Solvated interaction energy: from small-molecule to antibody drug design.

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15 years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH.

Optimizing Antibody-Antigen Binding Affinities with the ADAPT Platform.

The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform guides the selection of mutants that improve/modulate the affinity of antibodies and other biologics. Predicted affinities are based on a consensus z-score from three scoring functions. Computational predictions are interleaved with experimental validation, significantly enhancing the robustness of the design and selection of mutants. A key step is an initial exhaustive virtual single-mutant scan that identifies hot spots and the mutations predicted to improve affinity. A small number of proposed single mutants are then produced and assayed. Only the validated single mutants (i.e., having improved affinity) are used to design double and higher-order mutants in subsequent rounds of design, avoiding the combinatorial explosion that arises from random mutagenesis. Typically, with a total of about 30-50 designed single, double, and triple mutants, affinity improvements of 10- to 100-fold are obtained.

Antibody mutations favoring pH-dependent binding in solid tumor microenvironments: Insights from large-scale structure-based calculations.

Antibody-based therapeutics for treatment of various tumors have grown rapidly in recent years. Unfortunately, safety issues, attributed to off-tumor effects and cytotoxicity, are still a significant concern with the standard of care. Improvements to ensure targeted delivery of antitumor pharmaceuticals are desperately needed. We previously demonstrated that incorporating histidyl pH-switches in an anti-HER2 antibody induced selective antigen binding under acidic pH conditions (MAbs 2020;12:1682866). This led to an improved safety profile due to preferential targeting of the oncoprotein in the acidic solid tumor microenvironment. Following this success, we expanded this approach to a set of over 400 antibody structures complexed with over 100 different human oncoproteins, associated with solid tumors. Calculations suggested that mutations to His of certain residue types, namely Trp, Arg, and Tyr, could be significantly more successful for inducing pH-dependent binding under acidic conditions. Furthermore, 10 positions within the complementarity-determining region were also predicted to exhibit greater successes. Combined, these two accessible metrics could serve as the basis for a sequence-based engineering of pH-selective binding. This approach could be applied to most anticancer antibodies, which lack detailed structural characterization.

Redesigning an antibody H3 loop by virtual screening of a small library of human germline-derived sequences.

The design of superior biologic therapeutics, including antibodies and engineered proteins, involves optimizing their specific ability to bind to disease-related molecular targets. Previously, we developed and applied the Assisted Design of Antibody and Protein Therapeutics (ADAPT) platform for virtual affinity maturation of antibodies (Vivcharuk et al. in PLoS One 12(7):e0181490, https://doi.org/10.1371/journal.pone.0181490 , 2017). However, ADAPT is limited to point mutations of hot-spot residues in existing CDR loops. In this study, we explore the possibility of wholesale replacement of the entire H3 loop with no restriction to maintain the parental loop length. This complements other currently published studies that sample replacements for the CDR loops L1, L2, L3, H1 and H2. Given the immense sequence space theoretically available to H3, we focused on the virtual grafting of over 5000 human germline-derived H3 sequences from the IGMT/LIGM database increasing the diversity of the sequence space when compared to using crystalized H3 loop sequences. H3 loop conformations are generated and scored to identify optimized H3 sequences. Experimental testing of high-ranking H3 sequences grafted into the framework of the bH1 antibody against human VEGF-A led to the discovery of multiple hits, some of which had similar or better affinities relative to the parental antibody. In over 75% of the tested designs, the re-designed H3 loop contributed favorably to overall binding affinity. The hits also demonstrated good developability attributes such as high thermal stability and no aggregation. Crystal structures of select re-designed H3 variants were solved and indicated that although some deviations from predicted structures were seen in the more solvent accessible regions of the H3 loop, they did not significantly affect predicted affinity scores.

Structure-based engineering of pH-dependent antibody binding for selective targeting of solid-tumor microenvironment.

Recent development of monoclonal antibodies as mainstream anticancer agents demands further optimization of their safety for use in humans. Potent targeting and/or effector activities on normal tissues is an obvious toxicity concern. Optimization of specific tumor targeting could be achieved by taking advantage of the extracellular acidity of solid tumors relative to normal tissues. Here, we applied a structure-based computational approach to engineer anti-human epidermal growth factor receptor 2 (Her2) antibodies with selective binding in the acidic tumor microenvironment. We used an affinity maturation platform in which dual-pH histidine-scanning mutagenesis was implemented for pH selectivity optimization. Testing of a small set of designs for binding to the recombinant Her2 ectodomain led to the identification of antigen-binding fragment (Fab) variants with the desired pH-dependent binding behavior. Binding selectivity toward acidic pH was improved by as much as 25-fold relative to the parental bH1-Fab. In vitro experiments on cells expressing intact Her2 confirmed that designed variants formatted as IgG1/k full-size antibodies have high affinity and inhibit the growth of tumor spheroids at a level comparable to that of the benchmark anti-Her2 antibody trastuzumab (Herceptin®) at acidic pH, whereas these effects were significantly reduced at physiological pH. In contrast, both Herceptin and the parental bH1 antibody exhibited strong cell binding and growth inhibition irrespective of pH. This work demonstrates the feasibility of computational optimization of antibodies for selective targeting of the acidic environment such as that found in many solid tumors.

Binding symmetry and surface flexibility mediate antibody self-association.

Solution stability is an important factor in the optimization of engineered biotherapeutic candidates such as monoclonal antibodies because of its possible effects on manufacturability, pharmacology, efficacy and safety. A detailed atomic understanding of the mechanisms governing self-association of natively folded protein monomers is required to devise predictive tools to guide screening and re-engineering along the drug development pipeline. We investigated pairs of affinity-matured full-size antibodies and observed drastically different propensities to aggregate from variants differing by a single amino-acid. Biophysical testing showed that antigen-binding fragments (Fabs) from the aggregating antibodies also reversibly associated with equilibrium dissociation constants in the low-micromolar range. Crystal structures (PDB accession codes 6MXR, 6MXS, 6MY4, 6MY5) and bottom-up hydrogen-exchange mass spectrometry revealed that Fab self-association occurs in a symmetric mode that involves the antigen complementarity-determining regions. Subtle local conformational changes incurred upon point mutation of monomeric variants foster formation of complementary polar interactions and hydrophobic contacts to generate a dimeric Fab interface. Testing of popular in silico tools generally indicated low reliabilities for predicting the aggregation propensities observed. A structure-aggregation data set is provided here in order to stimulate further improvements of in silico tools for prediction of native aggregation. Incorporation of intermolecular docking, conformational flexibility, and short-range packing interactions may all be necessary features of the ideal algorithm.

ProPOSE: Direct Exhaustive Protein-Protein Docking with Side Chain Flexibility.

Despite decades of development, protein-protein docking remains a largely unsolved problem. The main difficulties are the immense space spanned by the translational and rotational degrees of freedom and the prediction of the conformational changes of proteins upon binding. FFT is generally the preferred method to exhaustively explore the translation-rotation space at a fine grid resolution, albeit with the trade-off of approximating force fields with correlation functions. This work presents a direct search alternative that samples the states in Cartesian space at the same resolution and computational cost as standard FFT methods. Operating in real space allows the use of standard force field functional forms used in typical non-FFT methods as well as the implementation of strategies for focused exploration of conformational flexibility. Currently, a few misplaced side chains can cause docking programs to fail. This work specifically addresses the problem of side chain rearrangements upon complex formation. Based on the observation that most side chains retain their unbound conformation upon binding, each rigidly docked pose is initially scored ignoring up to a limited number of side chain overlaps which are resolved in subsequent repacking and minimization steps. On test systems where side chains are altered and backbones held in their bound state, this implementation provides significantly better native pose recovery and higher quality (lower RMSD) predictions when compared with five of the most popular docking programs. The method is implemented in the software program ProPOSE (Protein Pose Optimization by Systematic Enumeration).

Assisted Design of Antibody and Protein Therapeutics (ADAPT).

Effective biologic therapeutics require binding affinities that are fine-tuned to their disease-related molecular target. The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform aids in the selection of mutants that improve/modulate the affinity of antibodies and other biologics. It uses a consensus z-score from three scoring functions and interleaves computational predictions with experimental validation, significantly enhancing the robustness of the design and selection of mutants. The platform was tested on three antibody Fab-antigen systems that spanned a wide range of initial binding affinities: bH1-VEGF-A (44 nM), bH1-HER2 (3.6 nM) and Herceptin-HER2 (0.058 nM). Novel triple mutants were obtained that exhibited 104-, 46- and 32-fold improvements in binding affinity for each system, respectively. Moreover, for all three antibody-antigen systems over 90% of all the intermediate single and double mutants that were designed and tested showed higher affinities than the parent sequence. The contributions of the individual mutants to the change in binding affinity appear to be roughly additive when combined to form double and triple mutants. The new interactions introduced by the affinity-enhancing mutants included long-range electrostatics as well as short-range nonpolar interactions. This diversity in the types of new interactions formed by the mutants was reflected in SPR kinetics that showed that the enhancements in affinities arose from increasing on-rates, decreasing off-rates or a combination of the two effects, depending on the mutation. ADAPT is a very focused search of sequence space and required only 20-30 mutants for each system to be made and tested to achieve the affinity enhancements mentioned above.

Assessment of Solvated Interaction Energy Function for Ranking Antibody-Antigen Binding Affinities.

Affinity modulation of antibodies and antibody fragments of therapeutic value is often required in order to improve their clinical efficacies. Virtual affinity maturation has the potential to quickly focus on the critical hotspot residues without the combinatorial explosion problem of conventional display and library approaches. However, this requires a binding affinity scoring function that is capable of ranking single-point mutations of a starting antibody. We focus here on assessing the solvated interaction energy (SIE) function that was originally developed for and is widely applied to scoring of protein-ligand binding affinities. To this end, we assembled a structure-function data set called Single-Point Mutant Antibody Binding (SiPMAB) comprising several antibody-antigen systems suitable for this assessment, i.e., based on high-resolution crystal structures for the parent antibodies and coupled with high-quality binding affinity measurements for sets of single-point antibody mutants in each system. Using this data set, we tested the SIE function with several mutation protocols based on the popular methods SCWRL, Rosetta, and FoldX. We found that the SIE function coupled with a protocol limited to sampling only the mutated side chain can reasonably predict relative binding affinities with a Spearman rank-order correlation coefficient of about 0.6, outperforming more aggressive sampling protocols. Importantly, this performance is maintained for each of the seven system-specific component subsets as well as for other relevant subsets including non-alanine and charge-altering mutations. The transferability and enrichment in affinity-improving mutants can be further enhanced using consensus ranking over multiple methods, including the SIE, Talaris, and FOLDEF energy functions. The knowledge gained from this study can lead to successful prospective applications of virtual affinity maturation.

Automated molecular formula determination by tandem mass spectrometry (MS/MS).

Automated software was developed to analyze the molecular formula of organic molecules and peptides based on high-resolution MS/MS spectroscopic data. The software was validated with 96 compounds including a few small peptides in the mass range of 138-1569 Da containing the elements carbon, hydrogen, nitrogen and oxygen. A Micromass Waters Q-TOF Ultima Global mass spectrometer was used to measure the molecular masses of precursor and fragment ions. Our software assigned correct molecular formulas for 91 compounds, incorrect molecular formulas for 3 compounds, and no molecular formula for 2 compounds. The obtained 95% success rate indicates high reliability of the software. The mass accuracy of the precursor ion and the fragment ions, which is critical for the success of the analysis, was high, i.e. the accuracy and the precision of 850 data were 0.0012 Da and 0.0016 Da, respectively. For the precursor and fragment ions below 500 Da, 60% and 90% of the data showed accuracy within < or = 0.001 Da and < or = 0.002 Da, respectively. The precursor and fragment ions above 500 Da showed slightly lower accuracy, i.e. 40% and 70% of them showed accuracy within < or = 0.001 Da and < or = 0.002 Da, respectively. The molecular formulas of the precursor and the fragments were further used to analyze possible mass spectrometric fragmentation pathways, which would be a powerful tool in structural analysis and identification of small molecules. The method is valuable in the rapid screening and identification of small molecules such as the dereplication of natural products, characterization of drug metabolites, and identification of small peptide fragments in proteomics. The analysis was also extended to compounds that contain a chlorine or bromine atom.

Solution structure of the E.coli TolA C-terminal domain reveals conformational changes upon binding to the phage g3p N-terminal domain.

The Tol-Pal system of Escherichia coli is a macromolecular complex located in the cell envelope. It is involved in maintaining the integrity of the outer membrane and is required for the uptake of two different types of macromolecules, which are bacteriotoxins (colicins) and DNA of filamentous bacteriophages. The TolA protein plays a central role in these import mechanisms. Its C-terminal domain (TolAIII) is involved in the translocation step via direct interaction with the N-terminal domain of colicins and the N-terminal domain of the phage minor coat gene 3 protein (g3pN1). Extreme behaviours of TolAIII have been previously observed, since the structure of TolAIII either remained unaffected or adopted disordered conformation upon binding to different pore-forming colicins. Here, we have solved the 3D structure of free TolAIII by heteronuclear NMR spectroscopy and compared it to the crystal structure of TolAIII bound to g3pN1 in order to study the effect of g3pN1 on the tertiary structure of TolAIII. Backbone 1H, 15N and 13C resonances of the g3pN1-bound TolAIII were also assigned and used to superimpose the solution structure of free TolAIII on the crystal structure of the g3pN1-TolAIII fusion protein. This allowed us to track conformational changes of TolAIII upon binding. While the global fold of free TolAIII is mainly identical to that of g3pN1-bound TolAIII, shift of secondary structures does occur. Thus, TolAIII, which interacts also in vivo with Pal and TolB, is able to adapt its conformation upon binding to various partners. Possible models for protein binding mechanisms are discussed to explain this so-far unobserved behaviour of TolAIII.

Two WXXF-based motifs in NECAPs define the specificity of accessory protein binding to AP-1 and AP-2.

The adaptor proteins AP-2 and AP-1/GGAs are essential components of clathrin coats at the plasma membrane and trans-Golgi network, respectively. The adaptors recruit accessory proteins to clathrin-coated pits, which is dependent on the adaptor ear domains engaging short peptide motifs in the accessory proteins. Here, we perform an extensive mutational analysis of a novel WXXF-based motif that functions to mediate the binding of an array of accessory proteins to the alpha-adaptin ear domain of AP-2. Using nuclear magnetic resonance and mutational studies, we identified WXXF-based motifs as major ligands for a site on the alpha-ear previously shown to bind the DPW-bearing proteins epsin 1/2. We also defined the determinants that allow for specific binding of the alpha-ear motif to AP-2 as compared to those that allow a highly related WXXF-based motif to bind to the ear domains of AP-1/GGAs. Intriguingly, placement of acidic residues around the WXXF cores is critical for binding specificity. These studies provide a structural basis for the specific recruitment of accessory proteins to appropriate sites of clathrin-coated vesicle formation.

Macromolecular import into Escherichia coli: the TolA C-terminal domain changes conformation when interacting with the colicin A toxin.

Various macromolecules such as bacteriotoxins and phage DNA parasitize some envelope proteins of Escherichia coli to infect the bacteria. A two-step import mechanism involves the primary interaction with an outer membrane receptor or with a pilus followed by the translocation across the outer membrane. However, this second step is poorly understood. It was shown that the TolA, TolQ, and TolR proteins play a critical role in the translocation of group A colicins and filamentous bacteriophage minor coat proteins (g3p). Translocation of these proteins requires the interaction of their N-terminal domain with the C-terminal domain of TolA (TolAIII). In this work, short soluble TolAIII domains were overproduced in the cytoplasm and in the periplasm of E. coli. In TolAIII, the two cysteine residues were found to be reduced in the cytoplasmic form and oxidized in the periplasmic form. The interaction of TolAIII with the N-terminal domain of colicin A (ATh) is observed in the presence and in the absence of the disulfide bridge. The complex formation of TolAIII and ATh was found to be independent of the ionic strength. An NMR study of TolAIII, both free and bound, shows a significant structural change when interacting with ATh, in the presence or absence of the disulfide bridge. In contrast, such a structural modification was not observed when TolAIII interacts with g3p N1. These results suggest that bacteriotoxins and Ff bacteriophages parasitize E. coli using different interactions between TolA and the translocation domain of the colicin and g3p protein, respectively.