Three-dimensional structures of the free and the antigen-complexed Fab from monoclonal anti-lysozyme antibody D44.1

Precision engineering for localization, validation, and modification of allergenic epitopes

The allergen-IgE interaction is essential for the genesis of allergic responses, yet investigation of the molecular basis of these interactions is in its infancy. Precision engineering has unveiled the molecular features of allergen-antibody interactions at the atomic level. High-resolution technologies, including x-ray crystallography, nuclear magnetic resonance spectroscopy, and cryo-electron microscopy, determine allergen-antibody structures. X-ray crystallography of an allergen-antibody complex localizes in detail amino acid residues and interactions that define the epitope-paratope interface. Multiple structures involving murine IgG mAbs have recently been resolved. The number of amino acids forming the epitope broadly correlates with the epitope area. The production of human IgE mAbs from B cells of allergic subjects is an exciting recent development that has for the first time enabled an actual IgE epitope to be defined. The biologic activity of defined IgE epitopes can be validated in vivo in animal models or by measuring mediator release from engineered basophilic cell lines. Finally, gene-editing approaches using the Clustered Regularly Interspaced Short Palindromic Repeats technology to either remove allergen genes or make targeted epitope engineering at the source are on the horizon. This review presents an overview of the identification and validation of allergenic epitopes by precision engineering.

Computational optimization of antibody humanness and stability by systematic energy-based ranking

Conventional methods for humanizing animal-derived antibodies involve grafting their complementarity-determining regions onto homologous human framework regions. However, this process can substantially lower antibody stability and antigen-binding affinity, and requires iterative mutational fine-tuning to recover the original antibody properties. Here we report a computational method for the systematic grafting of animal complementarity-determining regions onto thousands of human frameworks. The method, which we named CUMAb (for computational human antibody design; available at http://CUMAb.weizmann.ac.il ), starts from an experimental or model antibody structure and uses Rosetta atomistic simulations to select designs by energy and structural integrity. CUMAb-designed humanized versions of five antibodies exhibited similar affinities to those of the parental animal antibodies, with some designs showing marked improvement in stability. We also show that (1) non-homologous frameworks are often preferred to highest-homology frameworks, and (2) several CUMAb designs that differ by dozens of mutations and that use different human frameworks are functionally equivalent.

Contextual protein and antibody encodings from equivariant graph transformers

The optimal residue identity at each position in a protein is determined by its structural, evolutionary, and functional context. We seek to learn the representation space of the optimal amino-acid residue in different structural contexts in proteins. Inspired by masked language modeling (MLM), our training aims to transduce learning of amino-acid labels from non-masked residues to masked residues in their structural environments and from general (e.g., a residue in a protein) to specific contexts (e.g., a residue at the interface of a protein or antibody complex). Our results on native sequence recovery and forward folding with AlphaFold2 suggest that the amino acid label for a protein residue may be determined from its structural context alone (i.e., without knowledge of the sequence labels of surrounding residues). We further find that the sequence space sampled from our masked models recapitulate the evolutionary sequence neighborhood of the wildtype sequence. Remarkably, the sequences conditioned on highly plastic structures recapitulate the conformational flexibility encoded in the structures. Furthermore, maximum-likelihood interfaces designed with masked models recapitulate wildtype binding energies for a wide range of protein interfaces and binding strengths. We also propose and compare fine-tuning strategies to train models for designing CDR loops of antibodies in the structural context of the antibody-antigen interface by leveraging structural databases for proteins, antibodies (synthetic and experimental) and protein-protein complexes. We show that pretraining on more general contexts improves native sequence recovery for antibody CDR loops, especially for the hypervariable CDR H3, while fine-tuning helps to preserve patterns observed in special contexts.

The ClusPro AbEMap web server for the prediction of antibody epitopes

Antibodies play an important role in the immune system by binding to molecules called antigens at their respective epitopes. These interfaces or epitopes are structural entities determined by the interactions between an antibody and an antigen, making them ideal systems to analyze by using docking programs. Since the advent of high-throughput antibody sequencing, the ability to perform epitope mapping using only the sequence of the antibody has become a high priority. ClusPro, a leading protein-protein docking server, together with its template-based modeling version, ClusPro-TBM, have been re-purposed to map epitopes for specific antibody-antigen interactions by using the Antibody Epitope Mapping server (AbEMap). ClusPro-AbEMap offers three different modes for users depending on the information available on the antibody as follows: (i) X-ray structure, (ii) computational/predicted model of the structure or (iii) only the amino acid sequence. The AbEMap server presents a likelihood score for each antigen residue of being part of the epitope. We provide detailed information on the server's capabilities for the three options and discuss how to obtain the best results. In light of the recent introduction of AlphaFold2 (AF2), we also show how one of the modes allows users to use their AF2-generated antibody models as input. The protocol describes the relative advantages of the server compared to other epitope-mapping tools, its limitations and potential areas of improvement. The server may take 45-90 min depending on the size of the proteins.

Mapping of antibody epitopes based on docking and homology modeling

Antibodies are key proteins produced by the immune system to target pathogen proteins termed antigens via specific binding to surface regions called epitopes. Given an antigen and the sequence of an antibody the knowledge of the epitope is critical for the discovery and development of antibody based therapeutics. In this work, we present a computational protocol that uses template-based modeling and docking to predict epitope residues. This protocol is implemented in three major steps. First, a template-based modeling approach is used to build the antibody structures. We tested several options, including generation of models using AlphaFold2. Second, each antibody model is docked to the antigen using the fast Fourier transform (FFT) based docking program PIPER. Attention is given to optimally selecting the docking energy parameters depending on the input data. In particular, the van der Waals energy terms are reduced for modeled antibodies relative to x-ray structures. Finally, ranking of antigen surface residues is produced. The ranking relies on the docking results, that is, how often the residue appears in the docking poses' interface, and also on the energy favorability of the docking pose in question. The method, called PIPER-Map, has been tested on a widely used antibody-antigen docking benchmark. The results show that PIPER-Map improves upon the existing epitope prediction methods. An interesting observation is that epitope prediction accuracy starting from antibody sequence alone does not significantly differ from that of starting from unbound (i.e., separately crystallized) antibody structure.

Restricted epitope specificity determined by variable region germline segment pairing in rodent antibody repertoires

Antibodies from B-cell clonal lineages share sequence and structural properties as well as epitope specificity. Clonally unrelated antibodies can similarly share sequence and specificity properties and are said to be convergent. Convergent antibody responses against several antigens have been described in humans and mice and include different classes of shared sequence features. In particular, some antigens and epitopes can induce convergent responses of clonally unrelated antibodies with restricted heavy (V_H) and light (V_L) chain variable region germline segment usage without similarity in the heavy chain third complementarity-determining region (CDR H3), a critical specificity determinant. Whether these V germline segment-restricted responses reflect a general epitope specificity restriction of antibodies with shared V_H/V_L pairing is not known. Here, we investigated this question by determining patterns of antigen binding competition between clonally unrelated antigen-specific rat antibodies from paired-chain deep sequencing datasets selected based solely on V_H/V_L pairing. We found that antibodies with shared V_H/V_L germline segment pairings but divergent CDR H3 sequences almost invariably have restricted epitope specificity indicated by shared binding competition patterns. This epitope restriction included 82 of 85 clonally unrelated antibodies with 13 different V_H/V_L pairings binding in 8 epitope groups in 2 antigens. The corollary that antibodies with shared V_H/V_L pairing and epitope-restricted binding can accommodate widely divergent CDR H3 sequences was confirmed by in vitro selection of variants of anti-human epidermal growth factor receptor 2 antibodies known to mediate critical antigen interactions through CDR H3. Our results show that restricted epitope specificity determined by V_H/V_L germline segment pairing is a general property of rodent antigen-specific antibodies.

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83-98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

Surprisingly Fast Interface and Elbow Angle Dynamics of Antigen-Binding Fragments

Fab consist of a heavy and light chain and can be subdivided into a variable (V H and V L ) and a constant region (C H 1 and C L ). The variable region contains the complementarity-determining region (CDR), which is formed by six hypervariable loops, shaping the antigen binding site, the paratope. Apart from the CDR loops, both the elbow angle and the relative interdomain orientations of the V H -V L and the C H 1-C L domains influence the shape of the paratope. Thus, characterization of the interface and elbow angle dynamics is essential to antigen specificity. We studied nine antigen-binding fragments (Fab) to investigate the influence of affinity maturation, antibody humanization, and different light-chain types on the interface and elbow angle dynamics. While the CDR loops reveal conformational transitions in the micro-to-millisecond timescale, both the interface and elbow angle dynamics occur on the low nanosecond timescale. Upon affinity maturation, we observe a substantial rigidification of the V H and V L interdomain and elbow-angle flexibility, reflected in a narrower and more distinct distribution. Antibody humanization describes the process of grafting non-human CDR loops onto a representative human framework. As the antibody framework changes upon humanization, we investigated if both the interface and the elbow angle distributions are changed or shifted. The results clearly showed a substantial shift in the relative V H -V L distributions upon antibody humanization, indicating that different frameworks favor distinct interface orientations. Additionally, the interface and elbow angle dynamics of five antibody fragments with different light-chain types are included, because of their strong differences in elbow angles. For these five examples, we clearly see a high variability and flexibility in both interface and elbow angle dynamics, highlighting the fact that Fab interface orientations and elbow angles interconvert between each other in the low nanosecond timescale. Understanding how the relative interdomain orientations and the elbow angle influence antigen specificity, affinity, and stability has broad implications in the field of antibody modeling and engineering.

Antibodies exhibit multiple paratope states influencing VH-VL domain orientations

In the last decades, antibodies have emerged as one of the most important and successful classes of biopharmaceuticals. The highest variability and diversity of an antibody is concentrated on six hypervariable loops, also known as complementarity determining regions (CDRs) shaping the antigen-binding site, the paratope. Whereas it was assumed that certain sequences can only adopt a limited set of backbone conformations, in this study we present a kinetic classification of several paratope states in solution. Using molecular dynamics simulations in combination with experimental structural information we capture the involved conformational transitions between different canonical clusters and additional dominant solution structures occurring in the micro-to-millisecond timescale. Furthermore, we observe a strong correlation of CDR loop movements. Another important aspect when characterizing different paratope states is the relative VH/VL orientation and the influence of the distinct CDR loop states on the VH/VL interface. Conformational rearrangements of the CDR loops do not only have an effect on the relative VH/VL orientations, but also influence in some cases the elbow-angle dynamics and shift the respective distributions. Thus, our results show that antibodies exist as several interconverting paratope states, each contributing to the antibody's properties.

Structural Aspects of the Allergen-Antibody Interaction

The development of allergic disease involves the production of IgE antibodies upon allergen exposure in a process called sensitization. IgE binds to receptors on the surface of mast cells and basophils, and subsequent allergen exposure leads to cross-linking of IgE antibodies and release of cell mediators that cause allergy symptoms. Although this process is quite well-understood, very little is known about the epitopes on the allergen recognized by IgE, despite the importance of the allergen-antibody interaction for the allergic response to occur. This review discusses efforts to analyze allergen-antibody interactions, from the original epitope mapping studies using linear peptides or recombinant allergen fragments, to more sophisticated technologies, such as X-ray crystallography and nuclear magnetic resonance. These state-of-the-art approaches, combined with site-directed mutagenesis, have led to the identification of conformational IgE epitopes. The first structures of an allergen (egg lysozyme) in complex with Fab fragments from IgG antibodies were determined in the 1980s. Since then, IgG has been used as surrogate for IgE, due to the difficulty of obtaining monoclonal IgE antibodies. Technical developments including phage display libraries have contributed to progress in epitope mapping thanks to the isolation of IgE antibody constructs from combinatorial libraries made from peripheral blood mononuclear cells of allergic donors. Most recently, single B cell antibody sequencing and human hybridomas are new breakthrough technologies for finally obtaining human IgE monoclonal antibodies, ideal for epitope mapping. The information on antigenic determinants will facilitate the design of hypoallergens for immunotherapy and the investigation of the fundamental mechanisms of the IgE response.

Local and Global Rigidification Upon Antibody Affinity Maturation

During the affinity maturation process the immune system produces antibodies with higher specificity and activity through various rounds of somatic hypermutations in response to an antigen. Elucidating the affinity maturation process is fundamental in understanding immunity and in the development of biotherapeutics. Therefore, we analyzed 10 pairs of antibody fragments differing in their specificity and in distinct stages of affinity maturation using metadynamics in combination with molecular dynamics (MD) simulations. We investigated differences in flexibility of the CDR-H3 loop and global changes in plasticity upon affinity maturation. Among all antibody pairs we observed a substantial rigidification in flexibility and plasticity reflected in a substantial decrease of conformational diversity. To visualize and characterize these findings we used Markov-states models to reconstruct the kinetics of CDR-H3 loop dynamics and for the first time provide a method to define and localize surface plasticity upon affinity maturation.

Conformational selection of allergen-antibody complexes-surface plasticity of paratopes and epitopes

Antibodies have the ability to bind various types of antigens and to recognize different antibody-binding sites (epitopes) of the same antigen with different binding affinities. Due to the conserved structural framework of antibodies, their specificity to antigens is mainly determined by their antigen-binding site (paratope). Therefore, characterization of epitopes in combination with describing the involved conformational changes of the paratope upon binding is crucial in understanding and predicting antibody-antigen binding. Using molecular dynamics simulations complemented with strong experimental structural information, we investigated the underlying binding mechanism and the resulting local and global surface plasticity in the binding interfaces of distinct antibody-antigen complexes. In all studied allergen-antibody complexes, we clearly observe that experimentally suggested epitopes reveal less plasticity, while non-epitope regions show high surface plasticity. Surprisingly, the paratope shows higher conformational diversity reflected in substantially higher surface plasticity, compared to the epitope. This work allows a visualization and characterization of antibody-antigen interfaces and might have strong implications for antibody-antigen docking and in the area of epitope prediction.

Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces

Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.

Antibodies are highly important in research, biotechnology, and medical applications. Despite their great utility, however, many antibodies exhibit suboptimal stability and affinity, raising production costs and limiting their practical usefulness. To tackle this general limitation, we used deep mutational scanning to characterize the effects of mutations in an antibody variable fragment on its antigen-binding affinity. Surprisingly, many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface. We, therefore, developed an automated method, called AbLIFT (http://AbLIFT.weizmann.ac.il) to optimize this interface through design. Two unrelated antibodies were tested and showed improvements in expression levels, stability, and antigen-binding affinity. Since AbLIFT requires testing of only a few dozen specific designs, it may dramatically accelerate the development of promising antibodies into useful research and clinical tools.

Rapid characterization of secreted recombinant proteins by native mass spectrometry

Characterization of overexpressed proteins is essential for assessing their quality, and providing input for iterative redesign and optimization. This process is typically carried out following purification procedures that require pronounced cost of time and labor. Therefore, quality assessment of recombinant proteins with no prior purification offers a major advantage. Here, we report a native mass spectrometry method that enables characterization of overproduced proteins directly from culture media. Properties such as solubility, molecular weight, folding, assembly state, overall structure, post-translational modifications and binding to relevant biomolecules are immediately revealed. We show the applicability of the method for in-depth characterization of secreted recombinant proteins from eukaryotic systems such as yeast, insect, and human cells. This method, which can be readily extended to high-throughput analysis, considerably shortens the time gap between protein production and characterization, and is particularly suitable for characterizing engineered and mutated proteins, and optimizing yield and quality of overexpressed proteins.

Can alternative epitope mapping approaches increase the impact of B-cell epitopes in food allergy diagnostics?

In vitro allergy diagnostics are currently based on the detection of specific IgE binding on intact allergens or a mixture thereof. This approach has drawbacks as it may yield false‐negative and/or false‐positive results. Thus, we reviewed the impact of known B‐cell epitopes of food allergens to predict transience or persistence, tolerance or allergy and the severity of an allergic reaction and to examine new epitope mapping strategies meant to improve serum‐based allergy diagnostics. Recent epitope mapping approaches have been worthwhile in epitope identification and may increase the specificity of allergy diagnostics by using epitopes predominately recognized by allergic patients in some cases. However, these approaches did not lead to discrimination between clinically relevant and irrelevant epitopes so far, since the polyclonal serum IgE‐binding epitope spectrum seems to be too individual, independent of the disease status of the patients. New epitope mapping strategies are necessary to overcome these obstacles. The use of patient‐derived monoclonal antibodies instead of patient sera for functional characterization of clinically relevant and irrelevant epitope combinations, distinguished by their ability to induce degranulation, might be a promising approach to gain more insight into the allergic reaction and to improve serum‐based allergy diagnostics.

Food Allergen Epitope Mapping

With the increased global awareness and rise in food allergies, a multifold interest in food allergens is evident. The presence of undeclared food allergens results in expensive food recalls and increased risks of anaphylaxis for the sensitive individuals. Regardless of the allergenic food, the immunogen needs to be identified and detected before making any efforts to inactivate/eliminate it. In type I food allergies, protein immunogen cross-links immunoglobulin E, leading to basophil/mast cell degranulation, resulting in the symptoms that range from mild irritation to anaphylaxis. A portion/part of the protein, known as the epitope, can interact with either antibodies to elicit allergic reactions or T-cell receptors to initiate allergic sensitization. Antibody-recognized epitopes can be either a linear sequence of amino acids (linear epitope) or a three-dimensional motif (conformational epitope), while T-cell-receptor-recognized epitopes are exclusively linear peptides. Identifying and characterizing human-allergy-relevant epitopes are important for allergy diagnosis/prognosis, immunotherapy, and developing food processing methods that can reduce/eliminate immunogencity/immunoreactivity of the allergen.

Single Domain Antibodies as New Biomarker Detectors

Biomarkers are defined as indicators of biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. Biomarkers have been widely used for early detection, prediction of response after treatment, and for monitoring the progression of diseases. Antibodies represent promising tools for recognition of biomarkers, and are widely deployed as analytical tools in clinical settings. For immunodiagnostics, antibodies are now exploited as binders for antigens of interest across a range of platforms. More recently, the discovery of antibody surface display and combinatorial chemistry techniques has allowed the exploration of new binders from a range of animals, for instance variable domains of new antigen receptors (V_NAR) from shark and variable heavy chain domains (V_HH) or nanobodies from camelids. These single domain antibodies (sdAbs) have some advantages over conventional murine immunoglobulin owing to the lack of a light chain, making them the smallest natural biomarker binders thus far identified. In this review, we will discuss several biomarkers used as a means to validate diseases progress. The potential functionality of modern singe domain antigen binders derived from phylogenetically early animals as new biomarker detectors for current diagnostic and research platforms development will be described.

Modeling and fitting protein-protein complexes to predict change of binding energy

It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

Structural Repertoire of HIV-1-Neutralizing Antibodies Targeting the CD4 Supersite in 14 Donors

The site on the HIV-1 gp120 glycoprotein that binds the CD4 receptor is recognized by broadly reactive antibodies, several of which neutralize over 90% of HIV-1 strains. To understand how antibodies achieve such neutralization, we isolated CD4-binding-site (CD4bs) antibodies and analyzed 16 co-crystal structures -8 determined here- of CD4bs antibodies from 14 donors. The 16 antibodies segregated by recognition mode and developmental ontogeny into two types: CDR H3-dominated and VH-gene-restricted. Both could achieve greater than 80% neutralization breadth, and both could develop in the same donor. Although paratope chemistries differed, all 16 gp120-CD4bs antibody complexes showed geometric similarity, with antibody-neutralization breadth correlating with antibody-angle of approach relative to the most effective antibody of each type. The repertoire for effective recognition of the CD4 supersite thus comprises antibodies with distinct paratopes arrayed about two optimal geometric orientations, one achieved by CDR H3 ontogenies and the other achieved by VH-gene-restricted ontogenies.

Protein-protein docking with dynamic residue protonation states

Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc–FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

Protein-protein interactions are fundamental for biological function and are strongly influenced by their local environment. Cellular pH is tightly controlled and is one of the critical environmental factors that regulates protein-protein interactions. Three-dimensional structures of the protein complexes can help us understand the mechanism of the interactions. Since experimental determination of the structures of protein-protein complexes is expensive and time-consuming, computational docking algorithms are helpful to predict the structures. However, none of the current protein-protein docking algorithms account for the critical environmental pH effects. So we developed a pH-sensitive docking algorithm that can dynamically pick the favorable protonation states of the ionizable amino-acid residues. Compared to our previous standard docking algorithm, the new algorithm improves docking accuracy and generates higher-quality predictions over a large dataset of protein-protein complexes. We also use a case study to demonstrate efficacy of the algorithm in predicting a large pH-dependent binding affinity change that cannot be captured by the other methods that neglect pH effects. In principle, the approaches in the study can be used for rational design of pH-dependent protein inhibitors or industrial enzymes that are active over a wide range of pH values.

In situ click chemistry: from small molecule discovery to synthetic antibodies

Advances in the fields of proteomics, molecular imaging, and therapeutics are closely linked to the availability of affinity reagents that selectively recognize their biological targets. Here we present a review of Iterative Peptide In Situ Click Chemistry (IPISC), a novel screening technology for designing peptide multiligands with high affinity and specificity. This technology builds upon in situ click chemistry, a kinetic target-guided synthesis approach where the protein target catalyzes the conjugation of two small molecules, typically through the azide-alkyne Huisgen cycloaddition. Integrating this methodology with solid phase peptide libraries enables the assembly of linear and branched peptide multiligands we refer to as Protein Catalyzed Capture Agents (PCC Agents). The resulting structures can be thought of as analogous to the antigen recognition site of antibodies and serve as antibody replacements in biochemical and cell-based applications. In this review, we discuss the recent progress in ligand design through IPISC and related approaches, focusing on the improvements in affinity and specificity as multiligands are assembled by target-catalyzed peptide conjugation. We compare the IPISC process to small molecule in situ click chemistry with particular emphasis on the advantages and technical challenges of constructing antibody-like PCC Agents.

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Investigating allostery in molecular recognition: insights from a computational study of multiple antibody-antigen complexes

Antibody-antigen recognition plays a key role in the immune response against pathogens. Here, we have investigated various aspects of this problem by analyzing a large and diverse set of antibodies and their respective complexes with protein antigens through atomistic simulations. Common features of antibody response to the presence of antigens are elucidated by the analysis of the proteins' internal dynamics and coordination in different ligand states, combined with the analysis of the interaction networks implicated in the stabilization of functional structures. The use of a common structural reference reveals preferential changes in the dynamic coordination and intramolecular interaction networks induced by antigen binding and shared by all antibodies. Such changes propagate from the binding region through the whole immunoglobulin domains. Overall, complexed antibodies show more diffuse networks of nonbonded interactions and a general higher internal dynamic coordination, which preferentially involve the immunoglobulin (Ig) domains of the heavy chain. The combined results provide atomistic insights into the correlations between the modulation of conformational dynamics, structural stability, and allosteric signal transduction. In particular, the results suggest that specific networks of residues, shared among all the analyzed proteins, define the molecular pathways by which antibody structures respond to antigen binding. Our studies may have implications in practical use, such as the rational design of antibodies with specifically modulated antigen-binding affinities.

Engineering protein therapeutics: predictive performances of a structure-based virtual affinity maturation protocol

The implementation of a structure based virtual affinity maturation protocol and evaluation of its predictivity are presented. The in silico protocol is based on conformational sampling of the interface residues (using the Dead End Elimination/A* algorithm), followed by the estimation of the change of free energy of binding due to a point mutation, applying MM/PBSA calculations. Several implementations of the protocol have been evaluated for 173 mutations in 7 different protein complexes for which experimental data were available: the use of the Boltzamnn averaged predictor based on the free energy of binding (ΔΔG(*)) combined with the one based on its polar component only (ΔΔE(pol*)) led to the proposal of a subset of mutations out of which 45% would have successfully enhanced the binding. When focusing on those mutations that are less likely to be introduced by natural in vivo maturation methods (99 mutations with at least two base changes in the codon), the success rate is increased to 63%. In another evaluation, focusing on 56 alanine scanning mutations, the in silico protocol was able to detect 89% of the hot-spots.

Structure of Fab fragment of malaria transmission blocking antibody 2A8 against P. vivax P25 protein

Understanding the structural basis of recognition between antigen and antibody requires the structural comparison of free and complexed components. Previously, we have reported the crystal structure of the complex between Fab fragment of murine monoclonal antibody 2A8 (Fab2A8) and Plasmodium vivax P25 protein (Pvs25) at 3.2 Å resolution. We report here the crystallization and X-ray structure of native Fab2A8 at 4.0 Å resolution. The 2A8 antibody generated against Pvs25 prevents the formation of P. vivax oocysts in the mosquito, when assayed in membrane feeding experiment. Comparison of native Fab2A8 structure with antigen bound Fab2A8 structure indicates the significant conformational changes in CDR-H1 and CDR-H3 regions of V(H) domain and CDR-L3 region of V(L) domain of Fab2A8. Upon complex formation, the relative orientation between V(L) and V(H) domains of Fab2A8 is conserved, while significant differences are observed in elbow angles of heavy and light chains. The combing site residues of complexed Fab2A8 exhibited the reduced temperature factor compared to native Fab2A8, suggesting a loss of conformational entropy upon antigen binding.

Fab'-induced folding of antigenic N-terminal peptides from intrinsically disordered HIV-1 Tat revealed by X-ray crystallography

Tat, the transcriptional activator protein of human immunodeficiency virus type 1 (HIV-1), is critical for viral replication and is a potential HIV-1 vaccine candidate. This intrinsically disordered protein is present in the extracellular medium and is involved in the pathogenicity of HIV through its interaction with different cellular and viral biological partners. A monoclonal antibody termed 11H6H1, which is specific for the N-terminal region of Tat, was selected for a functional and structural study of the HIV-1 Tat protein. The equilibrium dissociation constants (K(d)) of Tat and Tat fragments complexed with 11H6H1 were estimated by competitive ELISA. Tat contains a single tryptophan residue, Trp11, located in the N-terminal region. We show that the substitution of Trp11 by a phenylalanine completely abolishes the binding of 11H6H1, whereas the transactivating activity of Tat is preserved. The epitope recognized by 11H6H1 was restricted to the 9-mer peptide P(6)KLEPWKHP(14) centered on Trp11. The crystal structures of this 9-mer peptide and of an overlapping 15-mer peptide were determined in complex with Fab' 11H6H1 at 2.4 Å and 2.1 Å resolution, respectively. Tat is intrinsically disordered and can undergo induced folding upon association with a biological partner. Our crystallographic study reveals that the two Tat peptides, which are lodged in the U-shaped groove of the Fab' antigen-binding site, adopt a standard type I β-turn conformation. The central Trp11 that is critical for Fab' recognition is further stabilized by π-stacking interactions. The structural and biological consequences of this induced folding in HIV pathogenesis are discussed.

On the use of structural templates for high-resolution docking

Reliable high-resolution prediction of protein complex structures starting from the free monomers is a considerable challenge toward large-scale mapping of the structural details of protein-protein interactions. The current major bottleneck is to model the conformational changes of the monomer backbone upon binding. We evaluate the use of homolog structures as source for conformational diversity, within the framework of RosettaDock-a leading high-resolution docking protocol. We find that the use of homolog templates can improve significantly the modeling of a complex structure, including known difficult cases. Several conformational changes however are not sampled by any of the templates, indicating the need for additional sources of conformational variability. Interestingly, the successful homolog templates are not restricted to a confined range of sequence identity, highlighting the importance of the backbone conformation rather than the sequence.

Computational mapping of anchoring spots on protein surfaces

Protein-protein and protein-peptide interactions are often controlled by few strong contacts that involve hot spot residues. Computational detection of such contacts, termed here anchoring spots, is important for understanding recognition processes and for predicting interactions; it is an essential step in designing interaction interfaces and therapeutic agents. We describe ANCHORSMAP, an algorithm for computational mapping of amino acid side chains on protein surfaces. The algorithm consists of two stages: A geometry based stage (LSMdet), in which sub-pockets adequate for binding single side chains are detected and amino acid probes are scattered near them, and an energy based stage in which optimal positions of the probes are determined through repeated energy minimization and clustering of nearby poses and their DeltaG are calculated. ANCHORSMAP employs a new function for DeltaG calculations, which is specifically designed for the context of protein-protein recognition by introducing a correction in the electrostatic energy term that compensates for the dielectric shielding exerted by a hypothetical protein bound to the probe. The algorithm successfully detects known anchoring sites and accurately positions the probes. The calculated DeltaG rank high the correct anchoring spots in maps produced for unbound proteins. We find that Arg, Trp, Glu and Tyr, which are favorite hot spot residues, are also more selective of their binding environment. The usefulness of anchoring spots mapping is demonstrated by detecting the binding surfaces in the protein-protein complex barnase/barstar and the protein-peptide complex kinase/PKI, and by identifying phenylalanine anchoring sites on the surface of the nuclear transporter NTF2, C-terminus anchors on PDZ domains and phenol anchors on thermolysin. Finally, we discuss the role of anchoring spots in molecular recognition processes.

SnugDock: paratope structural optimization during antibody-antigen docking compensates for errors in antibody homology models

High resolution structures of antibody-antigen complexes are useful for analyzing the binding interface and to make rational choices for antibody engineering. When a crystallographic structure of a complex is unavailable, the structure must be predicted using computational tools. In this work, we illustrate a novel approach, named SnugDock, to predict high-resolution antibody-antigen complex structures by simultaneously structurally optimizing the antibody-antigen rigid-body positions, the relative orientation of the antibody light and heavy chains, and the conformations of the six complementarity determining region loops. This approach is especially useful when the crystal structure of the antibody is not available, requiring allowances for inaccuracies in an antibody homology model which would otherwise frustrate rigid-backbone docking predictions. Local docking using SnugDock with the lowest-energy RosettaAntibody homology model produced more accurate predictions than standard rigid-body docking. SnugDock can be combined with ensemble docking to mimic conformer selection and induced fit resulting in increased sampling of diverse antibody conformations. The combined algorithm produced four medium (Critical Assessment of PRediction of Interactions-CAPRI rating) and seven acceptable lowest-interface-energy predictions in a test set of fifteen complexes. Structural analysis shows that diverse paratope conformations are sampled, but docked paratope backbones are not necessarily closer to the crystal structure conformations than the starting homology models. The accuracy of SnugDock predictions suggests a new genre of general docking algorithms with flexible binding interfaces targeted towards making homology models useful for further high-resolution predictions.

Antibodies are proteins that are key elements of the immune system and increasingly used as drugs. Antibodies bind tightly and specifically to antigens to block their activity or to mark them for destruction. Three-dimensional structures of the antibody-antigen complexes are useful for understanding their mechanism and for designing improved antibody drugs. Experimental determination of structures is laborious and not always possible, so we have developed tools to predict structures of antibody-antigen complexes computationally. Computer-predicted models of antibodies, or homology models, typically have errors which can frustrate algorithms for prediction of protein-protein interfaces (docking), and result in incorrect predictions. Here, we have created and tested a new docking algorithm which incorporates flexibility to overcome structural errors in the antibody structural model. The algorithm allows both intramolecular and interfacial flexibility in the antibody during docking, resulting in improved accuracy approaching that when using experimentally determined antibody structures. Structural analysis of the predicted binding region of the complex will enable the protein engineer to make rational choices for better antibody drug designs.

Rotamer optimization for protein design through MAP estimation and problem-size reduction

The search for the global minimum energy conformation (GMEC) of protein side chains is an important computational challenge in protein structure prediction and design. Using rotamer models, the problem is formulated as a NP-hard optimization problem. Dead-end elimination (DEE) methods combined with systematic A* search (DEE/A*) has proven useful, but may not be strong enough as we attempt to solve protein design problems where a large number of similar rotamers is eligible and the network of interactions between residues is dense. In this work, we present an exact solution method, named BroMAP (branch-and-bound rotamer optimization using MAP estimation), for such protein design problems. The design goal of BroMAP is to be able to expand smaller search trees than conventional branch-and-bound methods while performing only a moderate amount of computation in each node, thereby reducing the total running time. To achieve that, BroMAP attempts reduction of the problem size within each node through DEE and elimination by lower bounds from approximate maximum-a-posteriori (MAP) estimation. The lower bounds are also exploited in branching and subproblem selection for fast discovery of strong upper bounds. Our computational results show that BroMAP tends to be faster than DEE/A* for large protein design cases. BroMAP also solved cases that were not solved by DEE/A* within the maximum allowed time, and did not incur significant disadvantage for cases where DEE/A* performed well. Therefore, BroMAP is particularly applicable to large protein design problems where DEE/A* struggles and can also substitute for DEE/A* in general GMEC search.

Single domain antibodies: promising experimental and therapeutic tools in infection and immunity

Antibodies are important tools for experimental research and medical applications. Most antibodies are composed of two heavy and two light chains. Both chains contribute to the antigen-binding site which is usually flat or concave. In addition to these conventional antibodies, llamas, other camelids, and sharks also produce antibodies composed only of heavy chains. The antigen-binding site of these unusual heavy chain antibodies (hcAbs) is formed only by a single domain, designated VHH in camelid hcAbs and VNAR in shark hcAbs. VHH and VNAR are easily produced as recombinant proteins, designated single domain antibodies (sdAbs) or nanobodies. The CDR3 region of these sdAbs possesses the extraordinary capacity to form long fingerlike extensions that can extend into cavities on antigens, e.g., the active site crevice of enzymes. Other advantageous features of nanobodies include their small size, high solubility, thermal stability, refolding capacity, and good tissue penetration in vivo. Here we review the results of several recent proof-of-principle studies that open the exciting perspective of using sdAbs for modulating immune functions and for targeting toxins and microbes.

Crystal structure of the engineered neutralizing antibody M18 complexed to domain 4 of the anthrax protective antigen

The virulence of Bacillus anthracis is critically dependent on the cytotoxic components of the anthrax toxin, lethal factor (LF) and edema factor (EF). LF and EF gain entry into host cells through interactions with the protective antigen (PA), which binds to host cellular receptors such as CMG2. Antibodies that neutralize PA have been shown to confer protection in animal models and are undergoing intense clinical development. A murine monoclonal antibody, 14B7, has been reported to interact with domain 4 of PA (PAD4) and block its binding to CMG2. More recently, the 14B7 antibody was used as the platform for the selection of very high affinity, single-chain antibodies that have tremendous potential as a combination anthrax prophylactic and treatment. Here, we report the high-resolution X-ray structures of three high-affinity, single-chain antibodies in the 14B7 family; 14B7 and two high-affinity variants 1H and M18. In addition, we present the first neutralizing antibody-PA structure, M18 in complex with PAD4 at 3.8 A resolution. These structures provide insights into the mechanism of neutralization, and the effect of various mutations on antibody affinity, and enable a comparison between the binding of the M18 antibody and CMG2 with PAD4.

Structural basis of antibody-antigen interactions

Antibody molecules can be regarded as products of a protein engineering system for the generation of a virtually unlimited repertoire of complementary molecular surfaces. This extreme structural heterogeneity is required for recognition of the nearly infinite array of antigenic determinants. This chapter discusses the structures of antibodies and their specific recognition of antigens, the binding energetics of these interactions, the cross-reactivity and specificity of antibody-antigen interactions, the role of conformational flexibility in antigen recognition, and the structural basis of the antibody affinity maturation process.

PEPOP: computational design of immunogenic peptides

Background

Most methods available to predict protein epitopes are sequence based. There is a need for methods using 3D information for prediction of discontinuous epitopes and derived immunogenic peptides.

Results

PEPOP uses the 3D coordinates of a protein both to predict clusters of surface accessible segments that might correspond to epitopes and to design peptides to be used to raise antibodies that target the cognate antigen at specific sites. To verify the ability of PEPOP to identify epitopes, 13 crystallographically defined epitopes were compared with PEPOP clusters: specificity ranged from 0.75 to 1.00, sensitivity from 0.33 to 1.00, and the positive predictive value from 0.19 to 0.89. Comparison of these results with those obtained with two other prediction algorithms showed comparable specificity and slightly better sensitivity and PPV. To prove the capacity of PEPOP to predict immunogenic peptides that induce protein cross-reactive antibodies, several peptides were designed from the 3D structure of model antigens (IA-2, TPO, and IL8) and chemically synthesized. The reactivity of the resulting anti-peptides antibodies with the cognate antigens was measured. In 80% of the cases (four out of five peptides), the flanking protein sequence process (sequence-based) of PEPOP successfully proposed peptides that elicited antibodies cross-reacting with the parent proteins. Polyclonal antibodies raised against peptides designed from amino acids which are spatially close in the protein, but separated in the sequence, could also be obtained, although they were much less reactive. The capacity of PEPOP to design immunogenic peptides that induce antibodies suitable for a sandwich capture assay was also demonstrated.

Conclusion

PEPOP has the potential to guide experimentalists that want to localize an epitope or design immunogenic peptides for raising antibodies which target proteins at specific sites. More successful predictions of immunogenic peptides were obtained when a peptide was continuous as compared with peptides corresponding to discontinuous epitopes. PEPOP is available for use at .

An anti-urokinase plasminogen activator receptor (uPAR) antibody: crystal structure and binding epitope

Human urokinase-type plasminogen activator receptor (uPAR/CD87) is expressed at the invasive interface of the tumor-stromal microenvironment in many human cancers and interacts with a wide array of extracellular molecules. An anti-uPAR antibody (ATN615) was prepared using hybridoma technology. This antibody binds to uPAR in vitro with high affinity (K(d) approximately 1 nM) and does not interfere with uPA binding to uPAR. Here we report the crystal structure of the Fab fragment of ATN615 at 1.77 A and the analysis of ATN615-suPAR-ATF structure that was previously determined, emphasizing the ATN615-suPAR interaction. The complementarity determining regions (CDRs) of ATN615 consist of a high percentage of aromatic residues, and form a relatively flat and undulating surface. The ATN615 Fab fragment recognizes domain 3 of suPAR. The antibody-antigen recognition involves 11 suPAR residues and 12 Fab residues from five CDRs. Structural data suggest that Pro188, Asn190, Gly191, and Arg192 residues of uPAR are the key residues for the antibody recognition, while Pro189 and Arg192 render specificity of ATN615 for human uPAR. Interestingly, this antibody-antigen interface has a small contact area, mainly polar interaction with little hydrophobic character, yet has high binding strength. Furthermore, several solvent molecules (assigned as polyethylene glycols) were clearly visible in the binding interface between antibody and antigen, suggesting that solvent molecules may be important for the maximal binding between suPAR and ATN615 Fab. ATN615 undergoes small but noticeable changes in its CDR region upon antigen binding.

Early Protein Evolution: Building Domains from Ligand-binding Polypeptide Segments

It has been suggested that in the early evolution of proteins, segments of polypeptide, unable to fold in isolation, may have collapsed together to form folded proto-domains. We wondered whether the incorporation of segments with a pre-existing binding activity into a folded domain could, by fixing the ligand binding conformation and/or providing additional contacts, lead to large affinity improvements and provide an evolutionary advantage. As a model, we took a segment of polypeptide from hen egg lysozyme that in the native protein forms the binding interface with the monoclonal antibodies HyHEL5 and F10 (KD=60 pM). When expressed in bacteria the isolated segment was unfolded, readily proteolysed and only bound weakly to the antibodies (KD>1 microM). We then combined the segment with random genomic segments to create a repertoire of chimaeric polypeptides displayed on filamentous bacteriophage. By use of proteolysis (to select folded polypeptide) and anti-lysozyme antibodies (to select an active conformation) we isolated a folded dimeric protein with an enhanced antibody affinity (KD=400 pM). Unexpectedly the dimer also incorporated a single heme molecule (KD=33 nM) that stabilised the dimer (Tm=59 degrees C with heme, 35 degrees C without heme). These results show that the binding affinities of flexible polypeptide segments can be greatly enhanced on protein folding, and that the folding can be stabilised by prosthetic groups. This supports the hypothesis that sub-domain polypeptide segments with functional activities may have contributed to domain creation in early evolution.

Diversity in Hapten Recognition: Structural Study of an Anti-cocaine Antibody M82G2

Antibodies against cocaine and other drugs of abuse are the basis for diagnostic tests for the presence of those drugs in human serum. The 1.7A resolution crystal structure of the anti-cocaine monoclonal antibody M82G2 in complex with cocaine is presented. This structure determination was undertaken to establish the stereochemical features in the antibody binding site that confer specificity for cocaine, and as part of an ongoing project to understand the rules that govern molecular recognition. The cocaine-binding site can be characterized topologically as a narrow groove on the protein surface. The antibody utilizes water-mediated hydrogen bonding, and cation-pi and stacking (pi-pi) interactions to provide specificity. Comparison with the previously published structure of the anti-cocaine antibody GNC92H2 shows that binding of a small ligand can be achieved in diverse ways, both in terms of a binding site structure/topology and protein-ligand interactions.

The effect of resolution-dependent global shape modifications on rigid-body protein-protein docking

Docking unbound molecules presents a challenge in the case where no prior biological or bioinformatic knowledge exists. This is mainly due to differences between the structures of the molecules when in a complex and in the free state. Presumably, these differences interfere with the ability of protein-protein docking algorithms, which rely on a dominant shape descriptor, to identify the correct solution and rank it higher than false solutions. In this study we verify the notion that small discords in the molecular fit can be eliminated by using appropriately designed low-resolution shape descriptors, thereby improving the docking results. We exploit the inherent gradual resolution dependency of Fourier transforms and formulate a resolution-dependent shape descriptor by truncating selected Fourier transform terms. Thus, different levels of shape modification are attained, affecting the degree of detail in the depiction of the molecular surface. We applied the modified descriptor to a selection of 23 protein-protein systems, using the unbound structures where possible. The docking results obtained with the new geometric descriptor were considerably superior to former results, improving the ranks of nearly correct solutions for 17 systems. Unification of the results of scans in which different resolutions were employed further improved the ranks of nearly correct solutions to less than 100 for 12 of the 23 systems and less than 300 for 20 systems. The new geometric descriptor can be combined with other descriptors, which typify the electrostatic or hydrophobic character of the molecular surface, and with external experimental or bioinformatic data.

Structural convergence of antibody binding of carbohydrate determinants in Lewis Y tumor antigens

Antibodies targeting human epithelial carcinomas bearing Lewis Y (Le(y)) carbohydrate antigens provide a striking illustration of convergent immune recognition. We report a 1.9A resolution crystal structure of the Fab of a humanized antibody (hu3S193) in complex with the Le(y) tetrasaccharide, Fuc(alpha 1-->2)Gal(beta 1-->4)[Fuc(alpha 1-->3)]GlcNAc. Comparisons of the hu3S193 and BR96 antibodies bound to Le(y) tumor antigens revealed extremely similar mechanisms for recognition of the carbohydrate epitopes. Solvent plays a critical role in hu3S193 antibody binding to the Le(y) carbohydrate epitope. Specificity for Le(y) is maintained because a conserved pocket accepts an N-acetyl group of the core Gal(beta 1-->4)GlcNAc disaccharide. Closely related blood-group determinants (Le(a) and Le(b)) cannot enter the specificity pocket, making the Le(y) antibodies promising candidates for immunotherapy of epithelial cancer.

Phage-displayed antibody libraries of synthetic heavy chain complementarity determining regions

A structure-based approach was used to design libraries of synthetic heavy chain complementarity determining regions (CDRs). The CDR libraries were displayed as either monovalent or bivalent single-chain variable fragments (scFvs) with a single heavy chain variable domain scaffold and a fixed light chain variable domain. Using the structure of a parent antibody as a guide, we restricted library diversity to CDR positions with significant exposure to solvent. We introduced diversity with tailored degenerate codons that ideally only encoded for amino acids commonly observed in natural antibody CDRs. With these design principles, we reasoned that we would produce libraries of diverse solvent-exposed surfaces displayed on stable scaffolds with minimal structural perturbations. The libraries were sorted against a panel of proteins and yielded multiple unique binding clones against all six antigens tested. The bivalent library yielded numerous unique sequences, while the monovalent library yielded fewer unique clones. Selected scFvs were converted to the Fab format, and the purified Fab proteins retained high affinity for antigen. The results support the view that synthetic heavy chain diversity alone may be sufficient for the generation of high-affinity antibodies from phage-displayed libraries; thus, it may be possible to dispense with the light chain altogether, as is the case in natural camelid immunoglobulins.

Hydrophobic complementarity in protein-protein docking

Formation of hydrophobic contacts across a newly formed interface is energetically favorable. Based on this observation we developed a geometric-hydrophobic docking algorithm that estimates quantitatively the hydrophobic complementarity at protein-protein interfaces. Each molecule to be docked is represented as a grid of complex numbers, storing information regarding the shape of the molecule in the real part and information regarding the hydropathy of the surface in the imaginary part. The grid representations are correlated using fast Fourier transformations. The algorithm is used to compare the extent of hydrophobic complementarity in oligomers (represented by D2 tetramers) and in hetero-dimers of soluble proteins (complexes). We also test the implication of hydrophobic complementarity in distinguishing correct from false docking solutions. We find that hydrophobic complementarity at the interface exists in oligomers and in complexes, and in both groups the extent of such complementarity depends on the size of the interface. Thus, the non-polar portions of large interfaces are more often juxtaposed than non-polar portions of small interfaces. Next we find that hydrophobic complementarity helps to point out correct docking solutions. In oligomers it significantly improves the ranks of nearly correct reassembled and modeled tetramers. Combining geometric, electrostatic and hydrophobic complementarity for complexes gives excellent results, ranking a nearly correct solution < 10 for 5 of 23 tested systems, < 100 for 8 systems and < 1000 for 19 systems.

Structural mechanism for affinity maturation of an anti-lysozyme antibody

In the immune response against a typical T cell-dependent protein antigen, the affinity maturation process is fast and is associated with the early class switch from IgM to IgG. As such, a comprehension of the molecular basis of affinity maturation could be of great importance in biomedical and biotechnological applications. Affinity maturation of anti-protein antibodies has been reported to be the result of small structural changes, mostly confined to the periphery of the antigen-combining site. However, little is understood about how these small structural changes account for the increase in the affinity toward the antigen. Herein, we present the three-dimensional structure of the Fab fragment from BALB/c mouse mAb F10.6.6 in complex with the antigen lysozyme. This antibody was obtained from a long-term exposure to the antigen. mAb F10.6.6, and the previously described antibody D44.1, are the result of identical or nearly identical somatic recombination events. However, different mutations in the framework and variable regions result in an approximately 10(3) higher affinity for the F10.6.6 antibody. The comparison of the three-dimensional structures of these Fab-lysozyme complexes reveals that the affinity maturation produces a fine tuning of the complementarity of the antigen-combining site toward the epitope, explaining at the molecular level how the immune system is able to increase the affinity of an anti-protein antibody to subnanomolar levels.

The crystal structure of human angiogenin in complex with an antitumor neutralizing antibody

The murine monoclonal antibody 26-2F neutralizes the angiogenic and ribonucleolytic activities of human angiogenin (ANG) and is highly effective in preventing the establishment and metastatic dissemination of human tumors in athymic mice. Here we report a 2.0 A resolution crystal structure for the complex of ANG with the Fab fragment of 26-2F that reveals the detailed interactions between ANG and the complementarity-determining regions (CDRs) of the antibody. Surprisingly, Fab binding induces a dramatic conformational change in the cell binding region of ANG at the opposite end of the molecule from the combining site; crosslinking experiments indicate that this rearrangement also occurs in solution. The ANG-Fab complex structure should be invaluable for designing maximally humanized versions of 26-2F for potential clinical use.

Quantitative account of the enhanced affinity of two linked scFvs specific for different epitopes on the same antigen

Protein and other antigens typically have a number of different epitopes. This presents an opportunity for designing high-affinity antibodies by connecting via a flexible peptide linker two antibody fragments recognizing non-overlapping epitopes on the same antigen. The same strategy was employed in natural and designed DNA-binding proteins. According to a previous theory, the linking enhances the antigen-binding affinity over those of the individual antibody fragments (with association constants K(A) and K(B)) by p(d(0))K(B) or p(d(0))K(A), where p(d(0))=(3/4pil(p)bL)(3/2)exp(-3d(0)(2)/4l(p)bL)(1-5l(p)/4bL+ cdots, three dots, centered ) is the probability density for the end-to-end vector of the flexible linker with L residues to have a distance d(0). The predicted affinity enhancement is found to be actually approached by a bi-specific antibody against hen egg lysozyme consisting of scFv fragments of D1.3 and HyHEL-10. The wide applicability of the theory is demonstrated by diverse examples of protein-protein interactions constrained by flexible linkers.

Molecular recognition in antibody-antigen complexes

With the numerous detailed molecular descriptions of antibody-antigen interfaces, the structual study of these molecular interactions has evolved from an attempt to understand to immunological function to their use as model systems for protein-protein interactions. In this chapter, we describe the structual aspects common to antibody-antigen interfaces and discuss the roles they may play in antibody cross-rectivity and molecular mimicry. More detailed analysis of these interfaces has required the marriage of structural studies with extensive mutagenesis and thermodynamic analysis efforts. Here, we discuss the thermodynamic mapping of interfaces for two model antibody-antigen complexes, including the identification of thermodynamic hot spots in binding and the various mechanism used to accommodate interface mutations. We also discuss the functional roles for protein plasticity in antigen recognition, including the entropic control of antibody affinity maturation and the use of induced fit mechanism of different types and to varying degrees by mature antibodies in binding their specific antigens.

Generation of a functional monomolecular protein lattice consisting of an s-layer fusion protein comprising the variable domain of a camel heavy chain antibody

Crystalline bacterial cell surface layer (S-layer) proteins are composed of a single protein or glycoprotein species. Isolated S-layer subunits frequently recrystallize into monomolecular protein lattices on various types of solid supports. For generating a functional protein lattice, a chimeric protein was constructed, which comprised the secondary cell wall polymer-binding region and the self-assembly domain of the S-layer protein SbpA from Bacillus sphaericus CCM 2177, and a single variable region of a heavy chain camel antibody (cAb-Lys3) recognizing lysozyme as antigen. For construction of the S-layer fusion protein, the 3'-end of the sequence encoding the C-terminally truncated form rSbpA(31)(-)(1068) was fused via a short linker to the 5'-end of the sequence encoding cAb-Lys3. The functionality of the fused cAb-Lys3 in the S-layer fusion protein was proved by surface plasmon resonance measurements. Dot blot assays revealed that the accessibility of the fused functional sequence for the antigen was independent of the use of soluble or assembled S-layer fusion protein. Recrystallization of the S-layer fusion protein into the square lattice structure was observed on peptidoglycan-containing sacculi of B. sphaericus CCM 2177, on polystyrene or on gold chips precoated with thiolated secondary cell wall polymer, which is the natural anchoring molecule for the S-layer protein in the bacterial cell wall. Thereby, the fused cAb-Lys3 remained located on the outer S-layer surface and accessible for lysozyme binding. Together with solid supports precoated with secondary cell wall polymers, S-layer fusion proteins comprising rSbpA(31)(-)(1068) and cAbs directed against various antigens shall be exploited for building up monomolecular functional protein lattices as required for applications in nanobiotechnology.