Energy-based analysis and prediction of the orientation between light- and heavy-chain antibody variable domains

Synthetic Glycans Reveal Determinants of Antibody Functional Efficacy against a Fungal Pathogen

Antibodies play a vital role in the immune response to infectious diseases and can be administered passively to protect patients. In the case of Cryptococcus neoformans, a WHO critical priority fungal pathogen, infection results in antibodies targeting capsular glucuronoxylomannan (GXM). These antibodies yield protective, non-protective, and disease-enhancing outcomes when administered passively. However, it was unknown how these distinct antibodies recognized their antigens at the molecular level, leading to the hypothesis that they may target different GXM epitopes. To test this hypothesis, we constructed a microarray containing 26 glycans representative of those found in highly virulent cryptococcal strains and utilized it to study 16 well-characterized monoclonal antibodies. Notably, we found that protective and non-protective antibodies shared conserved reactivity to the M2 motif of GXM, irrespective of the strain used in infection or GXM-isolated to produce a conjugate vaccine. Here, only two antibodies, 12A1 and 18B7, exhibited diverse trivalent GXM motif reactivity. IgG antibodies associated with protective responses showed cross-reactivity to at least two GXM motifs. This molecular understanding of antibody binding epitopes was used to map the antigenic diversity of two Cryptococcus neoformans strains, which revealed the exceptional complexity of fungal capsular polysaccharides. A multi-GXM motif vaccine holds the potential to effectively address this antigenic diversity. Collectively, these findings underscore the context-dependent nature of antibody function and challenge the classification of anti-GXM epitopes as either "protective" or "non-protective".

abYpap: improvements to the prediction of antibody VH/VL packing using gradient boosted regression

The Fv region of the antibody (comprising VH and VL domains) is the area responsible for target binding and thus the antibody's specificity. The orientation, or packing, of these two domains relative to each other influences the topography of the Fv region, and therefore can influence the antibody's binding affinity. We present abYpap, an improved method for predicting the packing angle between the VH and VL domains. With the large data set now available, we were able to expand greatly the number of features that could be used compared with our previous work. The machine-learning model was tuned for improved performance using 37 selected residues (previously 13) and also by including the lengths of the most variable 'complementarity determining regions' (CDR-L1, CDR-L2 and CDR-H3). Our method shows large improvements from the previous version, and also against other modeling approaches, when predicting the packing angle.

Changes in antibody binding and functionality after humanizing a murine scFv anti-IFN-α2: From in silico studies to experimental analysis

The structural and dynamic changes introduced during antibody humanization continue to be a topic open to new contributions. For this reason, the study of structural and functional changes of a murine scFv (mu.scFv) anti-rhIFN-α2b after humanization was carried out. As it was shown by long molecular dynamics simulations and circular dichroism analysis, changes in primary sequence affected the tertiary structure of the humanized scFv (hz.scFv): the position of the variable domain of light chain (VL) respective to the variable domain of heavy chain (VH) in each scFv molecule was different. This change mainly impacted on conformation and dynamics of the complementarity-determining region 3 of VH (CDR-H3) which led to changes in the specificity and affinity of humanized scFv (hz.scFv). These observations agree with experimental results that showed a decrease in the antigen-binding strength of hz.scFv, and different capacities of these molecules to neutralize the in vitro rhIFN-α2b biological activity. Besides, experimental studies to characterize antigen-antibody binding showed that mu.scFv and hz.scFv bind to the same antigen area and recognize a conformational epitope, which is evidence of docking results. Finally, the differences between these molecules to neutralize the in vitro rhIFN-α2b biological activity were described as a consequence of the blockade of certain functionally relevant amino acids of the cytokine, after scFv binding. All these observations confirmed that humanization affected the affinity and specificity of hz.scFv and pointed out that two specific changes in the frameworks would be responsible.

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.

Mutations in the SARS-CoV-2 spike RBD are responsible for stronger ACE2 binding and poor anti-SARS-CoV mAbs cross-neutralization

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is a novel beta coronavirus. SARS-CoV-2 uses spike glycoprotein to interact with host angiotensin-converting enzyme 2 (ACE2) and ensure cell recognition. High infectivity of SARS-CoV-2 raises questions on spike-ACE2 binding affinity and its neutralization by anti-SARS-CoV monoclonal antibodies (mAbs). Here, we observed Val-to-Lys417 mutation in the receptor-binding domains (RBD) of SARS-CoV-2, which established a Lys-Asp electrostatic interaction enhancing its ACE2-binding. Pro-to-Ala475 substitution and Gly482 insertion in the AGSTPCNGV-loop of RBD possibly hinders neutralization of SARS-CoV-2 by anti-SARS-CoV mAbs. In addition, we identified unique and structurally conserved conformational-epitopes on RBDs, which can be potential therapeutic targets. Collectively, we provide new insights into the mechanisms underlying the high infectivity of SARS-CoV-2 and development of effective neutralizing agents.

Antigen-Antibody Complexes

In vertebrates, immunoglobulins (Igs), commonly known as antibodies, play an integral role in the armamentarium of immune defense against various pathogens. After an antigenic challenge, antibodies are secreted by differentiated B cells called plasma cells. Antibodies have two predominant roles that involve specific binding to antigens to launch an immune response, along with activation of other components of the immune system to fight pathogens. The ability of immunoglobulins to fight against innumerable and diverse pathogens lies in their intrinsic ability to discriminate between different antigens. Due to this specificity and high affinity for their antigens, antibodies have been a valuable and indispensable tool in research, diagnostics and therapy. Although seemingly a simple maneuver, the association between an antibody and its antigen, to make an antigen-antibody complex, is comprised of myriads of non-covalent interactions. Amino acid residues on the antigen binding site, the epitope, and on the antibody binding site, the paratope, intimately contribute to the energetics needed for the antigen-antibody complex stability. Structural biology methods to study antigen-antibody complexes are extremely valuable tools to visualize antigen-antibody interactions in detail; this helps to elucidate the basis of molecular recognition between an antibody and its specific antigen. The main scope of this chapter is to discuss the structure and function of different classes of antibodies and the various aspects of antigen-antibody interactions including antigen-antibody interfaces-with a special focus on paratopes, complementarity determining regions (CDRs) and other non-CDR residues important for antigen binding and recognition. Herein, we also discuss methods used to study antigen-antibody complexes, antigen recognition by antibodies, types of antigens in complexes, and how antigen-antibody complexes play a role in modern day medicine and human health. Understanding the molecular basis of antigen binding and recognition by antibodies helps to facilitate the production of better and more potent antibodies for immunotherapy, vaccines and various other applications.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

Constant domain-exchanged Fab enables specific light chain pairing in heterodimeric bispecific SEED-antibodies

BACKGROUND

Bispecific antibodies promise to broadly expand the clinical utility of monoclonal antibody technology. Several approaches for heterodimerization of heavy chains have been established to produce antibodies with two different Fab arms, but promiscuous pairing of heavy and light chains remains a challenge for their manufacturing.

METHODS

We have designed a solution in which the C_H1 and C_L domain pair in one of the Fab fragments is replaced with a C_H3-domain pair and heterodimerized to facilitate correct modified Fab-chain pairing in bispecific heterodimeric antibodies based on a strand-exchange engineered domain (SEED) scaffold with specificity for epithelial growth factor receptor and either CD3 or CD16 (FcγRIII).

RESULTS

Bispecific antibodies retained binding to their target antigens and redirected primary T cells or NK cells to induce potent killing of target cells. All antibodies were expressed at a high yield in Expi293F cells, were detected as single sharp symmetrical peaks in size exclusion chromatography and retained high thermostability. Mass spectrometric analysis revealed specific heavy-to-light chain pairing for the bispecific SEED antibodies as well as for one-armed SEED antibodies co-expressed with two different competing light chains.

CONCLUSION

Incorporation of a constant domain-exchanged Fab fragment into a SEED antibody yields functional molecules with favorable biophysical properties.

GENERAL SIGNIFICANCE

Our results show that the novel engineered bispecific SEED antibody scaffold with an incorporated Fab fragment with C_H3-exchanged constant domains is a promising tool for the generation of complete heterodimeric bispecific antibodies with correct light chain pairing.

A natively paired antibody library yields drug leads with higher sensitivity and specificity than a randomly paired antibody library

Deep sequencing and single-chain variable fragment (scFv) yeast display methods are becoming more popular for discovery of therapeutic antibody candidates in mouse B cell repertoires. In this study, we compare a deep sequencing and scFv display method that retains native heavy and light chain pairing with a related method that randomly pairs heavy and light chain. We performed the studies in a humanized mouse, using interleukin 21 receptor (IL-21R) as a test immunogen. We identified 44 high-affinity binder scFv with the native pairing method and 100 high-affinity binder scFv with the random pairing method. 30% of the natively paired scFv binders were also discovered with the randomly paired method, and 13% of the randomly paired binders were also discovered with the natively paired method. Additionally, 33% of the scFv binders discovered only in the randomly paired library were initially present in the natively paired pre-sort library. Thus, a significant proportion of “randomly paired” scFv were actually natively paired. We synthesized and produced 46 of the candidates as full-length antibodies and subjected them to a panel of binding assays to characterize their therapeutic potential. 87% of the antibodies were verified as binding IL-21R by at least one assay. We found that antibodies with native light chains were more likely to bind IL-21R than antibodies with non-native light chains, suggesting a higher false positive rate for antibodies from the randomly paired library. Additionally, the randomly paired method failed to identify nearly half of the true natively paired binders, suggesting a higher false negative rate. We conclude that natively paired libraries have critical advantages in sensitivity and specificity for antibody discovery programs.

In silico methods for design of biological therapeutics

It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.

Determinants of the assembly and function of antibody variable domains

The antibody Fv module which binds antigen consists of the variable domains V_L and V_H. These exhibit a conserved ß-sheet structure and comprise highly variable loops (CDRs). Little is known about the contributions of the framework residues and CDRs to their association. We exchanged conserved interface residues as well as CDR loops and tested the effects on two Fvs interacting with moderate affinities (K_Ds of ~2.5 µM and ~6 µM). While for the rather instable domains, almost all mutations had a negative effect, the more stable domains tolerated a number of mutations of conserved interface residues. Of particular importance for Fv association are V_LP44 and V_HL45. In general, the exchange of conserved residues in the V_L/V_H interface did not have uniform effects on domain stability. Furthermore, the effects on association and antigen binding do not strictly correlate. In addition to the interface, the CDRs modulate the variable domain framework to a significant extent as shown by swap experiments. Our study reveals a complex interplay of domain stability, association and antigen binding including an unexpected strong mutual influence of the domain framework and the CDRs on stability/association on the one side and antigen binding on the other side.

Computational Tools for Aiding Rational Antibody Design

Antibodies are a group of proteins responsible for mediating immune reactions in vertebrates. They are able to bind a variety of structural motifs on noxious molecules tagging them for elimination from the organism. As a result of their versatile binding properties, antibodies are currently one of the most important classes of biopharmaceuticals. In this chapter, we discuss how knowledge-based computational methods can aid experimentalists in the development of potent antibodies. When using common experimental methods for antibody development, we often know the sequence of an antibody that binds to our molecule, antigen, of interest. We may also have a structure or model of the antigen. In these cases, computational methods can help by both modeling the antibody and identifying the antibody-antigen contact residues. This information can then play a key role in the rational design of more potent antibodies.

Structural diversity in a human antibody germline library

To support antibody therapeutic development, the crystal structures of a set of 16 germline variants composed of 4 different kappa light chains paired with 4 different heavy chains have been determined. All four heavy chains of the antigen-binding fragments (Fabs) have the same complementarity-determining region (CDR) H3 that was reported in an earlier Fab structure. The structure analyses include comparisons of the overall structures, canonical structures of the CDRs and the VH:VL packing interactions. The CDR conformations for the most part are tightly clustered, especially for the ones with shorter lengths. The longer CDRs with tandem glycines or serines have more conformational diversity than the others. CDR H3, despite having the same amino acid sequence, exhibits the largest conformational diversity. About half of the structures have CDR H3 conformations similar to that of the parent; the others diverge significantly. One conclusion is that the CDR H3 conformations are influenced by both their amino acid sequence and their structural environment determined by the heavy and light chain pairing. The stem regions of 14 of the variant pairs are in the ‘kinked’ conformation, and only 2 are in the extended conformation. The packing of the VH and VL domains is consistent with our knowledge of antibody structure, and the tilt angles between these domains cover a range of 11 degrees. Two of 16 structures showed particularly large variations in the tilt angles when compared with the other pairings. The structures and their analyses provide a rich foundation for future antibody modeling and engineering efforts.

Shape complementarity and hydrogen bond preferences in protein-protein interfaces: implications for antibody modeling and protein-protein docking

MOTIVATIONS

Characterizing protein-protein interfaces and the hydrogen bonds is a first step to better understand proteins' structures and functions toward high-resolution protein design. However, there are few large-scale surveys of hydrogen bonds of interfaces. In addition, previous work of shape complementarity of protein complexes suggested that lower shape complementarity in antibody-antigen interfaces is related to their evolutionary origin.

RESULTS

Using 6637 non-redundant protein-protein interfaces, we revealed peculiar features of various protein complex types. In contrast to previous findings, the shape complementarity of antibody-antigen interfaces resembles that of the other interface types. These results highlight the importance of hydrogen bonds during evolution of protein interfaces and rectify the prevailing belief that antibodies have lower shape complementarity.

CONTACT

jgray@jhu.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Antibody humanization by structure-based computational protein design

Antibodies derived from non-human sources must be modified for therapeutic use so as to mitigate undesirable immune responses. While complementarity-determining region (CDR) grafting-based humanization techniques have been successfully applied in many cases, it remains challenging to maintain the desired stability and antigen binding affinity upon grafting. We developed an alternative humanization approach called CoDAH ("Computationally-Driven Antibody Humanization") in which computational protein design methods directly select sets of amino acids to incorporate from human germline sequences to increase humanness while maintaining structural stability. Retrospective studies show that CoDAH is able to identify variants deemed beneficial according to both humanness and structural stability criteria, even for targets lacking crystal structures. Prospective application to TZ47, a murine anti-human B7H6 antibody, demonstrates the approach. Four diverse humanized variants were designed, and all possible unique VH/VL combinations were produced as full-length IgG1 antibodies. Soluble and cell surface expressed antigen binding assays showed that 75% (6 of 8) of the computationally designed VH/VL variants were successfully expressed and competed with the murine TZ47 for binding to B7H6 antigen. Furthermore, 4 of the 6 bound with an estimated KD within an order of magnitude of the original TZ47 antibody. In contrast, a traditional CDR-grafted variant could not be expressed. These results suggest that the computational protein design approach described here can be used to efficiently generate functional humanized antibodies and provide humanized templates for further affinity maturation.

Prediction of VH-VL domain orientation for antibody variable domain modeling

The antigen-binding site of antibodies forms at the interface of their two variable domains, VH and VL, making VH-VL domain orientation a factor that codetermines antibody specificity and affinity. Preserving VH-VL domain orientation in the process of antibody engineering is important in order to retain the original antibody properties, and predicting the correct VH-VL orientation has also been recognized as an important factor in antibody homology modeling. In this article, we present a fast sequence-based predictor that predicts VH-VL domain orientation with Q(2) values ranging from 0.54 to 0.73 on the evaluation set. We describe VH-VL orientation in terms of the six absolute ABangle parameters that have recently been proposed as a means to separate the different degrees of freedom of VH-VL domain orientation. In order to assess the impact of adjusting VH-VL orientation according to our predictions, we use the set of antibody structures of the recently published Antibody Modeling Assessment (AMA) II study. In comparison to the original AMAII homology models, we find an improvement in the accuracy of VH-VL orientation modeling, which also translates into an improvement in the average root-mean-square deviation with regard to the crystal structures.

Antibodies: Computer-Aided Prediction of Structure and Design of Function

With the advent of high-throughput sequencing, and the increased availability of experimental structures of antibodies and antibody-antigen complexes, comes the improvement of computational approaches to predict the structure and design the function of antibodies and antibody-antigen complexes. While antibodies pose formidable challenges for protein structure prediction and design due to their large size and highly flexible loops in the complementarity-determining regions, they also offer exciting opportunities: the central importance of antibodies for human health results in a wealth of structural and sequence information that—as a knowledge base—can drive the modeling algorithms by limiting the conformational and sequence search space to likely regions of success. Further, efficient experimental platforms exist to test predicted antibody structure or designed antibody function, thereby leading to an iterative feedback loop between computation and experiment. We briefly review the history of computer-aided prediction of structure and design of function in the antibody field before we focus on recent methodological developments and the most exciting application examples.

Affinity maturation in an HIV broadly neutralizing B-cell lineage through reorientation of variable domains

Rapidly evolving pathogens, such as human immunodeficiency and influenza viruses, escape immune defenses provided by most vaccine-induced antibodies. Proposed strategies to elicit broadly neutralizing antibodies require a deeper understanding of antibody affinity maturation and evolution of the immune response to vaccination or infection. In HIV-infected individuals, viruses and B cells evolve together, creating a virus-antibody "arms race." Analysis of samples from an individual designated CH505 has illustrated the interplay between an antibody lineage, CH103, and autologous viruses at various time points. The CH103 antibodies, relatively broad in their neutralization spectrum, interact with the CD4 binding site of gp120, with a contact dominated by CDRH3. We show by analyzing structures of progenitor and intermediate antibodies and by correlating them with measurements of binding to various gp120s that there was a shift in the relative orientation of the light- and heavy-chain variable domains during evolution of the CH103 lineage. We further show that mutations leading to this conformational shift probably occurred in response to insertions in variable loop 5 (V5) of the HIV envelope. The shift displaced the tips of the light chain away from contact with V5, making room for the inserted residues, which had allowed escape from neutralization by the progenitor antibody. These results, which document the selective mechanism underlying this example of a virus-antibody arms race, illustrate the functional significance of affinity maturation by mutation outside the complementarity determining region surface of the antibody molecule.

Assessment of fully automated antibody homology modeling protocols in molecular operating environment

The success of antibody-based drugs has led to an increased demand for predictive computational tools to assist antibody engineering efforts surrounding the six hypervariable loop regions making up the antigen binding site. Accurate computational modeling of isolated protein loop regions can be quite difficult; consequently, modeling an antigen binding site that includes six loops is particularly challenging. In this work, we present a method for automatic modeling of the FV region of an immunoglobulin based upon the use of a precompiled antibody x-ray structure database, which serves as a source of framework and hypervariable region structural templates that are grafted together. We applied this method (on common desktop hardware) to the Second Antibody Modeling Assessment (AMA-II) target structures as well as an experimental specialized CDR-H3 loop modeling method. The results of the computational structure predictions will be presented and discussed.

Antibody modeling assessment II. Structures and models

To assess the state-of-the-art in antibody structure modeling, a blinded study was conducted. Eleven unpublished Fab crystal structures were used as a benchmark to compare Fv models generated by seven structure prediction methodologies. In the first round, each participant submitted three non-ranked complete Fv models for each target. In the second round, CDR-H3 modeling was performed in the context of the correct environment provided by the crystal structures with CDR-H3 removed. In this report we describe the reference structures and present our assessment of the models. Some of the essential sources of errors in the predictions were traced to the selection of the structure template, both in terms of the CDR canonical structures and VL/VH packing. On top of this, the errors present in the Protein Data Bank structures were sometimes propagated in the current models, which emphasized the need for the curated structural database devoid of errors. Modeling non-canonical structures, including CDR-H3, remains the biggest challenge for antibody structure prediction.

Redistribution of flexibility in stabilizing antibody fragment mutants follows Le Châtelier's principle

Le Châtelier's principle is the cornerstone of our understanding of chemical equilibria. When a system at equilibrium undergoes a change in concentration or thermodynamic state (i.e., temperature, pressure, etc.), La Châtelier's principle states that an equilibrium shift will occur to offset the perturbation and a new equilibrium is established. We demonstrate that the effects of stabilizing mutations on the rigidity ⇔ flexibility equilibrium within the native state ensemble manifest themselves through enthalpy-entropy compensation as the protein structure adjusts to restore the global balance between the two. Specifically, we characterize the effects of mutation to single chain fragments of the anti-lymphotoxin-β receptor antibody using a computational Distance Constraint Model. Statistically significant changes in the distribution of both rigidity and flexibility within the molecular structure is typically observed, where the local perturbations often lead to distal shifts in flexibility and rigidity profiles. Nevertheless, the net gain or loss in flexibility of individual mutants can be skewed. Despite all mutants being exclusively stabilizing in this dataset, increased flexibility is slightly more common than increased rigidity. Mechanistically the redistribution of flexibility is largely controlled by changes in the H-bond network. For example, a stabilizing mutation can induce an increase in rigidity locally due to the formation of new H-bonds, and simultaneously break H-bonds elsewhere leading to increased flexibility distant from the mutation site via Le Châtelier. Increased flexibility within the VH β4/β5 loop is a noteworthy illustration of this long-range effect.

Antibody variable domain interface and framework sequence requirements for stability and function by high-throughput experiments

Protein structural stability and biological functionality are dictated by the formation of intradomain cores and interdomain interfaces, but the intricate sequence-structure-function interrelationships in the packing of protein cores and interfaces remain difficult to elucidate due to the intractability of enumerating all packing possibilities and assessing the consequences of all the variations. In this work, groups of β strand residues of model antibody variable domains were randomized with saturated mutagenesis and the functional variants were selected for high-throughput sequencing and high-throughput thermal stability measurements. The results show that the sequence preferences of the intradomain hydrophobic core residues are strikingly flexible among hydrophobic residues, implying that these residues are coupled indirectly with antigen binding through energetic stabilization of the protein structures. By contrast, the interdomain interface residues are directly coupled with antigen binding. The interdomain interface should be treated as an integral part of the antigen-binding site.

A systematic comparison of free and bound antibodies reveals binding-related conformational changes

To study structural changes that occur in Abs upon Ag binding, we systematically compared free and bound structures of all 141 crystal structures of the 49 Abs that were solved in these two forms. We found that many structural changes occur far from the Ag binding site. Some of them may constitute a mechanism for the recently suggested allosteric effects in Abs. Within the binding site itself, CDR-H3 is the only element that shows significant binding-related conformational changes; however, this occurs in only one third of the Abs. Beyond the binding site, Ag binding is associated with changes in the relative orientation of the H and L chains in both the variable and constant domains. An even larger change occurs in the elbow angle between the variable and the constant domains, and it is significantly larger for binding of big Ags than for binding of small ones. The most consistent and substantial conformational changes occur in a loop in the H chain constant domain. This loop is implicated in the interaction between the H and L chains, is often intrinsically disordered, and is involved in complement binding. Hence, we suggest that it may have a role in Ab function. These findings provide structural insight into the recently proposed allosteric effects in Abs.

Computer-aided antibody design

Recent clinical trials using antibodies with low toxicity and high efficiency have raised expectations for the development of next-generation protein therapeutics. However, the process of obtaining therapeutic antibodies remains time consuming and empirical. This review summarizes recent progresses in the field of computer-aided antibody development mainly focusing on antibody modeling, which is divided essentially into two parts: (i) modeling the antigen-binding site, also called the complementarity determining regions (CDRs), and (ii) predicting the relative orientations of the variable heavy (V(H)) and light (V(L)) chains. Among the six CDR loops, the greatest challenge is predicting the conformation of CDR-H3, which is the most important in antigen recognition. Further computational methods could be used in drug development based on crystal structures or homology models, including antibody-antigen dockings and energy calculations with approximate potential functions. These methods should guide experimental studies to improve the affinities and physicochemical properties of antibodies. Finally, several successful examples of in silico structure-based antibody designs are reviewed. We also briefly review structure-based antigen or immunogen design, with application to rational vaccine development.

Germline VH/VL pairing in antibodies

Antibodies are key molecules of the adaptive immune response and are now a major class of biopharmaceuticals. Pairing of heavy and light chains is one of the ways of generating antibody diversity and, while little is known about mechanisms governing V(H)/V(L) pairing, previous studies have suggested that the germline source from which chains are paired is random. By selecting paired antibody protein sequences from human and mouse antibodies from the KabatMan database and mapping them onto their corresponding germline sequences, we find that pairing preferences do exist in the germline, but only for a small proportion of germline gene segments; others are much more promiscuous showing no preferences. The closest equivalent human and mouse gene families were identified and pairing preferences compared. This work may impact on the ability to generate more stable antibodies for use as biopharmaceuticals.

IBC's 22nd Annual Antibody Engineering and 9th Annual Antibody Therapeutics International Conferences and the 2011 Annual Meeting of The Antibody Society, December 5-8, 2011, San Diego, CA

The 22nd Annual Antibody Engineering and 9th Annual Antibody Therapeutics international conferences, and the 2011 Annual Meeting of The Antibody Society, organized by IBC Life Sciences with contributions from The Antibody Society and two Scientific Advisory Boards, were held December 5-8, 2011 in San Diego, CA. The meeting drew ~800 participants who attended sessions on a wide variety of topics relevant to antibody research and development. As a preview to the main events, a pre-conference workshop held on December 4, 2011 focused on antibodies as probes of structure. The Antibody Engineering Conference comprised eight sessions: (1) structure and dynamics of antibodies and their membrane receptor targets; (2) model-guided generation of binding sites; (3) novel selection strategies; (4) antibodies in a complex environment: targeting intracellular and misfolded proteins; (5) rational vaccine design; (6) viral retargeting with engineered binding molecules; (7) the biology behind potential blockbuster antibodies and (8) antibodies as signaling modifiers: where did we go right, and can we learn from success? The Antibody Therapeutics session comprised five sessions: (1)Twenty-five years of therapeutic antibodies: lessons learned and future challenges; (2) preclinical and early stage development of antibody therapeutics; (3) next generation anti-angiogenics; (4) updates of clinical stage antibody therapeutics and (5) antibody drug conjugates and bispecific antibodies.

Evaluation of three different formats of a neutralizing single chain human antibody against toxin Cn2: neutralization capacity versus thermodynamic stability

The single-chain antibody fragment (scFv) 6009F, obtained by directed evolution, neutralizes the effects of the Cn2 toxin, which is the major toxic component of Centruroides noxius scorpion venom. In this work we compared the neutralization capacity and the thermodynamic stability of scFv 6009F with those of two other derived formats: Fab 6009F and diabody 6009F. Additionally, the affinity constants to Cn2 toxin of the three recombinant antibody fragments were determined by means of BIAcore. We found a correlation between the thermodynamic stability of these antibody fragments with their neutralization capacity. The order of thermodynamic stability determined was Fab≫scFv>diabody. The Fab and scFv were capable of neutralizing the toxic effects of Cn2 and whole venom but the diabody was unable to fully neutralize intoxication. In silico analysis of the diabody format indicates that the reduction of stability and neutralization capacity could be explained by a less cooperative interface between the heavy and the light variable domains.

Predicting antibody complementarity determining region structures without classification

Antibodies are used extensively in medical and biological research. Their complementarity determining regions (CDRs) define the majority of their antigen binding functionality. CDR structures have been intensively studied and classified (canonical structures). Here we show that CDR structure prediction is no different from the standard loop structure prediction problem and predict them without classification. FREAD, a successful database loop prediction technique, is able to produce accurate predictions for all CDR loops (0.81, 0.42, 0.96, 0.98, 0.88 and 2.25 Å RMSD for CDR-L1 to CDR-H3). In order to overcome the relatively poor predictions of CDR-H3, we developed two variants of FREAD, one focused on sequence similarity (FREAD-S) and another which includes contact information (ConFREAD). Both of the methods improve accuracy for CDR-H3 to 1.34 Å and 1.23 Å respectively. The FREAD variants are also tested on homology models and compared to RosettaAntibody (CDR-H3 prediction on models: 1.98 and 2.62 Å for ConFREAD and RosettaAntibody respectively). CDRs are known to change their structural conformations upon binding the antigen. Traditional CDR classifications are based on sequence similarity and do not account for such environment changes. Using a set of antigen-free and antigen-bound structures, we compared our FREAD variants. ConFREAD which includes contact information successfully discriminates the bound and unbound CDR structures and achieves an accuracy of 1.35 Å for bound structures of CDR-H3.

Antigen recognition by antibody C836 through adjustment of V(L)/V(H) packing

C836 is a neutralizing monoclonal antibody to human interleukin IL-13 generated by mouse immunization. The crystal structure of the C836 Fab was determined at 2.5 Å resolution and compared with the IL-13-bound form determined previously. This comparison indicates an induced-fit mechanism of antigen recognition through rigid-body rotation of the V(L) and V(H) domains. The magnitude of this rearrangement is one of the largest observed for antibody-protein interactions.

The association of heavy and light chain variable domains in antibodies: implications for antigen specificity

The antigen-binding site of immunoglobulins is formed by six regions, three from the light and three from the heavy chain variable domains, which, on association of the two chains, form the conventional antigen-binding site of the antibody. The mode of interaction between the heavy and light chain variable domains affects the relative position of the antigen-binding loops and therefore has an effect on the overall conformation of the binding site. In this article, we analyze the structure of the interface between the heavy and light chain variable domains and show that there are essentially two different modes for their interaction that can be identified by the presence of key amino acids in specific positions of the antibody sequences. We also show that the different packing modes are related to the type of recognized antigen.

Crystal structure of human germline antibody 3-23/B3

The human antibody repertoire is dominated by a few combinations of germline sequences, with the genes 3-23 for the heavy chain and B3 for the light chain being among the most frequently used. Despite this fact, there was no experimental structure of the antibody composed of 3-23 and B3. The crystal structure of the Fab fragment of the synthetic antibody composed of the 3-23 and B3 germline sequences was determined to provide a template for antibody modeling. The antigen-binding loops were found in the canonical conformations. Comparison to the other structures where either 3-23 or B3 is paired with a different chain reveals a significant deviation in the orientation of the variable domains.

Analysis and prediction of VH/VL packing in antibodies

The packing of V(H) and V(L) domains in antibodies can vary, influencing the topography of the antigen-combining site. However, until recently, this has largely been ignored in modelling antibody structure. We present an analysis of the degree of variability observed in known structures together with a machine-learning approach to predict the packing angle. A neural network was trained on sets of interface residues and a genetic algorithm designed to perform 'feature selection' to define which sets of interface residues could be used most successfully to perform the prediction. While this training procedure was very computationally intensive, prediction is performed in a matter of seconds. Thus, not only do we provide a rapid method for predicting the packing angle, but also we define a set of residues that may be important in antibody humanization in order to obtain the correct binding site topography.

Immobilized antibody orientation analysis using secondary ion mass spectrometry and fluorescence imaging of affinity-generated patterns

This study assesses the capability of high-resolution surface analytical tools to distinguish immobilized antibody orientations on patterned surfaces designed for antibody affinity capture. High-fidelity, side-by-side copatterning of protein A (antibody Fc domain affinity reagent) and fluorescein (antibody Fab domain hapten) was achieved photolithographically on commercial amine-reactive hydrogel polymer surfaces. This was verified from fluorescence imaging using fluorescently labeled protein A and intrinsic fluorescence from fluorescein. Subsequently, dye-labeled murine antifluorescein antibody (4-4-20) and antibody Fab and Fc fragments were immobilized from solution onto respective protein A- and fluorescein- copatterned or control surfaces using antibody-ligand affinity interactions. Fluorescence assays support specific immobilization to fluorescein hapten- and protein A-patterned regions through antigen-antibody recognition and natural protein A-Fc domain interactions, respectively. Affinity-based antibody immobilization on the two different copatterned surfaces generated side-by-side full antibody "heads-up" and "tails-up" oriented surface patterns. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis, sensitive to chemical information from the top 2 to 3 nm of the surface, provided ion-specific images of these antibody patterned regions, imaging and distinguishing characteristic ions from amino acids enriched in Fab domains for antibodies oriented in "heads-up" regions, and ions from amino acids enriched in Fc domains for antibodies oriented in "tails-up" regions. Principal component analysis (PCA) improved the distinct TOF-SIMS amino acid compositional and ion-specific surface mapping sensitivity for each "heads-up" versus "tails-up" patterned region. Characteristic Fab and Fc fragment immobilized patterns served as controls. This provides first demonstration of pattern-specific, antibody orientation-dependent surface maps based on antibody domain- and structure-specific compositional differences by TOF-SIMS analysis. Since antibody immobilization and orientation are critical to many technologies, orientation characterization using TOF-SIMS could be very useful and convenient for immobilization quality control and understanding methods for improving the performance of antibody-based surface capture assays.

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.

Rapid structural characterization of human antibody-antigen complexes through experimentally validated computational docking

If we understand the structural rules governing antibody (Ab)-antigen (Ag) interactions in a given virus, then we have the molecular basis to attempt to design and synthesize new epitopes to be used as vaccines or optimize the antibodies themselves for passive immunization. Comparing the binding of several different antibodies to related Ags should also further our understanding of general principles of recognition. To obtain and compare the three-dimensional structure of a large number of different complexes, however, we need a faster method than traditional experimental techniques. While biocomputational docking is fast, its results might not be accurate. Combining experimental validation with computational prediction may be a solution. As a proof of concept, here we isolated a monoclonal Ab from the blood of a human donor recovered from dengue virus infection, characterized its immunological properties, and identified its epitope on domain III of dengue virus E protein through simple and rapid NMR chemical shift mapping experiments. We then obtained the three-dimensional structure of the Ab/Ag complex by computational docking, using the NMR data to drive and validate the results. In an attempt to represent the multiple conformations available to flexible Ab loops, we docked several different starting models and present the result as an ensemble of models equally agreeing with the experimental data. The Ab was shown to bind a region accessible only in part on the viral surface, explaining why it cannot effectively neutralize the virus.