Complementarity-determining Region Residues Research Articles

High-throughput analysis system of interaction kinetics for data-driven antibody design

Surface plasmon resonance (SPR) is widely used for antigen–antibody interaction kinetics analysis. However, it has not been used in the screening phase because of the low throughput of measurement and analysis. Herein, we proposed a high-throughput SPR analysis system named “BreviA” using the Brevibacillus expression system. Brevibacillus was transformed using a plasmid library containing various antibody sequences, and single colonies were cultured in 96-well plates. Sequence analysis was performed using bacterial cells, and recombinant antibodies secreted in the supernatant were immobilized on a sensor chip to analyze their interactions with antigens using high-throughput SPR. Using this system, the process from the transformation to 384 interaction analyses can be performed within a week. This system utility was tested using an interspecies specificity design of an anti-human programmed cell death protein 1 (PD-1) antibody. A plasmid library containing alanine and tyrosine mutants of all complementarity-determining region residues was generated. A high-throughput SPR analysis was performed against human and mouse PD-1, showing that the mutation in the specific region enhanced the affinity for mouse PD-1. Furthermore, deep mutational scanning of the region revealed two mutants with > 100-fold increased affinity for mouse PD-1, demonstrating the potential efficacy of antibody design using data-driven approach.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody–protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies’ specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody–protein complexes, we compared the contributions of the interaction types in antibody–protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody–protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

Eradicating mesothelin-positive human gastric and pancreatic tumors in xenograft models with optimized anti-mesothelin antibody\u2013drug conjugates from synthetic antibody libraries

Mesothelin (MSLN) is an attractive candidate of targeted therapy for several cancers, and hence there are increasing needs to develop MSLN-targeting strategies for cancer therapeutics. Antibody–drug conjugates (ADCs) targeting MSLN have been demonstrated to be a viable strategy in treating MSLN-positive cancers. However, developing antibodies as targeting modules in ADCs for toxic payload delivery to the tumor site but not to normal tissues is not a straightforward task with many potential hurdles. In this work, we established a high throughput engineering platform to develop and optimize anti-MSLN ADCs by characterizing more than 300 scFv CDR-variants and more than 50 IgG CDR-variants of a parent anti-MSLN antibody as candidates for ADCs. The results indicate that only a small portion of the complementarity determining region (CDR) residues are indispensable in the MSLN-specific targeting. Also, the enhancement of the hydrophilicity of the rest of the CDR residues could drastically increase the overall solubility of the optimized anti-MSLN antibodies, and thus substantially improve the efficacies of the ADCs in treating human gastric and pancreatic tumor xenograft models in mice. We demonstrated that the in vivo treatments with the optimized ADCs resulted in almost complete eradication of the xenograft tumors at the treatment endpoints, without detectable off-target toxicity because of the ADCs’ high specificity targeting the cell surface tumor-associated MSLN. The technological platform can be applied to optimize the antibody sequences for more effective targeting modules of ADCs, even when the candidate antibodies are not necessarily feasible for the ADC development due to the antibodies’ inferior solubility or affinity/specificity to the target antigen.

Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study.

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira–TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira–TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0–6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.

Back-to-Germline (B2G) Procedure for Antibody Devolution.

Bispecific antibodies (bsAbs) with avidity-enhanced specificity can be used to address target cells with increased specificity, ideally binding efficiently to cells that express two cognate antigens, yet not to cells that express only one of those. Building blocks required to generate such bsAbs are binders that recognize the two antigens with high specificity yet with various (including very low monovalent) affinities. The herein described ‘back-to-germline’ (B2G) procedure defines such derivatives. It converts parent antibodies with high specificity to derivatives that retain specificity but modulate affinity. The approach defines mutations to be introduced into antibody complementarity-determining regions (CDRs) regions without requiring structures of antibody-antigen complexes. Instead, it reverses the B-cell maturation process that increases affinities, with preference on CDR residues with high antigen contact probability. Placing germline residues at those positions generates VH and VL domains and Fv-combinations thereof that retain specificities but are ‘de-matured’ to different degrees. De-maturation influences on-rates and off-rates, and can produce entities with extremely low affinity for which binding can only be detected in bivalent formats. A comparison with alanine replacement in CDRs (so far, the most frequently applied technology) indicates that B2G may be more reliable/predictable without introduction of stickiness or poly-reactivity. The applicability for generating sets of affinity-modulated monospecific variants is exemplarily shown for antibodies that bind CD138, Her2/neu, and EGFR.

Subtle changes at the variable domain interface of the T-cell receptor can strongly increase affinity

Most affinity-maturation campaigns for antibodies and T-cell receptors (TCRs) operate on the residues at the binding site, located within the loops known as complementarity-determining regions (CDRs). Accordingly, mutations in contact residues, or so-called "second shell" residues, that increase affinity are typically identified by directed evolution involving combinatorial libraries. To determine the impact of residues located at a distance from the binding site, here we used single-codon libraries of both CDR and non-CDR residues to generate a deep mutational scan of a human TCR against the cancer antigen MART-1·HLA-A2. Non-CDR residues included those at the interface of the TCR variable domains (Vα and Vβ) and surface-exposed framework residues. Mutational analyses showed that both Vα/Vβ interface and CDR residues were important in maintaining binding to MART-1·HLA-A2, probably due to either structural requirements for proper Vα/Vβ association or direct contact with the ligand. More surprisingly, many Vα/Vβ interface substitutions yielded improved binding to MART-1·HLA-A2. To further explore this finding, we constructed interface libraries and selected them for improved stability or affinity. Among the variants identified, one conservative substitution (F45βY) was most prevalent. Further analysis of F45βY showed that it enhanced thermostability and increased affinity by 60-fold. Thus, introducing a single hydroxyl group at the Vα/Vβ interface, at a significant distance from the TCR·peptide·MHC-binding site, remarkably affected ligand binding. The variant retained a high degree of specificity for MART-1·HLA-A2, indicating that our approach provides a general strategy for engineering improvements in either soluble or cell-based TCRs for therapeutic purposes.

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

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

Using a Machine-Learning Approach to Predict Discontinuous Antibody-Specific B-Cell Epitopes

Background: Predicting B-cell epitopes is important for understanding disease pathogenesis, identifying potential autoantigens, and designing vaccines and immune-based cancer therapies. The experimental approaches used for detecting B-cell epitopes are often laborious and resource-intensive. Thus, several computational methods have been developed for predicting the epitopes of a given antigen. However, most of these methods are coarse binary classifications of antigen regions within epitopes or non-epitopes and do not specify antibodies. Therefore, we aim to solve this antibodyspecified epitope prediction problem using a developed structure-based computational machine-learning method, Epitopia, to reflect this biological reality accurately. Result: We selected 60 non-redundant antibody-antigen protein complexes to train and applied the leave-one-out cross-validation method to test the accuracy of our proposed methods; we compared the results with the Epitopia, Discotope 2.0,PEASE and the state-of-the-art tool SEPPA 2.0. We considered the role of both complementarity determining region residues and antigen surface residues in antigenantibody interactions and assigned a score for each antigen surface residue. If we considered a prediction to be successful if the average score of “epitope residues” exceeded the average score over all surface residues. Then the success rates of our proposed methods were all higher than Epitopia and the best one was 83.3%, which is 7% higher than the rate obtained with Epitopia (76%). The results show that antibody-specific methods are competitive with, and sometimes even better than, Epitopia, which only considers the antigen residues. Conclusion: Our antibody-specific methods provide sufficient accuracy in locating epitopes because whether an antigen surface residue is an epitope depends on whether the antibody recognizes it. This approach is a new method for identifying B-cell epitopes. Based on our results, we believe that the prediction of antibody-specific B cell epitopes is more meaningful and efficient than those which are only considering antigen residues. Keywords: Antibody-specific B-cell epitope, paratope-epitope residue pair, machine-learning, bioinformatics, antigen, epitopia.

Facile Affinity Maturation of Antibody Variable Domains Using Natural Diversity Mutagenesis.

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

Structural insights into a high affinity nanobody:antigen complex by homology modelling

Porphyromonas gingivalis is a major periodontitis-causing pathogens. P. gingivalis secrete a cysteine protease termed RgpB, which is specific for Arg-Xaa bonds in substrates. Recently, a nanobody-based assay was used to demonstrate that RgpB could represent a novel diagnostic target, thereby simplifying. P. gingivalis detection. The nanobody, VHH7, had a high binding affinity and was specific for RgpB, when tested towards the highly identical RgpA.In this study a homology model of VHH7 was build. The complementarity determining regions (CDR) comprising the paratope residues responsible for RgpB binding were identified and used as input to the docking. Furthermore, residues likely involved in the RgpB epitope was identified based upon RgpB:RgpA alignment and analysis of residue surface accessibility. CDR residues and putitative RgpB epitope residues were used as input to an information-driven flexible docking approach using the HADDOCK server. Analysis of the VHH7:RgpB model demonstrated that the epitope was found in the immunoglobulin-like domain and residue pairs located at the molecular paratope:epitope interface important for complex stability was identified.Collectively, the VHH7 homology model and VHH7:RgpB docking supplies knowledge of the residues involved in the high affinity interaction. This information could prove valuable in the design of an antibody-drug conjugate for specific RgpB targeting.

Retraction Note to: Structure-based development and optimization of therapy antibody drugs against TNFα.

Previously, we reported on the crystal structures of the Fab fragments of two food and drug administration approved therapeutic antibodies, Infliximab and Adalimumab, in complex with TNFα. The structurally identified epitopes on TNFα reveal the mechanism of TNFα inhibition by partially overlapping with the TNFα-receptor interface. In this study, we launched a screen of a phage display library to isolate novel anti-TNFα antibodies based on the adalimumab epitope. Structural analysis, the phage display antibody isolation technology, step-by-step antibody optimization, complementarity-determining region residues random mutagenesis, phage ELISA, binding affinity characterization, and cell signaling assays were used for the development and optimization of the novel anti-TNFα antibodies. Moreover, one of the novel antibodies, hAta09, has a superior inhibitory effect on TNFα function and signaling. Taken together, our report established that the novel anti-TNFα antibody hAta09 may achieve clinical efficacy in a TNFα-associated disease.

Deep Sequencing-guided Design of a High Affinity Dual Specificity Antibody to Target Two Angiogenic Factors in Neovascular Age-related Macular Degeneration

The development of dual targeting antibodies promises therapies with improved efficacy over mono-specific antibodies. Here, we engineered a Two-in-One VEGF/angiopoietin 2 antibody with dual action Fab (DAF) as a potential therapeutic for neovascular age-related macular degeneration. Crystal structures of the VEGF/angiopoietin 2 DAF in complex with its two antigens showed highly overlapping binding sites. To achieve sufficient affinity of the DAF to block both angiogenic factors, we turned to deep mutational scanning in the complementarity determining regions (CDRs). By mutating all three CDRs of each antibody chain simultaneously, we were able not only to identify affinity improving single mutations but also mutation pairs from different CDRs that synergistically improve both binding functions. Furthermore, insights into the cooperativity between mutations allowed us to identify fold-stabilizing mutations in the CDRs. The data obtained from deep mutational scanning reveal that the majority of the 52 CDR residues are utilized differently for the two antigen binding function and permit, for the first time, the engineering of several DAF variants with sub-nanomolar affinity against two structurally unrelated antigens. The improved variants show similar blocking activity of receptor binding as the high affinity mono-specific antibodies against these two proteins, demonstrating the feasibility of generating a dual specificity binding surface with comparable properties to individual high affinity mono-specific antibodies.

RETRACTED ARTICLE: Structure-based development and optimization of therapy antibody drugs against TNFα

Previously, we reported on the crystal structures of the Fab fragments of two food and drug administration approved therapeutic antibodies, Infliximab and Adalimumab, in complex with TNFα. The structurally identified epitopes on TNFα reveal the mechanism of TNFα inhibition by partially overlapping with the TNFα-receptor interface. In this study, we launched a screen of a phage display library to isolate novel anti-TNFα antibodies based on the adalimumab epitope. Structural analysis, the phage display antibody isolation technology, step-by-step antibody optimization, complementarity-determining region residues random mutagenesis, phage ELISA, binding affinity characterization, and cell signaling assays were used for the development and optimization of the novel anti-TNFα antibodies. Moreover, one of the novel antibodies, hAta09, has a superior inhibitory effect on TNFα function and signaling. Taken together, our report established that the novel anti-TNFα antibody hAta09 may achieve clinical efficacy in a TNFα-associated disease.

Changing the peptide specificity of a human T-cell receptor by directed evolution.

Binding of a T cell receptor (TCR) to a peptide/major histocompatibility complex is the key interaction involved in antigen specificity of T cells. The recognition involves up to six complementarity determining regions (CDR) of the TCR. Efforts to examine the structural basis of these interactions and to exploit them in adoptive T cell therapies has required the isolation of specific T cell clones and their clonotypic TCRs. Here we describe a strategy using in vitro, directed evolution of a single TCR to change its peptide specificity, thereby avoiding the need to isolate T cell clones. The human TCR A6, which recognizes the viral peptide Tax/HLA-A2, was converted to TCR variants that recognized the cancer peptide MART1/HLA-A2. Mutational studies and molecular dynamics simulations identified CDR residues that were predicted to be important in the specificity switch. Thus, in vitro engineering strategies alone can be used to discover TCRs with desired specificities.

Antibody humanization by redesign of complementarity-determining region residues proximate to the acceptor framework

Antibodies are key components of the adaptive immune system and are well-established protein therapeutic agents. Typically high-affinity antibodies are obtained by immunization of rodent species that need to be humanized to reduce their immunogenicity. The complementarity-determining regions (CDRs) contain the residues in a defined loop structure that confer antigen binding, which must be retained in the humanized antibody. To design a humanized antibody, we graft the mature murine CDRs onto a germline human acceptor framework. Structural defects due to mismatches at the graft interface can be fixed by mutating some framework residues to murine, or by mutating some residues on the CDRs’ backside to human or to a de novo designed sequence. The first approach, framework redesign, can yield an antibody with binding better than the CDR graft and one equivalent to the mature murine, and reduced immunogenicity. The second approach, CDR redesign, is presented here as a new approach, yielding an antibody with binding better than the CDR graft, and immunogenicity potentially less than that from framework redesign. Application of both approaches to the humanization of anti-α4 integrin antibody HP1/2 is presented and the concept of the hybrid humanization approach that retains “difficult to match” murine framework amino acids and uses de novo CDR design to minimize murine amino acid content and reduce cell-mediated cytotoxicity liabilities is discussed.

Monoclonal Antibody m18 Paratope Leading to Dual Receptor Antagonism of HIV-1 gp120

We sought to identify sequences in the monoclonal antibody m18 complementarity determining regions (CDRs) that are responsible for its interaction with HIV-1 gp120 and inhibition of the envelope receptor binding sites. In the accompanying paper (DOI 10.1021/bi101160r), we reported that m18 inhibits CD4 binding through a nonactivating mechanism that, at the same time, induces conformational effects leading to inhibition of the coreceptor site. Here, we sought to define the structural elements in m18 responsible for these actions. Direct binding and competition analyses using surface plasmon resonance showed that YU-2 gp120 binding is stabilized by a broad paratope of residues in the m18 CDRs. Additionally, several m18 residues were identified for which mutants retained high affinity for gp120 but had suppressed CD4 and 17b inhibition activities. A subset of these mutants did, however, neutralize HXBc2 viral infection. The results obtained in this work demonstrate that the combined m18 paratope contains subsets of residues that are differentially important for the binding and inhibition functions of the m18 neutralizing antibody. The data also add to prior observations that high-affinity antibodies that do not inhibit monomeric gp120 receptor site interactions may still exhibit significant antiviral activity.

Abstract CN07-01: Two-in-one antibody: Herceptin variants that target HER2 and VEGF

Abstract CN07-01: Two-in-one antibody: Herceptin variants that target HER2 and VEGF

Epitope Mapping of Anti-Interleukin-13 Neutralizing Antibody CNTO607

CNTO607 is a neutralizing anti-interleukin-13 (IL-13) human monoclonal antibody obtained from a phage display library. To determine how this antibody inhibits the biological effect of IL-13, we determined the binding epitope by X-ray crystallography. The crystal structure of the complex between CNTO607 Fab and IL-13 reveals the antibody epitope at the surface formed by helices A and D of IL-13. This epitope overlaps with the IL-4Ralpha/IL-13Ralpha1 receptor-binding site, which explains the neutralizing effect of CNTO607. The extensive antibody interface covers an area of 1000 A(2), which is consistent with the high binding affinity. The key features of the interface are the charge and shape complementarity of the molecules that include two hydrophobic pockets on IL-13 that accommodate Phe32 [complementarity-determining region (CDR) L2] and Trp100a (CDR H3) and a number of salt bridges between basic residues of IL-13 and acidic residues of the antibody. Comparison with the structure of the free Fab shows that the CDR residues do not change their conformation upon complex formation, with the exception of two residues in CDR H3, Trp100a and Asp100b, which change rotamer conformations. To evaluate the relative contribution of the epitope residues to CNTO607 binding, we performed alanine-scanning mutagenesis of the A-D region of IL-13. This study confirmed the primary role of electrostatic interactions for antigen recognition.

Humanization of an Anti-CD34 Monoclonal Antibody by Complementarity-determining Region Grafting Based on Computer-assisted Molecular Modelling

4C8 is a new mouse anti-human CD34 monoclonal antibody (mAb), which recognizes class II CD34 epitopes and can be used for clinical hematopoietic stem/progenitor cell selection. In an attempt to improve its safety profiles, we have developed a humanized antibody of 4C8 by complementarity-determining region (CDR) grafting method in this study. Using a molecular model of 4C8 built by computer-assisted homology modelling, framework region (FR) residues of potential importance to the antigen binding were identified. A humanized version of 4C8, denoted as h4C8, was generated by transferring these key murine FR residues onto a human antibody framework that was selected based on homology to the mouse antibody framework, together with the mouse CDR residues. The resultant humanized antibody was shown to possess antigen-binding affinity and specificity similar to that of the original murine antibody, suggesting that it might be an alternative to mouse anti-CD34 antibodies routinely used clinically.

A New Twist in TCR Diversity Revealed by a Forbidden αβ TCR

We report crystal structures of a negatively selected T cell receptor (TCR) that recognizes two I-A u-restricted myelin basic protein peptides and one of its peptide/major histocompatibility complex (pMHC) ligands. Unusual complementarity-determining region (CDR) structural features revealed by our analyses identify a previously unrecognized mechanism by which the highly variable CDR3 regions define ligand specificity. In addition to the pMHC contact residues contributed by CDR3, the CDR3 residues buried deep within the Vα/Vβ interface exert indirect effects on recognition by influencing the Vα/Vβ interdomain angle. This phenomenon represents an additional mechanism for increasing the potential diversity of the TCR repertoire. Both the direct and indirect effects exerted by CDR residues can impact global TCR/MHC docking. Analysis of the available TCR structures in light of these results highlights the significance of the Vα/Vβ interdomain angle in determining specificity and indicates that TCR/pMHC interface features do not distinguish autoimmune from non-autoimmune class II-restricted TCRs.