Affinity improvement of a therapeutic antibody by structure-based computational design: generation of electrostatic interactions in the transition state stabilizes the antibody-antigen complex

Structure-guided design fine-tunes pharmacokinetics, tolerability, and antitumor profile of multispecific frizzled antibodies

Aberrant activation of Wnt/β-catenin signaling occurs frequently in cancer. However, therapeutic targeting of this pathway is complicated by the role of Wnt in stem cell maintenance and tissue homeostasis. Here, we evaluated antibodies blocking 6 of the 10 human Wnt/Frizzled (FZD) receptors as potential therapeutics. Crystal structures revealed a common binding site for these monoclonal antibodies (mAbs) on FZD, blocking the interaction with the Wnt palmitoleic acid moiety. However, these mAbs displayed gastrointestinal toxicity or poor plasma exposure in vivo. Structure-guided engineering was used to refine the binding of each mAb for FZD receptors, resulting in antibody variants with improved in vivo tolerability and developability. Importantly, the lead variant mAb significantly inhibited tumor growth in the HPAF-II pancreatic tumor xenograft model. Taken together, our data demonstrate that anti-FZD cancer therapeutic antibodies with broad specificity can be fine-tuned to navigate in vivo exposure and tolerability while driving therapeutic efficacy.

Exploring designability of electrostatic complementarity at an antigen-antibody interface directed by mutagenesis, biophysical analysis, and molecular dynamics simulations

Antibodies protect organisms from a huge variety of foreign antigens. Antibody diversity originates from both genetic and structural levels. Antigen recognition relies on complementarity between antigen-antibody interfaces. Recent methodological advances in structural biology and the accompanying rapid increase of the number of crystal structures of proteins have enabled atomic-level manipulation of protein structures to effect alterations in function. In this study, we explored the designability of electrostatic complementarity at an antigen-antibody interface on the basis of a crystal structure of the complex. We designed several variants with altered charged residues at the interface and characterized the designed variants by surface plasmon resonance, circular dichroism, differential scanning calorimetry, and molecular dynamics simulations. Both successes and failures of the structure-based design are discussed. The variants that compensate electrostatic interactions can restore the interface complementarity, enabling the cognate antigen-antibody binding. Retrospectively, we also show that these mutational effects could be predicted by the simulations. Our study demonstrates the importance of charged residues on the physical properties of this antigen-antibody interaction and suggests that computational approaches can facilitate design of antibodies that recognize a weakly immunogenic antigen.

Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3)

Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16.3) is a latency-associated antigen that can be targeted for latent tuberculosis (TB) diagnostic and therapeutic development. We have previously developed human V_H domain antibodies (dAbs; clone E3 and F1) specific against HSP16.3. In this work, we applied computational methods to optimise and design the antibodies in order to improve the binding affinity with HSP16.3. The V_H domain antibodies were first docked to the dimer form of HSP16.3 and further sampled using molecular dynamics simulation. The calculated binding free energy of the HSP16.3-dAb complexes showed non-polar interactions were responsible for the antigen-antibody association. Per-residue free energy decomposition and computational alanine scanning have identified one hotspot residue for E3 (Y391) and 4 hotspot residues for F1 (M394, Y396, R397 and M398). These hotspot residues were then mutated and evaluated by binding free energy calculations. Phage ELISA assay was carried out on the potential mutants (E3_Y391W, F1_M394E, F1_R397N and F1_M398Y). The experimental assay showed improved binding affinities of E3_Y391W and F1_M394E against HSP16.3 compared with the wild type E3 and F1. This case study has thus showed in silico methods are able to assist in optimisation or improvement of antibody-antigen binding.

In Silico Methods in Antibody Design

Antibody therapies with high efficiency and low toxicity are becoming one of the major approaches in antibody therapeutics. Based on high-throughput sequencing and increasing experimental structures of antibodies/antibody-antigen complexes, computational approaches can predict antibody/antigen structures, engineering the function of antibodies and design antibody-antigen complexes with improved properties. This review summarizes recent progress in the field of in silico design of antibodies, including antibody structure modeling, antibody-antigen complex prediction, antibody stability evaluation, and allosteric effects in antibodies and functions. We listed the cases in which these methods have helped experimental studies to improve the affinities and physicochemical properties of antibodies. We emphasized how the molecular dynamics unveiled the allosteric effects during antibody-antigen recognition and antibody-effector recognition.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

Motivation

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction.

Results

We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed.

Availability and Implementation

Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx.

Supplementary information

Supplementary data are available at Bioinformatics online.

Antibody Affinity Maturation by Computational Design

The immune systems protect our bodies from foreign molecules or antigens, where antibodies play important roles. Antibodies evolve over time upon antigen encounter by somatically mutating their genome sequences. The end result is a series of antibodies that display higher affinities and specificities to specific antigens. This process is called affinity maturation. Recent improvements in computer hardware and modeling algorithms now enable the rational design of protein structures and functions, and several works on computer-aided antibody design have been published. In this chapter, we briefly describe computational methods for antibody affinity maturation, focusing on methods for sampling antibody conformations and for scoring designed antibody variants. We also discuss lessons learned from the successful computer-aided design of antibodies.

Integration of molecular dynamics simulation and hotspot residues grafting for de novo scFv design against Salmonella Typhi TolC protein

With the development of de novo binders for protein targets from non-related scaffolds, many possibilities for therapeutics and diagnostics have been created. In this study, we described the use of de novo design approach to create single-chain fragment variable (scFv) for Salmonella enterica subspecies enterica serovar Typhi TolC protein. Typhoid fever is a global health concern in developing and underdeveloped countries. Rapid typhoid diagnostics will improve disease management and therapy. In this work, molecular dynamics simulation was first performed on a homology model of TolC protein in POPE membrane bilayer to obtain the central structure that was subsequently used as the target for scFv design. Potential hotspot residues capable of anchoring the binders to the target were identified by docking "disembodied" amino acid residues against TolC surface. Next, scFv scaffolds were selected from Protein Data Bank to harbor the computed hotspot residues. The hotspot residues were then incorporated into the scFv scaffold complementarity determining regions. The designs recapitulated binding energy, shape complementarity, and interface surface area of natural protein-antibody interfaces. This approach has yielded 5 designs with high binding affinity against TolC that may be beneficial for the future development of antigen-based detection agents for typhoid diagnostics.

Thermodynamic analyses of amino acid residues at the interface of an antibody B2212A and its antigen roundabout homolog 1

Artificial affinity maturation of antibodies is promising but often shows difficulties because the roles of each amino acid residue are not well known. To elucidate their roles in affinity against the antigen and thermal stability, interface residues in single-chain Fv of an antibody B2212A with its antigen roundabout homolog 1 were mutated and analyzed. Some amino acids played important roles in the affinity while others contributed to thermal stability.

Facile Affinity Maturation of Antibody Variable Domains Using Natural Diversity Mutagenesis

The identification of mutations that enhance antibody affinity while maintaining high antibody specificity and stability is a time-consuming and laborious process. Here, we report an efficient methodology for systematically and rapidly enhancing the affinity of antibody variable domains while maximizing specificity and stability using novel synthetic antibody libraries. Our approach first uses computational and experimental alanine scanning mutagenesis to identify sites in the complementarity-determining regions (CDRs) that are permissive to mutagenesis while maintaining antigen binding. Next, we mutagenize the most permissive CDR positions using degenerate codons to encode wild-type residues and a small number of the most frequently occurring residues at each CDR position based on natural antibody diversity. This mutagenesis approach results in antibody libraries with variants that have a wide range of numbers of CDR mutations, including antibody domains with single mutations and others with tens of mutations. Finally, we sort the modest size libraries (~10 million variants) displayed on the surface of yeast to identify CDR mutations with the greatest increases in affinity. Importantly, we find that single-domain (V_HH) antibodies specific for the α-synuclein protein (whose aggregation is associated with Parkinson’s disease) with the greatest gains in affinity (>5-fold) have several (four to six) CDR mutations. This finding highlights the importance of sampling combinations of CDR mutations during the first step of affinity maturation to maximize the efficiency of the process. Interestingly, we find that some natural diversity mutations simultaneously enhance all three key antibody properties (affinity, specificity, and stability) while other mutations enhance some of these properties (e.g., increased specificity) and display trade-offs in others (e.g., reduced affinity and/or stability). Computational modeling reveals that improvements in affinity are generally not due to direct interactions involving CDR mutations but rather due to indirect effects that enhance existing interactions and/or promote new interactions between the antigen and wild-type CDR residues. We expect that natural diversity mutagenesis will be useful for efficient affinity maturation of a wide range of antibody fragments and full-length antibodies.

Monoclonal antibodies: technologies for early discovery and engineering

Antibodies are essential in modern life sciences biotechnology. Their architecture and diversity allow for high specificity and affinity to a wide array of biochemicals. Combining monoclonal antibody (mAb) technology with recombinant DNA and protein expression links antibody genotype with phenotype. Yet, the ability to select and screen for high affinity binders from recombinantly-displayed, combinatorial libraries unleashes the true power of mAbs and a flood of clinical applications. The identification of novel antibodies can be accomplished by a myriad of in vitro display technologies from the proven (e.g. phage) to the emerging (e.g. mammalian cell and cell-free) based on affinity binding as well as function. Lead candidates can be further engineered for increased affinity and half-life, reduced immunogenicity and/or enhanced manufacturing, and storage capabilities. This review begins with antibody biology and how the structure and genetic machinery relate to function, diversity, and in vivo affinity maturation and follows with the general requirements of (therapeutic) antibody discovery and engineering with an emphasis on in vitro display technologies. Throughout, we highlight where antibody biology inspires technology development and where high-throughput, "big data" and in silico strategies are playing an increasing role. Antibodies dominate the growing class of targeted therapeutics, alone or as bioconjugates. However, their versatility extends to research, diagnostics, and beyond.

Arginine mutations in antibody complementarity-determining regions display context-dependent affinity/specificity trade-offs

Antibodies commonly accumulate charged mutations in their complementarity-determining regions (CDRs) during affinity maturation to enhance electrostatic interactions. However, charged mutations can mediate non-specific interactions, and it is unclear to what extent CDRs can accumulate charged residues to increase antibody affinity without compromising specificity. This is especially concerning for positively charged CDR mutations that are linked to antibody polyspecificity. To better understand antibody affinity/specificity trade-offs, we have selected single-chain antibody fragments specific for the negatively charged and hydrophobic Alzheimer's amyloid β peptide using weak and stringent selections for antibody specificity. Antibody variants isolated using weak selections for specificity were enriched in arginine CDR mutations and displayed low specificity. Alanine-scanning mutagenesis revealed that the affinities of these antibodies were strongly dependent on their arginine mutations. Antibody variants isolated using stringent selections for specificity were also enriched in arginine CDR mutations, but these antibodies possessed significant improvements in specificity. Importantly, the affinities of the most specific antibodies were much less dependent on their arginine mutations, suggesting that over-reliance on arginine for affinity leads to reduced specificity. Structural modeling and molecular simulations reveal unique hydrophobic environments near the arginine CDR mutations. The more specific antibodies contained arginine mutations in the most hydrophobic portions of the CDRs, whereas the less specific antibodies contained arginine mutations in more hydrophilic regions. These findings demonstrate that arginine mutations in antibody CDRs display context-dependent impacts on specificity and that affinity/specificity trade-offs are governed by the relative contribution of arginine CDR residues to the overall antibody affinity.

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.

Antibody H3 Structure Prediction

Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction.

Computer-Aided Antibody Design: An Overview

The use of monoclonal antibody as the next generation protein therapeutics with remarkable success has surged the development of antibody engineering to design molecules for optimizing affinity, better efficacy, greater safety and therapeutic function. Therefore, computational methods have become increasingly important to generate hypotheses, interpret and guide experimental works. In this chapter, we discussed the overall antibody design by computational approches.

Determination of equilibrium dissociation constants for recombinant antibodies by high-throughput affinity electrophoresis

High-quality immunoreagents enhance the performance and reproducibility of immunoassays and, in turn, the quality of both biological and clinical measurements. High quality recombinant immunoreagents are generated using antibody-phage display. One metric of antibody quality – the binding affinity – is quantified through the dissociation constant (K_D) of each recombinant antibody and the target antigen. To characterize the K_D of recombinant antibodies and target antigen, we introduce affinity electrophoretic mobility shift assays (EMSAs) in a high-throughput format suitable for small volume samples. A microfluidic card comprised of free-standing polyacrylamide gel (fsPAG) separation lanes supports 384 concurrent EMSAs in 30 s using a single power source. Sample is dispensed onto the microfluidic EMSA card by acoustic droplet ejection (ADE), which reduces EMSA variability compared to sample dispensing using manual or pin tools. The K_D for each of a six-member fragment antigen-binding fragment library is reported using ~25-fold less sample mass and ~5-fold less time than conventional heterogeneous assays. Given the form factor and performance of this micro- and mesofluidic workflow, we have developed a sample-sparing, high-throughput, solution-phase alternative for biomolecular affinity characterization.

Engineering antibody therapeutics

The successful introduction of antibody-based protein therapeutics into the arsenal of treatments for patients has within a few decades fostered intense innovation in the production and engineering of antibodies. Reviewed here are the methods currently used to produce antibodies along with how our knowledge of the structural and functional characterization of immunoglobulins has resulted in the engineering of antibodies to produce protein therapeutics with unique properties, both biological and biophysical, that are leading to novel therapeutic approaches. Antibody engineering includes the introduction of the antibody combining site (variable regions) into a host of architectures including bi and multi-specific formats that further impact the therapeutic properties leading to further advantages and successes in patient treatment.

Charge Variants of an Avastin Biosimilar Isolation, Characterization, In Vitro Properties and Pharmacokinetics in Rat

The similarity between a proposed biosimilar product and the reference product can be affected by many factors. This study is designed to examine whether any subtle difference in the distribution of the charge variants of an Avastin biosimilar can affect its in vitro potency and in vivo PK. Here, the acidic, basic and main peak fractions of a biosimilar product were isolated using high-performance cation-exchange chromatography and were subjected to various studies to compare their in vitro properties and in vivo PK profile. A serial of analytical methods, including size exclusion chromatography (SEC), imaged capillary isoelectric focusing (icIEF) capillary zone electrophoresis (CZE) and cation-exchange chromatography (CEX-HPLC) were also used to characterize the isolated charge variants. The kinetics constant was measured using a Biacore X100 system. The study indicates the biosimilar product has a high similarity with avastin in physicochemical properties. The potency in vitro and PK profile in rat of charge variants and biosimilar product are consistent with avastin.

Structural and Thermodynamic Basis of Epitope Binding by Neutralizing and Nonneutralizing Forms of the Anti-HIV-1 Antibody 4E10

The 4E10 antibody recognizes the membrane-proximal external region (MPER) of the HIV-1 Env glycoprotein gp41 transmembrane subunit, exhibiting one of the broadest neutralizing activities known to date. The neutralizing activity of 4E10 requires solvent-exposed hydrophobic residues at the apex of the complementarity-determining region (CDR) H3 loop, but the molecular basis for this requirement has not been clarified. Here, we report the cocrystal structures and the energetic parameters of binding of a peptide bearing the 4E10-epitope sequence (4E10ep) to nonneutralizing versions of the 4E10 Fab. Nonneutralizing Fabs were obtained by shortening and decreasing the hydrophobicity of the CDR-H3 loop (termed ΔLoop) or by substituting the two tryptophan residues of the CDR-H3 apex with Asp residues (termed WDWD), which also decreases hydrophobicity but preserves the length of the loop. The analysis was complemented by the first crystal structure of the 4E10 Fab in its ligand-free state. Collectively, the data ruled out major conformational changes of CDR-H3 at any stage during the binding process (equilibrium or transition state). Although these mutations did not impact the affinity of wild-type Fab for the 4E10ep in solution, the two nonneutralizing versions of 4E10 were deficient in binding to MPER inserted in the plasma membrane (mimicking the environment faced by the antibody in vivo). The conclusions of our structure-function analysis strengthen the idea that to exert effective neutralization, the hydrophobic apex of the solvent-exposed CDR-H3 loop must recognize an antigenic structure more complex than just the linear α-helical epitope and likely constrained by the viral membrane lipids.

IMPORTANCE The broadly neutralizing anti-HIV-1 4E10 antibody blocks infection caused by nearly all viral strains and isolates examined thus far. However, 4E10 (or 4E10-like) antibodies are rarely found in HIV-1-infected individuals or elicited through vaccination. Impediments to the design of successful 4E10 immunogens are partly attributed to an incomplete understanding of the structural and binding characteristics of this class of antibodies. Since the broadly neutralizing activity of 4E10 is abrogated by mutations of the tip of the CDR-H3, we investigated their impact on binding of the MPER-epitope at the atomic and energetic levels. We conclude that the difference between neutralizing and nonneutralizing antibodies of 4E10 is neither structural nor energetic but is related to the capacity to recognize the HIV-1 gp41 epitope inserted in biological membranes. Our findings strengthen the idea that to elicit similar neutralizing antibodies, the suitable MPER vaccine must be “delivered” in a membrane environment.

Advances in Antibody Design

The use of monoclonal antibodies as therapeutics requires optimizing several of their key attributes. These include binding affinity and specificity, folding stability, solubility, pharmacokinetics, effector functions, and compatibility with the attachment of additional antibody domains (bispecific antibodies) and cytotoxic drugs (antibody-drug conjugates). Addressing these and other challenges requires the use of systematic design methods that complement powerful immunization and in vitro screening methods. We review advances in designing the binding loops, scaffolds, domain interfaces, constant regions, post-translational and chemical modifications, and bispecific architectures of antibodies and fragments thereof to improve their bioactivity. We also highlight unmet challenges in antibody design that must be overcome to generate potent antibody therapeutics.

Structural basis for binding of human IgG1 to its high-affinity human receptor FcγRI

Cell-surface Fcγ receptors mediate innate and adaptive immune responses. Human Fcγ receptor I (hFcγRI) binds IgGs with high affinity and is the only Fcγ receptor that can effectively capture monomeric IgGs. However, the molecular basis of hFcγRI's interaction with Fc has not been determined, limiting our understanding of this major immune receptor. Here we report the crystal structure of a complex between hFcγRI and human Fc, at 1.80 Å resolution, revealing an unique hydrophobic pocket at the surface of hFcγRI perfectly suited for residue Leu235 of Fc, which explains the high affinity of this complex. Structural, kinetic and thermodynamic data demonstrate that the binding mechanism is governed by a combination of non-covalent interactions, bridging water molecules and the dynamic features of Fc. In addition, the hinge region of hFcγRI-bound Fc adopts a straight conformation, potentially orienting the Fab moiety. These findings will stimulate the development of novel therapeutic strategies involving hFcγRI.

FcγRs are cell-surface receptors for IgGs that play key roles in the humoral and cellular immune response to infection. Here, the authors present a high-resolution crystal structure of the hFcγRI-Fc complex to reveal the molecular mechanisms underlying the high specificity of this important immunological interaction.

Antibody informatics for drug discovery

More and more antibody therapeutics are being approved every year, mainly due to their high efficacy and antigen selectivity. However, it is still difficult to identify the antigen, and thereby the function, of an antibody if no other information is available. There are obstacles inherent to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii) antibody numbering and IMGT. Here, we review "antibody informatics," which may integrate the above three fields so that bridging the gaps between industrial needs and academic solutions can be accelerated. This article is part of a Special Issue entitled: Recent advances in molecular engineering of antibody.