An scFv gene containing a short linker (RADAA) and the Leu 103H Val mutation (17), with a His₆ tag, was assembled by PCR and cloned into the phagemid pSK4. The construct was maintained in Escherichia coli TG1 cells. Cells from positive clones, as judged by DNA sequence analysis, were grown in minimal media, induced, and subjected to periplasmic extraction. The scFv dimer was purified from the extract by Ni²⁺ immobilized metal affinity chromatography, by elution with an imidazole gradient.

Affinity measurements were performed on a biolayer interferometer (Octet Red96, ForteBio). Data were processed using the Data Acquisition and Analysis 8.0 software (ForteBio), and kinetic binding constants were determined from a 1:1 binding model using the OriginPro software (OriginLab). The scFv was immobilized on an amine reactive second-generation (AR2G) biosensor (Lot No. 1311212, ForteBio). The BGA trisaccharide was analyzed as the conjugate to bovine serum albumin (BSA–BGA) and was dissolved in an analysis buffer containing 10 mM HEPES, 150 mM NaCl, 3.4 mM EDTA, and 0.005% Tween 20 at a range of pH values (5, 5.5, 6, 6.5, and 7). A BSA–Le^X trisaccharide conjugate (Prod. No. NGP0302, V-Labs, Inc.) and BSA (Prod. No. 23209, Pierce Thermo Scientific, Rockford, IL, USA) were used as negative controls. Details of the biolayer interferometry (BLI) conditions are provided in Supplemental Material.

Docking was performed using AutoDock VINA (18) with 20 docked poses generated for each experiment. The protein and the ligand files were prepared using Autodock tools (ADT) (20) with Gassteiger (21) partial atomic charges assigned to both the protein and ligand residues. The crystal structure of the scFv (PDB ID: 1JV5) was employed, together with a 3D structure of BGA obtained from the GLYCAM-Web server (www.glycam.org). Crystal waters were removed prior to docking and hydrogen atoms were added to the protein using ADT, whereas hydrogen atoms in the ligand were assigned from the GLYCAM residue templates. The glycosidic ϕ and φ torsion angles were allowed to be flexible during docking, as were all the hydroxyl groups. The protein was maintained rigid. The docking grid box (dimensions: 26.25 Å × 26.25 Å × 37.5 Å) was centered relative to the complementarity determining regions (CDRs) of the antibody as described previously (16). For the mutational-docking approach, Trp^H100 was mutated to Ala by deleting the side-chain atoms of the Trp residue in the crystal structure, followed by processing with the tleap module in AMBER (22). Ala^H100 was reverted back to Trp by restoring the crystal coordinates of the side chain of Trp^H100. The docked poses from the mutational approach were filtered based on the clashes with the reverted Trp. Poses in which the clashes could not be eliminated by implicit energy minimization (details are in the “MD simulations” section) were rejected. Ligand conformations of all the docked poses from both the flexible and mutational-docking approaches were scored using the recently reported carbohydrate intrinsic (CHI) energy scoring function (16). Any conformations with total CHI-energies >5 kcal/mol were rejected. The BGB complex was generated directly from that generated for BGA by simple replacement of the NAc group by an OH group.

All the MD simulations were performed with the GPU implementation of the pmed code, pmed.cud_SPDP (23), from AMBER12 (22). The calculations employed the ff99SSB (24) parameters for the protein and the GLYCAM06h (25) parameters for the carbohydrate. For the BGA, BGB–scFv complex simulations, an implicit solvent energy minimization (5000 steps of steepest descent followed by 5000 steps of conjugate gradient), were performed to optimize the side-chain positions of the reverted Trp residue. During this minimization, the backbone atoms of the framework regions were restrained with a 5 kcal/mol Ų while the CDRs and the ligand were allowed to be flexible. The systems were then solvated in a cubic water box [120 Å per side, with a TIP3P water (26)]. Each system was energy minimized using explicit solvent (10,000 steps of steepest descent, 10,000 steps of conjugate gradient). During this energy minimization, the protein residues were restrained with a force constant of 100 kcal/mol Ų allowing only the solvent and ligand to relax. This minimization was followed by heating from 5 to 300 K over the course of 50 ps at constant volume. Production MD simulations were performed for 50 ns at constant pressure (NPT ensemble) with the temperature held constant at 300 K using a Langevin thermostat. During the heating and the production MD, the backbone atoms of the protein were restrained with a force constant of 5 kcal/mol Ų, with the protein side chains and ligand atoms allowed to be flexible. The backbone atoms were restrained in order to ensure that the protein fold remained stable during the course of the simulation. For the BGA trisaccharide MD simulation, the system was solvated in a cubic water box (120 Å per side, with a TIP3P water) and energy minimized using explicit solvent (5000 steps of steepest descent, 5000 steps of conjugate gradient). This was followed by heating from 5 to 300 K for a period of 50 ps at constant volume. Production MD simulations were performed for 50 ns at constant pressure (NPT). During the minimization, heating, and production MD simulations, there were no restraints placed on the trisaccharide. For both BGA, BGB–scFv complexes and BGA trisaccharide simulations, all covalent bonds involving hydrogen atoms were constrained using the SHAKE (27) algorithm, allowing a time step of 2 fs. A non-bonded cut-off of 8 Å was used and long-range electrostatics were employed using the particle mesh Ewald (PME) method (28). Snapshots were collected at 1 ps intervals for subsequent analysis.

The stability of the complexes was assessed by monitoring the root-mean-squared-displacement (RMSD) of the ligand position, the glycosidic torsion angles, the ring conformations, and the protein–ligand hydrogen bonds. All these values except for the ring conformation analysis were generated using the ptraj module of AMBERTOOLS 12 (29). Ligand RMSD values were calculated for the ring atoms, relative to the first time step of the simulation. Hydrogen bond interactions between the protein and the ligand were measured with distance and angle cut-off values of 3.5 Å and 120°, respectively. The ring conformations of each individual residue in the ligand during the course of simulation were analyzed using the recently reported BFMP method (Makeneni et al., submitted). Binding free energies were calculated with the MM-GBSA (30, 31) module in AMBERTOOLS12. All the water molecules were removed prior to the MM-GBSA calculation, and desolvation free energies were approximated using the generalized born implicit solvation model (igb = 2) (32).

In preliminary experiments, docking to the rigid scFv structure yielded complexes that failed to remain stable during subsequent 10 ns MD simulations (Table S1 in Supplementary Material). The spontaneous dissociation of the complex during MD simulation suggested that the docking had failed to detect the correct, high affinity, pose (33). Upon inspection of the MD data, it was observed that light chain residue His49 (His^L49) forms a stacking interaction with heavy chain residue Trp100 (Trp^H100), which occupies a large volume of the presumed binding site, potentially preventing deeper penetration of the ligand (Figure 1).

As Trp residues can also form stacking interactions with the apolar face of monosaccharides in antibody complexes (34), we hypothesized that the trisaccharide ligand might compete for formation of such an interaction with Trp^H100. For example, the galactose (Gal) residue in a Salmonella trisaccharide antigen stacks against Trp^L93 in the complex with Fab Se155-4 (34). In addition, in the same complex, Trp^H33 stacks against the C-6 position in the 6-deoxy sugar Abequose. The BGA antigen contains GalNAc and a 6-deoxy monosaccharide (fucose, Fuc), thus a revised docking experiment was sought that would permit the formation of such interactions with the aromatic residues in the binding pocket. Thus, two alternative docking experiments were designed: in the first, the side-chain torsion angles of Trp^H100 were allowed to be flexible during docking (termed flexible residue docking); while in the second, Trp^H100 was mutated to Ala prior to docking, and then reverted back to Trp after docking (mutational residue docking). The docked poses were filtered based on three criteria. First, poses in which the GalNAc was not located within the binding pocket were eliminated (Figure 2C). This criterion was adopted based on the results from two array screenings, which indicated that the antibody interacts exclusively with the BGA antigens (Tables S2 and S3 in Supplementary Material) and because the only structural difference between BGA and BGB is the presence of the NAc moiety in the former. Therefore it was hypothesized that the ability of the antibody to discriminate between these two antigens would be dependent on interactions with this residue. Second, in the case of the mutational approach, poses were rejected if the Ala-Trp mutation led to irreconcilable steric clashes with the antigen (Figure 2B). All the docked poses obtained from each of these approaches were then scored using a CHI scoring function. After applying these criteria, both docking approaches identified essentially equivalent antigen poses (0.48 Å RMSD between ligand positions) (Figure 2A), in which the C-6 atom of the GalNAc forms a CH/π stacking interaction with the Trp^H96. This complex was selected for further analysis by MD simulation.

All histidines in the scFv were protonated by default for modeling with a hydrogen atom at the δ nitrogen position. During the MD simulation of the BGA–scFv complex, the χ2 angle of His^L49 flips (-73° to 115°) enabling a hydrogen bond to form with the carbonyl moiety of the NAc group in the GalNAc residue in BGA, which would be expected to be significant for enhancing the stability of the BGA–scFv complex. In the BGB complex, the same His^L49 forms an interaction with the non-terminal Gal residue. The interaction with HisL⁴⁹ suggests that there might also be a pH dependence on binding; at lower pH all histidines would be positively charged, potentially enhancing the strength of the His^L49–BGA hydrogen bond, leading to higher binding affinity. This prediction was confirmed by BLI measurements, which showed a marked decrease in the apparent K_D as the pH dropped below the pK_a of histidine (Figure 7). It should be noted that this protonation would not be localized to His^L49 nevertheless, no enhanced non-specific binding was observed at low pH for either BSA or BGA–Le^x (Figures S1–S3 in Supplementary Material), supporting a role for a direct interaction between His^L49 and the BGA antigen.

A per-residue decomposition of the interaction energies in the immune complexes indicated that, in the case of BGA, the GalNAc residue contributed 25% (-8.1 kcal/mol) toward the binding energy, compared to a reduced (-4.3 kcal/mol) contribution from the corresponding Gal residue in BGB (Table 3). This loss of 4 kcal/mol of interaction energy is the predominant difference between the two antigens, and would be enough to reduce the affinity by nearly 800-fold, consistent with the lack of apparent binding of the BGB analogs in the glycan array screening. In addition, this analysis identified the residues that contributed significantly toward antigen binding.

In the BGA–scFv complex, residues from CDR L3 make the maximum contributions to binding (Gly^L91 + Trp^L96 + Asn^L92 + Thr^L93 = -7.2 kcal/mol) followed by H3 (Asn^H98 + Trp^H100 + Leu^H99 = -5.5 kcal/mol), L1 (Tyr^L32 + Asn^L34 = -4.5 kcal/mol), and L2 (Tyr^L50 = -1.02 kcal/mol). In contrast, in the case of BGB, the same residues from L3 contribute less than a total of 1 kcal/mol to the interaction energies. The most significant single residues are Tyr^L32, Gly^L91, Trp^H100, and Trp^L96, which each contributes more than 2 kcal/mol and together account for 50% of the total affinity. Residues Gly^L91 and Asn^L92 that form hydrogen bonds with the Fuc residue together contribute -4.0 kcal/mol to the binding of BGA, but fail to make any stable interactions in the BGB simulation and therefore contribute negligibly to the affinity. It is these interactions that provide the predominant contributions to the preferential binding of the BGA antigen. While in the BGB complex, His^L49 does not form any stable hydrogen bonds with the terminal Gal, it is able to form new, albeit transient, interactions with the non-terminal Gal for 30% of the stable simulation period. Therefore, while the per-residue contribution values indicate that His^L49 makes a contribution greater than -1.5 kcal/mol in both cases, the interactions it forms in BGA are more stable when compared to the interactions in BGB.