 of 1530 nM (Figure 5a-b and Figure S23), a reduction in activity by 2-3 orders of magnitude. RT-qPCR was also used to quantify viral nucleic acids in cellular supernatants, yielding IC50 values of <0.0256 nM, 0.944 nM and 30.2 nM for FD3-32, FD3-33 and NTV, respectively (Figure 5c), largely consistent with the immunofluorescence staining results.

To understand why FD3-32 and FD3-33 were orders of magnitude more active than NTV in vitro despite a modest improvement in their inhibitory activity against Mpro, we compared FD3-32 and NTV in an in vitro infection assay where a P-gp efflux inhibitor, CP-100356, was used 13,51. As shown in Figure S24, while CP-100356 treatment had little effect on the antiviral activity of FD3-32 against SARS-CoV-2 Omicron BA.5.2 infection on Vero E6 cells, it enhanced far less potent NTV activity by at least 30-fold. These results indicate that the supremacy of FD3-32 and FD3-33 resides largely in their ability to evade P-gp-mediated efflux detrimental to NTV.

To prepare FD3-32 and FD3-33 for in vivo efficacy studies, we initially assessed their acute toxicity in healthy male BALB/c mice by orally administering (p.o.) low (100 mg/kg), medium (300 mg/kg), and high (900 mg/kg) doses of NTV, FD3-32 or FD3-33. All mice challenged with these compounds showed 100% survival with healthy alterations in body weights within 7 days post administration (Figure S25a). None of the three compounds showed any adverse effects on the liver and kidney (Figures S25b-c), indicative of pharmacologically acceptable safety profiles. We then evaluated their single-dose pharmacokinetic profiles in healthy male BALB/c mice through oral gavage (20 mg/kg) or intravenous injection (i.v.) (2 mg/kg). Compared with NTV, FD3-32 exhibited a ~2-fold increase in the volume of distribution (Vd) and a ~3-fold reduction in clearance (CL), translating into a prolonged i.v. half-life (t1/2) of ~1.18 h (as opposed to ~0.230 h for NTV) (Figure S26 and Table S5). Although FD3-33 retains the iso-quinoline ring at P1 as FD3-32, its difluoro-cyclopropyl (as opposed to trifluoromethyl or difluoro-chloromethyl) moiety at P4 led to a ~2-fold and a ~5-fold higher clearance than NTV and FD3-32, respectively, ensuing a rapid elimination (i.v. t1/2 = ~0.150 h) of FD3-33 with a comparable Vd to either NTV or FD3-32 (Figure S26 and Table S5). Notably, despite NTV’s longer p.o. t1/2 than those of FD3-32 and FD3-33, both lead compounds exhibited a substantially higher peak plasma concentration (Cmax) than NTV following oral administration, contributing to ~56% and ~170% improvement in oral bioavailability over NTV (Figure S26 and Table S5).

It is worth noting that the elimination t1/2 is an intrinsic pharmacokinetic parameter of a drug dependent only on CL and Vd and should not be influenced in linear pharmacokinetics by dose and the route of administration. However, the apparent p.o. t1/2 of FD3-32, FD3-33 or NTV in our pharmacokinetic studies was significantly longer than its i.v. t1/2, suggesting several possible scenarios. First, high oral doses (relative to low i.v. doses), which are typical in pharmacokinetic studies, may result in a high concentration in the systemic circulation that leads to elimination saturation. Second, poorly soluble oral drugs are often associated with slow absorption, leading to a prolonged p.o. t1/2 in so-called flip-flop kinetics. Third, if drug concentrations fall below quantification limit early as was the case with our tested compounds, inaccuracy in i.v. t1/2 measurements may ensue, thus yielding a falsely short elimination t1/2. Presumably for some of these reasons, the reported ratios of the apparent p.o. t1/2 of NTV and its derivatives to their corresponding i.v. t1/2 swing wildly from as low as 0.5 to as high as 5.5 13,37. Improved data analysis aided by contemporary pharmacokinetic modelling approaches is clearly warranted to address this limitation in our pharmacokinetic studies to better understand the disparity between i.v. t1/2 and p.o. t1/2 for this class of Mpro inhibitors.

Humanized male C57BL/6S mice were intranasally infected with Omicron BA.5.2 for 2 h, followed by orally administered drug treatment for 3 days with NTV at 200 mg/kg twice daily, and with FD3-32 or FD3-33 at the same dose once daily (Figure 5d). Of note, the dosage of FD3-32 or FD3-33 was half as much as that of NTV due to our inhibitors’ superior oral bioavailability and in vitro bioactivity. In addition, RTV was orally co-administered at 50 mg/kg to simulate NTV’s clinical application scenarios (Figure 5d). As shown in Figure 5e-f, treatment with FD3-32/FD3-33 dramatically decreased viral RNA load in both bronchus and lung tissues as quantified by RT-qPCR, whereas NTV treatment failed to reduce viral burden to a level significantly different from that of the vehicle control group. Interestingly, despite a high level of viral load in the brain of vehicle-treated mice, all three compounds showed excellent protective effects as they largely lowered RNA copies to the limit of detection (Figure 5g). These results were supported by immunohistochemical (IHC) and immunofluorescent (IF) analyses of SARS-CoV-2 nucleocapsid protein in the lung (Figure 5h and Figure S27a), where both FD3-32 and FD3-33 were more effective than NTV in controlling viral infection (Figure 5i), coinciding with different degrees of tissue damage in the lung revealed by H&E staining (Figure 5h). In fact, while histopathological analysis indicated severe organ injury in the vehicle control group as evidenced by large exudation and alveolar membrane thickening, treatment with FD3-32 or FD3-33, and with NTV to a much lesser extent, relieved the pathological alterations (Figure 5h and Figure S28), despite insignificant differences in lung injury scores between vehicle and NTV-treated mice (Figure 5j). These findings were further corroborated by semi-quantification of positive areas of SARS-CoV-2 nucleocapsid protein in the IF images of the lungs. As shown in Figure 5i, NTV, despite suppressing viral RNA load without statistical significance (Figure 5f), was efficacious in significantly reducing the expression of the viral protein in the lung. However, FD3-32 and FD3-33, once again, manifested more potency than NTV in the same in vivo setting.

Encouraged by these results, we then asked the question of whether compound FD3-32, due to its superb antiviral efficacy in vitro and in vivo, could be used in a monotherapy without the aid of RTV. Three groups of humanized male C57BL/6S mice (n=6) were challenged with Omicron BA.5.2 to establish infection, followed by oral administration, twice daily for 3 days, of saline as a vehicle control, FD3-32 at 200 mg/kg, and NTV at 200 mg/kg plus RTV at 50 mg/kg (Figure 5k). Quantification of viral RNA by RT-qPCR in the bronchus, lung and brain tissues showed that FD3-32 and NTV+RTV at the same dosage were largely comparable in activity against SARS-CoV-2 infection (Figure 5l-n). While FD3-32 significantly reduced viral load in the bronchus and brain, but not in the lung, NTV+RTV significantly lowered viral load in the brain and lung, but not in the bronchus. We further analyzed diseased tissues using IF and H&E staining and quantified SARS-CoV-2 nucleocapsid protein in the lung. As shown in Figure 5o-p, FD3-32 caused a pronounced reduction in the expression of SARS-CoV-2 nucleocapsid protein in the lung, with comparable efficacy to NTV+RTV (Figure S27b). Interestingly, histopathological analysis showed infection-stemmed tissue damage, characterized by large exudation and alveolar membrane thickening, was less severe in the FD3-32 treatment group than in the NTV+RTV treatment group (Figure 5o, Figure 5q and Figure S29-S30). Collectively, these in vitro and in vivo results demonstrate the pharmacological supremacy of FD3-32 over NTV in the treatment of SARS-CoV-2 infection.

Pharmacokinetic profiles and in vitro and in vivo antiviral efficacy of FD3-36. Data on NTV, FD3-32 and FD3-33 suggest that the P4 position exerted a strong pharmacokinetic influence on these Mpro inhibitors (Figure S26 and Table S5). In light of this observation, we further interrogated the impact of different haloalkanes at P4 on their pharmacokinetic properties as well as in vitro and in vivo therapeutic efficacy through comparison of FD3-32 (a difluoro-chloromethyl group at P4) and FD3-36 (a difluoro-bromomethyl group at P4) with ITV as a control (Figure 6a and Table S6). As shown in Table S5-S6, the substitution of the Br atom for Cl at P4 improved oral pharmacokinetic parameters of FD3-36 over FD3-32, as evidenced by increases of 99% in p.o. t1/2, 101% in total drug exposure (AUC and Cmax) and 99% in oral bioavailability, albeit their comparable CL, Vd and i.v. t1/2 values. A much more striking improvement came from FD3-36 over ITV (Table S6), where the former showed a 5-fold longer i.v. t1/2 than the latter (1.09 h as opposed to 0.216 h) but a comparable value in p.o. t1/2 (3.22 h versus 3.19 h). More importantly, the total exposure of FD3-36 in tested mice was higher than that of ITV, as indicated by 6-fold and 50-fold differences in AUC for i.v. and p.o. administration, respectively (Table S6). In addition, a higher Cmax of orally administered FD3-36 versus ITV represented an 8-fold improvement in oral bioavailability (Table S6).

To ascertain the translation of superior pharmacokinetic properties into potent therapeutic efficacy, we subjected FD3-32, FD3-36, Paxlovid and ITV to various in vitro and/or in vivo antiviral activity assays. Both FD3-36 and FD3-32 were at least three orders of magnitude more potent than ITV against Omicron BA.5.2 infection in vitro on Vero E6 cells, as evidenced by the IC50 values of 1235 nM, 0.565 nM and 0.177 nM for ITV, FD3-32 and FD3-36, respectively (Figure 6b-c and Figure S31). We further compared FD3-36 as a monotherapy with the combination of NTV and RTV with respect to their in vivo antiviral efficacy, where humanized male C57BL/6S mice were initially challenged with Omicron BA.5.2 to establish infection, followed by oral administration, twice daily for 3 days, of saline as a vehicle control, FD3-36 alone at 200 mg/kg, and NTV at 200 mg/kg plus RTV at 50 mg/kg (Figure 6d). Treatment with FD3-36 more effectively lowered viral load in the bronchus and lung, but not in the brain, than with NTV+RTV, as quantified by RT-qPCR (Figure 6e-g). Further analysis of the lung using IF and H&E staining revealed a remarkable protective effect of FD3-36, as compared with NTV+RTV (P = 0.0295) (Figure 6i and Figure S32), on infection-stemmed inflammatory tissue damage, coinciding with its potent inhibition of the expression SARS-CoV-2 nucleocapsid protein (Figure 6h-i). Consistent with the previous results (Figure 5), large exudation and alveolar membrane thickening were observed in the vehicle control group, which was not significantly alleviated by treatment with NTV+RTV (Figure 6h, 6j and Figure S33-S34), contrasting the powerful protective effect of FD3-36. These in vitro and in vivo results collectively demonstrate the pharmacological supremacy of FD3-36 over Paxlovid (and even FD3-32) in the treatment of SARS-CoV-2 infection.

Broad-spectrum inhibition of Mpro of SARS-CoV-1 and MERS-CoV. The canonical P1-S1 interaction involving a P1 Gln residue is evolutionarily conserved across different species of coronaviruses 52, suggesting our inhibitors may be of broad-spectrum against Mpro’s of different viral origin. SARS-CoV-1 and SARS-CoV-2 Mpro share a 96% sequence identity and are only ~50% identical to MERS-CoV Mpro 52. We thus expressed and purified recombinant Mpro of SARS-CoV-1 and MERS-CoV and quantified their inhibition by the clinical candidates NTV, ETV and ITV and our selected leads FD3-6, FD3-32, FD3-33, FD3-34 and FD3-36 (Figure S35 and Figure 6k). While the inhibitory activity of the three clinical candidates significantly weakened from low nanomolar Ki values for SARS-CoV-2 Mpro to approximately 30~40 nM for SARS-CoV-1 Mpro, FD3-6, FD3-32 and FD3-36 still maintained their potent, single-digit nanomolar inhibition of both main proteases (Ki, 1.5-3.5 nM), with FD3-33 and FD3-34 performing somewhere in the middle pack (Ki, ~12 nM) (Figure 6l and Table S7). FD3-6 and FD3-34 stood out to be the most potent inhibitors of MERS-CoV Mpro, with Ki values at ~8 nM, whereas ETV dropped two orders of magnitude in Ki from its inhibition of SARS-CoV-2 Mpro to of MERS-CoV Mpro (Figure 6l and Table S7). Otherwise, FD3-32, FD3-33 and FD3-36 showed modestly decreased but comparable inhibitory activities with NTV and ITV, with their Ki values clustering between 15 to 23 nM (Figure 6l and Table S7). These results largely validate our iso-quinoline-derived peptidomimetic inhibitors as potential broad-spectrum antivirals against sarbecoviruses and merbecoviruses.

Methods
Ethics Statement
Animal studies were conducted under the authorization of the Laboratory Animal Ethics Committee of the School of Basic Medical Sciences at Fudan University (approved number: 20210315-001). All animal experimental procedures strictly adhered to the International Ethical Guidelines and the National Institutes of Health Guide concerning the Care and Use of Laboratory Animals.

Cell lines and virus
Human lung epithelial cell A549, mouse macrophage J774A.1, transformed human liver epithelial-2 (THLE-2), and the African green monkey kidney epithelial cell Vero E6 cell lines were purchased from the American Type Culture Collection (ATCC). All cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) containing 10% FBS and 1% Pen/Strep, and incubated at 37 °C under 5% (v/v) CO2 atmosphere. SARS-CoV-2 Omicron BA.5.2 variant came from and was conducted in Biosafety Level 3 (BSL3) Laboratory at Shanghai Medical College, Fudan University.

Enzymatic assays
A fluorescence resonance energy transfer (FRET)-based assay was adopted to quantitatively determine the inhibitory activity of compounds against Mpro and its mutants, with an internally quenched fluorogenic peptidyl substrate Dabcyl-KTSAVLQSGFRKME-Edans (Beyotime) using wavelengths of 340 nm and 490 nm for excitation and emission, respectively 19,61. To determine enzymatic parameters, Mpro were initially diluted in assay buffer (20 mM Tris-HCl, 50 mM NaCl, 0.1 mM EDTA, pH 7.4) to specified concentrations. Specifically, the working concentrations were 100 nM for wild-type (WT) SARS-CoV-2 Mpro and its 15N-labelled protein as well as SARS-CoV-1 Mpro, 400 nM for MERS-CoV Mpro, 500 nM for three mutants including M49L/E166A, L50F/E166A/L167F and L50F/E166V, and 1600 nM for H163A mutant of SARS-CoV-2 Mpro. Different concentrations of fluorescent substrate were added into the diluted Mpro. Fluorescence intensities were kinetically monitored by a Spark® multifunctional plate reader (Tecan). Initial velocities were referred as the slopes calculated from fitting the linear portion of the curves to a straight line. A standard curve was generated using Edans, then the time-dependent changes in fluorescence signals of each sample were converted to the catalytic velocity using the unit of nM/s. Parameters including Km, kcat and Vmax were calculated using nonlinear regression fitting by GraphPad Prism 8.0 according to Michaelis-Menten equation.

For determining inhibition constants (Ki), Mpro were diluted in assay buffer to working concentrations (100 nM for WT Mpro of SARS-CoV-1 and SARS-CoV-2, 400 nM for MERS-CoV Mpro, L50F/E166A/L167F and L50F/E166V mutants, and 200 nM for M49L/E166A mutant as well as 1600 nM for H163A mutant). Different concentrations of compounds were then added into the diluted Mpro, and incubated at 37 °C for 5 min. Fluorescence intensities were kinetically monitored by a Spark® multifunctional plate reader (Tecan) after addition of fluorescent substrate (10 μM). The initial velocities were referred as the slopes calculated from fitting the linear portion of the curves to a straight line. Enzymatic activities were characterized by percent velocities in presence of different concentrations of compounds. Ki values were obtained via fitting to the Morrison equation by GraphPad Prism 8.0.

Cytotoxicity assays
Cell lines including A549, J774A.1, THLE-2 and Vero E6 were adopted to evaluate in vitro cytotoxic profiles of tested compounds. Specifically, these cells were plated in 96-well plates with a cell density of 20,000 cells per well, respectively, and incubated at 37 °C overnight. Tested compounds with concentrations ranging from 0.195 to 50 μM were added into cell medium, and the untreated cells cultured in fresh medium were set as control groups. After 24-hour incubation, 10 μL of WST-1 (Beyotime) was added into each well and incubated for 60 min at 37 °C. The optical density for each well was determined by microplate reader at 450 nm (OD450). The assay was biologically repeated for three times. Percent survival (%) of cells was calculated relative to control groups.

In vivo acute toxicity assays
Healthy 8- to 12-week-old male BALB/c mice (17~22 g) were orally administered with test compounds (NTV, FD3-32, and FD3-33) in a low (100 mg/kg), medium (300 mg/kg), or high (900 mg/kg) dosage, respectively. Mice were clinically observed for 7 days after administration, and the body weights were recorded every day. At the end of the experiment, blood samples collected from three mice per group were subjected for detection of alanine transaminase (ALT), aspartate transaminase (AST), creatinine (CREA), and urea nitrogen (BUN).

Pharmacokinetic analysis
NTV, FD3-32, FD3-33, ITV and FD3-36 were subjected to pharmacokinetic analysis via intravenous injection (i.v.) or oral administration (p.o.), respectively. 8- to 12-week-old male BALB/c mice were administered with a single dose of 20 mg/kg (i.v.) and 2 mg/kg (p.o.) compounds in saline containing 5% DMSO, 20% HP-β-CD, and 15% HS-15. Blood samples were collected at specified time points (0.083, 0.25, 0.5, 1, 2, 4, 8, and 24 h for i.v for all tested compounds.; 0.25, 0.5, 1, 2, 4, 6, 8, 24 h for p.o. for NTV, FD3-32 and FD3-33; 0.083, 0.25, 0.5, 1, 2, 4, 6, 8, 24 h for p.o. for ITV and FD3-36) pose-dose, and subsequently centrifuged at 3000 ×g at 4°C for 10 min. Blood samples retrieved from healthy mice were diluted in saline to prepare standard curves by adding specified concentrations (5, 10, 20, 50, 200, 1000, 2000, 5000, 10000 ng/mL) of tested compounds. Supernatants of blood samples were analyzed by LC-MS/MS to determine plasma drug concentrations. A Waters Acquity Premier UPLC-Xevo TQ Absolute equipped with a ACQUITY Premier BEH C18 column (2.1 × 50 mm, 1.7 μm) were employed for separation and quantification of tested compounds with a flow rate of 0.5 mL/min with mobile phase A (0.2% formic acid in ddH2O) and mobile phase B (acetonitrile). Gradient: 0-0.5 min, 10% solvent B; 0.5-1.2 min, 10-90% solvent B; 1.2-1.7 min, 90% solvent B; 1.7-1.8 min, 90-10% solvent B; 1.8-2.5 min, 10% solvent B. The average plasma concentration and standard deviation at each time point were calculated, and PKSolver was employed to fit the pharmacokinetic parameters using a non-compartmental model 62.

Cellular antiviral assays
Vero E6 cells were plated in 96-well plates with a cell density of 20,000 cells per well, and cultured overnight at 37 °C in DMEM medium plus 10% FBS and 1% Pen/Strep. SARS-CoV-2 Omicron BA.5.2 variant (100 TCID50) was then added in the presence or absence of NTV, FD3-32, FD3-33, ITV, or FD3-36 at specified concentrations in DMEM medium plus 2% FBS and 1% Pen/Strep, and the resultant cell plates were placed at 37 °C and cultured for 48 h. For characterizing sensitivity of tested inhibitors to P-gp-mediated efflux, cellular antiviral assays were additionally conducted in the presence and absence of 2 μM CP-100356 (a standard P-gp inhibitor) 13,51. Supernatants were collected from Vero E6 cell culture for RT-qPCR analysis using specific primers of SARS-CoV-2 nucleocapsid protein genes. The cells were fixed with 4% paraformaldehyde for 10 min, followed by permeabilization with 0.2 % Triton X-100 for 30 min, which were then stained with rabbit anti-SARS-CoV-2 nucleocapsid protein antibody (Sino Biological) and Rhodamine-conjugated goat anti-rabbit IgG (Proteintech). After immunofluorescence staining, expression and distribution of nucleocapsid protein in Vero E6 cells were imaged by BZ-X810 Fluorescence Microscope (KEYENCE). Semi-quantification of immunofluorescence images was performed by Image J.

In vivo antiviral assays
All animal experiments involving SARS-CoV-2 infection were performed within a certified animal biosafety level 3 (BSL3) laboratory at Shanghai Medical College, Fudan University. All animal studies were conducted under the authorization of the Laboratory Animal Ethics Committee of the School of Basic Medical Sciences at Fudan University (approved number: 20210315-001). Ten to fourteen-week-old male humanized C57BL6/S mice (CAG-hACE2-IRES-ALuc-Tg) were purchased from Shanghai Model Organisms, and then housed in a specific pathogen-free (SPF) facility of BSL3 laboratory in Fudan University in a 12-h light-dark cycle, under the condition with ad libitum access to irradiation sterilized rodent diet and aseptic water. Mice were divided into four groups (six mice per group) with initial anesthetization by 20 μL/g avertin (Nanjing Aibei Biotechnology), and subsequently challenged intranasally with ~5000 PFUs of SARS-CoV-2 Omicron BA.5.2 in a total volume of 40 μL DMEM. Additional three mice without infection were defined as a mock group. Therapeutic candidates (NTV, FD3-32, and FD3-33) plus RTV were formulated by dissolving in 0.5% methylcellulose solution containing 2% Tween-80 to satisfy requirements of oral administration. After two-hour infection, mice were orally administrated with 200 mg/kg NTV plus 50 mg/kg RTV twice a day (b.i.d.), or 200 mg/kg FD3-32/FD3-33 plus 50 mg/kg RTV once a day (q.d.). All mice were sacrificed after three-day treatments; lung and brain were collected for RT-qPCR assay to quantify loads of viral RNA; owing to time limit of BSL3, only three brain tissues from NTV group had been collected for quantifying viral RNA. Besides, parts of lung tissues were fixed with 4% paraformaldehyde and further submitted to immunohistochemical and immunofluorescence analysis for visualize/quantify the distribution and expression of SARS-CoV-2 nucleocapsid protein. H&E staining was conducted to show the histopathological alterations of lung tissues.

To demonstrate therapeutic efficacy of FD3-32 as a monotherapy, we additionally performed an in vivo antiviral assay. Ten to fourteen-week-old male humanized C57BL6/S mice (CAG-hACE2-IRES-Luc-Tg) were divided into three groups (six mice per group) with initial anesthetization by 20 μL/g avertin (Nanjing Aibei Biotechnology), and subsequently challenged intranasally with ~5000 PFUs of SARS-CoV-2 Omicron BA.5.2 in a total volume of 40 μL DMEM. Therapeutic candidates including FD3-32 alone or NTV plus RTV were also formulated by dissolving in 0.5% methylcellulose solution containing 2% Tween-80. After two-hour infection, infected mice were orally administrated with 200 mg/kg FD3-32 alone, or 200 mg/kg NTV plus 50 mg/kg RTV, or vehicle with equal volume, twice a day (b.i.d.). All mice were sacrificed after three-day treatments; bronchus, lung and brain were collected for RT-qPCR assay to quantify loads of viral RNA. Besides, tissues of lung were additionally fixed with 4% paraformaldehyde, and were further submitted to immunohistochemical and immunofluorescent analysis of SARS-CoV-2 nucleocapsid protein. H&E analysis was also performed to present the histopathological alterations of lung tissues from our tested mice. The same protocols were employed for determining the in vivo therapeutic efficacy of FD3-36 monotherapy against Omicron BA.5.2 infection, in comparison to NTV co-administrating RTV. Due to unexpected death of two mice before infecting virus, the data from 5 mice in the FD3-36 and NTV+RTV groups were ultimately collected. Histopathological lung injury was assessed and scored on a 5-point scale based on the exudation and alveolar membrane thickening: 0, minimal damage; 1, mild damage; 2, moderate damage; 3, severe damage; and 4, maximal damage 63.

Computational methods
Molecular docking
Virtual screening: A crystal structure of SARS-CoV-2 Mpro in complex with a non-covalent inhibitor X77 (PDB ID: 6W63) was employed for all docking calculations in this study. The crystal structure was then prepared via protonation at pH 7.0 by Epik and PROPKA in Maestro. According to a previous publication that used the same crystal structure (PDB: 6W63) for virtual screening 61, histidine residues including His41, His163, His164, His172, and His246 were modeled as Nε-protonated, whereas His64 and His80 were modeled as Nδ-protonated. Crystallographic waters within 3.0 Å from the ligand were retained otherwise removed from the structure. And then the structure was submitted to energy-minimization optimization with OPLS4 force field. Receptor Grid files were generated by applying a cube box with a center of inherent ligand and a size of 20 Å × 20 Å × 20 Å, by using Receptor Grid Generation. Approximately 3 million molecules from the Enamine library (comprising the Advanced, Functional, HTS, and Premium collections, downloaded in December 2021) were initially filtered using Lipinski's rule of five. A high throughput docking campaign was conducted using Schrödinger2021-2 by module of Virtual Screening Workflow on AMD CPU with 128 cores, 256 threads, which used CPU core time of ~120h. The van der Waals scaling was set to 0.8 for the nonpolar atoms of the ligand, and the partial charge cutoff was set to 0.15. Three level docking algorithms with differential accuracy, including HTVS, SP and XP, were applied to perform docking calculations, with 10% compounds reserved after each step’s computation. The final output of hit compounds after multiple docking was re-scored by Prime MM-GBSA to calculate binding free energy.

Induced fit docking: Predicted docking poses of our synthetic inhibitors in complex with Mpro were generated by Schrödinger software package. Receptor was prepared using the conditions consistent with those of virtual screening. LigPrep module was employed to calculate the molecular mechanic parameters of our compounds with OPLS4 force field, and generate states at pH 7.0 by Epik. Non-covalent docking was performed by using Induced Fit Docking module. Receptor Grid files were generated by applying a cube box with a center of inherent ligand and a size of 20 Å × 20 Å × 20 Å. The van der Waals scaling was set to 0.5 for the nonpolar atoms of the receptor and ligand, and the maximum number of poses was set to 20. Multi-thread parallel calculation was employed for individual compound by assigning 20 AMD CPU cores.

Covalent docking: Complexes of our peptidomimetic covalent inhibitors with Mpro were predicted by using the Covalent Docking module of Schrödinger software package. Preparation of receptor and ligands was conducted as previously described. Mass of center of inherent ligand was adopted as the centroid of cube box with a size of 20 Å × 20 Å × 20 Å. Reaction type between the -SH of C145 and -CN of our compounds was set to nucleophilic addition to a triple bond. ~20 AMD CPU cores were assigned to perform the covalent docking per compounds.

Molecular dynamics (MD) simulations
Crystal structures of Mpro in complex with NTV (PDB ID: 7RFS) and peptidyl substrate (PDB ID: 7DVP) 8,13, co-crystal structure of FD6-31/Mpro complex and those docking complexes of our synthetic compounds binding to Mpro were initially imported to PyMOL for removing hydrogens. Chemical structures of ligands were created by Chem3D, were then optimized, and the partial atomic charges were calculated by AM1-BCC method via Antechamber module in Amber20 to obtain the molecular mechanics parameters of small molecules 64. For complexes of covalent inhibitors, parameters of the non-canonical bond formed in the corresponding reactive site should be manually added to the force field files. The molecular mechanic parameters from ff19SB and GAFF2 force field were then assigned to these complexes which were subsequently neutralized by adding potassium/chlorine counter ions and solvated in a cuboid box of transferable interatomic potential with three points model (TIP3P) water molecules with solvent layers 12.0 Å between solute surface and box edges, via LEaP module 65,66. In parallel with the volume of box, specific counts of potassium/chlorine ions were added to achieve the physiological concentration (150 mM) of KCl. Overall, system setup parameters for all-atom MD simulations involved in this study were provided in Table S4. All MD simulations were conducted by using Amber20. The SHAKE algorithm was employed to restrict all covalent bonds involving hydrogen atoms. The pmemd.MPI module was used to perform the minimization, heat, density and equilibration of these solvated complexes through parallel computation with assignation of 64 AMD CPU cores. The solvent and ions were optimized using 10000 steps of steepest descent minimization and 10000 steps of conjugated gradient minimization with protein backbone restrained by 25 kcal mol-1Å-2. The systems were further undergone three steps of energy minimizations by 5000-step steepest descent and 5000-step conjugated gradient minimizations with restrain of backbone Cα atoms by 25, 10, and 5 kcal mol-1Å-2, respectively. Last, the systems were fully relaxed by 10000-step of steepest descent and 10000-step conjugated gradient minimizations without any restraint, thus to remove unfavorable contacts. After minimizations, the systems were heated from 0 K to 300 K in 160-ps timescale and maintained 300 K for 40 ps, by using Langevin dynamics at a constant volume, with a time step of 2 fs. A 200-ps density equilibration was then performed to optimize the heated system which was subsequently undergone two steps of NPT (T = 300 K, P = 1 atm) equilibration with or without backbone restrain for total 200 ps. Finally, these systems were respectively submitted to a 100-ns NPT (T = 300 K, P = 1 atm) production MD simulation with isotropic pressure scaling by using the pmemd.cuda module. Production simulations for each setting were run triplicate. MD trajectories were analyzed by employing CPPTRAJ to extract the RMSD and monitor hydrogen bonds. Conformations at specific frames were exported by using CPPTRAJ, and visualized by PyMOL. MMPBSA.py.MPI module was used to calculate the gibbs free energy change (ΔG) between ligands and Mpro according to the MM/GBSA approach, and the ΔG was further decomposed into the contributions of each residue in Mpro 67. Besides, MMPBSA.py.MPI was also used to run alanine scanning to calculate the ΔΔG after single mutation of residues in Mpro. All production simulations in this study were run for three times to obtain three independent trajectories. All quantitative data in MD simulations were analyzed and visualized by GraphPad Prism 8.0.

Cheminformatics
Enamine library computationally screened against Mpro finally identified a molecular set containing 10847 candidates. To further elucidate chemical features of these compounds to bind receptor, chemical spaces were explored via an extensive effort of RDKit. The molecular set in SDF file was initially imported and adjusted the order of individual compound randomly. Morgan fingerprints were then computed in a radius of 2, and the number of bits was set to 2048 68. Tanimoto similarity was calculated using Morgan fingerprints as input; and Tanimoto distance represented as 1-Tanimoto similarity, was used to construct distance matrix that subsequently transferred to numpy array 68. Compounds were thus clustered to ten groups based on the array of Tanimoto distances by adopting Ward method, and were further visualized as two-dimensional (2D) chemical space by principal components analysis (PCA). The compounds with the best MM/GBSA binding free energy among each group were automatically picked out. RDKit was also employed to search the compounds with substructures of specified aromatic nitrogen heterocycles through matching the simplified molecular-input line-entry system (SMILES) string. 2D chemical spaces were rendered by Seaborn to present the density of molecular distributions, in which the compounds with specified aromatic nitrogen heterocycles were scattered. Potential candidates in scattered compounds exhibited favorable fitting to Mpro were picked out in terms of the interactions with H163, H41, and G143.

Expression and purification of SARS-CoV-1, SARS-CoV-2, and MERS-CoV Mpro and SARS-CoV-2 Mpro E166X mutants
The DNA sequences encoding Mpro of SARS-CoV (nsp5, NCBI RefSeq NC_004718.3), MERS-CoV (nsp5, NCBI RefSeq NC_019843.3), and SARS-CoV-2 (GenBank: MN908947.3) was synthesized with codon optimization for expression in E. coli by TSINGKE, and constructed into the vector of pET28a-SUMO by homologous recombination. The M49L/E166A mutation plasmid was constructed based on above plasmid of wild-type Mpro as template, with the mutation primers as following:
F-M49L: AGATCTGCTGAATCCGAATTATGAAG;
R-M49L: CAGCAGATCTTCACTCGTGC;
F-E166A: CACATGGCACTGCCGACCG;
R-E166A: CAGTGCCATGTGATGCATATAACAAAAGCTC.

Expression vectors of SARS-CoV-2 mutants including L50F/E166V and L50F/E166Q/L167F were synthesized by DETAIBIO, and then constructed into the vector pET30a by homologous recombination. Abovementioned vectors were respectively transformed into E. coli BL21(DE3). A colony of the bacteria was inoculated into 10 mL of LB broth containing 100 μg/mL kanamycin, and cultured overnight at 200 rpm, 37 °C. The overnight inoculum was sub-cultured with ratio of 1:100 for ~150 min until OD600 ≈ 0.6-0.8, then 1 mM IPTG was added for induction of protein expression and incubated overnight at 180 rpm and 16 °C. The bacteria were resuspended in the binding buffer (Tris/HCl pH 8.4+20 mM Imidazole) equivalent to one-thirtieth of the volume of the raw induced bacterial suspension, and then lysed by ultra-high pressure microjet homogenizer at ~1050 bar and 6 °C for 15 min. After centrifuging the bacterial lysate at 12000 ×g for 20 min, the fusion protein existed in the supernatant of the bacterial lysate. The fusion protein was purified by Ni-NTA column (His-Trap FF5ml) with a protein purifier (BIO-RAD NGC Quest 10plus). Before purification, 10 CVs (column volumes) of the binding buffer were used to equilibrate the column at 5 mL/min, and then 15 mL of the sample was loaded at 3 mL/min. After that, 15 CVs of binding buffer were used to wash the non-specific miscellaneous proteins at 5 mL/min. Finally, the protein was eluted by the elution buffer (Tris/HCl pH 8.4+500 mM Imidazole) at a 0-60% gradience for 13 CVs. The final products of mutants L50F/E166V and L50F/E166A/L167F were obtained after eluting of Ni-NTA column. To remove the His6-Sumo tag at the N-terminus of Mpro and Mpro M49L/E166A mutant, the fusion protein was cut by the Sumo Protease (Smart-Lifesciences, China) as instructed by the manufacturer overnight at 4 °C. And the resultant samples were dialyzed overnight at 4 °C against 4 L of fresh binding buffer, the His6-SUMO tag and SUMO protease were both removed when the sample was passed through the Ni-NTA column (His-Trap FF5ml). These final products of proteins were verified by LC-MS, and were concentrated up to about 8 mg/ml, flash frozen in liquid nitrogen and then stored at -80°C until used.

15N-labelled SARS-CoV-2 Mpro expression and purification
A colony of the E. coli BL21(DE3) (pET28a-SUMO-Mpro) was inoculated into 10 ml M9 broth containing 100 μg/ml kanamycin, using 15N-NH4Cl (1g/L) as nitrogen source, and cultured at 200 rpm, 37°C overnight. The overnight inoculum was 1:100 sub-cultured for ~150 min until OD600 ≈ 0.6-0.8, then 1 mM IPTG was added for induction of protein expression. The expression was induced at 180 rpm 37 °C for 3 h and then 16 °C overnight. The bacteria were resuspended in the binding buffer (Tris/HCl pH 8.4+20 mM Imidazole) equivalent to one-thirtieth of the volume of the raw induced bacterial suspension, and then lysed by ultra-high pressure microjet homogenizer at ~1050 bar and 6 °C for 15 min. After centrifuging the bacterial lysate at 12000 ×g for 20 min, the fusion protein existed in the supernatant of the bacterial lysate. The fusion protein was purified by Ni-NTA column (His-Trap FF5ml) with a protein purifier (BIO-RAD NGC Quest 10plus). Before purification, 10 CVs (column volumes) of the binding buffer were used to equilibrate the column at 5 mL/min, and then 15 mL of the sample was loaded at 3 mL/min. After that, 15 CVs of binding buffer were used to wash the non-specific miscellaneous proteins at 5 mL/min. Finally, the protein was eluted by the elution buffer (Tris/HCl pH 8.4+500 mM Imidazole) at a 0-60% gradience for 13 CVs. Then they were added into the dialysis bag, and by dialyzing the sample overnight at 4°C against 3 L of fresh binding buffer with 5 mM β-mercaptoethanol, The His6-SUMO tag and SUMO protease were both removed when the sample was passed through a HisTrap FF5ml column (Cytiva). The flow-through containing the native Mpro was dialyzed (cut-off 6-8 kDa) twice at 4 °C against 4 L of NMR buffer (100 mM NaPi, 50 mM NaCl, 1 mM EDTA, 2 mM DTT, pH 6.8). The protein was verified by LC-MS, the products were concentrated up to about 8 mg/ml, flash frozen in liquid nitrogen and then stored at -80 °C until used.

Electrospray ionization time-of-flight (ESI-TOF) mass spectrometer Assay
To validate the covalent-inhibition mechanism, purified wild-type (WT) Mpro (15 μM) were mixed with FD3-6, FD3-9, FD3-32 and FD3-33 respectively, at a molar ratio of 4:1 (Mpro:inhibitor), and incubated at 37 °C for 10 min. Besides, for characterizing dose-response relationships, purified WT Mpro, M49L/E166A mutant, L50F/E166V mutant and L50F/E166A/L167F mutant (15 μM) were incubated with NTV or FD3-33 at molar ratios ranging from 1:5 to 1:0.039 (Mpro:inhibitor), respectively, and incubated at 37 °C for 10 min. All samples were prepared with a single biological replicate and were then injected into LC-MS system (Agilent HPLC Infinity II 1290 system coupled with a TOF 6230 detector) by using XBridge® Protein BEH C4 column (2.1 mm × 150 mm, 3.5 μm) for separation with a flow rate of 0.4 mL/min with solvent A (0.1% (v/v) TFA in Milli-Q water) and solvent B (0.1% (v/v) TFA in acetonitrile). The initial gradient of 5% solvent B was maintained for 2 min, followed by a gradual increase to 95% for 15 min and maintained for 2 min, and finally back to 5% solvent that maintained for 2 min. Samples went through column were automatically detected by ESI-TOF real time to reflect the relative abundances of Mpro as well as the covalent complexes of Mpro with inhibitors. The exact mass was calculated by deconvoluting molecular ion peaks in ESI-TOF spectra. MS parameters: Gas Temp, 300 °C; Drying Gas, 5 L/min; Nebulizer, 40 psi; Sheath Gas Temp, 325 °C; Sheath Gas Flow, 11 L/min; VCap, 3500 V.

Crystallization, data collection, structure determination, and refinement
SARS-CoV-2 Mpro protein (16 mg/ml) was preincubated with 100 mM FD6-31 (in 100% DMSO) for a molar ratio of approximately 1:3, for 12-18 h at 4 °C. The complex was then passed through a 0.22 μM cellulose-acetate spin filter and set up for crystallization using crystallization robot (Art Robbins Instruments). Each drop consisted of 0.6 μL of protein solution and 0.6 μL of reservoir solution (0.1 M Bis-Tris 6.5, 20% PEG5000MME) and was equilibrated against 80 μL of reservoir solution at 16 °C for 5–7 days to allow crystals to grow. Large crystals were flash cooled in liquid nitrogen after being passed through a cryoprotectant consisting of reservoir solution containing 20% ethylene glycol. The diffraction data were collected using a single crystal at 100 K with a wavelength of 0.979 Å at beamline BL10U2 of the Shanghai Synchrotron Radiation Facility (SSRF) and were integrated and scaled using HKL2000. The structure was solved by molecular replacement using the Mpro complex structure (PDB code: 7VIC) as the search model in the program Molrep. Iterative refinements of the structure model were carried out using Coot and Refmac5. The stereochemical quality of the final model was assessed using MolProbity. The statistics of the data collection and structural refinement are listed in Table S1. The coordinate and structural factors of the Mpro-6-31 complex have been deposited in Protein Data Bank (PDB) under the accession code 9L13.

2D-NMR characterization
All NMR samples were prepared in an NMR buffer containing 100 mM NaPi (pH 6.8), 50 mM NaCl, 1 mM EDTA, 2 mM DTT, and 10% D2O. The final concentration of Mpro were approximately 500 μM. Compounds were titrated from a stock solution to protein at a molar ratio of 2:1. All samples were prepared with a single biological replicate. All NMR spectra were collected at 298.15 K on a Bruker Avance III HD 800 MHz spectrometer equipped with 1H-13C-15N RT-probe. The operating frequencies were 800 MHz for 1H, 201 MHz for 13C, and 80 MHz for 15N. 2D [15N, 1H] TROSY-HSQC spectra were acquired by using the standard Bruker pulse sequence trosyetf3gpsi.2. The spectral widths were set to 13.9486 ppm (F2/1H) and 35.0000 ppm (F1/15N). A total of 1024 complex data points were collected in the direct dimension (F2), and 160 complex increments were collected in the indirect dimension (F1). The spectrum was accumulated with 256 scans per increment. Data were collected and processed by Topspin 4.4.1, and analyzed by CCPNMR3.2.2. Partial assignments were performed through superimposing collected spectra with previously reported spectra 43,44. Combined chemical shift deviations (CCSD) were adopted as a measure of assignment reliability/ambiguity. CCSD were computed for assigned signals in [1H, 15N] TROSY-HSQC spectra according to Eq.1 (below) 69,70:
CCSD = √0.5×[(δH-δH,ref)2 + (αδN-αδN,ref)2] (1)

Differential scanning fluorimetry
Thermal-shift profiles of WT Mpro and mutants in the presence and absence of inhibitors were determined by employing a fluorescence-based thermal shift assay as previously reported 48-50. Purified WT Mpro and resistant mutants including M49L/E166A, L50F/E166V, and L50F/E166A/L167F were diluted in buffer containing 40 mM Tris-HCl (pH 8.4) and 150 mM NaCl to a final concentration of 10 μM. For characterizing influence of inhibitors to thermal profiles, NTV and FD3-33 were added to each Mpro in a final concentration of 10 μM, respectively, and incubated at 25 °C for 10 min. After addition of SYPRO Orange dye (Sigma-Aldrich, final concentration = 20×), the melting curves and melting temperatures (Tm) were thus determined by detecting fluorescent intensity (RFU) of SYRPRO Orange at 490/530 nm excitation/emission wavelengths with heating from 25°C to 95 °C with increment of 0.5 °C (Bio-Rad CFX Connect Real-Time PCR System, FRET mode). The -d(RFU)/dT was plotted against temperature (T), and the minimal signal of the peak was used to define Tm.

Medicinal chemistry
Details on medicinal chemistry including synthesis and compound characterization used in this study can be found in the Supplementary Information.

Statistics and reproducibility
Statistical analyses were performed using GraphPad Prism 8.0. No statistical method was used to predetermine sample size. The investigators were not blinded to allocation during experiments and outcome assessment. Data are presented as mean ± SD or mean ± SEM as specified. The statistical comparisons between two groups were analyzed using an unpaired two-tailed Student’s t-test, and comparisons among multiple groups were performed by two-sided one-way ANOVA or two-way ANOVA. Differences were considered statistically significant when P < 0.05. The Ki values were calculated by fitting to the Morrison equation, while the IC50 values were obtained by fitting to the four-parameter dose-response model in GraphPad Prism 8.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Luo et al reported a systematic design strategy to improve next-generation SARS-CoV-2 Mpro targeted inhibitors with a\nhighly significant improvement in antiviral potency, toxicity, and pharmacokinetics profiles over Paxlovid (NTV). The authors\nelegantly provided a rationale for how they strategize the design to principally avoid the interaction of the γ-lactam ring with\nF140, H163, and E166, which were found to stabilize the interaction of NTV with Mpro. Mutations of H163 and E166 also\nconfer resistance to NTV. The study was done systematically, starting with virtual screening, MD simulations, NMR, X-ray\ncrystallography, in vitro and in vivo antiviral assays, SAR, and pharmacokinetics measurements. The best compounds, FD3-\n32, FD3-33, and FD3-36, showed significant improvement in all aspects compared to NTV and a recent clinical candidate,\nIbuzatrelvir (ITV). The major achievement is that, unlike NTV, which requires pretreatment with Ritonavir (RTV) for its\nefficacy, the newly developed compounds can be used as monotherapy like ITV.\nOverall, this is an outstanding study that has significantly advanced NTV and\nITV. The study will pave the way for designing other antivirals using similar\nstrategies. The authors also presented the methodology in detail with detailed\nstatistical analyses.\nHowever, the author should address the possibility of H163 mutations by the\nnewly designed compounds since the new compounds principally bind to H163,\nand it was shown that the H163A mutation completely abolishes the catalytic\nactivity of Mpro. To make this contribution even more impactful, the authors\nshould try to generate laboratory-evolved mutations by 1-2 of the most active\nand pharmacologically improved compounds.", "reviewer_2": "This work presents the discovery and optimization of a lead compounds, designed to circumvent two limitations of the\ncurrently available therapeutic, Paxlovid. 1) The requirement of co-administration with Ritonavir and 2) The susceptibility of\nnirmatrelvir to mutations at E166.\nThe paper first starts with the screening of a virtual library to discover a replacement for the γ-lactam group that occupies the\nS1 pocket of Mpro. Binders were confirmed by chemical-shift perturbation using NMR, a crystal structure of one compound\n(FD6-31) with Mpro to confirm the binding pose, molecular dynamics simulations of this complex and a virtual alanine scan\nto confirm the importance of contacting residues. This initial part of the study concluded that the iso-quinoline is an\nacceptable substituent to bind the S1 pocket of Mpro.\nThis has previously been observed \"An increase in potency was unlocked by replacing pyridine with isoquinoline, which\npicks up additional hydrophobic interactions with N142. \"Open science discovery of potent noncovalent SARS-CoV-2 main\nprotease inhibitors. Science382,eabo7201(2023).DOI:10.1126/science.abo7201\nSubsequent experiments took this observation and replaced the γ-lactam of nirmatrelvir with an iso-quinoline and used this\nas a base to perform SAR. Activity was measured with enzymatic assays with recombinant protein, while optimizing other\nsubstituents to generate high affinity compounds that could be tested against variants of Mpro that escape nirmatrelvir. The\nreplacement of the γ-lactam with iso-quinoline enabled subsequent compounds to be less sensitive to tested E166 variants\nand I believe this is novel.\nAlthough virtual screening and validation was performed, the main crux of work is a SAR study on nirmatrelvir. Other studies\ninvolving nirmatrelvir SAR have been published - eg: Arun K. Ghosh, et al,. Exploration of P1 and P4 modifications of\nnirmatrelvir: Design, synthesis, biological evaluation, and X-ray structural studies of SARS-CoV-2 Mpro inhibitors, European\nJournal of Medicinal Chemistry, Volume 267, 2024. This detracts from the overall novelty of the work, as novel candidates\nfrom the virtual screen were not pursued.\nThe work then extends further into cellular and in vivo models of infection. The authors claim that they have identified\ncompounds that are more potent than nirmatrelvir, do not need to be co-administered with ritonavir. They claim their\ncompounds have comparable PK properties to Paxlovid and are also active against SARS1 and MERS.\nThe claim that the designed inhibitors are 3 orders of magnitude more potent than nirmatrelvir is misleading. Most readers\nwould assume this means a compound with 1000-fold better binding affinity, but this is likely due to altered efflux in the\ncellular assay, which were performed without P-gp efflux inhibitors. Testing compounds with and without P-gp inhibitors\nshould be done if specific claims about sensitivity to efflux via this route are made. A supplementary dataset should be\nprovided that contains the compounds with Ki values against Mpro wildtype and Mpro variants.\nIt is difficult to assess whether the in vivo data shows a benefit of the new compounds compared to Paxlovid. A central claim\nof the paper is that ritonavir is not required for the new compounds, but this is not tested head-to-head. Figure 5D shows an\nexperiment with nirmatrelvir, FD3-32, FD3-33 all with ritonavir. This shows the FD3-x compounds as performing better than\nnirmatrelvir, however, this differentiating feature is lost in the experiment in Figure 5K where FD3.32 is tested without\nritonavir.\nIt is well known that nirmatrelvir pharmacokinetics are poor in the absence of ritonavir. Nirmatrelvir and the compounds\ntested in the paper all show poor serum half-life. FD3.32 is better, but still has a half-life of less than an hour, suggesting that\nmodification of the compounds has probably not addressed the issue requiring co-administration of ritonavir. Head-to-head\ncomparison of PK +/- ritonavir would determine how dependent the PK properties are on CYP3A/P-gp-mediated clearance.\nThese arguments could be strengthened if these points are addressed.\nMajor points:\n1) The statistical treatment of the data is weak. When discussing Ki values in the section exploring the structure activity\nrelationship, claims such as \"However, iso-quinoline replacement of γ-lactam improved inhibitory activity of FD3-6 over NTV\nby 40%\" can't be supported unless multiple biological replicates are performed. It would be helpful if there were a table\ncontaining all compounds tested, and Ki values for each replicate performed. I'm not suggesting all compounds require\nmultiple replicates but claims in the text should be robustly supported when differences are small, such as 5.10 nM for\nnirmatrelvir and 3.08 nM for FD3-6. Take care to explain if biological replicates or technical replicates have been performed.\nMinor points:\n1) Can the authors elaborate why Nirmatrelvir always outperforms FD3-x series in brain tissue? Is this because of blood-\nbrain barrier or the chemical properties of FD3-x series after introducing the pyridine/iso-quinoline?\n2) Line 11-14, Page 26 is at odds with Line 10, Page 5. Actually, GISAID data only indicates 10-1000 counts of E166 escape\nvariants out of more than 10 million counts. Is there literature to support the claim that these variants are \"becoming\nincreasingly prevalent\".\n3) Line 11, Page 28. The study shows that only E166A can be inhibited by FD3-x compounds in the nM range, while E166V\nis µM range. The claims around E166 should be limited to those variants that have been tested.\n4) Page 12 - SAR section. Please clarify the nature of the assay used to determine Ki values. I assume this is the enzymatic\nassay with peptide substrate as described in the methods, but as NMR could potentially be used to extract binding by\nchemical shift perturbations, it would be helpful to clarify this in the main text.\n5) The \"Enamine\" Library is not defined. This company sells many libraries.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The comments below are on the pharmacokinetics of the developed antiviral compounds reported in this manuscript. The\ndeveloped compounds appear to present pharmacokinetic improvements over current compounds. However the evaluation\nof the data and interpretation of the results should be based on applying the pharmacokinetic principles and should be\nbiologically meaningful.\nPage 6, lines 13-15 and elsewhere in the manuscript: Improved pharmacokinetic properties are not linked to enhancement\nof in vitro efficacy because pharmacokinetics are related to processes in the body and not reactions that happen in vitro. The\nmanuscript also mixes principles of PK with potency. Correct representation of the terminology and underlying basic\nconcepts would be beneficial.\nPage 19 and Figure S20: The manuscript claims that FD3-32 has a longer PO t1/2 compared to IV t1/2, however Figure S20\nsuggests that this conclusion may be based on a 10-fold differences in dose amounts and on a lack of measurement at 24 h\nfor the IV dose, potentially due to the limit of quantification. Based on pharmacokinetic principles, the elimination half-life is\nnot affected by the route of administration, unless there is a rare case of flip-flop kinetics which appears not to be the\ncase here (and if it was, it needs to discussed). Rather, the difference in half-lives appears to be an artifact of comparing\ndifferent dose levels with the concentrations following the lower (IV) dose falling below the limit of quantification much\nearlier. Contemporary PK modelling approaches can account for samples below the quantification limit.\nFigure S20: How many samples in the FD3-32 panel were measurable at 24 h (given no error bar is visible) and if not all of\nthem, how were the others treated in the analysis? Simply leaving out samples with concentrations below the limit of\nquantification can substantially bias the conclusions and comparisons.\nTables S2 and S3: The SD or %CV should be reported not only the average of the parameter estimates.\nElimination half-life is not a primary PK parameter but it is a composite parameter which is determined by elimination\nclearance and volume of distribution which are the primary biological PK parameters. Therefore, meaningful comparisons\nshould be based on clearance and volume of distribution and not primarily on elimination half-life.\nPage 22, lines 14-16: This is not really a biologically informed statement because elimination t1/2 is a composite parameter\nof the biological PK parameters elimination clearance and volume of distribution, whereas bioavailability is related to the\nextent absorbed. It would be more informative to evaluate which underlying biological processes are affected by the different\nstructures of the compounds.", "reviewer_5": "The following comments are made from the reviewer’s expertise in NMR.\n1. The resolution of Figure S9A should be increased to ensure that peak assignments are clearly visible.\n2. The TROSY-HSQC spectrum in Figure S9 shows noticeable noise peaks and peak clusters compared with previously\nreported spectra (Figure S9A). This suggests that the protein sample used in this study has some solubility issue or\nfolding problem. The authors state that assignments were made according to published data. To substantiate this, the reported\nspectrum should be directly overlaid with the spectrum collected in this study, using distinct colors. Additionally,\nassignments from the BMRB should be mapped directly onto the newly collected spectrum. This step is essential because\nmany peaks claimed to undergo CSP overlap with nearby signals, making the assignments potentially ambiguous. For\nexample, assignments of residues such as V171 and T175 appear reliable, whereas those of G170, V186, V42, and Q192 are\nambiguous due to crowding (Fig. 2). Similarly, L141, N142, and E166 assignments are unreliable because of severe\noverlap.\n3. The authors report that upon inhibitor addition, NMR peaks become sharper (Fig. S10). However, peak line-shape\nchanges should be presented more objectively, for example, by displaying normalized 1D slices. Apparent differences in\ncontour maps can be misleading because they depend on the contour level chosen.", "reviewer_6": "The manuscript by Gan Luo et al. presents an integrative approach to develop new inhibitors against SARS-CoV-2 Mpro\nwith an emphasis on tackling the main drawbacks of the approved Paxlovid. While the manuscript is overall well written,\nsome language editing could be helpful as strange use of words appear in various places. The amount of data and evidence\nof the superior characteristics of the new compounds is impressive and warrants publication in Nat Commun. It is however\nhard to assess all methods and per request of the editor, the focus is here on the presented mass spectrometry data, for\nwhich I have just a few comments.\nMajor comments:\n- Figures are on the small end and would benefit from enlarging. The supplementary figures are in part better but e.g. S2 is\nalso very small, it is impossible to read the labels in the structures.\n- None of the compounds shows the expected occupancy in MS reflecting nM affinities. What is the mechanism of covalent\nattachment? Can the chemistry be reverted under the experimental workflow? Since the authors have performed titrations, it\nis advisable to use quantitation rather than just saying it recapitulates the other data. Please also mention in legend of Fig. 4\nwhat concentrations have been used, so it is possible to compare to Fig. S16.\nMinor:\n- p.3 l.17 the processed proteins are implicated in replication, whether some may also play a role in assembly, suggest to\nrephrase.\n- with three replicates reporting SD is usually suboptimal and SEM is to be preferred as statistics are insufficient to determine\na standard deviation\n- please order supplementary figures in order of appearance. Fig. S5 should be shown much later. If it is shown at that place\nfor the WT, then it would be worthwhile showing that with S8 and mention that this is to prove the 15N incorporation, which is\ncurrently not the case.\n- Fig. S8 - please mention/label that this is WT Mpro\n- Fig. 4 and S15 - please provide the calculated mass of the inhibitors next to the compound in Fig. S15 as well. Importantly\nalso provide the absolute concentrations (at least in the figure legends) as these determine bound fractions. Just providing a\nratio is misleading.\nSupplement p.15 ESI-MS\n-please specify the mass spectrometer and software used for deconvolution\n-is the elution profile of free Mpro and inhibitor-modified Mpro identical? If not, this may explain the high fraction of\nunmodified Mpro in Figs. 4 and S16.", "reviewer_7": "This study combines computational and experimental methods to develop improved SARS-CoV-2 Mpro inhibitors that\novercome drug resistance and pharmacokinetic limitations associated with Paxlovid. Through structure-based virtual\nscreening, molecular dynamics simulations, and both in vitro and in vivo testing, the authors identify iso-quinoline-based\npeptidomimetics with good antiviral activity and pharmacokinetic properties. The compounds offer a promising new scaffold\nand contribute to the goal of pan-coronavirus antiviral development, since they show activity against both SARS-CoV-1 and\nMERS-CoV. The approach is rational, integrating computational tools and experiments for compound testing and validation\nof in silico predictions.\nValidation of the docking protocol through redocking of known ligands to the target (e.g. positive control testing) is a standard\nbest practice that appears to be missing. Such validation confirms that the docking setup can accurately reproduce\nexperimentally observed binding poses for target under study and supports confidence in the screening results. If this step\nwas performed but omitted from the writeup for brevity, including it would strengthen confidence in the docking approach and\nserve as a reference for other researchers who may work on Mpro inhibitor development in the future.\nLine 17 on Page 6 in the Supplementary Information appears to repeat the initial lines of the Molecular Docking section.\nSeparating multiple docking methods into clearly defined subsections would improve clarity and reproducibility.\nThe authors mention using Epik and PROPKA to assign protonation states at pH 7, but they do not specify selected\nprotonation states. Histidine can be sensitive to local environment including at pH 7, besides the choice of epsilon versus\ndelta hydrogen when neutral. These chemical-level details can be important for understanding ligand binding preferences if\ntitratable residues occur in the antiviral binding site.\nGiven extensive experimental testing and validation, including in vitro enzymatic and antiviral assays, pharmacokinetics,\nand in vivo efficacy in infected mice, results of the study are compelling, and concerns related to computational methodology\nare minor."}, "author_response": "Response: We thank the reviewer for the extremely positive feedback!\nAs suggested by the reviewer, we have produced the H163A mutant and\ncharacterized its enzymatic activity as well as inhibition by our compounds. The\nH163A mutation indeed substantially impaired Mpro’s enzymatic activity as\nevidenced by a reduction in k /K of ~600 fold (Figure 3F-G). All tested\ncat m\ninhibitors, including FD3-32, FD3-36, NTV and ITV, also exhibited significantly\ndiminished potency against the H163A mutant, with K values increasing to the\ni\ndouble-digit micromolar range (Figure 3H and Table S4). These additional data\nvalidate not only the importance of His163 for catalysis but also its critical role\nin directly engaging the designed inhibitors. Although these inhibitors in\nprinciple can still induce mutations at position 163 to confer resistance, it may\nbe difficult for drug-resistant mutants to emerge due to its greatly reduced\n1\nactivity (thus replication fitness). Laboratory-evolved drug resistance is a great\nidea, one that clearly warrants a future study beyond the scope of our current\nwork. Accordingly, we have made substantial changes to the Results section by\nadding three paragraphs with the following subtitle (Page 16-18):\nThe importance of H163 for Mpro inhibition by FD3-32 and FD3-36.\nH163 in the S1 pocket of Mpro forms via its imidazole ring a critical H-bond with\nthe sidechain of Gln at P1 of the substrate (Figure 1A) 8, thus important for\ncatalysis. Tran et al. previously reported that an H163A mutation completely\ninactivated Mpro by inducing in the active site a conformational change confined\nby a newly formed disulfide bridge between the catalytic thiol group of C145\nand neighboring C117 18. Given that the iso-quinoline ring at P1 of our inhibitors\nis also H-bonded to H163 (Figure 2H), we produced an H163A mutant and\ncharacterized its inhibition by NTV, ITV, FD3-32 and FD3-36 to better\nunderstand the functional importance of H163 for Mpro inhibition.\nAs shown in Figure 3F-G, the H163A mutation markedly reduced enzymatic\nactivity (k /K ) by a whopping 600-fold (Figure 3G) but did not fully obliterate\ncat m\nit, contrasting the previous report 18. Since the catalytic activity of a cysteine\nprotease depends much on the use of a strongly reducing agent in the assay\nbuffer to keep the catalytic thiol group from being oxidized or forming a disulfide\nbond 47, this observed discrepancy may likely be attributable to differences in\nexperimental conditions pertinent to reducibility. Importantly, the 600-fold\ndecrease in enzymatic activity mostly came from the loss of the turnover\nnumber or k , but not from K , suggesting that during catalysis H163 likely\ncat m\nformed a much stronger H-bond with P1 Gln of the substrate in the transition\nstate than in the ground state.\nWhile important for catalysis, H163 was also crucial for Mpro inhibition by NTV,\nITV, FD3-32 and FD3-36 as it formed the critical H-bond with the γ-lactam or\niso-quinoline ring at P1 (Figure 1A and Figure 2H). As shown in Figure 3H, a\nhuge reduction of ~4 orders of magnitude in inhibitory activity was observed for\nthese Mpro inhibitors against the H163A mutant, registering decreases in K of\ni\n40,000-fold for FD3-32 and of 4,000-fold for FD3-36 (Table S4). Of note,\nalthough these Mpro inhibitors can theoretically induce mutations at position 163\nconferring resistance, it is likely to be difficult for drug-resistant H163X mutants\nto emerge due to its greatly reduced catalytic activity or replication fitness.\nNevertheless, adaptive laboratory evolution of SARS-CoV-2 in the presence of\nFD3-32 and FD3-36 is warranted in future studies to rigorously survey the\nlandscape of resistance for our inhibitors to attest their ability or lack thereof to\novercome additional Mpro mutations that may arise.\n(WT) Mpro and its H163A mutant in the presence of 10 μM substrate. (G)\nEnzyme kinetics curve demonstrating enzyme-catalysis velocity of WT Mpro and\nits H163A mutant in the presence of different concentrations of substrate.\nEnzyme kinetic parameters including concentration of enzymes ([E] ),\n0\nmaximum velocity (V ), Michaelis constant (K ), catalytic constant (k ) and\nmax m cat\nk /K , are calculated by fitting to the Michaelis-Menten equation in GraphPad\ncat m\nPrism 8. (H) Dose-response curves of NTV, ITV, FD3-32 and FD3-36 against\nH163A mutant. All assays were performed triplicate, data are presented as\nmean ± SEM, and the K values are calculated by fitting to the Morrison equation\ni\nin GraphPad Prism 8.\nTable S4. K values of NTV, ITV, FD3-32 and FD3-36 against Mpro H163A\ni\nmutant of SARS-CoV-2. Kᵢ values were derived from enzyme inhibition kinetics\ndata of individual and combined biological replicates.\nK fitted from dataset of each\ni\nK fitted from dataset of\nMutation ID replicate (nM) i\nthree replicates\nRep.1 Rep.2 Rep.3\nNTV 24518 45575 43066 36.8 μM (27.1 - 50.3, n=3)\nITV 37961 37786 65990 46.6 μM (24.8 - 92.3, n=3)\nH163A\nFD3-32 84125 5185 24770 22.0 μM (5.40 - 82.1, n=3)\nFD3-36 12082 7868 21269 13.8 μM (2.98 - 54.7, n=3)\nResponse: We appreciate the reviewer’ comments on the novelty of this work.\nWe regret the omission of the Science paper mentioned above, which is now\ncited with the following sentences to describe it in the Results section (Page 8,\nLine 145-150):\n“…… In a non-peptidic inhibitor scaffold discovered by the COVID Moonshot\nteam, iso-quinoline in place of pyridine at P1 was found to substantially boost\nMpro inhibition through expanded hydrophobic interactions 42. Unfortunately,\nthese non-covalent inhibitors failed to achieve sufficient therapeutic exposure\nin vivo due to high clearance and low bioavailability 42.”\nResponse: The reviewer is correct that we are not the first laboratory that have\nconducted an SAR study on nirmatrelvir, which is part of this report. However,\nwe believe our study is likely the first that has led to the discovery of several\nnirmatrelvir-inspired inhibitors with a substantially improved drug resistance\n4\nprofile as well as significantly enhanced in vitro and in vivo antiviral efficacy\nindependent of ritonavir. The publication mentioned by the reviewer mainly\ndescribed the replacement of the γ-lactam ring at P1 of nirmatrelvir by a six-\nmembered δ-lactam ring with enhanced inhibitory and antiviral activity. However,\nsince the δ-lactam NH also maintained a strong H-bond with E166 side chain,\nthese types of inhibitors would undoubtedly suffer the same fate as nirmatrelvir,\nwhich our work precisely tried to avoid. Therefore, we respectfully beg to\ndisagree with the reviewer on the assertion that their work detracts from the\noverall novelty of ours. Having said all that, we fully concur with the reviewer\nthat the EJMC paper by Arun et al should be cited. We have remedied this\nomission by adding the following sentence to the Introduction section (Page\n4~5, Line 78-81):\n“When a six-membered δ-lactam ring was introduced at P1 of nirmatrelvir, a\nstronger H-bond formed between the lactam NH and E166 side chain\ncarboxylate, largely responsible for several-fold enhancement of inhibitory and\nantiviral activity 17.”\nResponse: While the reviewer’s viewpoint is clearly valid, our claim was hardly\nmisleading. In fact, we said the following to the same effect in the Discussion\nof the original submission (Page 29 Line 4-8 in original submission):\n“In sharp contrast, our leads, FD3-32, FD3-33 and FD3-36, were 2~3 orders of\nmagnitude more active than NTV in vitro despite a merely 1.5~10-fold\nimprovement in their inhibitory activity against Mpro, suggesting that these three\ninhibitors with iso-quinoline at P1 may have markedly retarded P-gp-mediated\ndrug efflux detrimental to NTV activity.”\nTo ascertain as per the reviewer’s suggestion, however, we compared our\n5\ncompound FD3-32 and NTV in vitro with and without a P-gp efflux inhibitor, CP-\n100356, as described (Owen DR et al., Science, 2021;374(6575):1586-1593;\nBoras B et al., Nat Commun. 2021;12(1):6055). The new data are now included\nas Figure S24. In a nutshell, the antiviral activity of FD3-32 was far more potent\nthan NTV, as expected, but unaffected by CP-100356 treatment. By contrast,\nCP-100356 treatment enhanced NTV activity by at least 30-fold. These results\nhave indeed qualified our assumption in the Discussion and, accordingly, we\nhave revised the manuscript by inserting a whole paragraph describing these\nnew results in the Results section (Page 22, Line 422-430):\n“To understand why FD3-32 and FD3-33 were orders of magnitude more active\nthan NTV in vitro despite a modest improvement in their inhibitory activity\nagainst Mpro, we compared FD3-32 and NTV in an in vitro infection assay where\na P-gp efflux inhibitor, CP-100356, was used 13, 51. As shown in Figure S24,\nwhile CP-100356 treatment had little effect on the antiviral activity of FD3-32\nagainst SARS-CoV-2 Omicron BA.5.2 infection on Vero E6 cells, it enhanced\nfar less potent NTV activity by at least 30-fold. These results indicate that the\nsupremacy of FD3-32 and FD3-33 resides largely in their ability to evade P-gp-\nmediated efflux detrimental to NTV.”\nIn addition, we have inserted the following sentence to the Discussion to reflect\nthese new results (Page 34, Line 662-665):\n“Indeed, a P-gp efflux inhibitor did significantly improve NTV antiviral activity in\nvitro while exerting no impact on FD3-32, underscoring the important role of the\nP-gp efflux pump in dictating the therapeutic efficacy of these inhibitors by\ndifferentially regulating their cellular transport.”\nFinally, as suggested, a supplementary table containing the compounds with K\ni\nvalues against Mpro wildtype and Mpro variants is now provided as Table S3-S4\nand Table S7.\nResponse: We are afraid that the reviewer’s characterization is not terribly\naccurate in this case. We did indeed compare, head-to-head, Paxlovid with\nFD3-32 alone (Figure 5K-5Q) and with FD3-36 alone (Figure 6D-6J). We also\ncompared FD3-32, FD3-33 and NTV in the presence of RTV (Figure 5D-5J).\ncentral claim that ritonavir is not required for our compounds to be efficacious.\nResponse: The reviewer is correct about the poor pharmacokinetics of NTV\nitself. As suggested by Reviewer 4, PK parameters were recalculated using\nunbiased datasets, showing serum half-lives of 0.23, 1.18, 0.15, 0.22 and 1.09\nh for NTV, FD3-32, FD3-33, ITV and FD3-36, respectively. The two most\npromising candidates FD3-32 and FD3-36 were obviously more stable than\nNTV or ITV in serum, as evidenced by a ~5-fold increase in IV t .\n1/2\nHowever,\nwe agree with the reviewer that t alone does not necessarily predict the\n1/2\noutcome of therapeutic efficacy, which is also dependent on factors such as\noral bioavailability, total drug exposure, and, perhaps more importantly, P-gp-\nmediated drug efflux. In fact, our compounds also showed significantly\nimproved oral bioavailability and total drug exposure (Table S5-S6). With\nrespect to P-gp-mediated clearance, we heeded the reviewer’s incisive advice\nand indeed confirmed that the superb in vivo antiviral activity of FD3-32 and\nFD3-36 was largely attributable to their ability to evade it (Figure S24).\nFigure S24. Antiviral activity of NTV and FD3-32 against SARS-CoV-2\nOmicron BA.5.2 infection on Vero E6 cells in the absence and presence\n7\nof 2 μM P-gp inhibitor (CP-100356). (A) Immunofluorescent images of SARS-\nCoV-2 nucleocapsid protein in Vero E6 cells infected with Omicron infection.\nBlue: nucleus of Vero E6, red: SARS-CoV-2 nucleocapsid protein. (B) Semi-\nquantitative analysis of immunofluorescent images. (C) Antiviral activities\ndetermined by quantifying viral nucleic acid in cell supernatants. Data are\npresented as mean ± SEM for three biological replicates, and the IC50 values\nare calculated by fitting to the four-parameter dose–response model in\nGraphPad Prism 8.\nResponse: We thank the reviewer for the suggestion. The K values presented\ni\nin the manuscript were obtained from curve fitting of datasets from three\nindependent biological experiments. To address the reviewer’s concern as well\nas for clarification, we have provided supplementary tables also containing K\ni\nvalues individually fitted from each dataset as shown in Table S3-S4 and Table\nS7 of this revised manuscript.\nResponse: It is not clear to us that Nirmatrelvir necessarily outperforms FD3-x\nseries in brain tissue. When head-to-head comparisons of FD3-32 and FD3-33\nwith NTV were made in the presence of RTV (Figure 5G), they pretty much\nbehaved similarly without statistical significance. Although NTV did fare better\nthan FD3-32 (Figure 5N), it achieved so with the help of RTV, which makes an\nindirect comparison less meaningful. Besides, even with the help of RTV, NTV\ndid not outperform FD3-36 (Figure 6G). The question raised by the reviewer\n8\nwith respect to blood-brain barrier (BBB) is obviously a thoughtful and important\none. However, it is difficult to address at present without more definitive data or\nevidence. For these reasons, we prefer not to elaborate and hope the reviewer\nwill understand and agree.\nResponse: The reviewer is correct that Paxlovid-resistant mutations of Mpro are\nnot at all abundant in the GISAID database. Although cases of E166V mutation\nincreased as annotated by GISAID following the use of Paxlovid (Zhu, Y. et al.\nIn vitro selection and analysis of SARS-CoV-2 nirmatrelvir resistance mutations\ncontributing to clinical virus resistance surveillance. Sci Adv 10, eadl4013), they\nare not widespread enough to be claimed as “becoming increasingly prevalent.”\nThus, we have removed “becoming increasingly prevalent” and restated the\nsentence as follows (Page 31, Line 605-608):\n“Drug resistant variants of SARS-CoV-2 have emerged both clinically and under\nselective pressure in the laboratory 48-51, albeit their relatively low prevalence\naccording to the Global Initiative on Sharing Avian Influenza Data (GISAID)\ndatabase 25,48,52.”\nResponse: We concur and have made the change as suggested (Page 33,\nLine 645):\n9\n“While it is by design that potent inhibitory activity against Mpro and its NTV-\nresistant E166A/V mutants is achieved for FD3-32 and FD3-36 as an impetus\nof this study…”\nResponse: The reviewer’s point is well taken. We used a standardized, FRET-\nbased enzymatic assay to determine K value of each inhibitor. For clarity, we\ni\ninserted the following sentence in the SAR section (Page 13, Line 246-248):\n… for γ-lactam. “A fluorescence resonance energy transfer (FRET)-based\nenzymatic assay was employed to determine the K value of each inhibitor 45,\ni\n46.” To this end, …\nResponse: We have defined the Enamine library as suggested (Page 7, Line\n127-128):\n“…, followed by virtual screening of a commercial library of ~3,000,000\ncompounds from four Enamine collections (advanced, functional, hts and\npremium) against the catalytic cleft of Mpro…”\nResponse: We appreciate the reviewer’s efforts.\nResponse: We thank the reviewer for his/her pointed comments. We have\ncorrected the loosely worded description by removing three words, “in vitro and.”\nThe sentence now reads (Page 6, Line 115-118):\n“Additional modifications at P4 drastically improved pharmacokinetic properties\nof these inhibitors, which led in a monotherapy to significantly enhanced in vivo\nantiviral efficacy compared with NTV (with or without RTV).”\nResponse: We thank the reviewer for these insightful comments, with which\nwe fully concur. Indeed, the elimination half-life is an intrinsic pharmacokinetic\nparameter of an ideal one-compartment drug dependent only on clearance (CL)\nand volume of distribution (V ) and should not be influenced in linear PK by\nd\ndose and the route of administration. However, the apparent elimination t of\n1/2\na drug often differs quite a bit when comparing its IV and oral routes. For\nexample, PO t of NTV in mice (10 mg/kg dose) was reported to be 3-3.5 times\n1/2\nlonger than IV t (3 mg/kg dose) in one study (Chen X, et al. Preclinical\n1/2\nevaluation of the SARS-CoV-2 Mpro inhibitor RAY1216 shows improved\npharmacokinetics compared with nirmatrelvir. Nat Microbiol. 2024;9(4):1075-\n1088). In another study, however, PO t of NTV in rats (10 mg/kg dose) was\n1/2\nroughly half as long as IV t (1 mg/kg dose) (Owen DR, et al. An oral SARS-\n1/2\nCoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19. Science.\n2021;374(6575):1586-1593). In studying various derivatives of NTV, Owen DR\net al. reported a wide range of PO t -to-IV t ratios from as low as 0.5 to as\n1/2 1/2\nhigh as 5.5 without no apparent rationale (Owen DR, et al. An oral SARS-CoV-\n11\n2021;374(6575):1586-1593).\nOral doses are invariably higher, by design, than IV doses in PK studies\nbecause only a fraction of the oral dose survives absorption and first-pass\nmetabolism to reach systemic circulation, whereas IV dosing delivers 100%\nimmediately. High PO dose can prolong the apparent PO t when (1)\n1/2\nelimination saturates (due to saturable metabolic and transport pathways at\nhigh concentrations), and (2) slow absorption limited by poor solubility occurs\n(flip-flop kinetics, quite common with poorly soluble drugs). Further, as the\nreviewer correctly pointed out, drug concentrations falling below quantification\nlimit early can also contribute to the inaccuracy of measured IV t even though\n1/2\nit reflects true elimination and is considered the gold standard as the IV route\nrequires no absorption that can sometimes mask drug elimination.\nConsidering the reviewer’s comments, we have inserted the following\nparagraph to the Results section (Page 23-24, Line 454-470):\n“It is worth noting that the elimination t is an intrinsic pharmacokinetic\n1/2\nparameter of an ideal one-compartment drug dependent only on CL and V and\nd\nshould not be influenced in linear pharmacokinetics by dose and the route of\nadministration. However, the apparent p.o. t of FD3-32, FD3-33 or NTV in our\n1/2\npharmacokinetic studies was significantly longer than its i.v. t , suggesting\n1/2\nseveral possible scenarios. First, high oral doses (relative to low i.v. doses),\nwhich are typical in pharmacokinetic studies due to fractional absorption and\nfirst-pass metabolism, may result in elimination saturation. Second, poorly\nsoluble oral drugs are often associated with slow absorption, leading to a\nprolonged p.o. t in so-called flip-flop kinetics. Third, if drug concentrations fall\n1/2\nbelow quantification limit early, inaccuracy in i.v. t measurements may ensue.\n1/2\nPresumably for these reasons, the reported ratios of the apparent p.o. t of\n1/2\nNTV and its derivatives to their corresponding i.v. t swing wildly from as low\n1/2\nas 0.5 to as high as 5.5 13, 37. Despite that i.v. t reflects true elimination and is\n1/2\nconsidered the gold standard as the i.v. route requires no absorption that can\nmask drug elimination, more pharmacokinetic studies are clearly warranted to\nbetter understand the disparity between i.v. t and p.o. t for this class of Mpro\n1/2 1/2\ninhibitors.”\nResponse: We thank the reviewer for raising this important methodological\npoint. Regarding the FD3-32 panel at 24 h, only one sample had a plasma\nconcentration above the limit of quantification (LOQ), which might introduce\nsignificant bias in the calculation of PK parameters. To address this issue and\nminimize potential bias, we have taken the following steps in the revised\nmanuscript: (1) all individual data points above the LOQ are now displayed as\nscatters in the concentration-time curves (Figure 6A and Figure S26); (2)\npharmacokinetic parameters were derived by performing noncompartmental\nanalysis on the data from each animal individually, rather than using averaged\nconcentration values. This approach allows for a more accurate representation\nof the pharmacokinetic profiles. The updated parameters are presented in\nTable S5 and S6.\nResponse: Provided as suggested.\nResponse: We fully concur with the reviewer on this important and valid point.\nAccordingly, we have revised the manuscript to prioritize the comparison of\nthese two primary PK parameters in the relevant sections (Page 23, Line 441-\n452 and Page 27, Line 531-535):\n“Compared with NTV, FD3-32 exhibited a ~2-fold increase in the volume of\ndistribution (V ) and a ~3-fold reduction in clearance (CL), translating into a\nd\nprolonged i.v. t of ~1.18 h (as opposed to ~0.230 h for NTV) (Figure S26 and\n1/2\nTable S5). Although FD3-33 retains the iso-quinoline ring at P1 as FD3-32, its\ndifluoro-cyclopropyl (as opposed to trifluoromethyl or difluoro-chloromethyl)\nmoiety at P4 led to a ~2-fold and a ~5-fold higher clearance than NTV and FD3-\n32, respectively, ensuing a rapid elimination (i.v. t = ~0.150 h) of FD3-33 with\n1/2\na comparable V to either NTV or FD3-32 (Figure S26 and Table S5). Notably,\nd\ndespite NTV’s longer p.o. t than those of FD3-32 and FD3-33, both lead\n1/2\ncompounds exhibited a substantially higher peak plasma concentration (C )\nmax\nthan NTV following oral administration, contributing to ~56% and ~170%\nimprovement in oral bioavailability over NTV (Figure S26 and Table S5).”\n“As shown in Table S5-S6, the substitution of the Br atom for Cl at P4\nsignificantly improved oral pharmacokinetic parameters of FD3-36 over FD3-\n32, as evidenced by increases of 99% in p.o. t , 101% in total drug exposure\n1/2\n(AUC and C ) and 99% in oral bioavailability, albeit their comparable CL, V\nmax d\nand i.v. t values.”\n1/2\nResponse: We appreciate the reviewer’s comments and have revised the\nsentence as follows (Page 27, Line 525-526):\nBefore revision: “Pharmacokinetic data on NTV, FD3-32 and FD3-33 suggest\nthat the P4 position exerted a stronger influence than P1 on their elimination\nt1/2 and oral bioavailability.”\nAfter revision: “Data on NTV, FD3-32 and FD3-33 suggest that the P4 position\nexerted a strong pharmacokinetic influence on these Mpro inhibitors.”\nResponse: We thank the reviewer for this important suggestion. To improve\nthe clarity of peak assignments in Figure S9A of the initial submission, we\nretrieved the high-resolution source images from the cited publications,\nreprocessed them alongside our measured 2D NMR spectrum, and presented\nthem both separately and superimposed with distinct colors. Despite limitations\nof the originally published images, these steps have improved peak visibility,\nand the figure of concern has now been updated in the revised manuscript as\nFigure S11-S12.\nResponse: We thank the reviewer for pointing out this deficiency, which we\ntake very seriously. As the first step toward a remedy, we re-examined our\nprotein sample used for the NMR experiment with respect to its purity, solubility\nand activity. We made the following findings:\n(1) Our 15N‑labeled Mpro is highly soluble in the NMR buffer and remains\nsoluble under storage conditions for days at a concentration of up to 500\nμM. Shown in the following HPLC chromatograms is the sample stored\nat both 4 °C and room temperature and analyzed at day 0, 7 and 14.\nWhile prolonged storage for 2 weeks at room temperature (black and red\nlines) did lead to significant degradation presumably due to autolysis, the\nenzyme showed little change at 4 °C for at least one week (black and\ngreen lines).\n(2) For further verification, we quantified the enzymatic activity of this week-\nold 15N‑labeled Mpro stored 4 °C in comparison with freshly prepared un-\nlabeled Mpro whose structure was determined by X‑ray crystallography.\nAs shown in Figure S10C, 15N‑labeled Mpro was fully active with catalytic\nparameters highly similar, if not identical, to those of un-labeled Mpro\n(Figure S7B).\nTogether, these results suggest that the noisy peaks and peak clusters seen in\nFigure S9 of the initial submission are likely not caused by the protein itself.\nRather, we believe they were blemishes of suboptimal NMR data processing.\nAs alluded in our response to the reviewer’s first comment, we reprocessed our\nTROSY‑HSQC spectrum and presented it separately (Figure S11), which now\nshows better-resolved peaks with significantly reduced noises compared with\nFigure S9A of the initial submission. While superposition of both TROSY‑HSQC\nspectra (Figure S12) demonstrates an overall agreement between our 15N-\nlabelled Mpro and the protein previously reported, clear differences in the\nspectra do exist, which are likely attributable to interlaboratory methodological\nand technical differences in areas such as protein preparation, experimental\nskill and condition, and data acquisition and processing, etc. For these reasons,\nwe only made partial assignments in this report in the absence of a more\ncomprehensive NMR study of our protein with limited spectroscopic data.\nTo acknowledge and clearly identify potential ambiguity of assignments due to\npeak crowding and/or overlapping, we have added the following to the\nSupplementary Information (Table S1): 1) the chemical shifts assigned in this\nstudy alongside the previously reported values; 2) calculated combined\nchemical shift deviations (CCSD) as a measure of assignment\nreliability/ambiguity; 3) assignment grouping and color coding to denote the\ndegree of resonance crowding/overlapping (green: low; yellow: medium;\norange: high).\nWe have updated the manuscript, figures and tables accordingly and noted the\nlimitations of NMR data where assignments may be ambiguous. For clarity, we\nhave inserted the following sentences to the Results section (Page 10, Line\n184-191):\n“In the absence of a more comprehensive NMR study of our Mpro with limited\nspectroscopic data, we only made partial assignments according to the\npublished spectra (Figure S11-S12). The chemical shifts assigned in this study\nalongside the previously reported values are listed in Table S1, accompanied\nby calculated combined chemical shift deviations (CCSD) as a measure of\nassignment reliability/ambiguity. For clarity, the assignments were further\ngrouped and differentially colored based on the degree of resonance peak\ncrowding and/or overlapping in Table S1.”\n16\nmn\n412\nta\necnabrosba\nVU\n3\n2\n2\n1\n1\n0\n5\n0\n5\n0\n5\n0\n0\n0\n0\n0\n0\n0\n0\n0\n0\n0\n0\n0\n0 5 1\nT\n0\nim e ( m\n1 5\nin )\n2 0 2 5\nD\nD\nD\nD\nD\na\na\na\na\na\ny\ny\ny\ny\ny\n0\n7\n7\n1\n1\n( 1 0 0 % )\na t 4 ° C ( 9 8\na t R T ( 8 7 . 5\n4 a t 4 ° C ( 8\n4 a t R T ( 5 5\n. 4\n3\n6\n. 5\n3\n%\n. 6\n5\n%\n)\n7\n%\n)\n%\n)\n)\nHPLC chromatograms of 15N-labeled Mpro under different storage\nconditions. The chromatogram was acquired at 40 °C using an XBridge\nProtein BEH C4 column (300 Å, 3.5 µm, 2.1 × 150 mm) with a solvent gradient\nof 5–95% B over 15 min at a flow rate of 0.4 mL/min. Mobile phase A was 0.1%\nTFA in H O, and mobile phase B was 0.1% TFA in acetonitrile.\ntemperature as described. Data are shown as mean ± SEM for three biologically\nreplicates.\nResponse: We fully agree with the reviewer on this suggestion. As\nrecommended, we have extracted and analyzed normalized 1D slices of the\nrelevant NMR peaks. These data, which clearly illustrate significant line-shape\nchanges, are now presented in Figure S13 and Figure S18E of the revised\nmanuscript.\nResponse: We thank the reviewer for this highly positive feedback.\nResponse: We fully concur and have split the original Figure S2 into two\nseparate figures, which are labeled as Figure S3 and Figure S5 in the revised\nmanuscript. Both figures have been significantly enlarged with improved\nreadability. Additionally, we have adjusted the sizes of several other figures to\ncomply with the journal’s formatting guidelines.\nResponse: The reviewer is absolutely correct in his/her observation! It turns\nout that the covalent bond formed between the catalytic thiol group (R1-SH) of\nthe enzyme and the cyano group (R2-CN) of the inhibitor, i.e., R2-CH(=NH)S-\nR1, is known to be acid labile. Under RP-HPLC-ESI-MS conditions where either\ntrifluoroacetic acid or formic acid is present, the thioimidate intermediate breaks\ndown reversibly, a process dependent not only on the on and off reaction rate\nconstants in the gas phase but also on other factors difficult to quantify. For\nthese reasons, quantitative titrations, although desirable, are not easily\nattainable nor would they accurately inform solution-phase binding affinity. That\nsaid, we commend the reviewer for this sharp observation and address it in the\nResults section by add the following sentence (Page 20, Line 382-385):\n“Of note, we could not quantify these interactions as the covalent bond of\nthioimidate formed by the catalytic thiol group of the enzyme and the cyano\ngroup of the inhibitor is known to be acid labile and readily breaks down\nreversibly under LC-MS conditions.”\nWith respect to the legend of Fig 4, we have now specified the enzyme\nconcentration (15 μM) as suggested.\nResponse: We agree with the reviewer and have corrected this sentence as\nfollows (Page 3, Line 54-56):\n“SARS-CoV-2 Mpro is a cysteine protease that processes viral polyproteins\n18\nimportant for the assembly and replication of the positive-sense single-stranded\nRNA β-coronavirus 3,6-9.”\nResponse: We agree with the reviewer and have now reported SEM (rather\nthan SD) for experiments done in triplicates.\nResponse: We thank the reviewer for this sensible suggestion. We have now\nrearranged all supplementary figures in the order they are first referenced in the\nmain text.\nResponse: Changed as suggested.\nResponse: All good points. We have made these changes as suggested.\nResponse: We have now added this information to the legends of Figure S20-\nS21 in the revised manuscript as follows:\n“Mass spectrometric data were acquired on an Agilent 6230 LC/TOF mass\nspectrometer and deconvoluted using the manufacture’s MassHunter\nWorkstation Software Bioconfirm 10.0.”\nResponse: A short answer is yes, their elution profiles are indeed identical. As\nexplained earlier, the high fraction of unmodified Mpro arises from reversible\nbreakdown of the covalent complex under acidic analytical conditions\n(containing 0.1% TFA).\nResponse: We thank the reviewer for these positive comments.\nResponse: Following the reviewer’s valuable suggestion for validation, we\nhave added the docking pose of SARS-CoV-2 Mpro complexed with Ensitrelvir\n(ETV, a non-covalent clinical inhibitor) superimposed onto the reported co-\ncrystal structure, which is presented in Figure S2 of this revised submission.\nOverall, the co-crystal structure largely corroborates the docking model of the\nEnsitrelvir-Mpro complex (RMSD=0.524), attesting to the validity of the\ncomputational protocol used in this study. For clarity, we have inserted the\nfollowing sentence in the Results section (Page 7, Line 126):\n“To discover an alternative class of P1 groups in replace of γ-lactam, we first\nvalidated our docking protocol using ETV as a quality control (Figure S2),\nfollowed by virtual screening of the Enamine…”\nFigure S2. Superposition of the X-ray co-crystal structure of the Mpro-ETV\ncomplex with its docking pose.\nResponse: We appreciate the reviewer’s helpful suggestion. In the revised\nSupplementary Information, the docking methods are now organized into three\nclearly defined subsections: Virtual Screening, Induced Fit Docking, and\nCovalent Docking (SI: Page 49, lines 41-44; Page 50, lines 1-41). As\nrecommended, we have also removed the redundant text and streamlined\noverlapping descriptions to improve clarity and readability:\n“1.2 Induced fit docking\nPredicted docking poses of our synthetic inhibitors in complex with Mpro were\ngenerated by Schrödinger software package. Receptor was prepared using the\nconditions consistent with those of virtual screening. LigPrep module was\nemployed to calculate…”\nResponse: We thank the reviewer for this valuable suggestion. In this study,\nthe protonation states of histidine residues were assigned following a previous\npublication that used the same crystal structure (PDB: 6W63) for virtual\nscreening (Luttens A, et al. Ultralarge Virtual Screening Identifies SARS-CoV-2\nMain Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses.\nJ Am Chem Soc. 2022;144(7):2905–2920). To clarify this point, we have added\nthe following sentence to the Materials and Methods section of the\nSupplementary Information in the revised manuscript (SI: Page 50, Line 1-4):\n“According to a previous publication that used the same crystal structure (PDB:\n6W63) for virtual screening 1, histidine residues including His41, His163,\nHis164, His172, and His246 were modeled as Nε-protonated, while His64 and\nHis80 were modeled as Nδ-protonated.”\nResponse: We sincerely thank the reviewer for his/her valuable efforts to\nimprove our manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have meticulously addressed all my concerns and revised the manuscript accordingly. Therefore, the\nmanuscript is recommended for publication.", "reviewer_2": "I thank the authors for their carefully considered responses to my review and confirm that my concerns have been addressed\nin full.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.", "reviewer_4": "Comment on original submission:\n“Page 19 and Figure S20: The manuscript claims that FD3-32 has a longer PO t1/2 compared to IV t1/2, however Figure\nS20 suggests that this conclusion may be based on a 10-fold differences in dose amounts and on a lack of measurement at\n24 h for the IV dose, potentially due to the limit of quantification. Based on pharmacokinetic principles, the elimination half-\nlife is not affected by the route of administration, unless there is a rare case of flip-flop kinetics which appears not to be the\ncase here (and if it was, it needs to discussed). Rather, the difference in half-lives appears to be an artifact of comparing\ndifferent dose levels with the concentrations following the lower (IV) dose falling below the limit of quantification much\nearlier. Contemporary PK modelling approaches can account for samples below the quantification limit.”\nComments on authors’ new paragraph in the manuscript that was added in response to the previous comment above:\nThe elimination half-life is not “an intrinsic pharmacokinetic parameter of an ideal one-compartment drug”. All drug have\nelimination half-lives, not only those with one-compartment pharmacokinetic behaviour, but also those with more than one\ndisposition compartment. The authors should note as a limitation in their manuscript that their conclusions on the half-life\ncomparison may be inaccurate.\nThis statement “First, high oral doses (relative to low i.v. doses), which are typical in pharmacokinetic studies due to\nfractional absorption and first-pass metabolism, may result in elimination saturation.” This statement is also incorrect\nbecause it is not the dose but the concentration amount in the systemic circulation that would lead to any saturation of\nelimination. Fractional absorption and first-pass metabolism would lead to lower concentrations in the systemic circulation\ntherefore cannot be used as justification for saturation of elimination as a potential reason for nonlinearity.\nThis is also not correct: “Despite that i.v. t1/2 reflects true elimination and is considered the gold standard as the i.v. route\nrequires no absorption that can mask drug elimination, more pharmacokinetic studies are clearly warranted to better\nunderstand the disparity between i.v. t1/2 and p.o. t1/2 for this class of Mpro inhibitors.”\nFirstly, due to lack of measurements for the IV dose later in the PK profile, the elimination half-life derived from these IV\ncurves may well be falsely short.\nSecondly, as previously stated in the original comments, contemporary PK modelling approaches should be applied, or at\nthe very least, the lack of having applied such appropriate approaches for data analysis should be stated as an important\nlimitation of the study.\nThe authors state that more studies are warranted. This is not necessarily the case, but instead improved data analysis\napproaches applied to the data in the current studies would be likely be beneficial to provide confidence in the conclusions\nfrom the study.", "reviewer_5": "The revision has addressed all issues and made the NMR data analysis more transparent.", "reviewer_6": "The authors have addressed all my comments satisfactorily and the manuscript can be published as is from the mass\nspectrometry perspective.", "reviewer_7": "The authors have addressed my concerns. I recommend publication."}, "author_response": "Response: Reviewer 4’s latest comments on a new paragraph in our revised\nmanuscript are much appreciated and are addressed thoroughly and\nresponsively as follows:\nWe fully concur and have changed “an ideal one-compartment drug”\nto “a drug”. The sentence now reads (Page 23, Line 454-456):\n“It is worth noting that the elimination t is an intrinsic pharmacokinetic\n1/2\nparameter of a drug dependent only on CL and V and should not be influenced\nd\nin linear pharmacokinetics by dose and the route of administration.”\nAgain, we agree with the reviewer and have removed “due to\nfractional absorption and first-pass metabolism” and added “a high\nconcentration in the systemic circulation that leads to.” The sentence now reads\n(Page 24, Line 459-461):\n“First, high oral doses (relative to low i.v. doses), which are typical in\npharmacokinetic studies, may result in a high concentration in the systemic\ncirculation that leads to elimination saturation.”\nWe have rephrased several sentences to reflect the reviewer’s\nconcerns and, more importantly, to emphasize a limitation in our PK studies that\ncan be tackled in future studies by improved data analysis techniques. The\nsentences now read (Page 24, Line 462-470):\n“Third, if drug concentrations fall below quantification limit early as was the case\nwith our tested compounds, inaccuracy in i.v. t measurements may ensue,\n1/2\nthus yielding a falsely short elimination t . Presumably for some of these\n1/2\nreasons, the reported ratios of the apparent p.o. t of NTV and its derivatives\n1/2\nto their corresponding i.v. t swing wildly from as low as 0.5 to as high as 5.5.\n1/2\nImproved data analysis aided by contemporary pharmacokinetic modelling\napproaches is clearly warranted to address this limitation in our\npharmacokinetic studies to better understand the disparity between i.v. t and\n1/2\np.o. t for this class of Mpro inhibitors.”\n1/2"}, {"round": 3, "reviewer_comments": {"reviewer_4": "The revision is satisfactory."}, "author_response": ""}]

Decision letter