Plant fucosyltransferase FUT11 distorts the sugar acceptor to catalyze via a transient oxocarbenium intermediate mechanism

Domain: neuroscience
Published: 2026-01-23
Editorial outcome: major_revision

Abstract
Glycosyltransferases catalyze glycosidic bond formation by activating the donor sugar, while the sugar acceptor substrate is considered passive, maintaining a chair conformation during catalysis. We challenge this through a multidisciplinary study of Arabidopsis thaliana FUT11, a core α1,3-fucosyltransferase essential for plant development and reproduction. AtFUT11 adopts a GT-B fold with an additional N-terminal subdomain that anchors the G0 N-glycan, while the α1,3 arm is mainly recognized by the acceptor Rossmann subdomain. The α1,6 arm remains solvent-exposed, allowing diverse modifications, while solvent exposure of the central mannose’s OH2 explains tolerance for β1,2-xylose. Remarkably, simulations suggest the catalytic base Glu158 may promote the innermost GlcNAc’s transient puckering distortion to align the hydroxyl for nucleophilic attack. This enables an asynchronous SN2-like mechanism bordering SN1 character, with formation of a transient oxocarbenium ion triggered by pyrophosphate departure, followed by nucleophilic attack coupled with proton transfer. Homology with human FUT9 explains AtFUT11’s side activity on LacNAc, revealing plasticity and evolutionary convergence between plant and mammalian antenna-fucosyltransferases.

Introduction
N-glycosylation is an evolutionarily conserved post-translational modification essential for the proper folding, stability, and function of glycoproteins across all domains of life1–3. In eukaryotes, the process is initiated in the endoplasmic reticulum (ER), where a preassembled oligosaccharide is transferred by the oligosaccharyltransferase (OST) complex to an asparagine residue within the canonical consensus sequence–Asn-X-Ser/Thr–(where X≠Pro) of nascent polypeptides4. Although most N-glycosylation events target this canonical sequon, evidence also supports the occurrence of modifications at non-consensus motifs, suggesting an unexpected degree of substrate plasticity and regulatory complexity in this pathway5,6. The early stages of the N-glycosylation machinery are broadly conserved, while subsequent N-glycan remodeling in the Golgi is divergent across kingdoms, contributing to the remarkable structural and functional diversity of glycoproteins7. Notably, in some prokaryotes, N-glycosylation pathways are even more distinct, employing distinct lipid-linked donors and OST-like enzymes to generate diverse glycan structures3.

In plants, Golgi-resident glycosyltransferases further elaborate the N-glycan precursor, starting with N-acetylglucosaminyltransferase I (GnTI or MGAT1), which adds a GlcNAc residue to the α1,3 Man arm that initiates complex N-glycan formation and branching8. In mammals, the pathway yields multi-antennary N-glycans with LacNAc units terminated by sialic acids and featuring core α1,6-linked fucose—a modification introduced by FUT8 and essential for development and immunity9,10. In contrast, plants generate biantennary N-glycans without sialic acids and are distinctly different by having core α1,3-fucose as well as β1,2-xylose residues attached to the innermost GlcNAc and central Man residue, respectively. These distinct plant modifications, catalyzed by the enzymes FUT118,11 and β1,2-xylosyltransferase (XYLT)8,12, are immunogenic in humans and hence have implications for use of plant expressing systems for production of glycoprotein therapeutics13. Core fucosylation of N-glycans involves the addition of a fucose residue to the innermost N-acetylglucosamine (GlcNAc) of the N-glycan chitobiose core, but with differing linkage specificities (α1,6 in mammals versus α1,3 in plants). The β1,2-linked xylose, attached to the OH2 position of the central mannose, is a hallmark of plant N-glycans and may modulate glycoprotein folding or receptor interactions14.

FUT11-mediated core α1,3-fucosylation is essential for normal growth, fertility, and hormone signaling in diverse plant species, as demonstrated by severe phenotypes in Oryza sativa and Lotus japonicus upon gene disruption8,15–17. Intriguingly, the combined loss of the FUT isoforms FUT11 (FucTA) and FUT12 (FucTB) in Arabidopsis thaliana results in no major morphological defects18. Despite its central role in plant N-glycosylation and its biotechnological relevance, the structural and catalytic mechanism of FUT11 remain poorly defined. The functional specificity of FUT11 was demonstrated using recombinant AtFUT11 expressed in Pichia pastoris19, and more lately evaluated by expressing AtFUT11 in N-glycoengineered human HEK293 cells20. Glycan microarray screening with 18 defined N-glycan structures revealed that AtFUT11 selectively targets complex and hybrid N-glycans with requirement for GlcNAc on the α1,3 arm. AtFUT11 can also fucosylate N-glycans with α1,6 core fucosylation by FUT8, yielding double α1-3/6 core-fucosylated N-glycan structures21. This substrate tolerance was confirmed in mammalian cells co-expressing FUT8 and AtFUT1120.

The mechanistic borderline between SN1 and SN2 reactions has long been a subject of interest in carbohydrate and related chemistry, including enzymatic glycosylation reactions, in which the formation of a transient oxocarbenium ion has been proposed as a key intermediate22 bridging the two mechanistic extremes23. While the SN1 mechanism involves a fully developed glycosyl cation, and SN2 mechanism proceeds through a concerted transition state, many reactions exhibit features of both pathways. In other words, along the continuum between SN1 and SN2, the latter may gradually shift towards the former as the transition state develops a carbocation character24. Several experimental25 and theoretical26 studies have addressed this continuum27, suggesting the real formation of a glycosyl cation28. In glycosyltransferases, acceptor recognition is commonly discussed in terms of binding determinants and preorganization29,30, but the possibility that these enzymes actively distort the sugar acceptor conformation has remained unexplored.

Here, we show that AtFUT11 recognizes its N-glycan acceptor through a modular GT-B architecture and an acceptor-binding region organized into two subdomains, enabling selective engagement of the α1,3 arm while tolerating β1,2-xylose and conformational variability at the α1,6 arm. Using glycan microarrays, X-ray crystallography of AtFUT11 bound to GDP and a G0 N-glycan, structure-guided mutagenesis, and multiscale computations, we identify residues contributing to donor/acceptor recognition and support an asynchronous SN1–SN2-like pathway in which a transient oxocarbenium-like cationic species is populated. The simulations further indicate that enzyme–acceptor interactions can promote a transient puckering distortion of the innermost GlcNAc, aligning the reactive hydroxyl for nucleophilic attack, with Glu158 implicated as a key contributor to this process. Finally, structural similarity to mammalian FUT9 provides a rationale for AtFUT11 activity toward LacNAc in vitro, consistent with its low efficiency.

Results
AtFUT11 substrate specificity by glycan microarray
Based on the previously described activity for this enzyme, a G0 peptide derived from chicken egg yolk sialylglycopeptide (SGP) was incubated in the presence of GDP-fucose (GDP-Fuc) with AtFUT11 expressed in HEK293. The introduction of a fucose molecule on G0 peptide was clearly detected by MALDI-TOF mass spectrometry (Fig. 1a). As this recombinant enzyme carries mammalian-type N-glycans, the predicted sites present in our construct (Asn337, Asn420, and Asn481) map to solvent-exposed regions far from the donor/acceptor pockets (Supplementary Fig. 1a), supporting the view that heterogeneity at these sites is unlikely to affect the fucosyltransferase properties reported here. Steady-state kinetics with GDP-Fuc and the G0 acceptor showed classic Michaelis–Menten behavior, with AtFUT11 displaying turnover rates comparable to human FUT831 on the GDP-Fuc/G0 pair and a modestly higher apparent Km for GDP-Fuc but a similar Km for G0 (Supplementary Fig. 1b).

To gain deeper insights into the substrate specificity of FUT11, we utilized an extensive collection of 144 glycan structures immobilized on microarrays with a focus on synthetic N-glycan structures (Supplementary Fig. 2)32. This diverse array, which encompasses a wide range of structural variability and complexity, allowed us to comprehensively assess FUT11’s substrate preferences. Glycan microarrays were incubated with AtFUT11 expressed in HEK293 in the presence of GDP-Fuc (Fig. 1b). The introduction of fucose by the action of the enzyme was detected with fluorescently labelled Aleuria aurantia lectin (AAL) and an antibody raised against horseradish peroxidase (anti-HRP). These reagents were chosen based on their broad recognition of fucosylated structures (AAL) and the high specificity against core α1,3 fucose N-glycans (anti-HRP)33. Anti-HRP reacts with β1,2-xylose-containing and core α1,3-fucosylated N-glycans, the major substituents in HRP N-glycans. As core α1,6 fucose N-glycan structures (GL64-GL71) and LDNF N-glycans (GL130 and GL131) are ligands for AAL lectin, anti-HRP was critical to distinguish core α1,3 fucosylation events. For Fig. 1b, we excluded structures that already contained core α1,3-fucose, as well as fragments lacking a chitobiose core and O-glycan-type structures, as these are not substrates for AtFUT11. All structures included in the histograms in Fig. 1b, showed negligible recognition with AAL or anti-HRP before the reaction with AtFUT11. After incubation with recombinant AtFUT11, several structures printed showed the introduction of fucose as determined by the successful interactions with one of the two fucose recognizing reagents. The minimal structure that supported fucosylation was GL49, a truncated structure that only presents the α1,3 arm with a terminal GlcNAc in agreement with our previous results21.

The presence of β1,2-xylose was tolerated by AtFUT11 (GL3), and core α1,6-fucosylated N-glycans were also efficiently fucosylated, consistent with earlier results. Even highly branched α1,6 arms (GL50, GL54) did not significantly affect substrate recognition. N-glycans bearing β1,4-galactose on the α1,3 arm were accepted as substrates (GL59, GL126), whereas the presence of β1,4-GalNAc, Lewis X, or LDNF epitopes on the α1,3 arm (GL128, GL92, GL130) impaired AtFUT11 activity. These results refine our understanding of the structural requirements for AtFUT11 substrate recognition and are largely consistent with previous reports.

Architecture of the AtFUT11-GDP-G0 complex
To explain AtFUT11’s preferences for the N-glycans described above, we successfully obtained P21 crystals of AtFUT11 bound to GDP and G0 N-glycan (Table 1). These crystals enabled structure determination at high resolution (1.41 Å) and clear interpretation of the electron density map (Table 1). As expected, structural comparison using the DALI server34 revealed homology to other α1,3-FUTs, including mango FUT13 (PDB entry 7YRO35), human FUT9 (PDB 8D0Q, 8D0W, 8D0U, 8D0P, and 8D0R36), and Helicobacter pylori FUT (PDB 2NZX, 2NZY, 2NZW37). Although AtFUT11 differs substantially from these enzymes in acceptor specificity, the superpositions yielded good structural alignments (RMSDs of ~2.9 to ~3.4 Å over 297–338 aligned residues), indicating a conserved fold.

The structure of AtFUT11 in complex with GDP and G0 reveals an unusual GT-B architecture. The donor domain (residues 201–347) adopts a canonical Rossmann fold that coordinates GDP-Fuc. The acceptor domain comprises an N-terminal subdomain (residues 88–200) and a second Rossmann fold subdomain (residues 348–501). These subdomains are covalently connected by three disulfide bridges (C91–C391, C124–C326, and C128–C367; Fig. 2a) and engage in close intramolecular interactions. Notably, the N-terminal subdomain is distinct to AtFUT11 and is absent from other α1,3-FUTs (Fig. 2a). The electron densities for both GDP and the G0 glycan are well resolved (Fig. 2b). However, interestingly, the electron density for the innermost GlcNAc (AG0) is only partially defined, which may reflect either intrinsic flexibility of this sugar moiety, or—as shown below—be compatible with a transient conformational distortion away from its canonical chair geometry within the enzyme–substrate complex that could facilitate catalysis. In contrast to FUT8, where the G0 chitobiose core adopts an anti-ψ conformation9, the G0 in AtFUT11 assumes the more stable syn-ψ conformation38 (Fig. 2b), specifically affecting the GlcNAcβ1,4GlcNAc linkage between AG0 and BG0 units.

The structure further reveals that GDP is solvent-exposed and located exclusively within the donor domain, while the majority of the G0 glycan is anchored in the N-terminal subdomain. The α1,3 arm of the N-glycan is positioned within the Rossmann subdomain, while the α1,6 arm remains exposed to solvent (Fig. 2c). This suggests that the N-terminal subdomain, together with the second Rossmann subdomain, forms the N-glycan binding site, facilitating G0 recognition. Unlike proper exosites that can also recognize N-glycans and are found in other FUTs such as FUT89 and the more distantly related MGAT239, the N-terminal subdomain in AtFUT11 is not a true exosite, as it also provides the catalytic base (see below).

Recognition of GDP-Fuc in the donor site of AtFUT11
The active site of AtFUT11 is large, accommodating both the GDP-Fuc and N-glycan (Fig. 3a). The guanosine moiety of GDP-Fuc is anchored via hydrogen bonds involving the side chains of Ser218, Arg248, Lys256, and Glu280, as well as the backbone of Phe216. The pyrophosphate group is stabilized by interactions with the backbones of Ser218 and Asn219, and the side chains of Asn219, Arg226, Asn271, and Lys281. The enrichment of positively charged residues such as Arg226 and Lys281 is a characteristic feature of GT-B fold glycosyltransferases, which do not require metal ions for activity40. These basic residues substitute for the divalent metal ions typically used by GT-A fold enzymes, helping stabilize the pyrophosphate and ensuring the correct positioning of the sugar nucleotide for catalysis40.

To gain structural insight into the catalytic mechanism, we modeled GDP-Fuc into the donor site using coordinates from HpFUT complexed with GDP-Fuc (PDB entry: 2NZY)37. The resulting AtFUT11–GDP-Fuc–G0 ternary complex shows that Glu158 is positioned near the OH3 group of AG0, the acceptor hydroxyl targeted for fucosylation, suggesting a key role in catalysis (Fig. 3a, b). This arrangement provides the structural foundation to explore the reaction mechanism described below.

Molecular recognition of the G0 N-glycan by AtFUT11
AG0 is anchored via hydrogen bonds between its carbonyl group and the side chain of Tyr163, and between its OH3 group and Glu158. BG0 is stabilized through interactions involving its OH6 group and the side chains of Glu158 and Tyr192. The adoption of the more stable syn-ψ conformation by the AG0–BG0 chitobiose core is essential, as it orients the AG0 OH3 group towards GDP-Fuc, enabling fucosylation (Fig. 3a, b). The branching sugars of G0 (CG0, FG0, and GG0) are positioned within the N-terminal subdomain, while DG0 and EG0 are recognized by both subdomains (Fig. 3a). CG0 OH4 forms a hydrogen bond with the side chain of Glu197, and FG0 OH6 interacts with the backbone of Glu197. GG0 (the GlcNAc on the α1,6 arm) is fully solvent-exposed and does not interact with the enzyme. This limited recognition of the α1,6 arm likely accounts for the greater substrate tolerance observed at this branch. In contrast, the α1,3 arm is tightly recognized. DG0 OH3 forms a hydrogen bond with the side chain of His361, OH4 with Asp120, and OH6 with Met157. Similarly, EG0 OH1 interacts with His361, its carbonyl group contacts both the side chain and backbone of Ser362, and OH3 forms a hydrogen bond with the backbone of Ala358. His361 also establishes a CH–π interaction with EG0, contributing further to binding. These extensive contacts with EG0 rationalize the strict requirement for a GlcNAc moiety at this position, as it enhances α1,3 arm recognition and stabilizes the entire glycan in the bound state. Additional sugars can be tolerated at EG0 OH4 and OH6, as these hydroxyls are solvent-exposed (Fig. 3c). Likewise, CG0 OH2 is solvent-accessible, explaining AtFUT11’s tolerance for β1,2-xylose at this site. AG0 OH6 is also exposed, allowing the enzyme to accommodate core α1,6-fucosylation (Fig. 3c). However, it remains unclear why AtFUT11 does not tolerate GalNAc moieties at the EG0 position, while Gal residues are accepted.

AtFUT11 mutant analysis in glycoengineered HEK293 cells
To dissect the functional importance of specific residues in AtFUT11, we designed four alanine single-substitution mutants—E158A, Y192A, E197A, and H361A—based on structural analysis of the enzyme in complex with GDP and G0 N-glycan. Glu158 was predicted to function as the catalytic base due to its hydrogen bond to the hydroxyl group of the innermost GlcNAc acceptor, while the other residues are involved in G0 substrate binding. We assessed the catalytic ability of AtFUT11 wild-type enzyme and these mutants by introducing the full coding constructs of AtFUT11 and those variants via targeted knock-in (KI) in a genetically engineered HEK293 cell line (HEK293 Biantennary) that lacks multiple endogenous glycosyltransferases involved in various steps of N-glycosylation biosynthesis (capping by ST3GAL4/6, ST6GAL1, FUT4, elongation by B4GALNT3/4, and branching by MGAT3/4A/4B/5, and FUT8) (Fig. 4a). This glycoengineered background, displaying simplified biantennary N-glycans as substrates, provided a clean slate to evaluate the activity of introduced AtFUT11 variants without interference from competing glycosylation pathways, as previously described20. Importantly, the FUT8 gene, which catalyzes the α1,6 core fucosylation on the same core GlcNAc residue, was deleted. Each AtFUT11 variant (wt and mutants) was integrated individually into the AAVS1 safe harbor locus using ZFN-mediated targeted KI and the clones were validated by junction PCR to confirm proper integration of the gene (Supplementary Fig. 3). To quantify the α1,3-fucosylation activity, we then employed flow cytometry using an α1,3-fucose-specific polyclonal antibody. As shown in Fig. 4b, wild-type AtFUT11 expressed in HEK293 Biantennary clearly exhibited α1,3-fucosylation, with no detectable α1,6-fucosylation as confirmed by staining with Lens culinaris agglutinin (LCA) lectin. This absence of α1,6-fucosylation across all KI mutant cell lines validates the KO of FUT8 in the cell background and further supports the specificity of α1,3-fucosylation by AtFUT11. The E158A mutant completely abolished enzymatic activity, consistent with its predicted role as the catalytic base. Mutations at Tyr192 and Glu197 resulted in only minimal α1,3-fucosylation, likely due to impaired acceptor substrate binding or disruption of the precise orientation of the innermost GlcNAc required for catalysis. In contrast, the H361A mutant retained activity comparable to the wild-type enzyme, indicating that His361 is not essential for catalytic function. This observation is further supported by molecular dynamics simulations, which show that His361 does not form stable interactions with the α1,3 arm of the N-glycan, reinforcing its dispensability for substrate engagement and enzymatic turnover (Supplementary Fig. 4).

Prompted by these findings, we sought to provide a molecular explanation for the functional redundancy between AtFUT11 and its isoform, AtFUT12. As previously reported, AtFUT12 shares high sequence identity with AtFUT11 and displays overlapping enzymatic activity in heterologous expression systems, including mammalian cells engineered to express biantennary N-glycans and core α1,6-fucosylation machinery20. An alignment of their protein sequences reveals that residues critical for donor and acceptor binding—including the catalytic base Glu158 and G0-binding residues Tyr192 and Glu197—are strictly conserved (Supplementary Fig. 5). This high degree of active site conservation provides a clear rationale for their overlapping activity20 and validates the use of AtFUT11 as a representative model for this enzyme class.

Collectively, this cellular assay confirmed the catalytic role of Glu158, highlighted additional residues crucial for activity, and linked our structural insights with both in-cell functional readouts and the known isoform redundancy in Arabidopsis.

Dynamic behavior and sugar puckering in AtFUT11
Molecular dynamics (MD) simulations of the Michaelis complex (MC) revealed notable ligand instability, especially in the acceptor substrate. Comparative analyses, including simulations with positional restraints, showed that interactions between Glu158 and the AG0 subunit are crucial for maintaining complex integrity. These interactions are consistent with a transient conformational distortion of the innermost GlcNAc unit in G0. To characterize this distortion, conformational analysis was conducted on the AG0 and fucose moieties. In the MC context, the AG0 subunit adopts a distorted 1S3-like minimum (see below).

Given the well-known limitations of classical force fields (FFs) in accurately describing sugar flexibility41, hybrid QM/MM/MD simulations were performed to more accurately capture the structural and electronic features relevant for substrate recognition and catalysis. These simulations confirmed that several interactions observed in the crystal structure persist throughout the trajectory. Glu280 and Ser218 consistently interacted with the guanosine moiety of GDP-Fuc, while the diphosphate group remained stably bound to Lys281 and Arg226. Additional contacts were observed between Thr272, Glu270, and Tyr162 and the hydroxyls of the fucose unit.

Conversely, interactions involving Arg248, Phe219, Tyr163, Asn219, and Asn271 were not retained; instead, new contacts formed between the main chains of Val254 and Gly252 and the guanine base. This shift may be due to the fucose moiety modifying the interaction landscape as the complex approaches the reactive state (Fig. 5a and Supplementary Fig. 6).

Consistent interactions were also observed between Ser362, Asp120, Glu197, Tyr192, and Glu158 and the E, D, C, B, and A subunits of the acceptor, respectively (Fig. 5a and Supplementary Fig. 6). Additionally, further interactions emerged involving the α1,3-arm of the glycan, particularly between Ser194 and the backbone of Gly191 with the EG0 subunit. In contrast, His361 did not form stable interactions in any simulation, consistent with the catalytic activity retained in the H361A mutant, indicating it is dispensable for α1,3-arm recognition (Supplementary Fig. 4). To probe the reactive conformation, distance restraints were applied to approximate the pre-glycosylation state. Under these conditions, the fucose unit favored a canonical 4C1 conformation (Supplementary Fig. 7), while AG0 adopted a single minimum resembling a B3,O-1S3-like conformation, optimally orienting the OH3 group for nucleophilic attack and proton transfer (Fig. 5b).

When restraints were removed (MC), two minima emerged: one representing the B3,O-1S3-like conformation (as in the RE) and another 1S3-like. This shift results from the interaction between OH3 and the GDP-Fuc pyrophosphate, leading to AG0 organization, as supported by metadynamics (Supplementary Fig. 8).

To assess donor-induced effects, conformational studies were conducted on AtFUT11–G0–GDP (trimer) and AtFUT11–G0 (dimer). The trimer retained both energy minima seen in the MC, with minor free energy landscape (FEL) changes likely due to increased flexibility in the absence of fucose. In contrast, the dimer favored 1S5–OS2-like states, likely due to the absence of stabilizing interactions between AG0 and the diphosphate group (Supplementary Fig. 9). Finally, the role of Glu158 in conformational activation was confirmed through simulations of the E158A mutant, which favored a single 4C1 chair formation, typical of unstrained GlcNAc residues. These findings underscore the dual role of Glu158: acting not only as the catalytic base but also as a conformational effector, potentially promoting distortion of the acceptor GlcNAc into a reactive conformation that could facilitate catalysis (Fig. 5c).

Mechanistic insights into the fucosyl transfer reaction
QM/MM/MD simulations revealed a preferential interaction between the OH3 group and the pyrophosphate moiety of GDP-Fuc. To assess the feasibility of OH3 activation, we investigated the transition from the Michaelis complex (MC) to the reactive state (RE). Metadynamics simulations successfully bridged these conformations, revealing an energy difference of ~2.5 kcal/mol between MC and RE, with a transition barrier below 7 kcal/mol (Supplementary Fig. 10). Taken together, these low energetic requirements, along with the spontaneous OH3 exchange observed in the QM/MM/MD trajectories (Supplementary Fig. 6), are consistent with a rapid, dynamically exchanging process.

Using a representative minimum-energy structure from the puckering analysis of the AG0 moiety with soft restraints (Fig. 5b), the free energy surface (FES) for the fucosyl transfer reaction was computed based on two collective variables:

CV1 = d1 - d2 (1)

representing glycosyl transfer such as the difference between the glycosidic bond that is broken (d1) and the one that is formed (d2), and

CV2 = d3 - d4 (2)

describing proton transfer as the difference between the O–H bond that is broken in the nucleophile (d3) and the one that is formed in the catalytic base (d4) (Fig. 6a). Each point on the FES reflects a discrete stage along the reaction coordinate (with the X-axis corresponding to C1–O3 bond formation and the Y-axis to proton transfer from OH3 to Glu158). Free energy surface (FES) analysis revealed two local minima corresponding to the reactant (RE) at CV1 ≈ –1.49 Å and CV2 ≈ –0.91 Å, and the product (PR) at CV1 ≈ 1.46 Å and CV2 ≈ 0.94 Å (Supplementary Fig. 11). The calculation of the minimum free-energy path (MFEP), which can be considered as an equivalent of the well-known intrinsic reaction coordinate (IRC) revealed a transition state (TS) located at CV1 ≈ 0.43 Å and CV2 ≈ –0.64 Å (Fig. 6b and Supplementary Fig. 11). The transition-state nature of this TS was confirmed through a committor analysis42, which showed that the system relaxed almost equally toward RE and PR (see 10.5281/zenodo.17558724). The calculated activation barrier from the Michaelis complex was ~18.5 kcal mol⁻¹, in agreement with values reported for other fucosyltransferases (17–20 kcal·mol⁻¹)43,44, and consistent with our experimental results. The studied reaction is exergonic by 0.4 kcal/mol, which reflects a thermodynamically slightly favored process. However, it must be considered that the molecular process analyzed leads to a product (PR) in which the catalytic base (E158) remains protonated. It is reasonable to assume that this PR product would promptly exchange a proton with the surrounding aqueous medium, thereby regenerating the catalytic base and allowing the catalytic cycle to restart (For a proposed catalytic cycle, see Supplementary Fig. 12).

Closer inspection of the FES topology reveals a flat region beyond the TS, which may be indicative of the presence of a transient intermediate or, at least, of a transient meta-stable situation, as reflected by a small shoulder, characteristic of such scenarios in non-enzymatic reactions26,45,46, along the corresponding MFEP represented in Fig. 6b. Interatomic distances at the TS (d4 ≈ 1.6 Å; d3 ≈ 1.0 Å) indicate an asynchronous mechanism, where proton transfer occurs after the TS, consistent with a late transition state and an associative reaction profile. Close inspection of the residues surrounding the transition structure shows stabilizing electrostatic interactions between the pyrophosphate group and Arg226, Lys281, and Ser218, which collectively facilitate GDP departure. At this point, the fucose adopts a ³H₄-like conformation (Fig. 6c). Non-covalent interaction (NCI)47,48 analysis of the transition structure further confirms that proton transfer has not yet taken place, supporting the asynchronous nature of the process (Fig. 6d). In fact, in the MFEP-based reaction movie, we observe features consistent with a short-lived oxocarbenium-like species (Supplementary Movie 1).

To gain deeper insight into the electronic rearrangements along the reaction coordinate, we performed an Electron Localization Function (ELF)49,50 analysis on representative snapshots along the MFEP, which connects the RE and product PR states through the TS. The Electron Localization Function (ELF) enables the visualization of changes in electron density through entities known as attractors, which correspond to local maxima within specific spatial regions called basins (disynaptic when shared between two atoms or monosynaptic when belongs to one atom). By observing how these attractors shift, it becomes possible to determine the precise moment when a bond is formed or broken, or when an atom gains or loses an electron pair. Accordingly, distinct stages (or events) of a reaction can be defined, independent of the number of reaction steps, which are determined by the corresponding kinetics. By defining these stages, temporally stable situations may arise with significant implications, such as stereochemical consequences. These situations may exhibit an appreciable lifetime without constituting local energy minima, and thus cannot be considered true intermediates but transient intermediates26,45,46. While ELF analysis has proven effective for characterizing transient intermediates computationally51–53, its application to enzymatic reaction mechanisms remains relatively rare in the literature54–57.

In the FUT11-catalyzed reaction, we initially performed an ELF analysis along the MFEP (Fig. 6b) represented in Fig. 6e (for the populations of the basins in each point see Supplementary Table 1). It can be clearly observed how the C1–OP bond starts to break at the beginning of the process (point 9, Fig. 6f) and is fully cleaved by point 13, at which point neither the nucleophilic attack of O3 nor the OH3 group transfer has yet occurred. Therefore, we can state that from this point onwards, a glycosyl cation is formed, though it would be more accurate to describe it as an intimate ion pair. However, this species cannot be localized as an energy minimum and must be classified as a transient intermediate, and thus it does not represent a proper reaction step. What is certain is that this situation persists until point 67 (Fig. 6f), where hydrogen transfer begins, almost simultaneously with the onset of C1–O3 bond formation. Finally, the bond is formed, and the OH3 group is transferred (point 74, Fig. 6f). In summary, according to this analysis, a transient glycosyl cation exists, placing this reaction on the borderline between SN1 and SN2 mechanisms.

The ELF analysis along the MFEP reveals the presence of a transient intermediate, but does not provide information about its lifetime. For this, molecular dynamics simulations are required, considering some geometric feature that distinguishes the different reaction stages, as we have previously demonstrated for organocatalytic (non-enzymatic) reactions. In our case, for example, the planarity of C1 could be considered a potential criterion. Unfortunately, the amplitude of C–H bond vibrations makes it difficult to pinpoint the precise moment when C1 becomes planar and when it re-pyramidalizes. Since this is an enzymatic reaction, molecular dynamics simulations tend to be highly reproducible, and generally only a few replicas are sufficient to gain insight into the system’s temporal evolution. Nevertheless, due to the stochastic nature of these simulations, a certain number of replicas is necessary. Our approach in this work is to perform a series of QM/MM/MD simulations of the reaction, including several replicas, and then apply ELF analysis to the resulting trajectories.

Under these conditions, we obtain plots in which the x-axis corresponding to reaction time, which allows us to estimate, at least approximately, the lifetime range of the glycosyl cation (Fig. 6e). It should be noted that ELF analysis must be performed on all QM/MM/MD simulations, and together with the high computational cost of each QM/MM/MD run, this results in a very demanding overall computational workload, thereby limiting the precision of time estimates.

To obtain reactive trajectories connecting RE and PR through the TS, a total of 20 independent replica pairs were generated from the TS using unbiased QM/MM/MD. For each replica, two runs were performed: one with random Maxwell–Boltzmann initial velocities and another with their opposite values (v → −v), thus yielding complementary TS→RE and TS→PR connections. Each branch was propagated for 2 ps (4 ps per replica after concatenation into RE→TS→PR trajectories). Trajectories were saved every 5 fs, resulting in 800 frames per concatenated replica. These linked trajectories were used to estimate event lifetimes and verify basin connectivity in collective-variable space (Fig. 6g) (For per-replicate analyses, see 10.5281/zenodo.17558724).

The data shown in Fig. 6e, g clearly reveal a defined temporal window between GDP departure and the formation of the new O3–C1 glycosidic bond, corroborated by the concerted evolution of key reactivity distances (d–d1,4), a transient shortening of C1–O5, and a reduction in the distance of C1 from the O5–H–C2 plane, together consistent with transient glycosidic oxocarbenium-like character (Supplementary Fig. 13).

Notably, we observe an increased population of the C1–O5 basin, consistent with resonance stabilization of a transient glycosyl cation during this interval. Despite some variability, with gaps extending up to 800 fs, no combination of trajectories yields a lifetime for the carbocation species shorter than 500 fs, supporting the interpretation of a transient state consistent with the existence of a transient intermediate. Consequently, although a classical SN1 mechanism involving an intimate ion pair and full configuration inversion cannot be definitively confirmed, the data strongly support a pathway that lies at the borderline between SN2 and SN1 mechanisms. The process appears to be concerted yet highly asynchronous, with sufficient temporal separation between key chemical events to impart partial intermediate character, while still ensuring inversion of configuration. In essence, FUT11 catalyzes fucose transfer through a mechanism that skirts the edge of SN1 territory.

AtFUT11 can synthesize Lewis x
Finally, a comparison of the HsFUT9 crystal structures complexed with GDP-H-type 2 and GDP-extended type 2 lacto-N-neotetraose (LNnT) with the AtFUT11-GDP-G0 complex revealed that the chitobiose of G0 aligns well with the GlcNAc and Gal residues of the H-type 2 and LNnT oligosaccharides (Fig. 7a). This structural similarity indicates that AtFUT11 can also fucosylate type 2 LacNAc substrates, thereby generating the Lewis x structures. To confirm this, we incubated AtFUT11 with GDP-Fuc and a Lewis x precursor, specifically p-nitrophenyl N-acetyllactosamine, revealing that AtFUT11 is capable of fucosylating this derivative in a modest yield of 7.6% as determined by UHPLC/ESI-TOF-MS analysis. While the activity is weak, it is not unexpected given the structural similarity to HsFUT9 and their shared membership in the GT10 family58. This supports the idea that AtFUT11 retains structural elements common to antenna-fucosylating enzymes, explaining its latent activity on LacNAc. Rather than reflecting an unusual gain-of-function, this side activity illustrates a shared structural and evolutionary origin within GT10, emphasizing the inherent flexibility of this fold. Overall, these findings indicate that the GT10 architecture of AtFUT11 enables partial functional overlap with mammalian antenna-FUTs such as FUT9. Its ability to generate Lewis X in vitro—albeit at much lower efficiency than core α1,3-fucosylation of G0 (compare Fig. 7b vs 1a)—represents a suboptimal yet mechanistically plausible activity, highlighting how GT10 structural features support evolutionary plasticity and expanded substrate scope, even in enzymes specialized for core fucosylation.

It is noteworthy that this dual activity (core and LacNAc fucosylation) is not unprecedented; in C. elegans, a related enzyme, CEFT1 catalyzes both core α1,3-fucosylation and, to a minor extent, Lewis X antigen synthesis on distinct acceptor types59. By contrast, CEFT2 does not catalyze core fucosylation but instead acts exclusively on LacdiNAc acceptors59.

However, it is important to note that there is currently no evidence supporting a physiological role for Lewis X synthesis by AtFUT11 in Arabidopsis or other plants. Unlike animals, where Lewis X plays important biological roles60, these epitopes are not naturally detected in plants61,62, and the low in vitro activity likely reflects enzymatic promiscuity and structural conservation rather than a biologically significant process. Thus, while the ability of AtFUT11 to fucosylate Lewis X precursors in vitro is intriguing as an example of catalytic flexibility, it does not imply direct physiological relevance.

Methods
Expression and purification of AtFUT11
The DNA sequence encoding amino acid residues 84–501 of AtFUT11 was codon optimized and synthesized by GenScript (USA) for expression in HEK293F cells (Thermo Fisher Scientific, R79007). The DNA, containing at the 5′-end a recognition sequence for KpnI, and at the 3′ end a stop codon and a recognition sequence for XhoI, was cloned into a modified pHLSec containing after the secretion signal sequence, a 12x His tag, a superfolder GFP and a Tobacco Etch Virus (TEV) cleavage site, rendering the vector pHLSec-12Hist-GFP-TEV-AtFUT11(84–501). Both the synthesis of the AtFUT11 construct and the engineered pHLSec together with the cloning of AtFUT11 into pHLSec-12His-GFP-TEV were performed by GenScript.

pHLSec-12Hist-GFP-TEV-AtFUT11(84-end) was transfected into the HEK293F cell line (Thermo Fisher Scientific) as described below. Cells were grown in suspension in a humidified 37 °C and 5% CO2 incubator with rotation at 130 r.p.m. using F17 serum-free media with 2% Gluta-max and 0.1% P188. Transfection was performed at a cell density of 2.5×106 cell/mL in fresh media using a ratio of 3 μg plasmid per mL of cell culture. Cells were then incubated 5 min at 37 °C and PEI-MAX 40K (1 mg/mL) was added to the cell culture flask in a ratio of 9 μg PEI per mL of cell culture. At the time of transfection, Kifunensine-Bio-X (CarboSynth) was added to the culture (5 μM final concentration) to facilitate trimming of N-glycans during the purification.

After 24 h post-transfection, cells were diluted 1:1 with pre-warmed media supplemented with valproic acid to a final concentration of 2.2 mM. Cells were harvested 6 days post-transfection by spinning down at 300 × g for 5 min, after which the supernatants were collected and centrifuged at 4000 × g for 15 min.

Supernatant was loaded into a HisTrap™ Excel Column (GE Healthcare). Protein was eluted with an imidazole gradient from 10 mM (buffer A: 25 mM TRIS pH 7.5, 500 mM NaCl, 10 mM imidazole) up to 500 mM (buffer B: 25 mM TRIS pH 7.5, 500 mM NaCl, 500 mM Imidazole). Buffer was then exchanged to buffer C (25 mM TRIS pH 7.5, 150 mM NaCl) using a HiPrep 26/10 Desalting Column (GE Healthcare). Thereafter, the TEV recognition site was cleaved using TEV protease, added in a ratio of 1:50 (TEV: protein) to the fusion construct in order to cleavage the His-GFP tag. After 20 h of reaction at 18 °C, the cleavage was satisfactorily verified through SDS-PAGE.

TEV protease and GFP were later removed from the solution using a HisTrap Column (GE Healthcare), and isolated AtFUT11 was dialyzed to buffer D (25 mM MES pH 6.5, 150 mM NaCl). Endoglycosidase-H (Endo-H) was then added in a ratio 3:250 (Endo-H: protein) in order to trim the N-glycans. After 20 h of reaction at 18 °C, the cleavage was verified through SDS-PAGE. Endo-H was later removed from the solution using a MBP-Trap Column (GE Healthcare), and deglycosylated AtFUT11 was then loaded into a HiLoad 26/60 Superdex 75 Colum (GE Healthcare), previously equilibrated with buffer C.

The protein was concentrated using Amicon Ultra-15 mL (Merck) and quantification of protein was carried out by absorbance at 280 nm using its theoretical extinction coefficient (ε AtFUT11 = 46465–45,840 M−1 cm−1).

Reaction of AtFUT11 with G0 N-glycan
G0 glycopeptide (peptide: NH2-Lys-Val-Ala-Asn-Lys-Thr-CO2H) was isolated from chicken egg yolk as previously described9. A solution containing G0 glycopeptide (10 nmol) and GDP-Fuc (20 nmol) were incubated in the presence of AtFUT11 (70 µg) in TBS buffer (Tris 50 mM, 150 mM NaCl, pH=7.5) at room temperature for 18 h. The reaction mixture was analyzed by MALDI-TOF mass spectrometry, performed on an Ultraflex treme III time-of-flight mass spectrometer equipped with a pulsed N2 laser (337 nm) and controlled by FlexControl 3.3 software (Bruker Daltonics). 2,5-Dihydroxybenzoic acid (DHB) (5 mg/mL in 70/30 ACN: water with 0.1% TFA) was employed as matrix. Reaction mixture (1 µL) was spotted on MTP 384 polished steel MALDI plate and dried. Matrix (1 µL) was spotted on top, dried and measured (n=4). G0 glycopeptide was included as control. Data was analyzed employing FlexAnalysis 3.3 software (Bruker Daltonics). Raw mass spectrometry data have been deposited in the GlycoPOST repository under accession GPST000666.

Microarray screening of AtFUT11 activity
A collection of aminopentyl functionalized glycans (144 structures) were immobilized on NHS activated microarray slides as previously described9. After printing, the microarrays were incubated overnight at room temperature with a solution (200 µL) containing recombinant AtFUT11 (58 µg) with GDP-Fuc (500 µM) in TBS buffer (50 Mm TRIS, 150 mM NaCl, pH=7.5). After incubation, the microarrays are washed with TBST (50 mM TRIS, 150 mM NaCl, pH=7.5 + 0.01% Tween 20) and water. Solutions of fluorescently labelled (Alexa Fluor-555) Aleuria aurantia lectin (Vector Lab, L-1390-2, 1.4 µM) and Anti-HRP (Merck, P7899, 2.0 µM) in TBST (50 mM TRIS, 150 mM NaCl, pH=7.5 + 0.01% Tween 20) were incubated in the dark at room temperature for 1 hour. As controls unreacted microarrays were incubated with AAL-555 and anti-HRP-555. After incubation, microarrays were washed with TBST and water, dried in a slide spinner and fluorescence was measured in Agilent G265BA microarray scanner system (Agilent Technologies, Santa Clara, USA). Quantification was performed with ProScanArray® Express (PerkinElmer, Shelton, USA) and Microsoft Excel. Average of mean relative fluorescence units (RFU) values after local background subtraction and standard deviation for four replicates spots were represented as histograms employing GraphPad Prism 6 software.

Crystallization and data collection
Purified AtFUT11 was concentrated and co-crystallized with 5 mM GDP and 1.5 mM G0 in the absence of NaCl. Appropriate size of crystals were grown by sitting drop experiments at 18 °C by mixing 0.5 µL of protein solution (5.5 mg/mL AtFUT11, 5 mM GDP and 1.5 mM G0 in 25 mM TRIS pH 7.5) with an equal volume of a reservoir solution (90 mM LiNaK, 0.1 M TRIS pH 8 and 32.5% precipitant mix 6) (Molecular Dimensions) and 0.25 µL of an additive solution (40% Acetonitrile) (Hampton Research). The crystals were cryoprotected in mother liquor containing 25% glycerol and flash frozen in liquid nitrogen.

Structure determination and refinement
The data were collected in the beamline BL13 XALOC of ALBA at a wavelength of 0.97 Å and a temperature of 100 K. Data were processed and scaled using XDS63 and CCP464 software packages. Relevant statistics are given in Table 1. The crystal structure was solved by molecular replacement with Phaser64 using a model generated with AlphaFold65 as the template. Initial phases were further improved by cycles of manual model building in Coot and refinement with REFMAC564,66. Further rounds of Coot and refinement with REFMAC5 were performed to obtain the final structure. The final model was validated with PROCHECK; model statistics are given in Table 1. The Ramachandran plots for the AtFUT11-GDP-G0 show that 90.3%, 9.7%, 0%, and 0% of the amino acids are in most favoured, allowed, generously allowed and disallowed regions, respectively.

Synthesis of Lewis x with recombinant AtFUT11
A solution containing p-nitrophenyl N-acetyllactosamine (50 nmol) and GDP-Fuc (100 nmol) were incubated in the presence of AtFUT11 (288 µg) in TBS buffer (50 mM TRIS, 150 mM NaCl, pH=7.5) at room temperature for 18 h. The reaction mixture was quenched with acetonitrile and analyzed by ultra-high-performance liquid chromatography and mass spectrometry detection with an electrospray source and high-resolution time-of-flight analyzer (UHPLC/ESI-TOF-MS). The reaction mixture was separated by liquid chromatography using Acquity Premier-type equipment (Waters, Milford, MA, USA) equipped with a BEH HILIC amide type column of dimensions 50 × 2.1 mm and particle size of 1.7 µm (Waters, Milford, MA, USA). The column temperature was set at 30 °C, and the injection volume was 1 µL. The total analysis time was 20 min. For the chromatographic separation, a mixture of aqueous 100 mM ammonium formiate (A) and ACN (B) as the mobile phases was employed with a gradient as follows: 10% B held for 0.5 min at 0.3 mL min−1, increased linearly to 100% B over 4.5 min at 0.2 mL min−1, held at 100% B for 2 min at 0.2 mL min−1, then returned to 10% B over 0.5 min and equilibrated for 3.5 min at 0.3 mL min−1. The peak mass detection was carried out using ESI-QTOF Synapt XS equipment (Waters, Milford, MA, USA). All instrumental parameters were optimized to obtain the best signal, the capillary voltage and cone voltage were firmly set to 700 and 50 V, respectively, while the nebulization and cone gas flow rates were firmly set at 700 and 150 L/h, respectively, and the nebulization and source temperatures were set at 350 °C. The acquisition was performed in positive mode with the mass range m/z 50–1200 Da. Data were processed using MassLynx v4.2 (Waters, Milford, MA, USA). UV detection was set to 298 nm. Peaks were integrated and mass spectra were analysed. The formation of a new peak (tR = 2.44 min) corresponding to the mass of p-nitrophenyl Lewis x was observed. m/z [M+Na]+, calculated for C26H38N2NaO17 673.2068, found 673.2057. Raw mass spectrometry data have been deposited in the GlycoPOST repository under accession GPST000666.

Cell culture
The original HEK293 was obtained from ATCC (CRL-1573) and used for glycoengineered experiments. All isogenic glycoengineered HEK293 cell lines were cultured in DMEM (Sigma-Aldrich) supplemented with 10% heat-inactivated fetal bovine serum (Sigma-Aldrich) and 2 mM GlutaMAX (Gibco) in a humidified incubator at 37 °C and 5% CO2.

CRISPR/Cas9-targeted KO in HEK293 cells
CRISPR/Cas9 knockout (KO) was conducted using the GlycoCRISPR resource, which includes validated gRNA libraries targeting all human glycosyltransferases (GTs)67. HEK293 Biantennary (KO ST3GAL4/6, ST6GAL1, FUT4, B4GALNT3/4, and MGAT3/4A/4B/5) cells were developed through four rounds of KO: the first targeting B4GALNT3/4 and MGAT3; the second targeting FUT4, ST3GAL4/6, and ST6GAL1; the third targeting MGAT4A/4B/5; and the fourth targeting FUT8. In each round, HEK293 cells were cultured in 6-well plates until approximately 70% confluence and transfected with a total of 3 µg of gRNA and GFP-tagged Cas9-PBKS plasmid using Lipofectamine 3000 (Thermo Fisher Scientific), following the manufacturer’s instructions. One day after the transfection, GFP-positive cells were bulk-sorted using FACS (SONY SH800). After a week of culture, bulk-sorted cells were single-cell sorted into 96-well plates. KO clones were screened by Indel Detection via Amplicon Analysis PCR with primers amplifying the gRNA target sites, and indel sequences were further confirmed through Sanger sequencing. All gRNA and primers were synthesized by TAG Copenhagen A/S, and their sequences are listed in Supplementary Table 3.

AtFUT11 construct design and site-directed mutagenesis
The synthetic full-length DNA of At3g19280 (also known as AtFucTA or FUT11) was previously synthesized20 and cloned into the EPB71 vector (Addgene #90018) using BamHI and NotI restriction sites, enabling targeted integration into the human AAVS1 safe harbor locus. Mutations of four candidate residues (E158, Y192, E197, and H361) to alanine were introduced individually using the PrimeSTAR Mutagenesis Basal Kit (Takara Bio).

ZFN KI of AtFUT11 variants in HEK293 Biantennary cells
For site-directed knock-in (KI), a modified ObLiGaRe approach targeting the AAVS1 safe harbor site was employed, utilizing two inverted ZFN binding sites flanking the AtFUT11 variants within the donor plasmids. KI was carried out as previously described. Briefly, HEK293 Biantennary cells were grown in 6-well plates to ~70% confluency and transfected with 1 µg of each ZFN tagged with GFP or Crimson alongside 2 µg of donor plasmid. 48 h post-transfection, cells expressing both GFP and Crimson were enriched by FACS (Sony SH800), and following one week of culture, the bulk-sorted cells were single-cell sorted into 96-well plates. The targeted KI single clones were screened by junction PCR using primer pairs specific to the junction between the donor plasmid and the human AAVS1 locus. All primers were synthesized by TAG Copenhagen A/S, and their sequences are listed in Supplementary Table 3.

Flow cytometry analysis
The level of α3 fucose structures on the cell surface was measured by flow cytometry using a rabbit polyclonal antibody specific for α3 fucose glycosylation. Cells were washed with PBS containing 1% BSA (PBA) and incubated on ice with α3 Fuc pAb (Agrisera, AS07268, 1:500 dilution in PBA) or biotinylated LCA lectins (Vector lab, B-1045-5, 0.5 µg/mL in PBA) for 1 h, followed by washing and incubation with Alexa Fluor 647-conjugated goat anti-rabbit IgG (Invitrogen, A21245, 1 µg/mL in PBA) or Alexa Fluor 647-conjugated streptavidin (Invitrogen, S32357, 1 µg/mL in PBA) for 30 min. Cells were then resuspended for flow cytometry analysis (Sony SA3800), and the mean fluorescent intensity (MFI) of α3 Fuc pAb binding was quantified using FlowJo software (FlowJo LLC).

MC model building
The Michaelis complex (MC), comprising the protein, the acceptor hexasaccharide (G0), and GDP-fucose (GDP-Fuc), was generated based on the crystal structure of the ternary complex (AtFUT11, G0 and GDP). The GDP-Fuc coordinates were obtained by superimposing the nucleoside moiety of GDP-Fuc (from HpFUT complexed with GDP-Fuc PDB: 2NZY) onto the GDP molecule in the experimental structure, yielding the ternary model used for molecular dynamics (MD) simulations. All additional models used in this study were derived from this initial configuration. In the case of the E158A mutant, the substitution was performed using the mutagenesis tool implemented in PyMOL68. Protonation states were assigned using PROPKA369 at pH ≈ 7.0 for all models. All trajectory analyses were performed with CPTRAJ software70 as implemented in AMBER2371. Root-mean-square deviation (RMSD) analyses were carried out using the first snapshot following the second equilibration step as reference (see below).

Molecular dynamics simulations
All molecular dynamics (MD) simulations were performed using the AMBER23 simulation package71. The protein was modeled using the FF14SB force field72, while the acceptor glycan (G0) was described using the GLYCAM06 force field73. The donor substrate GDP-Fuc was parametrized using the ANTECHAMBER module within AmberTools23, employing GAFF as the base force field and AM1-BCC for partial atomic charge calculation74,75. Michaelis complex (MC) was constructed using the LEaP module in AmberTools2376. The system was solvated in a 15 Å orthorhombic TIP3P water box77,78 (box dimensions 117.2 × 79.4 × 92.2 Å³), and electroneutrality was achieved by adding two Cl⁻ counterions, resulting in a total of 21,507 water molecules.

A standardized five-step equilibration protocol was applied:
(i) Solvent minimization: 5000 steps, including 2500 steepest descent followed by 2500 conjugate gradient steps, with harmonic restraints on the solute (protein and ligands). (ii) Unrestrained minimization: An additional 5000 steps under the same conditions without restraints. (iii) Gradual heating: The system was heated from 0 K to 300 K under constant pressure (1 atm) using periodic boundary conditions. Harmonic restraints of 30 kcal/mol were applied to the solute. Langevin dynamics were used for temperature control79 with a 1 fs timestep. Long-range electrostatics were handled using the PME mesh Ewald method80 and a non-bonded cutoff of 8 Å was applied for Lennard-Jones interactions. (iv) Equilibration: The system was equilibrated for 2 ns under NVT conditions at 300 K using a 2 fs timestep. This step was repeated to confirm system stability. (v) Production runs: Final MD simulations were performed under constant volume and temperature (300 K), using a Langevin thermostat with a collision frequency of 2.0 ps⁻¹. All bonds involving hydrogen atoms were constrained using the SHAKE algorithm81 with a 2 fs timestep for integration.

QM/MM molecular dynamics simulations
QM/MM molecular dynamics simulations were carried out using the CP2K (version 2022.1) simulation package82, in combination with PLUMED283 for trajectory monitoring and collective variable tracking. Simulation models were prepared by extracting representative snapshots from preceding classical MD simulations.

The quantum region comprised 49 atoms enclosed within an orthorhombic box of 16.5960 × 17.2951 × 13.7381 Å³. This QM region included the innermost N-acetylglucosamine (GlcNAc), atoms C1, C2, O5, and C5 of the adjacent sugar ring, and their respective substituents. QM–MM boundaries were saturated with hydrogen link atoms (see Supplementary Fig. 14). QM atoms were treated using the semi-empirical PM6 method, selected to capture the conformational behavior of the AG0 unit while maintaining computational efficiency. The MM atoms were described using the same force fields employed in the classical MD simulations. The MM environment consisted of a periodic orthorhombic box (74.9 × 122.8 × 90.2 Å³) containing 21,508 TIP3P water molecules and 2 Cl⁻ counterions.

All QM/MM/MD simulations followed a standardized multi-step protocol: (i) a progressive annealing phase to relieve steric clashes, (ii) a 5 ps QM/MM equilibration run in the NVT ensemble at 300 K with a timestep of 0.5 fs and no external bias, allowing the system to relax at the QM/MM level, (iii) a 100 ps production simulation at 300 K under NVT conditions, with a 1 fs integration timestep. Five independent replicas were performed for each model, restarting the velocity distribution in each run to enhance sampling of the conformational landscape of the enzyme–substrate complex84.

QM/MM/MD metadynamics simulations
Metadynamics simulations were performed using CP2K82 in combination with the metadynamics algorithm implemented in PLUMED283 which was also used to monitor collective variables (Supplementary Fig. 15) and compute the associated FES. Starting structures were derived from the MC described above. The MM region was treated using the same force fields as in the classical MD simulations, while the QM region (see Supplementary Fig. 14) was described using density functional theory (DFT) with the PBE exchange–correlation functional85. This choice is consistent with previous studies on glycosyltransferases43 and carbohydrate conformational analysis86. The QM region was treated using the Gaussian and plane waves (GPW) approach. The electronic wave functions were expanded with the triple-ζ valence polarized TZV2P basis set87, and the electron density was converged using an auxiliary plane-wave basis set with a variable cutoff, optimized for each model. GTH pseudopotentials were used to describe core electrons88.

All metadynamics simulations followed a standardized protocol: (i) optimization of the plane-wave density cutoff for each system, (ii) a multi-step annealing process to remove residual strain, (iii) a 5 ps QM/MM equilibration run at 300 K under NVT conditions with a 0.5 fs timestep and no external bias, (iv) the production metadynamics simulation, initiated from the final snapshot of the equilibration phase. In specific simulations, distance restraints were applied. These were implemented using the uwalls module in PLUMED283.

Free energy landscapes of carbohydrate units
The conformational free energy landscape (FEL) of the innermost GlcNAc subunit of the G0 acceptor and the fucose moiety from GDP-Fuc was computed for different models using collective variables derived from Cremer–Pople puckering89. coordinates. Specifically, Cartesian projection coordinates normalized by the puckering amplitude (Q) were employed:

CV1 = qx / Q (3)

CV2 = qy / Q (4)

CV3 = qz / Q (5)

In all cases, the reweighting of the puckering coordinates θ and ϕ was performed using PLUMED283.

The QM region consisted of the indicated number of atoms enclosed within an orthorhombic box of a × b × c Å³. Hydrogen atoms were added to cap the QM–MM boundaries (see Supplementary Fig. 14). Gaussian bias potentials were deposited every 60 fs with an initial height of 1.2 kcal/mol. The widths were set to 0.035, 0.030, and 0.020 collective variable units (c.v.u.) for CV1, CV2, and CV3, respectively. The simulation was extended until the free energy landscape (FEL) reached convergence.

Free energy landscapes of carbohydrates
A detailed summary of the QM/MM system setup, simulation parameters, and convergence times for all carbohydrate free energy landscape calculations is provided in Table 2.

Fucose: The region included the entire fucose moiety, the diphosphate group, and the CH₂ bridge linking the ribose ring to the diphosphate; the metadynamics free-energy reconstruction was terminated upon convergence at 225 ps (7500 deposited Gaussians).
AG0: The region comprised the innermost GlcNAc, along with atoms C1, C2, O5, and C5 of the adjacent sugar and their corresponding substituents.

• With restraints in OH3, the bias height was reduced to 0.6 kcal/mol after 300 ps (10,000 deposited Gaussians) to enhance sampling accuracy, and the simulation was extended by 50 ps with the lower bias (≈1667 additional Gaussians).
• In Michaelis complex, the bias height was reduced to 0.6 kcal/mol after 300 ps (10,000 deposited Gaussians) to enhance sampling accuracy, and the simulation was extended by 50 ps with the lower bias (≈1667 additional Gaussians).
• In the AtFUT11-G0-GDP complex, the metadynamics free-energy reconstruction was terminated upon convergence at 300 ps (10,000 deposited Gaussians).
• In the AtFUT11-G0 complex, the metadynamics free-energy reconstruction was terminated upon convergence at 225 ps (7500 deposited Gaussians).
• In the E158A mutant complex, the bias height was reduced to 0.6 kcal/mol after 300 ps (~10,000 deposited Gaussians) to enhance sampling accuracy, and the simulation was extended by 50 ps with the lower bias (≈1667 additional Gaussians).

Activation of the OH3 Group via Interaction with Glu158
The initial structure was a representative snapshot from one of the minima identified in the conformational free energy landscape of the innermost GlcNAc subunit (AG0b). The atoms included in the QM region correspond to those previously defined in the conformational free energy landscape studies of the same GlcNAc unit. Hydrogen atoms were added at the QM–MM boundaries for capping purposes. A plane-wave cutoff of 250 Ry was employed. Gaussian bias potentials were deposited every 100 MD steps. To improve precision, an initial bias height of 0.2 kcal/mol and a width of 0.2 were used. To restrict sampling to the subspace directly related to OH3 activation, we applied soft restraining walls (PLUMED uwalls).

The simulation was stopped once the free energy surface reached convergence, which occurred following a switch in the interaction pattern of the OH3 group. A total of 800 Gaussian functions were deposited, with a final simulation time of 40 ps. The MM environment consisted of a periodic orthorhombic box (75.5 × 123.0 × 92.5 Å³) containing 21,508 TIP3P water molecules and 2 Cl⁻ counterions.

Fucose transfer free energy surface
Simulations were initiated from a representative snapshot corresponding to the minimum identified in the AG0a puckering analysis, where the OH3 group interacts with the catalytic base. The study of the fucose transfer reaction was performed using a combination of two collective variables (CVs), both defined as differences between key interatomic distances.

CV1 describes the glycosyl transfer process and is defined as the difference between the distance from the anomeric carbon of fucose (C1) to the phosphate oxygen and the distance from C1 to the oxygen at position O3 (OH3 group) of the A subunit of G0, which acts as the nucleophile:

CV1 = d(C1-OP) - d(C1-O3) (6)

To restrict sampling to the subspace directly related to fucose transfer, we applied soft restraining walls (PLUMED uwalls), thus preventing deviations from the catalytic pose without imposing any bias along CV1 or CV2.

CV2 capture the proton transfer and is calculated as the difference between the distance from O3 to its bonded proton (OH3) and the distance between that same proton and the carboxylate oxygen of Glu158:

CV2 = d(O3-OH3) - d(OH3-COO-E158) (7)

The QM region included 115 atoms within an orthorhombic box of 21.3830 × 22.2040 × 21.7931 Å³. This region comprised the side chains of Arg226 and Lys281, the side chain of Glu158 (the catalytic base), the same GDP-Fuc atoms used in the conformational study of fucose, and the atoms from the G0 acceptor subunit included in the previous conformational analyses, excluding C2 and its substituents to reduce computational cost. The QM–MM boundaries were capped with hydrogen atoms (see Supplementary Fig. 14). The MM environment consisted of a periodic orthorhombic box (75.5 × 123.0 × 92.5 Å³) containing 21,508 TIP3P water molecules and 2 Cl⁻ counterions.

A plane-wave cutoff of 370 Ry was used. Gaussian bias potentials were deposited every 100 MD steps, with an initial height of 1.0 kcal/mol and a width of 0.2 (c.v.u.) for both CVs. To improve accuracy near the transition state (TS), the bias height was reduced to 0.1 kcal/mol. Following established recommendations90 the simulation was stopped after observing TS recrossing (Supplementary Fig. 15), yielding a total of 1280 deposited Gaussians over 64 ps. The free energy surface (FES) associated with the fucose transfer was reconstructed from the HILLS file generated during the metadynamics run, using the sum_hills utility in PLUMED283. The resulting surface was further analyzed using the MEPSAnd tool for topological characterization91, enabling precise identification of the CV coordinates corresponding to the key points along the reaction coordinate. The minimum free-energy path (MFEP), connecting the reactant (RE) and product (PR) states via the TS, was defined as the trajectory following the lowest free energy in the CV1–CV2 space. Evolution of key distances and puckering along the MFEP is given in Supplementary Figs. 16 and 17.

Representative structures along the MFEP were extracted from the full metadynamics trajectory using the CV coordinates as references. The transition state was confirmed by performing unbiased QM/MM molecular dynamics simulations starting from the TS structure and observing the relaxation of trajectories toward both the RE and PR.

Non-covalent interactions (NCI)
NCI (non-covalent interactions) were computed using the methodology previously described47. Semi-quantitative data were obtained with the NCIPLOT4 program48. A density cutoff of ρ = 0.5 a.u. was applied and isosurfaces of s(r)=0.32 were colored by sign(λ2)ρ in the [−0.03, 0.03] a.u. range using VMD 1.9 software92.

Electron localization function (ELF)
We used the gradient field of electron localization function (ELF) developed by Silvi and Savin49,50. The density.cube and elf.cube files were generated using the module implemented in CP2K (E_DENSITY_CUBE and ELF_CUBE). The obtained cube files for each point were processed with the Multiwfn 3.8 software93,94 to obtain the corresponding information on basins, attractors and population.

RE→TS→PR trajectories
To generate linking trajectories, we ran 20 independent unbiased QM/MM/MD simulations initiated from the TS structure, at the DFT level (PBE/GPW, TZV2P basis, GTH pseudopotentials). Each replica was propagated in the NVT ensemble at 300 K (timestep 0.5 fs). Initial velocities were sampled from a Maxwell–Boltzmann distribution; to ensure independence and reproducibility, distinct random seeds were provided via &GLOBAL SEED in CP2K. For every replica, we launched two runs: one with the assigned velocities and a second with velocity inversion (v → −v), yielding paired TS→RE and TS→PR connections. Each individual trajectory was run for 2 ps, and the paired paths were concatenated to construct a global RE→TS→PR trajectory of 4 ps. These trajectories were then used to estimate event lifetimes.

Kinetic analysis
Enzyme kinetics were assayed for AtFUT11. AtFUT11 was determined using the GDP-Glo assay (Promega) containing 100 nM enzyme in 25 mM Tris pH 7.5, 150 mM NaCl. To determine the Km for GDP-Fuc, the reaction contained 500 μM G0 acceptor and GDP-Fuc (2.5–500 μM). To measure the Km for G0, the reaction contained 500 μM GDP-Fuc and G0 (5 μM–1 mM). Reactions were incubated 30 min at 37 °C, then mixed 1:1 with GDP-Glo reagent (5 μL per well) in a white, opaque 384-well plate and incubated in the dark for 1 h at room temperature before measuring with a CLARIOstar (BMG Labtech). To estimate GDP produced, a GDP standard curve was used; values were background-corrected for GDP-Fuc hydrolysis. Data were fit to a nonlinear Michaelis–Menten model in GraphPad Prism 6, from which Km, kcat, and Vmax with standard errors were obtained. All experiments were performed in duplicate (n=2), following Promega’s recommendations.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript investigates the plant fucosyltransferase AtFUT11 using glycan microarrays, crystallography, enzymatic\nassays, and multiscale simulations. The enzyme is shown to adopt a GT-B fold with a distinctive N-terminal subdomain for\nG0 N-glycan anchoring, while tolerating β1,2-xylose and α1,6 modifications. A central finding is that the catalytic base\nGlu158 distorts the innermost GlcNAc, aligning it for nucleophilic attack and enabling an asynchronous mechanism with\ntransient oxocarbenium character. The work provides structural and mechanistic insights into plant-specific core fucosylation\nand its evolutionary parallels with mammalian FUTs.\nOverall, the manuscript offers interesting insights into these enzymes and their catalytic strategies. The mechanistic\ndiscussion of the borderline SN1/SN2 character of the reaction, and the appearance of a transient oxocarbenium ion, is\nparticularly relevant to the community. However, in my opinion, the paper requires a major revision before it can be\nconsidered for publication. As a computational chemist, I will limit my comments to the computational aspects of the work:\n1. One of the most interesting aspects of the manuscript is the proposed\nborderline SN1/SN2 mechanism with a transient oxocarbenium ion. I would have\nexpected a clearer introduction to this long-standing debate, with explicit\nreference to previous studies in the field.\n2. The conclusions regarding the mechanistic character may depend on the level\nof theory employed. The authors should demonstrate the robustness of their\nresults and to what extent they might change with different levels of theory.\n3. A substantial part of the work relies on the analysis of reactive trajectories, but\nvery few details are provided on how these were generated. How were the\nstarting points selected? How was statistical independence ensured? How were\ninitial velocities assigned, and how were trajectories propagated in both\ndirections, R and P? Under what conditions were these simulations carried out?\nThis information is essential for assessing the reliability of the results.\n4. It is also important to provide the structural evolution of key distances\nassociated with bond formation and cleavage during the reactive trajectories.\nSuch structural information must also include torsional angles describing\nplanarity around the anomeric carbon. This would complement the electronic\nanalysis and help clarify the nature of the transient species along the reaction\npath.\n5. Another point concerns the conformational states of the reactants. The authors\ndistinguish between a Michaelis complex and a reactive state and they show their\nfree energy difference in the Supplementary Material (about 5 kcal/mol). It is\nunclear if the activation free energy reported in the manuscript (16 kcal/mol)\nincludes or not that contribution.\n6. The terminology “hidden intermediate” does not seem ideal. The designation\n“transient species,” which the authors themselves use in parts of the text,\nwould be more appropriate and less ambiguous.\n7. The use of the term “Minimum Energy Path” to describe a pathway on the free\nenergy surface (for example in Figure 6) is confusing. The authors should clarify\nwhether they computed a true minimum energy path on the potential energy\nsurface, or a minimum free energy path.\n8. Finally, data accessibility is an issue. It was not possible to retrieve the\nsimulation data from the DOI provided\n(https://doi.org/10.5281/zenodo.16733350) at the time of review. This must be\ncorrected to ensure transparency and reproducibility.\nIn summary, the manuscript contains important results and has the potential to\nmake an important contribution to the field. Nevertheless, the issues outlined\nabove should be addressed through a careful revision before the paper can be\naccepted.", "reviewer_2": "This manuscript presents a comprehensive and multidisciplinary investigation into the structure and catalytic mechanism of\nArabidopsis thaliana FUT11, a core α1,3-fucosyltransferase. The authors combine glycan microarray profiling, X-ray\ncrystallography, mutagenesis, cellular assays, and advanced computational simulations to provide a detailed mechanistic\npicture of this plant-specific glycosyltransferase. The work is well-executed and the findings are of broad interest to the\nglycobiology community, particularly in understanding how glycosyltransferases achieve substrate specificity and catalysis.\nHowever, major and minor comments would need to be addressed to improve the quality of the manuscript.\nMajor comments:\n1. While the MD simulations suggest that Glu158 induces conformational distortion in the acceptor GlcNAc, the experimental\nelectron density for this GlcNAc is described as \"partially defined\". Additional experimental validation (e.g., via NMR or\nalternative crystal forms) would strengthen this claim.\n2. AtFUT11 exhibited low activity in catalyzing Lewisx synthesis in vitro. Is there any potential physiological relevance of this\nactivity? The authors should briefly discuss about it.\nMinor comments:\nProvide brief descriptive legends for Supplementary Movies 1 and 2 in the main text or figure legends.", "reviewer_3": "This study is focused on a unique enzyme from the commonly studied plant Arabidopsis thaliana. The enzyme is FUT11\nwhich adds fucose residues in α1,3-linkage to N-acetylglucosamine (GlcNAc) residues within the chitobiose core of\nasparagine-linked (N-glycans) of the plants glycoproteins. The enzyme represents a type of unique activity common in\nplants and many insects, but not in vertebrates. The detailed catalytic mechanisms have not been defined for this type of\nenzyme. Often glycans with this fucose linkage also have a xylose residues in β1,2 linkage to mannose (Man) residues.\nHere the authors utilized a recombinant enzyme, multiple glycan acceptors with or without xylose and other extensions, a\ncrystal structure of AtFUT11 bound to GDP and an N-glycan precursor/acceptor (G0), unusual GT-B architecture for the\nenzyme, and identified an asynchronous SN2-like mechanism for fucose addition that is accompanied by distortion of the\nglycan structure to position the acceptor GlcNAc for modification. Overall, the study is interesting and insightful about this\nunusual type of fucosylation in plants and in other organisms. The key insights in this work that may be of general interest is\nthe evidence that the enzyme restructures or distorts the acceptor for functioning, rather than passively binding, and provide\ninsights into novel catalytic strategies for glycosylating enzymes. While relatively limited in scope with a focus on a single\nenzyme, this study is very well done, and well presented, and represents a nice step ahead for understanding the catalytic\nfunctions and activities of these novel core α1,3-fucosyltransferases. k\n• It is not a massively critical issue, but having the recombinant enzyme would allow kinetic studies beyond just the overall\nand relatively superficial screening performed using microarrays. This could be insightful, as in that case the glycans would\nbe in solution and not immobilized on a surface. The authors should provide some basic kinetic information for a few of the\nbest acceptor substrates and the GDP-Fuc donor (Km, Vmax) in their study to further enhance the mechanistic insights. This\ntype of information is useful in modeling within systems biology approaches and predictive nature of glycosylation. I nature\nthis enzyme is competitive with many other enzymes.\n• The differential activity of FUT11 on different acceptors in Fig. 1 might be related to their unavailable or structural\nlimitations because of the covalent attachment to the glad slides.\n• In earlier related studies on these types of enzymes in C. elegans, there was evidence for such enzymes (CEFT1 and\nCEFT2) generating the core fucosylation as well as the Lewis x antigen, using different types of acceptors, similar in\nsomewhat to what has been found here for A. thaliana FUT11. (DOI: 10.1093/glycob/cwm023).\n• The recombinant enzyme was expressed in mammalian cells, and the glycosylation of the enzyme itself in such cells,\nmight be abnormal compared to the natural glycosylation in plants. There are several predicted sites of N-glycosylation in\nFUT11/12, based on Supplementary Fig. 4Do the authors have any evidence that ‘differential’ glycosylation might affect the\noutcome of their experiments?"}, "author_response": "Response: Thank you very much for your positive comments.\n1. One of the most interesting aspects of the manuscript is the proposed\nborderline SN1/SN2 mechanism with a transient oxocarbenium ion. I would have\nexpected a clearer introduction to this long-standing debate, with explicit\nreference to previous studies in the field.\nResponse: We have added in the introduction some comments on this debate\nand representative bibliography.\n2. The conclusions regarding the mechanistic character may depend on the level\nof theory employed. The authors should demonstrate the robustness of their\nresults and to what extent they might change with different levels of theory.\nResponse: The level of theory employed in this work can be placed on the second\nrung of Jacob’s ladder, which provides an excellent balance between\ncomputational cost and reliability, a crucial aspect for metadynamics studies (see\nMetadynamics A. Barducci, M. Bonomi, M. Parrinello WIREs Comput. Mol. Sci.\n2011, 1, 826). Higher levels of theory would indeed be expected to improve the\nquantitative agreement to some extent; however, they would also lead to a\nprohibitive increase in computational time, making such calculations unfeasible\nfor the present study. The chosen level of theory has been extensively validated\nin previous works addressing metadynamics studies of enzymatic reactivity (ACS\nCatal. 11, 9926 (2021), https://doi.org/10.1021/acscatal.1c01785; JACS. 146,\n11234 (2024), https://doi.org/10.1021/jacs.4c11677; Nat. Commun. 16, 2670\n(2025), https://doi.org/10.1038/s41467-025-56754-5; JACS 147, 23594 (2025),\nhttps://doi.org/10.1021/jacs.5c03557; Angew. Chem. Int. Ed. 63, e202404193\n(2024), https://doi.org/10.1002/anie.202411171). The robustness of our results is\nalso supported by the dynamical simulations initiated from the transition state\nobtained through metadynamics, which confirm that this transition state indeed\nconnects the reactant and the product identified in our calculations. Finally, our\nmechanistic assignment relies not only on absolute free-energy values but also\non structural/dynamical observables (ELF analysis, evolution of key bond\ndistances, etc), which are less sensitive to moderate changes in the exchange–\ncorrelation functional. Accordingly, we consider PBE to provide an appropriate\nbalance between accuracy and efficiency, enabling reliable qualitative\nmechanistic inferences in systems of this complexity.\n3. A substantial part of the work relies on the analysis of reactive trajectories, but\nvery few details are provided on how these were generated. How were the\nstarting points selected? How was statistical independence ensured? How were\ninitial velocities assigned, and how were trajectories propagated in both\ndirections, R and P? Under what conditions were these simulations carried out?\nThis information is essential for assessing the reliability of the results.\nResponse: We have dedicated a subsection in Methods (“RE→TS→PR\ntrajectories”) detailing how the trajectories were generated.\nStarting points: All trajectories were initiated from the transition state (TS)\nidentified on the fucose-transfer free energy surface (FES) validated by unbiased\nrelaxation runs connecting both reactant (RE) and product (PR) basins\n(committor analysis)\n(DOI: 10.1146/annurev.physchem.53.082301.113146)\nStatistical independence: We performed 20 independent replicas, each\ninitialized with a distinct random seed specified via &GLOBAL SEED in CP2K.\nInitial velocities and bidirectional propagation: Initial velocities were\ngenerated from a Maxwell–Boltzmann distribution at 300 K. For each replica, two\nruns were launched, one with the assigned velocities and another with velocity\ninversion (v → −v), yielding paired TS→RE and TS→PR connections.\nSimulation conditions: All trajectories were unbiased QM/MM/MD runs in the\nNVT ensemble (300 K, 0.5 fs timestep), using DFT (PBE/GPW, TZV2P basis,\nGTH pseudopotentials) for the QM region and the same MM setup as in the\nclassical MD simulations. Each individual trajectory was propagated for 2 ps, and\nthe paired paths were concatenated to produce a full RE→TS→PR trajectory of\n4 ps per replica, which was used to estimate event lifetimes.\n4. It is also important to provide the structural evolution of key distances\nassociated with bond formation and cleavage during the reactive trajectories.\nSuch structural information must also include torsional angles describing\nplanarity around the anomeric carbon. This would complement the electronic\nanalysis and help clarify the nature of the transient species along the reaction\npath.\nResponse: In the revised version, we have added a new Supplementary Figure\n(Supplementary Fig. 13a) showing the time evolution of all key distances along\nthe reactive trajectories (RE→TS→PR), namely d , d , d , and d .\n1 2 3 4\nRegarding planarity around the anomeric carbon (C1), we fully agree that\ntorsional descriptors provide valuable structural insight. However, as noted in the\nmain text, the amplitude of C–H vibration makes it difficult to pinpoint the exact\nonset and decay of planarity.\nTo address this, we now include in the Supplementary Information:\n(i) the C1–O5 bond-length trace, which indirectly supports oxocarbenium-like\ncharacter via the transient shortening distance of this bond (Supplementary Fig.\n13b); and (ii) the distance from C1 to the plane defined by O5–H–C2, which,\ndespite the higher noise associated with H vibrations, still shows a clear\nplanarization trend of the fucose unit (Supplementary Fig. 13c).\nTogether, these structural readouts complement the ELF analysis and reinforce\na concerted yet highly asynchronous pathway with transient cationic character.\n5. Another point concerns the conformational states of the reactants. The authors\ndistinguish between a Michaelis complex and a reactive state and they show their\nfree energy difference in the Supplementary Material (about 5 kcal/mol). It is\nunclear if the activation free energy reported in the manuscript (16 kcal/mol)\nincludes or not that contribution.\nResponse: The reported activation energy (16 kcal·mol⁻¹) corresponds to the\nreaction proceeding from the reactive form of the Michaelis complex (RE),\nin which the hydroxyl group (OH3) forms a hydrogen bond with the catalytic base\nGlu158. This configuration represents the starting point of the reaction, as the\ninteraction between the atom that performs the nucleophilic attack and the\ncatalytic base is essential for facilitating the attack.\nTo reach this state, the puckering of the carbohydrate was investigated through\nunbiased metadynamics simulations (Figure S8), which revealed that OH3\ninitially forms a hydrogen bond with the pyrophosphate group. To establish a\nsuitable reactive conformation, the rotation of OH3 was examined to enable the\ntransition from the hydrogen bond with the pyrophosphate to that with the\ncatalytic base (Figure S10), a process associated with an energy cost of\napproximately 2.5 kcal/mol. Once this hydrogen bond, required for the initiation\nof the reaction, was established, a subsequent metadynamics analysis of the\ncarbohydrate puckering (Figure 5b in the manuscript) yielded the most\nappropriate structure (RE) for launching the metadynamics simulation of the\nreaction using the corresponding collective variables.\nTo clarify these processes, Figure S12 has been updated to depict the complete\ncatalytic cycle together with the associated energy profile.\n6. The terminology “hidden intermediate” does not seem ideal. The designation\n“transient species,” which the authors themselves use in parts of the text,\nwould be more appropriate and less ambiguous.\nResponse: we fully agree and we used “transient” in all places, including title\n7. The use of the term “Minimum Energy Path” to describe a pathway on the free\nenergy surface (for example in Figure 6) is confusing. The authors should clarify\nwhether they computed a true minimum energy path on the potential energy\nsurface, or a minimum free energy path.\nResponse: We appreciate the clarification request. In our work, the path shown\nin Fig. 6 is the minimum free-energy path (MFEP) on the metadynamics-\nreconstructed free-energy surface (FES), expressed in the CV1–CV2 space for\nfucose transfer, not a minimum-energy path on the potential energy surface. The\nMFEP was obtained with MEPS and by following the lowest-free-energy route\nconnecting RE→TS→PR on the FES. To avoid confusion, we will (i) replace\n“MEP” with “MFEP” throughout the manuscript, (ii) state explicitly in Methods and\nin the Fig. 6 caption that the path is computed on the FES in CV space. These\nwording adjustments do not affect the results or conclusions.\n8. Finally, data accessibility is an issue. It was not possible to retrieve the\nsimulation data from the DOI provided\n(https://doi.org/10.5281/zenodo.16733350) at the time of review. This must be\ncorrected to ensure transparency and reproducibility.\nResponse: We appreciate the reviewer’s observation. The simulation data are\nnow freely accessible for review and verification at the following DOI:\nhttps://doi.org/10.5281/zenodo.17558724.\nIn summary, the manuscript contains important results and has the potential to\nmake an important contribution to the field. Nevertheless, the issues outlined\nabove should be addressed through a careful revision before the paper can be\naccepted.\nResponse: Thank you very much for your positive comments.\nReviewer #2 (Remarks to the Author):\nThis manuscript presents a comprehensive and multidisciplinary investigation\ninto the structure and catalytic mechanism of Arabidopsis thaliana FUT11, a core\nα1,3-fucosyltransferase. The authors combine glycan microarray profiling, X-ray\ncrystallography, mutagenesis, cellular assays, and advanced computational\nsimulations to provide a detailed mechanistic picture of this plant-specific\nglycosyltransferase. The work is well-executed and the findings are of broad\ninterest to the glycobiology community, particularly in understanding how\nglycosyltransferases achieve substrate specificity and catalysis. However, major\nand minor comments would need to be addressed to improve the quality of the\nmanuscript.\nResponse: Thank you very much for your positive comments.\nMajor comments:\n1. While the MD simulations suggest that Glu158 induces conformational\ndistortion in the acceptor GlcNAc, the experimental electron density for this\nGlcNAc is described as \"partially defined\". Additional experimental validation\n(e.g., via NMR or alternative crystal forms) would strengthen this claim.\nResponse:\nWe performed NOESY and transferred-NOESY experiments on the glycan free\nand bound to AtFUT11 across a range of mixing times. We did not observe\nchanges in NOE patterns between conditions, nor cross-peaks consistent with a\ndistinct populated ring pucker in the bound state. This is expected if the distorted\nconformer is short-lived and interconverts rapidly with the chair, because NMR\nreports ensemble-averaged observables; a minor state would only be visible if it\npersisted on the millisecond timescale. We also attempted alternative\ncrystallization conditions but obtained the same lattice. Together, these data\nneither prove nor refute a persistent distorted conformer. Accordingly, we have\ntempered our language throughout to emphasize that our simulations are\ncompatible with, rather than conclusively demonstrating, enzyme-promoted\nacceptor distortion, and we frame the mechanistic model as a plausible\nasynchronous SN1/SN2-borderline pathway.\n2. AtFUT11 exhibited low activity in catalyzing Lewisx synthesis in vitro. Is there\nany potential physiological relevance of this activity? The authors should briefly\ndiscuss about it.\nResponse: We thank the reviewer for the insightful comment regarding the low in\nvitro activity of AtFUT11 in catalyzing Lewisx synthesis and its potential\nphysiological relevance. While AtFUT11 exhibits this activity in vitro, current\nevidence indicates that this reaction likely does not have a significant\nphysiological role in Arabidopsis as it lacks the B4GALT1 gene and it does not\nnaturally produce N-glycans with terminal N-acetyllactosamine (LacNAc)\nepitopes, which serve as substrates for Lewisx formation. Consequently, there\nare no reports describing the presence of Lewisx epitopes in natural A. thaliana\nN-glycans (doi:10.1074/mcp.RA117.000165). The observed activity appears to\nreflect catalytic flexibility and enzyme promiscuity rather than a biologically\nmeaningful function. We have expanded this into the Results and Discussion\nsection to address this point with relevant literature references.\nMinor comments:\nProvide brief descriptive legends for Supplementary Movies 1 and 2 in the main\ntext or figure legends.\nResponse: We have moved the movies to the repository and we have included\nthe corresponding explanation for each Figure.\nReviewer #3 (Remarks to the Author):\nThis study is focused on a unique enzyme from the commonly studied plant\nArabidopsis thaliana. The enzyme is FUT11 which adds fucose residues in α1,3-\nlinkage to N-acetylglucosamine (GlcNAc) residues within the chitobiose core of\nasparagine-linked (N-glycans) of the plants glycoproteins. The enzyme\nrepresents a type of unique activity common in plants and many insects, but not\nin vertebrates. The detailed catalytic mechanisms have not been defined for this\ntype of enzyme. Often glycans with this fucose linkage also have a xylose\nresidues in β1,2 linkage to mannose (Man) residues. Here the authors utilized a\nrecombinant enzyme, multiple glycan acceptors with or without xylose and other\nextensions, a crystal structure of AtFUT11 bound to GDP and an N-glycan\nprecursor/acceptor (G0), unusual GT-B architecture for the enzyme, and\nidentified an asynchronous SN2-like mechanism for fucose addition that is\naccompanied by distortion of the glycan structure to position the acceptor GlcNAc\nfor modification. Overall, the study is interesting and insightful about this unusual\ntype of fucosylation in plants and in other organisms. The key insights in this work\nthat may be of general interest is the evidence that the enzyme restructures or\ndistorts the acceptor for functioning, rather than passively binding, and provide\ninsights into novel catalytic strategies for glycosylating enzymes. While relatively\nlimited in scope with a focus on a single enzyme, this study is very well done, and\nwell presented, and represents a nice step ahead for understanding the catalytic\nfunctions and activities of these novel core α1,3-fucosyltransferases.\nResponse: Thank you very much for your positive comments.\n• It is not a massively critical issue, but having the recombinant enzyme would\nallow kinetic studies beyond just the overall and relatively superficial screening\nperformed using microarrays. This could be insightful, as in that case the glycans\nwould be in solution and not immobilized on a surface. The authors should\nprovide some basic kinetic information for a few of the best acceptor substrates\nand the GDP-Fuc donor (Km, Vmax) in their study to further enhance the\nmechanistic insights. This type of information is useful in modeling within systems\nbiology approaches and predictive nature of glycosylation. I nature this enzyme\nis competitive with many other enzymes.\nResponse: We thank the reviewer for this constructive suggestion. In the revised\nmanuscript we now include steady-state kinetics for AtFUT11 with the GDP-Fuc\ndonor and the G0 acceptor, reporting 𝐾 , 𝑘 , and 𝑘 /𝐾 values obtained from\n! \"#$ \"#$ !\nnonlinear Michaelis–Menten fits (Supplementary Fig. 1b). These data\ncomplement the microarray results, confirm hyperbolic behavior, and place\nAtFUT11’s catalytic efficiency in a range comparable to benchmark mammalian\nfucosyltransferases under matched donor/acceptor conditions. Unfortunately, we\nare unable to provide data with other acceptors. We currently only have enough\nmaterials to perform microarray-based analysis, which provides a miniaturized\nassay, but not enough for solution-based measurements and the de novo\nsynthesis of these complex structures would require a significant synthetic effort.\n• The differential activity of FUT11 on different acceptors in Fig. 1 might be related\nto their unavailable or structural limitations because of the covalent attachment\nto the glad slides.\nResponse: On glycan microarrays, only picomol amounts of the glycans are\nimmobilized in the individual spots and during the enzymatic reactions,\ncomparatively high excess of enzyme and donor concentrations (µM) are used.\nTherefore, substrate accessibility, rather than catalytic turnover, primarily limits\nthe reaction rate. We always prepare glycan microarrays on Nexterion slide H\nslides, that are coated with a 3D hydrogel that offers enhanced accessibility to\nthe immobilized carbohydrates, compared to other 2D based surfaces.\nAdditionally, our previous experimental results allow us to be confident that the\nmicroarray-based enzymatic activity screening is a reliable technique perform a\nsubstrate specificity screening. In our prior research, utilising FUT11 expressed\nin Pichia pastoris (J Am Chem Soc 133, 16495–502 (2011)\nhttps://doi.org/10.1021/ja205392z) with a smaller N-glycan microarray, we could\ndemonstrate a strong correlation between reactivity on the solid support and in\nsolution. Furthermore, FUT8 microarray-based screening published by us in Nat\nCommun 11, 973 (2020). https://doi.org/10.1038/s41467-020-14794-z, was\ncompletely correlated with the substrate specificity described in solution in a later\npublication (Journal of Biological Chemistry, Volume 295, Issue 50, 17027 –\n17045 DOI: 10.1074/jbc.RA120.014625).\n• In earlier related studies on these types of enzymes in C. elegans, there was\nevidence for such enzymes (CEFT1 and CEFT2) generating the core fucosylation\nas well as the Lewis x antigen, using different types of acceptors, similar in\nsomewhat to what has been found here for A. thaliana FUT11. (DOI:\n10.1093/glycob/cwm023).\nResponse: Thank you for this comment. The reviewer is correct regarding\nCEFT1, as this enzyme indeed core-fucosylates using a different acceptor and,\nin a very minor proportion, synthesizes the Lewis x antigen in C. elegans, similar\nto what we observed for A. thaliana FUT11. However, CEFT2 does not core-\nfucosylate according to the available literature—instead, it primarily fucosylates\nLacdiNAc-containing structures and exhibits distinct specificity [Nguyen et al.,\nGlycobiology, 2007, doi:10.1093/glycob/cwm023]. We have clarified this in the\nResults and Discussion section and added an appropriate reference.\n• The recombinant enzyme was expressed in mammalian cells, and the\nglycosylation of the enzyme itself in such cells, might be abnormal compared to\nthe natural glycosylation in plants. There are several predicted sites of N-\nglycosylation in FUT11/12, based on Supplementary Fig. 4Do the authors have\nany evidence that ‘differential’ glycosylation might affect the outcome of their\nexperiments?\nResponse: We agree that recombinant expression in mammalian cells introduces\nmammalian-type N-glycans on AtFUT11. To address whether this could bias our\nresults, we have mapped the three predicted N-glycosylation sequons present in\nour construct (N337, N420, N481; Supplementary Fig.1) onto the AtFUT11\nstructure. All three sites are on solvent-exposed surfaces remote from the\ndonor/acceptor subsites and do not contact the loops that shape the active site.\nThus, while we cannot exclude generic effects on folding or stability, differential\nN-glycosylation of the enzyme itself is unlikely to influence the fucosyltransferase\nproperties measured here (substrate recognition, turnover trends, or the\nmechanistic features we report). We have noted this point in Results and\nDiscussion (“Substrate specificity of AtFUT11 revealed by glycan microarray\nprofiling”)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "In the revised version, the authors have substantially improved the manuscript and have satisfactorily addressed most of the\nissues raised in my previous report. Nevertheless, two important points remain insufficiently clarified and, in my view, require\nfurther consideration before the paper can be accepted.\n1. In my previous report, I emphasized the importance of demonstrating the robustness of the mechanistic conclusions with\nrespect to the chosen level of theory. While PBE has indeed been widely used to study enzymatic systems, the central\nquestion here is not the general validity of this functional but to what extent the identification of a carbocation-like\nintermediate might depend on the functional employed. In particular, PBE is known in some cases to over-stabilize\ndissociative pathways, which raises the legitimate concern of whether the transient carbocation observed could be, at least\npartially, a functional-dependent artifact. This specific point has not been fully addressed. The authors should explicitly\ndiscuss how the mechanistic picture—especially the presence and stability of the putative carbocation intermediate—\nmight change when using alternative functionals, and provide evidence or arguments supporting the robustness of their\nconclusions against such methodological choices.\n2. The revised manuscript states that “The calculated activation barrier was ~16.0 kcal/mol, in agreement with values\nreported for other fucosyltransferases, and it is also consistent with our experimental results.” However, the value reported\ncorresponds to the barrier measured from the “reactive state,” which is energetically higher than the Michaelis complex.\nTo enable a meaningful comparison with the experimentally derived activation free energy for the chemical step, the relevant\nquantity is the free-energy difference between the TS and the Michaelis complex. Consequently, the energy cost required to\nreach the reactive conformation must be included in the reported activation barrier. This clarification is essential to ensure a\nvalid comparison with experiment.", "reviewer_2": "All my concerns with the previous submission are addressed in this version.\nHowever, I have another concern regarding the crystallography data. The completeness in the outer shell is 78.7%, which\nfalls below the commonly accepted threshold for reliable data. To ensure the robustness of the structural model, I\nrecommend that the authors reprocess the diffraction data to achieve an outer-shell completeness of at least 80%.\nFigure 2b is somewhat unclear because the sugar unit A (GlcNAc) is depicted in two different orientations. To improve\nclarity, I recommend that the authors: 1) Clearly label the two orientations to illustrate their spatial relationship. 2) Consider\nhighlighting the panel that focuses solely on sugar unit A (GlcNAc) with a black dashed box."}, "author_response": "Reviewer #1\nReviewer comment: In my previous report, I emphasized the importance of\ndemonstrating the robustness of the mechanistic conclusions with respect to the chosen\nlevel of theory. While PBE has indeed been widely used to study enzymatic systems,\nthe central question here is not the general validity of this functional but to what extent\nthe identification of a carbocation-like intermediate might depend on the functional\nemployed. In particular, PBE is known in some cases to over-stabilize dissociative\npathways, which raises the legitimate concern of whether the transient carbocation\nobserved could be, at least partially, a functional-dependent artifact. This specific point\nhas not been fully addressed. The authors should explicitly discuss how the mechanistic\npicture—especially the presence and stability of the putative carbocation intermediate—\nmight change when using alternative functionals, and provide evidence or arguments\nsupporting the robustness of their conclusions against such methodological choices.\nResponse:\nWe thank the reviewer for raising this important point. We fully agree that the\nidentification of transient carbocation-like species should be carefully examined with\nrespect to the chosen level of theory.\nOur mechanistic picture is qualitative in nature, since we do not perform a conventional\nlocation and characterization of well-defined stationary points. Instead, we analyze the\ntopology of the free-energy surface obtained from metadynamics simulations. From these\ndata, free-energy minima and maxima are inferred and associated with the singular points\nof the reaction (reactant, transition state, and, if present, intermediates). Importantly, we\ndo not claim the existence of a “carbocation intermediate” in the strict IUPAC sense,\nwhich would require a true local minimum on the potential-energy surface. Rather, we\nrefer to a transient, short-lived, post-transition-state oxocarbenium-like configuration that\ndoes not become stabilized as an energy minimum, but nevertheless has a finite lifetime\nalong the reaction coordinate. The “intermediate” discussed in our work should therefore\nbe understood in this dynamic sense, not as a well-separated thermodynamic species.\nThe use of different exchange–correlation functionals could indeed affect the lifetime of\nthis transient species (though not its “stability,” since it is not a stationary point). This\ncould, in principle, lead to different minimum-energy trajectories analogous to distinct\nIRC-like paths. In our work, this issue is addressed through the application of ELF\nanalysis to a statistically significant ensemble of independent molecular-dynamics\ntrajectories, whose reliability increases with the number of sampled trajectories. The\nobservation of very similar bonding patterns in all trajectories, differing only in the\ntemporal duration of the oxocarbenium-like configuration, and always displaying its\npresence, strongly supports the robustness of our mechanistic interpretation. If the\nmechanistic picture were an artifact of the functional, some trajectories would evolve\ntoward a clearly stabilized carbocation minimum (if favored by the functional) or toward\na purely SN2-like pathway. This is not what we observe. Instead, all trajectories\nconsistently fall within the same SN1–SN2 continuum, supporting the reliability of the\ncomputational approach.\nThe use of more expensive hybrid or meta-GGA functionals is not computationally\nfeasible for a metadynamics study of this size due to the prohibitive computational cost.\nNevertheless, for smaller model systems, where higher-level functionals have been\nemployed, very similar mechanistic features have been reported. This indicates that, for\nthe present problem, PBE reproduces the relevant features of the free-energy surface in a\nreliable way. For instance, results consistent with our findings were obtained in a study\ninvolving one of the present authors (PMID: 32579343; see also the SI of that article). In\naddition, a review by one of the authors reports multiple closely related cases studied with\nhigher-level functionals that lead to conclusions fully consistent with those obtained here\nusing PBE (PMID: 33481977).\nMore specifically:\n(i) Multiple QM/MM studies of retaining and inverting glycosyltransferases\n(e.g., LgtC, GalNAcT2, O-fucosyltransferases, OGT) using both GGA\nfunctionals (PBE, BLYP) and hybrid/meta-GGA functionals (B3LYP, PBE0,\nM06-2X) consistently report an SN1–SN2 continuum with oxocarbenium-like\ncharacter in the transition-state region, sometimes accompanied by very\nshallow post-TS minima. These results demonstrate that the appearance of\nsuch cation-like configurations is not an artifact of a specific functional, even\nthough barrier heights may vary by a few kcal·mol⁻¹ (PMID: 26862188,\n22352786, 26415846, 25849117, 34868727). In addition, a recent QM/MM\nstudy on PoFUT2 (PMID: 36260536) supports a more classical inverting\nSN2-like pathway, underscoring that the position along the SN1–SN2\ncontinuum is enzyme-dependent.\n(ii) Benchmark studies on glycosidic hydrolysis and carbohydrate conformations\nindicate that going from GGA to hybrid/meta-GGA functionals typically\nchanges relative barriers by only ≈1–3 kcal·mol⁻¹ and does not qualitatively\nalter the concerted vs. stepwise nature of the mechanism, nor does it eliminate\nvery shallow ion-pair or glycosyl-cation wells when present (Int. J. Quantum\nChem. 2017, 117, e25409). These results support that the presence of a\nshallow post-TS shoulder such as the one observed here is robust with respect\nto reasonable changes in the functional.\nReviewer comment:\nThe revised manuscript states that “The calculated activation barrier was ~16.0 kcal/mol,\nin agreement with values reported for other fucosyltransferases, and it is also consistent\nwith our experimental results.” However, the value reported corresponds to the barrier\nmeasured from the “reactive state,” which is energetically higher than the Michaelis\ncomplex. To enable a meaningful comparison with the experimentally derived activation\nfree energy for the chemical step, the relevant quantity is the free-energy difference\nbetween the TS and the Michaelis complex. Consequently, the energy cost required to\nreach the reactive conformation must be included in the reported activation barrier. This\nclarification is essential to ensure a valid comparison with experiment.\nResponse:\nYes, we fully agree. If we consider the full step from the Michaelis complex we should\ninclude the cost of rising the reactive state. We are under the conditions showed in the\nscheme:\nUnder these conditions the Michaelis complex and the reactive state are in equilibrium\nand the barrier for the full process is the difference between the transition state and the\nMichaelis complex 18.5 kcal/mol\nThe revised sentence now reads (indicative wording):\n\"The calculated activation barrier from the reactive state to the transition state is ~16.0\nkcal·mol⁻¹ (Fig. 6b), and when the ~2.5 kcal·mol⁻¹ required to reach the reactive\nconformation from the Michaelis complex is included, the overall barrier from the\nMichaelis complex amounts to ~18.5 kcal·mol⁻¹. This value falls within the 17–20\nkcal·mol⁻¹ range reported for inverting fucosyltransferases (PMID: 36260536 and\n34868727) and is consistent with the activation free energies inferred from our kinetic\nmeasurements.\"\nWe believe this addresses the reviewer's concern and improves the clarity of the\ncomparison between computation and experiment.\nReviewer #2\nReviewer comment:\nThe completeness in the outer shell is 78.7%, which falls below the commonly accepted\nthreshold for reliable data. To ensure the robustness of the structural model, I recommend\nthat the authors reprocess the diffraction data to achieve an outer-shell completeness of\nat least 80%.\nResponse:\nWe appreciate the reviewer’s careful examination of the crystallographic statistics. In the\ncurrent data processing, the reported outer-shell completeness (1.40–1.46 Å) is 78.7%,\nwith overall completeness of 93.6%, a CC1/2 of 0.619, and acceptable refinement\nstatistics (Rwork/Rfree) and geometry (Table 1).\nWe agree that data quality in the highest-resolution shell is important, but we note that\ncurrent crystallographic best practice emphasizes CC1/2 and related correlation-based\nmetrics, rather than a strict completeness cut-off, when deciding on the resolution limit.\nKarplus & Diederichs and Evans & Murshudov showed that weak but correlated high-\nresolution data can still improve maps and models, and that CC1/2 provides a statistically\nsound criterion for selecting a resolution cutoff, even when outer-shell completeness is\nbelow 80% (Karplus & Diederichs, 2012; Evans, 2011; Evans & Murshudov, 2013).\nThese studies also emphasize that including such data “may make some improvement and\ndoes no harm” provided CC1/2 remains significant (Evans & Murshudov, 2013).\nNevertheless, to align with the reviewer’s request and to adopt a more conservative\nstatistics set, we have slightly relaxed the nominal high-resolution cutoff used for\nrefinement and map calculation.\nSpecifically:\n• We re-examined the scaling statistics as a function of resolution, and\n• Set the new high-resolution cutoff at a slightly lower resolution (1.41 Å instead of\n1.40 Å), where the outer-shell completeness exceeds 80% while CC1/2 and I/σ(I) remain\nwithin recommended ranges (Evans, 2011; Evans & Murshudov, 2013).\nWe then re-refined the structure at this updated resolution and regenerated the maps. The\nmodel coordinates and overall Rwork/Rfree values change only marginally, and all key\nstructural features—including the active site and the acceptor glycan—are unaffected.\nTable 1 has been updated to report the new outer-shell statistics. This addresses the\nreviewer’s concern without requiring additional experiments or new diffraction data\ncollection.\nFull citations:\n• Karplus, P. A. & Diederichs, K. Linking crystallographic model and data\nquality. Science 336, 1030–1033 (2012).\n• Evans, P. R. An introduction to data reduction: space-group determination,\nscaling and intensity statistics. Acta Crystallogr. D Biol. Crystallogr. 67, 282–\n292 (2011).\n• Evans, P. R. & Murshudov, G. N. How good are my data and what is the\nresolution? Acta Crystallogr. D Biol. Crystallogr. 69, 1204–1214 (2013).\nReviewer comment:\nFigure 2b is somewhat unclear because the sugar unit A (GlcNAc) is depicted in two\ndifferent orientations. To improve clarity, I recommend that the authors: 1) Clearly label\nthe two orientations to illustrate their spatial relationship. 2) Consider highlighting\nthe panel that focuses solely on sugar unit A (GlcNAc) with a black dashed box.\nResponse:\nWe thank the reviewer for this helpful suggestion and agree that the previous version of\nFig. 2b could be confusing. In the revised figure, we have made it explicit that both\nrepresentations correspond to the same GlcNAc residue (sugar unit A) but from two\nviewing orientations. The close-up of GlcNAc A is now highlighted with a black dashed\nbox to guide the reader’s eye, and the legend has been updated to state that the boxed\npanel is a zoomed, alternative viewing orientation of sugar unit A to better illustrate the\nelectron density."}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed the points raised in my previous report. In my opinion, the paper can be accepted\nin its present form.", "reviewer_2": "All my concerns with the previous submission are addressed in this version."}, "author_response": ""}]

Decision letter