Analysis and prediction of VH/VL packing in antibodies

Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures

Antibodies are attractive therapeutic candidates due to their ability to bind cognate antigens with high affinity and specificity. Still, the underlying molecular rules governing the antibody-antigen interface remain poorly understood, making in silico antibody design inherently difficult and keeping the discovery and design of novel antibodies a costly and laborious process. This study investigates the characteristics of antibody-antigen binding interfaces through a computational analysis of more than 850,000 atom-atom contacts from the largest reported set of antibody-antigen complexes with 1833 nonredundant, experimentally determined structures. The analysis compares binding characteristics of conventional antibodies and single-domain antibodies (sdAbs) targeting both protein- and peptide antigens. We find clear patterns in the number antibody-antigen contacts and amino acid frequencies in the paratope. The direct comparison of sdAbs and conventional antibodies helps elucidate the mechanisms employed by sdAbs to compensate for their smaller size and the fact that they harbor only half the number of complementarity-determining regions compared to conventional antibodies. Furthermore, we pinpoint antibody interface hotspot residues that are often found at the binding interface and the amino acid frequencies at these positions. These findings have direct potential applications in antibody engineering and the design of improved antibody libraries.

AptaShield: A Universal Signal-Transduction System for Fast and High-Throughput Optical Molecular Biosensing

Biosensing technologies are often described to provide facile, sensitive, and minimally to noninvasive detection of molecular analytes across diverse scientific, environmental, and clinical diagnostic disciplines. However, commercialization has been very limited mostly due to the difficulty of biosensor reconfiguration for different analyte(s) and limited high-throughput capabilities. The immobilization of different biomolecular probes (e.g., antibodies, peptides, and aptamers) requires the sensor surface chemistry to be tailored to provide optimal probe coupling, orientation, and passivation and prevent nonspecific interactions. To overcome these challenges, here we report the development of a solution-phase biosensor consisting of an engineered aptamer, the AptaShield, capable of universally binding to any antigen recognition site (Fab') of fluorescently labeled immunoglobulins (IgG) produced in rabbits. The resulting AptaShield biosensor relies on a low affinity dynamic equilibrium between the fluorescently tagged aptamer and IgG to generate a specific Förster resonance energy transfer (FRET) signal. As the analyte binds to the IgG, the AptaShield DNA aptamer-IgG complex dissociates, leading to an analyte concentration-dependent decrease of the FRET signal. The biosensor demonstrates high selectivity, specificity, and reproducibility for analyte quantification in different biological fluids (e.g., urine and blood serum) in a one-step and low sample volume (0.5-6.25 μL) format. The AptaShield provides a universal signal transduction mechanism as it can be coupled to different rabbit antibodies without the need for aptamer modification, therefore representing a robust high-throughput solution-phase technology suitable for point-of-care applications, overcoming the current limitations of gold standard enzyme-linked immunosorbent assays (ELISA) for molecular profiling.

Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their conformation when they bind to an antigen. Existing surveys of antibody-antigen complex structures have only examined CDR conformational change in case studies or small-scale surveys. With an increasing number of antibodies where both free and complexed structures have been deposited in the Protein Data Bank, a large-scale survey of CDR conformational change during binding is now possible. To this end, we built a dataset, AbAgDb, that currently includes 177 antibodies with high-quality CDRs, each of which has at least one bound and one unbound structure. We analyzed the conformational change of the Cα backbone of each CDR upon binding and found that, in most cases, the CDRs (other than CDR-H3) show minimal movement, while 70.6% and 87% of CDR-H3s showed global Cα RMSD ≤ 1.0Å and ≤ 2.0Å, respectively. We also compared bound CDR conformations with the conformational space of unbound CDRs and found most of the bound conformations are included in the unbound conformational space. In future, our results will contribute to developing insights into antibodies and new methods for modeling and docking.

Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines

Antibodies and other new antibody-like formats have emerged as one of the most rapidly growing classes of biotherapeutic proteins. Understanding the structural features that drive antibody function and, consequently, their molecular recognition is critical for engineering antibodies. Here, we present the structural architecture of conventional IgG antibodies alongside other formats. We emphasize the importance of considering antibodies as conformational ensembles in solution instead of focusing on single-static structures because their functions and properties are strongly governed by their dynamic nature. Thus, in this review, we provide an overview of the unique structural and dynamic characteristics of antibodies with respect to their antigen recognition, biophysical properties, and effector functions. We highlight the numerous technical advances in antibody structure prediction and design, enabled by the vast number of experimentally determined high-quality structures recorded with cryo-EM, NMR, and X-ray crystallography. Lastly, we assess antibody and vaccine design strategies in the context of structure and dynamics.

Cross-linking disulfide bonds govern solution structures of diabodies

In the last years, antibodies have emerged as a promising new class of therapeutics, due to their combination of high specificity with long serum half-life and low risk of side-effects. Diabodies are a popular novel antibody format, consisting of two Fv domains connected with short linkers. Like IgG antibodies, they simultaneously bind two target proteins. However, they offer altered properties, given their smaller size and higher rigidity. In this study, we conducted the-to our knowledge-first molecular dynamics (MD) simulations of diabodies and find a surprisingly high conformational flexibility in the relative orientation of the two Fv domains. We observe rigidifying effects through the introduction of disulfide bonds in the Fv -Fv interface and characterize the effect of different disulfide bond locations on the conformation. Additionally, we compare VH -VL orientations and paratope dynamics between diabodies and an antigen binding fragment (Fab) of the same sequence. We find mostly consistent structures and dynamics, indicating similar antigen binding properties. The most significant differences can be found within the CDR-H2 loop dynamics. Of all CDR loops, the CDR-H2 is located closest to the artificial Fv -Fv interface. All examined diabodies show similar VH -VL orientations, Fv -Fv packing and CDR loop conformations. However, the variant with a P14C-K64C disulfide bond differs most from the Fab in our measures, including the CDR-H3 loop conformational ensemble. This suggests altered antigen binding properties and underlines the need for careful validation of the disulfide bond locations in diabodies.

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.

Adaptive Immune Receptor Repertoire (AIRR) Community Guide to TR and IG Gene Annotation

High-throughput sequencing of adaptive immune receptor repertoires (AIRR, i.e., IG and TR) has revolutionized the ability to carry out large-scale experiments to study the adaptive immune response. Since the method was first introduced in 2009, AIRR sequencing (AIRR-Seq) has been applied to survey the immune state of individuals, identify antigen-specific or immune-state-associated signatures of immune responses, study the development of the antibody immune response, and guide the development of vaccines and antibody therapies. Recent advancements in the technology include sequencing at the single-cell level and in parallel with gene expression, which allows the introduction of multi-omics approaches to understand in detail the adaptive immune response. Analyzing AIRR-seq data can prove challenging even with high-quality sequencing, in part due to the many steps involved and the need to parameterize each step. In this chapter, we outline key factors to consider when preprocessing raw AIRR-Seq data and annotating the genetic origins of the rearranged receptors. We also highlight a number of common difficulties with common AIRR-seq data processing and provide strategies to address them.

Structural Basis of Antibody Conformation and Stability Modulation by Framework Somatic Hypermutation

Accumulation of somatic hypermutation (SHM) is the primary mechanism to enhance the binding affinity of antibodies to antigens in vivo. However, the structural basis of the effects of many SHMs remains elusive. Here, we integrated atomistic molecular dynamics (MD) simulation and data mining to build a high-throughput structural bioinformatics pipeline to study the effects of individual and combination SHMs on antibody conformation, flexibility, stability, and affinity. By applying this pipeline, we characterized a common mechanism of modulation of heavy-light pairing orientation by frequent SHMs at framework positions 39_H, 91_H, 38_L, and 87_L through disruption of a conserved hydrogen-bond network. Q39L_H alone and in combination with light chain framework 4 (FWR4_L) insertions further modulated the elbow angle between variable and constant domains of many antibodies, resulting in improved binding affinity for a subset of anti-HIV-1 antibodies. Q39L_H also alleviated aggregation induced by FWR4_L insertion, suggesting remote epistasis between these SHMs. Altogether, this study provides tools and insights for understanding antibody affinity maturation and for engineering functionally improved antibodies.

Structural arrangement of the VH and VL domains in the COBRA™ T-cell engaging single-chain diabody

BACKGROUND

COBRA™ (COnditional Bispecific Redirected Activation) T-cell engagers are designed to target solid tumors as a single polypeptide chain prodrug that becomes activated by proteolysis in the tumor microenvironment. One COBRA molecule comprises seven Ig domains: three single-domain antibodies (sdAbs) recognizing a tumor target or human serum albumin (HSA), and CD3ε-binding variable fragment heavy chain (VH) and variable fragment light chain (VL) and their inactivated counterparts, VHi and VLi. Pairing of VH and VL, and VLi and VHi into single-chain variable fragments (Fv) is prevented by shortened inter-domain linkers. Instead, VH and VL are expected to interact with VLi and VHi, respectively, thus making a diabody whose binding to CD3ε on the T-cells is impaired.

METHODS

We analyzed the structure of an epidermal growth factor receptor (EGFR) COBRA in solution using negative stain electron microscopy (EM) and small-angle X-ray scattering (SAXS).

RESULTS

We found that this EGFR COBRA forms stable monomers with a very dynamic interdomain arrangement. At most, only five domains at a time appeared ordered, and only one VH-VL pair was found in the Fv orientation. Nonenzymatic posttranslational modifications suggest that the CDR3 loops in the VL-VHi pair are exposed but are buried in the VH-VLi pair. The MMP9 cleavage rate of the prodrug when bound to recombinant EGFR or HSA is not affected, indicating positioning of the MMP9-cleavable linker away from the EGFR and HSA binding sites.

CONCLUSION

Here, we propose a model for EGFR COBRA where VH and VLi form an Fv, and VL and VHi do not, possibly interacting with other Ig domains. SAXS and MMP9 cleavage analyses suggest that all COBRA molecules tested have a similar structural architecture.

Shelf-Life Extension of Fc-Fused Single Chain Fragment Variable Antibodies by Lyophilization

Generation of sequence defined antibodies from universal libraries by phage display has been established over the past three decades as a robust method to cope with the increasing market demand in therapy, diagnostics and research. For applications requiring the bivalent antigen binding and an Fc part for detection, phage display generated single chain Fv (scFv) antibody fragments can rapidly be genetically fused to the Fc moiety of an IgG for the production in eukaryotic cells of antibodies with IgG-like properties. In contrast to conversion of scFv into IgG format, the conversion to scFv-Fc requires only a single cloning step, and provides significantly higher yields in transient cell culture production than IgG. ScFv-Fcs can be effective as neutralizing antibodies in vivo against a panel of pathogens and toxins. However, different scFv fragments are more heterologous in respect of stability than Fab fragments. While some scFv fragments can be made extremely stable, this may change due to few mutations, and is not predictable from the sequence of a newly selected antibody. To mitigate the necessity to assess the stability for every scFv-Fc antibody, we developed a generic lyophilization protocol to improve their shelf life. We compared long-term stability and binding activity of phage display-derived antibodies in the scFv-Fc and IgG format, either stored in liquid or lyophilized state. Conversion of scFv-Fcs into the full IgG format reduced protein degradation and aggregation, but in some cases compromised binding activity. Comparably to IgG conversion, lyophilization of scFv-Fc resulted in the preservation of the antibodies' initial properties after storage, without any drop in affinity for any of the tested antibody clones.

Quantitative Description of Surface Complementarity of Antibody-Antigen Interfaces

Antibodies have the remarkable ability to recognise their cognate antigens with extraordinary affinity and specificity. Discerning the rules that define antibody-antigen recognition is a fundamental step in the rational design and engineering of functional antibodies with desired properties. In this study we apply the 3D Zernike formalism to the analysis of the surface properties of the antibody complementary determining regions (CDRs). Our results show that shape and electrostatic 3DZD descriptors of the surface of the CDRs are predictive of antigen specificity, with classification accuracy of 81% and area under the receiver operating characteristic curve (AUC) of 0.85. Additionally, while in terms of surface size, solvent accessibility and amino acid composition, antibody epitopes are typically not distinguishable from non-epitope, solvent-exposed regions of the antigen, the 3DZD descriptors detect significantly higher surface complementarity to the paratope, and are able to predict correct paratope-epitope interaction with an AUC = 0.75.

Structural Analysis of Anti-Hapten Antibodies to Identify Long-Range Structural Movements Induced by Hapten Binding

Antibodies are well known for their high specificity that has enabled them to be of significant use in both therapeutic and diagnostic applications. Antibodies can recognize different antigens, including proteins, carbohydrates, peptides, nucleic acids, lipids, and small molecular weight haptens that are abundantly available as hormones, pharmaceuticals, and pesticides. Here we focus on a structural analysis of hapten-antibody couples and identify potential structural movements originating from the hapten binding by comparison with unbound antibody, utilizing 40 crystal structures from the Protein Data Bank. Our analysis reveals three binding surface trends; S1 where a pocket forms to accommodate the hapten, S2 where a pocket is removed when the hapten binds, and S3 where no pockets changes are found. S1 and S2 are expected for induced-fit binding, whereas S3 indicates that a pre-existing population of optimal binding antibody conformation exists. The structural analysis reveals four classifications of structural reorganization, some of which correlate to S2 but not to the other binding surface changes. These observations demonstrate the complexity of the antibody-antigen interaction, where structural changes can be restricted to the binding sites, or extend through the constant domains to propagate structural changes. This highlights the importance of structural analysis to ensure successful and compatible transformation of small antibody fragments at the early discovery stage into full antibodies during the subsequent development stages, where long-range structural changes are required for an Fc effector response.

Machine Learning Attempts for Predicting Human Subcutaneous Bioavailability of Monoclonal Antibodies

PURPOSE

One knowledge gap related to subcutaneous (SC) delivery is unpredictable and variable bioavailability. This study was aimed to develop machine learning methods to predict whether mAb's bioavailability was ≥70% or below, without completely knowing the mechanism and causality between inputs and outputs.

METHODS

A database of mAb SC products was built. The model training and validation were accomplished based on this database and a set of the inputs (product properties) were mapped to the output (bioavailability) using different machine learning algorithms. Dimensionality reduction was undertaken using principal component analysis (PCA).

RESULTS

The bioavailability of the mAb products being investigated varied from 35% to 90%. The tree-based methods, including random forest (RF), Adaptive Boost (AdaBoost), and decision tree (DT) presented the best predictability and generalization power on bioavailability classification. The models based on Multi-layer perceptron (MLP), Gaussian Naïve Bayes (GaussianNB), and k nearest neighbor (kNN) algorithms also provided acceptable prediction accuracy.

CONCLUSION

Machine learning could be a potential tool to predict mAb's bioavailability. Since all input features were acquired using theoretical calculations and predictions rather than experiments, the models may be particularly applicable to some early-stage research activities such as mAb molecule triage, design/optimization, mutant screening, molecule selection, and formulation design.

Monoclonal Antibodies: A Prospective and Retrospective View

BACKGROUND

Monoclonal Antibodies (mAbs) represent one of the most important classes of biotherapeutic agents. They are used to cure many diseases, including cancer, autoimmune diseases, cardiovascular diseases, angiogenesis-related diseases and, more recently also haemophilia. They can be highly varied in terms of format, source, and specificity to improve efficacy and to obtain more targeted applications. This can be achieved by leaving substantially unchanged the basic structural components for paratope clustering.

OBJECTIVES

The objective was to trace the most relevant findings that have deserved prestigious awards over the years, to report the most important clinical applications and to emphasize their latest emerging therapeutic trends.

RESULTS

We report the most relevant milestones and new technologies adopted for antibody development. Recent efforts in generating new engineered antibody-based formats are briefly reviewed. The most important antibody-based molecules that are (or are going to be) used for pharmacological practice have been collected in useful tables.

CONCLUSION

The topics here discussed prove the undisputed role of mAbs as innovative biopharmaceuticals molecules and as vital components of targeted pharmacological therapies.

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.

Antibody-protein binding and conformational changes: identifying allosteric signalling pathways to engineer a better effector response

Numerous monoclonal antibodies have been developed successfully for the treatment of various diseases. Nevertheless, the development of biotherapeutic antibodies is complex, expensive, and time-consuming, and to facilitate this process, careful structural analysis beyond the antibody binding site is required to develop a more efficacious antibody. In this work, we focused on protein antigens, since they induce the largest antibody changes, and provide interesting cases to compare and contrast. The structures of 15 anti-protein antibodies were analysed to compare the antigen-bound/unbound forms. Surprisingly, three different classes of binding-induced changes were identified. In class (B1), the antigen binding fragment distorted significantly, and we found changes in the loop region of the heavy chain's constant domain; this corresponds well with expected allosteric movements. In class (B2), we found changes in the same loop region without the overall distortion. In class (B3), these changes did not present, and only local changes at the complementarity determining regions were found. Consequently, structural analysis of antibodies is crucial for therapeutic development. Careful evaluation of allosteric movements must be undertaken to develop better effector responses, especially during the transformation of these antibodies from small fragments at the discovery stage to full antibodies at the subsequent development stages.

VH -VL interdomain dynamics observed by computer simulations and NMR

The relative orientation of the two variable domains, VH and VL , influences the shape of the antigen binding site, that is, the paratope, and is essential to understand antigen specificity. ABangle characterizes the VH -VL orientation by using five angles and a distance and compares it to other known structures. Molecular dynamics simulations of antibody variable domains (Fvs) reveal fluctuations in the relative domain orientations. The observed dynamics between these domains are confirmed by NMR experiments on a single-chain variable fragment antibody (scFv) in complex with IL-1β and an antigen-binding fragment (Fab). The variability of these relative domain orientations can be interpreted as a structural feature of antibodies, which increases the antibody repertoire significantly and can enlarge the number of possible binding partners substantially. The movements of the VH and VL domains are well sampled with molecular dynamics simulations and are in agreement with the NMR ensemble. Fast Fourier transformation of the ABangle metrics allows to assign timescales of 0.1-10 GHz to the fastest collective interdomain movements. The results clearly show the necessity of dynamics to understand and characterize the favorable orientations of the VH and VL domains implying a considerable binding interface flexibility and reveal in all antibody fragments (Fab, scFv, and Fv) very similar VH -VL interdomain variations comparable to the distributions observed for known X-ray structures of antibodies. SIGNIFICANCE STATEMENT: Antibodies have become key players as therapeutic agents. The binding ability of antibodies is determined by the antigen-binding fragment (Fab), in particular the variable fragment region (Fv). Antigen-binding is mediated by the complementarity-determining regions consisting of six loops, each three of the heavy and light chain variable domain VH and VL . The relative orientation of the VH and VL domains influences the shape of the antigen-binding site and is a major objective in antibody design. In agreement with NMR experiments and molecular dynamics simulations, we show a considerable binding site flexibility in the low nanosecond timescale. Thus we suggest that this flexibility and its implications for binding and specificity should be considered when designing and optimizing therapeutic antibodies.

Loxoscelism: Advances and Challenges in the Design of Antibody Fragments with Therapeutic Potential

Envenoming due to Loxosceles spider bites still remains a neglected disease of particular medical concern in the Americas. To date, there is no consensus for the treatment of envenomed patients, yet horse polyclonal antivenoms are usually infused to patients with identified severe medical conditions. It is widely known that venom proteins in the 30–35 kDa range with sphingomyelinase D (SMasesD) activity, reproduce most of the toxic effects observed in loxoscelism. Hence, we believe that monoclonal antibody fragments targeting such toxins might pose an alternative safe and effective treatment. In the present study, starting from the monoclonal antibody LimAb7, previously shown to target SMasesD from the venom of L. intermedia and neutralize its dermonecrotic activity, we designed humanized antibody V-domains, then produced and purified as recombinant single-chain antibody fragments (scFvs). These molecules were characterized in terms of humanness, structural stability, antigen-binding activity, and venom-neutralizing potential. Throughout this process, we identified some blocking points that can impact the Abs antigen-binding activity and neutralizing capacity. In silico analysis of the antigen/antibody amino acid interactions also contributed to a better understanding of the antibody’s neutralization mechanism and led to reformatting the humanized antibody fragment which, ultimately, recovered the functional characteristics for efficient in vitro venom neutralization.

Antibody humanization-the Influence of the antibody framework on the CDR-H3 loop ensemble in solution

Antibody engineering of non-human antibodies has focused on reducing immunogenicity by humanization, being a major limitation in developing monoclonal antibodies. We analyzed four series of antibody binding fragments (Fabs) and a variable fragment (Fv) with structural information in different stages of humanization to investigate the influence of the framework, point mutations and specificity on the complementarity determining region (CDR)-H3 loop dynamics. We also studied a Fv without structural information of the anti-idiotypic antibody Ab2/3H6, because it completely lost its binding affinity upon superhumanization, as an example of a failed humanization. Enhanced sampling techniques in combination with molecular dynamics simulations allow to access micro- to milli-second timescales of the CDR-H3 loop dynamics and reveal kinetic and thermodynamic changes involved in the process of humanization. In most cases, we observe a reduced conformational diversity of the CDR-H3 loop when grafted on a human framework and find a conformational shift of the dominant CDR-H3 loop conformation in solution. A shallow side minimum of the conformational CDR-H3 loop ensemble attached to the murine framework becomes the dominant conformation in solution influenced by the human framework. Additionally, we observe in the case of the failed humanization that the potentially binding competent murine CDR-H3 loop ensemble in solution shows nearly no kinetical or structural overlap with the superhumanized variant, thus explaining the loss of binding.

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.

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.

Antibody Fragments Humanization: Beginning with the End in Mind

Molecular engineering has made possible to reformat monoclonal antibodies into smaller antigen-binding structures like scFvs, diabodies, Fabs with new potential in vivo applications because they do not induce Fc-mediated functions. However, most of these molecules are from rodent origin. As a consequence, they are immunogenic and approval for administration to humans requires prior humanization. Today, there is no well-identified strategy to create recombinant humanized antibody V-domains that preserve the antigen-binding characteristics of the parental antibody associated with high stability and solubility. Here, we propose a strategy that consists in grafting CDRs onto properly chosen human antibody frameworks in order to reduce immunogenicity. A flowchart indicates the way to proceed in order to introduce an internal affinity purification tag while structural refinements are proposed to maintain antigen-binding characteristics. The best humanized candidates are identified through selection steps including in silico analysis, research scale production followed by early functional evaluation, purification assays, aggregation, and stability assessment.

Deciphering evolution of immune recognition in antibodies

Background

Antibody, the primary effector molecule of the immune system, evolves after initial encounter with the antigen from a precursor form to a mature one to effectively deal with the antigen. Antibodies of a lineage diverge through antigen-directed isolated pathways of maturation to exhibit distinct recognition potential. In the context of evolution in immune recognition, diversity of antigen cannot be ignored. While there are reports on antibody lineage, structural perspective with respect to diverse recognition potential in a lineage has never been studied. Hence, it is crucial to evaluate how maturation leads to topological tailoring within a lineage enabling them to interact with significantly distinct antigens.

Results

A data-driven approach was undertaken for the study. Global experimental mouse and human antibody-antigen complex structures from PDB were compiled into a coherent database of germline-linked antibodies bound with distinct antigens. Structural analysis of all lineages showed variations in CDRs of both H and L chains. Observations of conformational adaptation made from analysis of static structures were further evaluated by characterizing dynamics of interaction in two lineages, mouse V_H1–84 and human V_H5–51. Sequence and structure analysis of the lineages explained that somatic mutations altered the geometries of individual antibodies with common structural constraints in some CDRs. Additionally, conformational landscape obtained from molecular dynamics simulations revealed that incoming pathogen led to further conformational divergence in the paratope (as observed across datasets) even while maintaining similar overall backbone topology. MM-GB/SA analysis showed binding energies to be in physiological range. Results of the study are coherent with experimental observations.

Conclusions

The findings of this study highlight basic structural principles shaping the molecular evolution of a lineage for significantly diverse antigens. Antibodies of a lineage follow different developmental pathways while preserving the imprint of the germline. From the study, it can be generalized that structural diversification of the paratope is an outcome of natural selection of a conformation from an available ensemble, which is further optimized for antigen interaction. The study establishes that starting from a common lineage, antibodies can mature to recognize a wide range of antigens. This hypothesis can be further tested and validated experimentally.

Electronic supplementary material

The online version of this article (10.1186/s12900-018-0096-1) contains supplementary material, which is available to authorized users.

Understanding the Significance and Implications of Antibody Numbering and Antigen-Binding Surface/Residue Definition

Monoclonal antibodies are playing an increasing role in both human and animal health. Different strategies of protein and chemical engineering, including humanization techniques of non-human antibodies were applied successfully to optimize clinical performances of antibodies. Despite the emergence of techniques allowing the development of fully human antibodies such as transgenic Xeno-mice, antibody humanization remains a standard procedure for therapeutic antibodies. An important prerequisite for antibody humanization requires standardized numbering methods to define precisely complementary determining regions (CDR), frameworks and residues from the light and heavy chains that affect the binding affinity and/or specificity of the antibody-antigen interaction. The recently generated deep-sequencing data and the increasing number of solved three-dimensional structures of antibodies from human and non-human origins have led to the emergence of numerous databases. However, these different databases use different numbering conventions and CDR definitions. In addition, the large fluctuation of the variable chain lengths, especially in CDR3 of heavy chains (CDRH3), hardly complicates the comparison and analysis of antibody sequences and the identification of the antigen binding residues. This review compares and discusses the different numbering schemes and "CDR" definition that were established up to date. Furthermore, it summarizes concepts and strategies used for numbering residues of antibodies and CDR residues identification. Finally, it discusses the importance of specific sets of residues in the binding affinity and/or specificity of immunoglobulins.

AbDb: antibody structure database-a database of PDB-derived antibody structures

In order to analyse structures of proteins of a particular class, these need to be extracted from Protein Data Bank (PDB) files. In the case of antibodies, there are a number of special considerations: (i) identifying antibodies in the PDB is not trivial, (ii) they may be crystallized with or without antigen, (iii) for analysis purposes, one is normally only interested in the Fv region of the antibody, (iv) structural analysis of epitopes, in particular, requires individual antibody–antigen complexes from a PDB file which may contain multiple copies of the same, or different, antibodies and (v) standard numbering schemes should be applied. Consequently, there is a need for a specialist resource containing pre-numbered non-redundant antibody Fv structures with their cognate antigens. We have created an automatically updated resource, AbDb, which collects the Fv regions from antibody structures using information from our SACS database which summarizes antibody structures from the PDB. PDB files containing multiple structures are split and numbered and each antibody structure is associated with its antigen where available. Antibody structures with only light or heavy chains have also been processed and sequences of antibodies are compared to identify multiple structures of the same antibody. The data may be queried on the basis of PDB code, or the name or species of the antibody or antigen, and the complete datasets may be downloaded.

Database URL: www.bioinf.org.uk/abs/abdb/

A strategy to identify linker-based modules for the allosteric regulation of antibody-antigen binding affinities of different scFvs

Antibody single-chain variable fragments (scFvs) are used in a variety of applications, such as for research, diagnosis and therapy. Essential for these applications is the extraordinary specificity, selectivity and affinity of antibody paratopes, which can also be used for efficient protein purification. However, this use is hampered by the high affinity for the protein to be purified because harsh elution conditions, which may impair folding, integrity or viability of the eluted biomaterials, are typically required. In this study, we developed a strategy to obtain structural elements that provide allosteric modulation of the affinities of different antibody scFvs for their antigen. To identify suitable allosteric modules, a complete set of cyclic permutations of calmodulin variants was generated and tested for modulation of the affinity when substituting the linker between VH and VL. Modulation of affinity induced by addition of different calmodulin-binding peptides at physiologic conditions was demonstrated for 5 of 6 tested scFvs of different specificities and antigens ranging from cell surface proteins to haptens. In addition, a variety of different modulator peptides were tested. Different structural solutions were found in respect of the optimal calmodulin permutation, the optimal peptide and the allosteric effect for scFvs binding to different antigen structures. Significantly, effective linker modules were identified for scFvs with both VH-VL and VL-VH architecture. The results suggest that this approach may offer a rapid, paratope-independent strategy to provide allosteric regulation of affinity for many other antibody scFvs.

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.

Fv-clasp: An Artificially Designed Small Antibody Fragment with Improved Production Compatibility, Stability, and Crystallizability

Antibody fragments are frequently used as a "crystallization chaperone" to aid structural analysis of complex macromolecules that are otherwise crystallization resistant, but conventional fragment formats have not been designed for this particular application. By fusing an anti-parallel coiled-coil structure derived from the SARAH domain of human Mst1 kinase to the variable region of an antibody, we succeeded in creating a novel chimeric antibody fragment of ∼37 kDa, termed "Fv-clasp," which exhibits excellent crystallization compatibility while maintaining the binding ability of the original IgG molecule. The "clasp" and the engineered disulfide bond at the bottom of the Fv suppressed the internal mobility of the fragment and shielded hydrophobic residues, likely contributing to the high heat stability and the crystallizability of the Fv-clasp. Finally, Fv-clasp antibodies showed superior "chaperoning" activity over conventional Fab fragments, and facilitated the structure determination of an ectodomain fragment of integrin α6β1.

Design, development and characterization of ACT017, a humanized Fab that blocks platelet's glycoprotein VI function without causing bleeding risks

Glycoprotein VI is a platelet-specific collagen receptor critical for in vivo formation of arterial thrombosis. It is also considered as an attractive target for the development of anti-thrombotic drugs because blocking glycoprotein (GP)VI inhibits platelet aggregation without inducing detrimental effects on physiologic hemostasis.

Here, we present data on the identification, in vitro and ex vivo pharmacology of a humanized Fab fragment designated as ACT017. ACT017 was selected out of 15 humanized variants based upon structural and functional properties. It was produced under GMP-like conditions followed by detailed physico-chemical analysis and functional characterization indicating high antigen-binding specificity and affinity. In addition, we demonstrate, in a dose-escalation study, that ACT017 has a high capacity to specifically inhibit collagen-induced platelet aggregation ex vivo after injection to the macaque without inducing thrombocytopenia, GPVI depletion or bleeding side effects as is the case for conventional anti-platelets. Therefore, ACT017 is a promising therapeutic candidate for the development of a new generation of safe and efficient anti-thrombotic drugs.

Computer-Aided Antibody Design: An Overview

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

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.

VH-VL orientation prediction for antibody humanization candidate selection: A case study

Antibody humanization describes the procedure of grafting a non-human antibody's complementarity-determining regions, i.e., the variable loop regions that mediate specific interactions with the antigen, onto a β-sheet framework that is representative of the human variable region germline repertoire, thus reducing the number of potentially antigenic epitopes that might trigger an anti-antibody response. The selection criterion for the so-called acceptor frameworks (one for the heavy and one for the light chain variable region) is traditionally based on sequence similarity. Here, we propose a novel approach that selects acceptor frameworks such that the relative orientation of the 2 variable domains in 3D space, and thereby the geometry of the antigen-binding site, is conserved throughout the process of humanization. The methodology relies on a machine learning-based predictor of antibody variable domain orientation that has recently been shown to improve the quality of antibody homology models. Using data from 3 humanization campaigns, we demonstrate that preselecting humanization variants based on the predicted difference in variable domain orientation with regard to the original antibody leads to subsets of variants with a significant improvement in binding affinity.

High-accuracy modeling of antibody structures by a search for minimum-energy recombination of backbone fragments

Current methods for antibody structure prediction rely on sequence homology to known structures. Although this strategy often yields accurate predictions, models can be stereo-chemically strained. Here, we present a fully automated algorithm, called AbPredict, that disregards sequence homology, and instead uses a Monte Carlo search for low-energy conformations built from backbone segments and rigid-body orientations that appear in antibody molecular structures. We find cases where AbPredict selects accurate loop templates with sequence identity as low as 10%, whereas the template of highest sequence identity diverges substantially from the query's conformation. Accordingly, in several cases reported in the recent Antibody Modeling Assessment benchmark, AbPredict models were more accurate than those from any participant, and the models' stereo-chemical quality was consistently high. Furthermore, in two blind cases provided to us by crystallographers prior to structure determination, the method achieved <1.5 Ångstrom overall backbone accuracy. Accurate modeling of unstrained antibody structures will enable design and engineering of improved binders for biomedical research directly from sequence. Proteins 2016; 85:30-38. © 2016 Wiley Periodicals, Inc.

abYsis: Integrated Antibody Sequence and Structure-Management, Analysis, and Prediction

abYsis is a web-based antibody research system that includes an integrated database of antibody sequence and structure data. The system can be interrogated in numerous ways-from simple text and sequence searches to sophisticated queries that apply 3D structural constraints. The publicly available version includes pre-analyzed sequence data from the European Molecular Biology Laboratory European Nucleotide Archive (EMBL-ENA) and Kabat as well as structure data from the Protein Data Bank. A researcher's own sequences can also be analyzed through the web interface. A defining characteristic of abYsis is that the sequences are automatically numbered with a series of popular schemes such as Kabat and Chothia and then annotated with key information such as complementarity-determining regions and potential post-translational modifications. A unique aspect of abYsis is a set of residue frequency tables for each position in an antibody, allowing "unusual residues" (those rarely seen at a particular position) to be highlighted and decisions to be made on which mutations may be acceptable. This is especially useful when comparing antibodies from different species. abYsis is useful for any researcher specializing in antibody engineering, especially those developing antibodies as drugs. abYsis is available at www.abysis.org.

MoFvAb: Modeling the Fv region of antibodies

Knowledge of the 3-dimensional structure of the antigen-binding region of antibodies enables numerous useful applications regarding the design and development of antibody-based drugs. We present a knowledge-based antibody structure prediction methodology that incorporates concepts that have arisen from an applied antibody engineering environment. The protocol exploits the rich and continuously growing supply of experimentally derived antibody structures available to predict CDR loop conformations and the packing of heavy and light chain quickly and without user intervention. The homology models are refined by a novel antibody-specific approach to adapt and rearrange sidechains based on their chemical environment. The method achieves very competitive all-atom root mean square deviation values in the order of 1.5 Å on different evaluation datasets consisting of both known and previously unpublished antibody crystal structures.

Improved prediction of antibody VL-VH orientation

Antibodies are important immune molecules with high commercial value and therapeutic interest because of their ability to bind diverse antigens. Computational prediction of antibody structure can quickly reveal valuable information about the nature of these antigen-binding interactions, but only if the models are of sufficient quality. To achieve high model quality during complementarity-determining region (CDR) structural prediction, one must account for the VL-VH orientation. We developed a novel four-metric VL-VH orientation coordinate frame. Additionally, we extended the CDR grafting protocol in RosettaAntibody with a new method that diversifies VL-VH orientation by using 10 VL-VH orientation templates rather than a single one. We tested the multiple-template grafting protocol on two datasets of known antibody crystal structures. During the template-grafting phase, the new protocol improved the fraction of accurate VL-VH orientation predictions from only 26% (12/46) to 72% (33/46) of targets. After the full RosettaAntibody protocol, including CDR H3 remodeling and VL-VH re-orientation, the new protocol produced more candidate structures with accurate VL-VH orientation than the standard protocol in 43/46 targets (93%). The improved ability to predict VL-VH orientation will bolster predictions of other parts of the paratope, including the conformation of CDR H3, a grand challenge of antibody homology modeling.

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.

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.

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected]

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Antibody VH and VL recombination using phage and ribosome display technologies reveals distinct structural routes to affinity improvements with VH-VL interface residues providing important structural diversity

In vitro selection technologies are an important means of affinity maturing antibodies to generate the optimal therapeutic profile for a particular disease target. Here, we describe the isolation of a parent antibody, KENB061 using phage display and solution phase selections with soluble biotinylated human IL-1R1. KENB061 was affinity matured using phage display and targeted mutagenesis of VH and VL CDR3 using NNS randomization. Affinity matured VHCDR3 and VLCDR3 library blocks were recombined and selected using phage and ribosome display protocol. A direct comparison of the phage and ribosome display antibodies generated was made to determine their functional characteristics.In our analyses, we observed distinct differences in the pattern of beneficial mutations in antibodies derived from phage and ribosome display selections, and discovered the lead antibody Jedi067 had a ~3700-fold improvement in KD over the parent KENB061. We constructed a homology model of the Fv region of Jedi067 to map the specific positions where mutations occurred in the CDR3 loops. For VL CDR3, positions 94 to 97 carry greater diversity in the ribosome display variants compared with the phage display. The positions 95a, 95b and 96 of VLCDR3 form part of the interface with VH in this model. The model shows that positions 96, 98, 100e, 100f, 100 g, 100h, 100i and 101 of the VHCDR3 include residues at the VH and VL interface. Importantly, Leu96 and Tyr98 are conserved at the interface positions in both phage and ribosome display indicating their importance in maintaining the VH-VL interface. For antibodies derived from ribosome display, there is significant diversity at residues 100a to 100f of the VH CDR3 compared with phage display. A unique deletion of isoleucine at position 102 of the lead candidate, Jedi067, also occurs in the VHCDR3.As anticipated, recombining the mutations via ribosome display led to a greater structural diversity, particularly in the heavy chain CDR3, which in turn led to antibodies with improved potencies. For this particular analysis, we also found that VH-VL interface positions provided a source of structural diversity for those derived from the ribosome display selections. This greater diversity is a likely consequence of the presence of a larger pool of recombinants in the ribosome display system, or the evolutionary capacity of ribosome display, but may also reflect differential selection of antibodies in the two systems.

Examining variable domain orientations in antigen receptors gives insight into TCR-like antibody design

The variable domains of antibodies and T-Cell receptors (TCRs) share similar structures. Both molecules act as sensors for the immune system but recognise their respective antigens in different ways. Antibodies bind to a diverse set of antigenic shapes whilst TCRs only recognise linear peptides presented by a major histocompatibility complex (MHC). The antigen specificity and affinity of both receptors is determined primarily by the sequence and structure of their complementarity determining regions (CDRs). In antibodies the binding site is also known to be affected by the relative orientation of the variable domains, VH and VL. Here, the corresponding property for TCRs, the Vβ-Vα orientation, is investigated and compared with that of antibodies. We find that TCR and antibody orientations are distinct. General antibody orientations are found to be incompatible with binding to the MHC in a canonical TCR-like mode. Finally, factors that cause the orientation of TCRs and antibodies to be different are investigated. Packing of the long Vα CDR3 in the domain-domain interface is found to be influential. In antibodies, a similar packing affect can be achieved using a bulky residue at IMGT position 50 on the VH domain. Along with IMGT VH 50, other positions are identified that may help to promote a TCR-like orientation in antibodies. These positions should provide useful considerations in the engineering of therapeutic TCR-like antibodies.

The immune system needs to be able to sense molecules that might be harmful to the organism. Such harmful molecules are known as antigens. Two classes of receptor proteins that mediate antigen recognition are antibodies and T-Cell receptors (TCRs). Antibodies are able to bind a diverse range of antigen shapes whilst TCRs are specialised to recognise a cell-surface protein, the pMHC. Antibodies that bind the pMHC are rarely created naturally. However, such TCR-like antibodies are of therapeutic importance. The binding regions of the TCR and the antibody have very similar three dimensional structures. Both consist of two independent units, domains, which associate and form the antigen binding site between them. This work examines how the two domains orientate with respect to one another in TCRs and antibodies. Our results show that the conformations that exist in TCRs and antibodies are distinct. Consequently it is difficult for an antibody to bind to a pMHC in the same way a TCR would. However, a similar conformation can be achieved in antibodies as in TCRs by the presence of certain amino-acids in the domain interface. This knowledge should aid the development of therapeutic TCR-like antibodies.

Antibody informatics for drug discovery

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

Design, expression and characterization of a single chain anti-CD20 antibody; a germline humanized antibody derived from Rituximab

CD20 is a B cell lineage specific surface antigen involved in various B cell malignancies. So far, several murine and chimeric antibodies have been produced against this antigen among which Rituximab is a commercially approved antibody widely used in treatment of cancers associated with CD20 overexpression. The current study reports the production and characterization of a humanized single chain version of Rituximab through CDR grafting method. For either heavy or light chain variable domains, a human antibody with the highest sequence homology to Rituximab was selected from human germline sequences and used as framework donors. Vernier zone residues in framework regions were replaced with those of Rituximab to retain the antigen binding affinity of parental antibody. The reactivity of humanized single chain antibody with CD20 was examined by ELISA and dot blot assays. The ability of antibody to suppress the growth of CD20 overexpressing Raji cells was tested by MTT assay. Analysis of reactivity with CD20 antigen revealed that the humanized single chain antibody reacted to the target antigen with high affinity. Proliferation inhibition assay showed that humanized scFv could suppress the proliferation of Raji cells efficiently in a dose-dependent manner. This successful production of a humanized scFv with the ability to inhibit growth of CD20-expressing cancer cell may provide a promising alternative strategy for CD20 targeted therapy.

Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization

Antibody Modeling Assessment II (AMA-II) provided an opportunity to benchmark RosettaAntibody on a set of 11 unpublished antibody structures. RosettaAntibody produced accurate, physically realistic models, with all framework regions and 42 of the 55 non-H3 CDR loops predicted to under an Ångström. The performance is notable when modeling H3 on a homology framework, where RosettaAntibody produced the best model among all participants for four of the 11 targets, two of which were predicted with sub-Ångström accuracy. To improve RosettaAntibody, we pursued the causes of model errors. The most common limitation was template unavailability, underscoring the need for more antibody structures and/or better de novo loop methods. In some cases, better templates could have been found by considering residues outside of the CDRs. De novo CDR H3 modeling remains challenging at long loop lengths, but constraining the C-terminal end of H3 to a kinked conformation allows near-native conformations to be sampled more frequently. We also found that incorrect VL -VH orientations caused models with low H3 RMSDs to score poorly, suggesting that correct VL -VH orientations will improve discrimination between near-native and incorrect conformations. These observations will guide the future development of RosettaAntibody.

Reconciling the structural attributes of avian antibodies

Antibodies are high value therapeutic, diagnostic, biotechnological, and research tools. Combinatorial approaches to antibody discovery have facilitated access to unique antibodies by surpassing the diversity limitations of the natural repertoire, exploitation of immune repertoires from multiple species, and tailoring selections to isolate antibodies with desirable biophysical attributes. The V-gene repertoire of the chicken does not utilize highly diverse sequence and structures, which is in stark contrast to the mechanism employed by humans, mice, and primates. Recent exploitation of the avian immune system has generated high quality, high affinity antibodies to a wide range of antigens for a number of therapeutic, diagnostic and biotechnological applications. Furthermore, extensive examination of the amino acid characteristics of the chicken repertoire has provided significant insight into mechanisms employed by the avian immune system. A paucity of avian antibody crystal structures has limited our understanding of the structural consequences of these uniquely chicken features. This paper presents the crystal structure of two chicken single chain fragment variable (scFv) antibodies generated from large libraries by phage display against important human antigen targets, which capture two unique CDRL1 canonical classes in the presence and absence of a non-canonical disulfide constrained CDRH3. These structures cast light on the unique structural features of chicken antibodies and contribute further to our collective understanding of the unique mechanisms of diversity and biochemical attributes that render the chicken repertoire of particular value for antibody generation.

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.