Restricted Diversity of Antigen Binding Residues of Antibodies Revealed by Computational Alanine Scanning of 227 Antibody–Antigen Complexes

Analysis of how antigen mutations disrupt antibody binding interactions toward enabling rapid and reliable antibody repurposing

Antibody repurposing is the process of changing a known antibody so that it binds to a mutated antigen. One of the findings to emerge from the Coronavirus Disease 2019 (COVID-19) pandemic was that it was possible to repurpose neutralizing antibodies for Severe Acute Respiratory Syndrome, a related disease, to work for COVID-19. Thus, antibody repurposing is a possible pathway to prepare for and respond to future pandemics, as well as personalizing cancer therapies. For antibodies to be successfully repurposed, it is necessary to know both how antigen mutations disrupt their binding and how they should be mutated to recover binding, with this work describing an analysis to address the first of these topics. Every possible antigen point mutation in the interface of 246 antibody-protein complexes were analyzed using the Rosetta molecular mechanics force field. The results highlight a number of features of how antigen mutations affect antibody binding, including the effects of mutating critical hotspot residues versus other positions, how many mutations are necessary to be likely to disrupt binding, the prevalence of indirect effects of mutations on binding, and the relative importance of changing attractive versus repulsive energies. These data are expected to be useful in guiding future antibody repurposing experiments.

Discovery of a pan anti-SARS-CoV-2 monoclonal antibody with highly efficient infected cell killing capacity for novel immunotherapeutic approaches

Unlocking the potential of broadly reactive coronavirus monoclonal antibodies (mAbs) and their derivatives offers a transformative therapeutic avenue against severe COVID-19, especially crucial for safeguarding high-risk populations. Novel mAb-based immunotherapies may help address the reduced efficacy of current vaccines and neutralizing mAbs caused by the emergence of variants of concern (VOCs). Using phage display technology, we discovered a pan-SARS-CoV-2 mAb (C10) that targets a conserved region within the receptor-binding domain (RBD) of the virus. Noteworthy, C10 demonstrates exceptional efficacy in recognizing all assessed VOCs, including recent Omicron variants. While C10 lacks direct neutralization capacity, it efficiently binds to infected lung epithelial cells and induces their lysis via natural killer (NK) cell-mediated antibody-dependent cellular cytotoxicity (ADCC). Building upon this pan-SARS-CoV-2 mAb, we engineered C10-based, Chimeric Antigen Receptor (CAR)-T cells endowed with efficient killing capacity against SARS-CoV-2-infected lung epithelial cells. Notably, NK and CAR-T-cell mediated killing of lung infected cells effectively reduces viral titers. These findings highlight the potential of non-neutralizing mAbs in providing immune protection against emerging infectious diseases. Our work reveals a pan-SARS-CoV-2 mAb effective in targeting infected cells and demonstrates the proof-of-concept for the potential application of CAR-T cell therapy in combating SARS-CoV-2 infections. Furthermore, it holds promise for the development of innovative antibody-based and cell-based therapeutic strategies against severe COVID-19 by expanding the array of therapeutic options available for high-risk populations.Trial registration: ClinicalTrials.gov identifier: NCT04093596.

Isoelectric point, net charge and amino acid analysis of experimentally validated therapeutic antibodies

The isoelectric point (pI) of an antibody is known to affect its non-specific interactions and repulsive self-interactions. However, analytical outcomes for the pI of a large number of therapeutic antibodies remain unexplored. In this study, we explored the pI and net charge of variable heavy (VH), variable light (VL), CDR (complementarity determining regions) and whole IgG on a large number of therapeutic antibodies, additionally amino acids distribution in the CDR regions were also analyzed. A total of 708 experimentally validated antibodies from the Thera-SAbDab database were analyzed in this study. Analysis of the antibody dataset showed that the pI of the whole IgG sequence is between 5 and 9, while the majority was in the intermediate range between 7 and 9 (86.7%). The charge had a wide range from - 10 to 12, with the majority falling between the charges 2-6 (53.4%). However, the combined pI score of the CDRs of light chains (60%) as well as for the heavy chains (67%) was observed in the range of 4-6. The amino acid composition analysis of CDR regions revealed that most of the amino acids in the light chain are uncharged-polar (46.3%) followed by hydrophobic-aliphatic (28.4%), while in the heavy chain; it is hydrophobic-aliphatic (35.2%) followed by uncharged-polar (24.6%). In conclusion, the pI and net charge analysis of therapeutic antibodies are crucial for understanding pharmacokinetic properties. Moreover, amino acid composition of the light and heavy chain CDR regions has a significant impact on the pI and charge of the entire IgG antibody.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00356-y.

Predicting Antibody Affinity Changes upon Mutation Based on Unbound Protein Structures

Antibodies are key proteins in the immune system that can reversibly and non-covalently bind specifically to their corresponding antigens, forming antigen-antibody complexes. They play a crucial role in recognizing foreign or self-antigens during the adaptive immune response. Monoclonal antibodies have emerged as a promising class of biological macromolecule therapeutics with broad market prospects. In the process of antibody drug development, a key engineering challenge is to improve the affinity of candidate antibodies, without experimentally resolved structures of the antigen-antibody complexes as input for computer-aided predictive methods. In this work, we present an approach for predicting the effect of residue mutations on antibody affinity without the structures of the antigen-antibody complexes. The method involves the graph representation of proteins and utilizes a pre-trained encoder. The encoder captures the residue-level microenvironment of the target residue on the antibody along with the antigen context pre- and post-mutation. The encoder inherently possesses the potential to identify paratope residues. In addition, we curated a benchmark dataset specifically for mutations of the antibody. Compared to baseline methods based on complex structures and sequences, our approach achieves superior or comparable average accuracy on benchmark datasets. Additionally, we validate its advantage of not requiring antigen-antibody complex structures as input for predicting the effects of mutations in antibodies against SARS-CoV-2, influenza, and human cytomegalovirus. Our method shows its potential for identifying mutations that improve antibody affinity in practical antibody engineering applications.

Amino acids characterization based on frequency and interaction analysis in human antigen-antibody complexes from Thera-SAbDab

BackgroundAntibodies are composed of light and heavy chains, both of which have constant and variable regions. The diversity, specific binding ability and therapeutic potential of antibodies are determined by hypervariable loops called complementarity-determining regions (CDRs), with the other regions being the framework regions.ObjectiveTo investigate the key amino acid patterns in various antibody regions in the human therapeutic antigen-antibody (Ag-Ab) complexes collected from the Thera-SAbDab database.MethodThe study focuses on identifying the amino acid frequency, diversity index in CDRs, paratope-epitope amino acid interactions, amino acid bond formation frequency, and bond types among selected therapeutic Ag-Ab complexes.ResultsThe results revealed that Ser is highly distributed in the overall light chain CDRs while Gly is highly distributed in the heavy chain CDRs. CDR profiling analysis indicated that the average amino acid diversity in heavy chain CDRs is 60% to 70%, while in the light chain, it is 50% to 60%. Aromatic residues such as Tyr, Trp and Phe are the top contributors to these paratope-epitope interactions in the light and heavy chains. Moreover, we examined the frequency of amino acids in light and heavy chains of Ag-Ab complexes. Importantly, the outcome of this study leverages the in depth analysis on single residues, dipeptides, and tripeptides for the therapeutic Ag-Ab complexes.ConclusionWe conclude that the amino acid frequency and interaction analysis centered on therapeutic Ag-Ab complexes will benefit antibody engineering parameters such as antibody design, optimization, affinity maturation, and overall antibody development.

Amino Acids Frequency and Interaction Trends: Comprehensive Analysis of Experimentally Validated Viral Antigen-Antibody Complexes

Antibodies have specific binding capabilities and therapeutic potential for treating various diseases, including viral infections. The amino acid composition of the hypervariable complementarity determining regions (CDR) loops and the framework regions (FR) are the determining factors for the affinity and therapeutic efficacy of the antibodies. In this study selected and curated, 77 viral antigen-human antibody complexes from Protein data bank from the Thera-SAbdab database were analyzed. The results revealed diversity indices within specific CDR regions, amino acid frequencies, paratope-epitope interactions, bond formations, and bond types among the analyzed viral Ag-Ab complexes. The finding revealed that Ser, Gly, Tyr, Thr, and Phe are prominently present in the antibody CDRs. Analysis of CDR profiles indicated an average amino acid diversity of 60-80% in heavy chain CDRs and 45-60% in light chain CDRs. Aromatic residues, particularly Tyr, Phe, and Trp showed significant involvement in the paratope-epitope interactions in the heavy chain, while Tyr, Ser, and Thr were key contributors in the light chain. Furthermore, the study examined the occurrence of amino acids in both light and heavy chains of viral Ag- human Ab complexes, analyzing the presence of amino acids as single residues, dipeptides and tripeptides. The analysis is crucial for enhancing the antibody engineering processes including, design, optimization, affinity enhancement, and overall antibody development.

Rapid affinity optimization of an anti-TREM2 clinical lead antibody by cross-lineage immune repertoire mining

We describe a process for rapid antibody affinity optimization by repertoire mining to identify clones across B cell clonal lineages based on convergent immune responses where antigen-specific clones with the same heavy (VH) and light chain germline segment pairs, or parallel lineages, bind a single epitope on the antigen. We use this convergence framework to mine unique and distinct VH lineages from rat anti-triggering receptor on myeloid cells 2 (TREM2) antibody repertoire datasets with high diversity in the third complementarity-determining loop region (CDR H3) to further affinity-optimize a high-affinity agonistic anti-TREM2 antibody while retaining critical functional properties. Structural analyses confirm a nearly identical binding mode of anti-TREM2 variants with subtle but significant structural differences in the binding interface. Parallel lineage repertoire mining is uniquely tailored to rationally explore the large CDR H3 sequence space in antibody repertoires and can be easily and generally applied to antibodies discovered in vivo.

Identification of monoclonal antibodies from naive antibody phage-display libraries for protein detection in formalin-fixed paraffin-embedded tissues

Most antibodies used in immunohistochemistry (IHC) have been developed by animal immunization. We wanted to explore naive antibody repertoires displayed on filamentous phages as a source of full-length antibodies for IHC on Formalin-Fixed and Paraffin-Embedded (FFPE) tissues. We used two isogenic mouse fibroblast cell lines that express or not human HER2 to generate positive and negative FFPE pseudo-tissue respectively. Using these pseudo-tissues and previously described approaches based on differential panning, we isolated very efficient antibody clones, but not against HER2. To optimize HER2 targeting and tissue specificity, we first performed 3-4 rounds of in vitro panning using recombinant HER2 extracellular domain (ECD) to enrich the phage library in HER2 binders, followed by one panning round using the two FFPE pseudo-tissues to retain binders for IHC conditions. We then analyzed the bound phages using next-generation sequencing to identify antibody sequences specifically associated with the HER2-positive pseudo-tissue. Using this approach, the top-ranked clone identified by sequencing was specific to the HER2-positive pseudo-tissue and showed a staining pattern similar to that of the antibody used for the clinical diagnosis of HER2-positive breast cancer. However, we could not optimize staining on other tissues, showing that specificity was restricted to the tissue used for selection and screening. Therefore, future optimized protocols must consider tissue diversity early during the selection by panning using a wide collection of tissue types.

Understanding the Specific Implications of Amino Acids in the Antibody Development

As the demand for immunotherapy to treat and manage cancers, infectious diseases and other disorders grows, a comprehensive understanding of amino acids and their intricate role in antibody engineering has become a prime requirement. Naturally produced antibodies may not have the most suitable amino acids at the complementarity determining regions (CDR) and framework regions, for therapeutic purposes. Therefore, to enhance the binding affinity and therapeutic properties of an antibody, the specific impact of certain amino acids on the antibody's architecture must be thoroughly studied. In antibody engineering, it is crucial to identify the key amino acid residues that significantly contribute to improving antibody properties. Therapeutic antibodies with higher binding affinity and improved functionality can be achieved through modifications or substitutions with highly suitable amino acid residues. Here, we have indicated the frequency of amino acids and their association with the binding free energy in CDRs. The review also analyzes the experimental outcome of two studies that reveal the frequency of amino acids in CDRs and provides their significant correlation between the outcomes. Additionally, it discusses the various bond interactions within the antibody structure and antigen binding. A detailed understanding of these amino acid properties should assist in the analysis of antibody sequences and structures needed for designing and enhancing the overall performance of therapeutic antibodies.

A bioinspired approach for the modulation of electroosmotic flow and protein-surface interactions in capillary electrophoresis using silylated amino-amides blocks and covalent grafting

We explore a bioinspired approach to design tailored functionalized capillary electrophoresis (CE) surfaces based on covalent grafting for biomolecules analysis. First, the approach aims to overcome well-known common obstacles in CE protein analysis affecting considerably the CE performance (asymmetry, resolution, and repeatability) such as the unspecific adsorption on fused silica surface and the lack of control of electroosmotic flow (EOF). Then, our approach, which relies on new amino-amide mimic hybrid precursors synthesized by silylation of amino-amides (Si-AA) derivatives with 3-isocyanatopropyltriethoxysilane, aims to recapitulate the diversity of protein-protein interactions (π-π stacking, ionic, Van der Waals…) found in physiological condition (bioinspired approach) to improve the performance of CE protein analysis (electrochromatography). As a proof of concept, these silylated Si-AA (tyrosinamide silylation, serinamide silylation, argininamide silylation, leucinamide silylation, and isoglutamine silylation acid) have been covalently grafted in physiological conditions in different amount on bare fused silica capillary giving rise to a biomimetic coating and allowing both the modulation of EOF and protein-surface interactions. The analytical performances of amino-amide functionalized capillaries were assessed using lysozyme, cytochrome C and ribonuclease A and compared to traditional capillary coatings poly(ethylene oxide), poly(diallyldimethylammonium chloride), and sodium poly(styrenesulfonate). EOF, protein adsorption rate, protein retention factor k, and selectivity were determined for each coating. All results obtained showed this approach allowed to modulate the EOF, reduce unspecific adsorption, and generate specific interactions with proteins by varying the nature and the amount of Si-AA in the functionalization mixture.

Developing similarity matrices for antibody-protein binding interactions

The inventions of AlphaFold and RoseTTAFold are revolutionizing computational protein science due to their abilities to reliably predict protein structures. Their unprecedented successes are due to the parallel consideration of several types of information, one of which is protein sequence similarity information. Sequence homology has been studied for many decades and depends on similarity matrices to define how similar or different protein sequences are to one another. A natural extension of predicting protein structures is predicting the interactions between proteins, but similarity matrices for protein-protein interactions do not exist. This study conducted a mutational analysis of 384 non-redundant antibody-protein antigen complexes to calculate antibody-protein interaction similarity matrices. Every important residue in each antibody and each antigen was mutated to each of the other 19 commonly occurring amino acids and the percentage changes in interaction energies were calculated using three force fields: CHARMM, Amber, and Rosetta. The data were used to construct six interaction similarity matrices, one for antibodies and another for antigens using each force field. The matrices exhibited both commonalities, such as mutations of aromatic and charged residues being the most detrimental, and differences, such as Rosetta predicting mutations of serines to be better tolerated than either Amber or CHARMM. A comparison to nine previously published similarity matrices for protein sequences revealed that the new interaction matrices are more similar to one another than they are to any of the previous matrices. The created similarity matrices can be used in force field specific applications to help guide decisions regarding mutations in protein-protein binding interfaces.

A cell hybridization-based method of generating recombinant rabbit monoclonal antibodies for detecting cytokines

Recombinant rabbit monoclonal antibodies (rabbit rAbs) have shown promise in various biomedical fields. However, it is challenging and costly to generate rabbit rAbs using traditional techniques. Here we describe a convenient and cost-effective method. Using this method, we generated rabbit rAbs against mouse soluble IL-6 receptor α with affinities in the range of 10-9 to 10-12 M. The presented method is suitable for industrial and academic scientists looking to customize rabbit rAbs for their research.

Fc-engineered monoclonal antibodies to reduce off-target liver uptake

BACKGROUND

Radiolabeled-antibodies usually display non-specific liver accumulation that may impair image analysis and antibody biodistribution. Here, we investigated whether Fc silencing influenced antibody biodistribution. We compared recombinant 89Zr-labeled antibodies (human IgG1 against different targets) with wild-type Fc and with mutated Fc (LALAPG triple mutation to prevent binding to Fc gamma receptors; FcγR). After antibody injection in mice harboring xenografts of different tumor cell lines or of immortalized human myoblasts, we analyzed antibody biodistribution by PET-CT and conventional biodistribution analysis.

RESULTS

Accumulation in liver was strongly reduced and tumor-specific targeting was increased for the antibodies with mutated Fc compared with wild-type Fc.

CONCLUSION

Antibodies with reduced binding to FcγR display lower liver accumulation and better tumor-to-liver ratios. These findings need to be taken into account to improve antibody-based theragnostic approaches.

Antibody-mediated neutralization of galectin-3 as a strategy for the treatment of systemic sclerosis

Systemic sclerosis (SSc) is an autoimmune, inflammatory and fibrotic disease with limited treatment options. Developing new therapies is therefore crucial to address patient needs. To this end, we focused on galectin-3 (Gal-3), a lectin known to be associated with several pathological processes seen in SSc. Using RNA sequencing of whole-blood samples in a cross-sectional cohort of 249 patients with SSc, Gal-3 and its interactants defined a strong transcriptomic fingerprint associated with disease severity, pulmonary and cardiac malfunctions, neutrophilia and lymphopenia. We developed new Gal-3 neutralizing monoclonal antibodies (mAb), which were then evaluated in a mouse model of hypochlorous acid (HOCl)-induced SSc. We show that two of these antibodies, D11 and E07, reduced pathological skin thickening, lung and skin collagen deposition, pulmonary macrophage content, and plasma interleukin-5 and -6 levels. Moreover, E07 changed the transcriptional profiles of HOCl-treated mice, resulting in a gene expression pattern that resembled that of control mice. Similarly, pathological pathways engaged in patients with SSc were counteracted by E07 in mice. Collectively, these findings demonstrate the translational potential of Gal-3 blockade as a therapeutic option for SSc.

AREA-AFFINITY: A Web Server for Machine Learning-Based Prediction of Protein-Protein and Antibody-Protein Antigen Binding Affinities

Protein-Protein binding affinity reflects the binding strength between the binding partners. The prediction of protein-protein binding affinity is important for elucidating protein functions and also for designing protein-based therapeutics. The geometric characteristics such as area (both interface and surface areas) in the structure of a protein-protein complex play an important role in determining protein-protein interactions and their binding affinity. Here, we present a free web server for academic use, AREA-AFFINITY, for prediction of protein-protein or antibody-protein antigen binding affinity based on interface and surface areas in the structure of a protein-protein complex. AREA-AFFINITY implements 60 effective area-based protein-protein affinity predictive models and 37 effective area-based models specific for antibody-protein antigen binding affinity prediction developed in our recent studies. These models take into consideration the roles of interface and surface areas in binding affinity by using areas classified according to different amino acid types with different biophysical nature. The models with the best performances integrate machine learning methods such as neural network or random forest. These newly developed models have superior or comparable performance compared to the commonly used existing methods. AREA-AFFINITY is available for free at: https://affinity.cuhk.edu.cn/.

Activation of neuronal FLT3 promotes exaggerated sensorial and emotional pain-related behaviors facilitating the transition from acute to chronic pain

Acute pain has been associated with persistent pain sensitization of nociceptive pathways increasing the risk of transition from acute to chronic pain. We demonstrated the critical role of the FLT3- tyrosine kinase receptor, expressed in sensory neurons, in pain chronification after peripheral nerve injury. However, it is unclear whether injury-induced pain sensitization can also promote long-term mood disorders. Here, we evaluated the emotional and sensorial components of pain after a single (SI) or double paw incision (DI) and the implication of FLT3. DI mice showed an anxiodepressive-like phenotype associated with extended mechanical pain hypersensitivity and spontaneous pain when compared to SI mice. Behavioral exaggeration was associated with peripheral and spinal changes including increased microglia activation after DI versus SI. Intrathecal microglial inhibitors not only eliminated the exaggerated pain hypersensitivity produced by DI but also prevented anxiodepressive-related behaviors. Behavioral and cellular changes produced by DI were blocked in Flt3 knock-out animals and recapitulated by repeated intrathecal FL injections in naive animals. Finally, humanized antibodies against FLT3 reduced DI-induced behavioral and microglia changes. Altogether our results show that the repetition of peripheral lesions facilitate not only exaggerated nociceptive behaviors but also induced anxiodepressive disorders supported by spinal central changes that can be blocked by targeting peripheral FLT3.

Characterization of Phosphorylation-Dependent Antibody Binding to Cancer-Mutated Linkers of C2H2 Zinc Finger Proteins by Intact Transition Epitope Mapping-Thermodynamic Weak-Force Order Analysis

With Intact Transition Epitope Mapping-Thermodynamic Weak-force Order (ITEM-TWO) analysis in combination with molecular modeling, the phosphorylation-dependent molecular recognition motif of the anti-HpTGEKP antibody has been investigated with binary and ternary component mixtures consisting of antibody and (phospho-) peptides. Amino acid sequences have been selected to match either the antibody's recognition motif or the cancer-related zinc finger protein mutations and phosphorylations of the respective amino acid residues. Upon electrospraying of all the components of the mixtures, that is, hexapeptides, antibody, and intact immune complexes, the produced ions were subjected to mass spectrometric mass filtering. The antibody ions as well as the immune complex ions traversed into the mass spectrometer's collision chamber, whereas paths of unbound peptide ions were blocked prior to entering the collision cell. After dissociation of the multiply charged immune complexes in the gas phase, the complex-released peptide ions were recorded after having traversed the second mass filter. Complex-released peptides were unambiguously identified by their masses using mass analysis with isotope resolution. From the results of our studies with seven (phospho-) peptides with distinct amino acid sequences, which resembled either the antibody's binding motif or mutations, we conclude the following: (i) A negatively charged phospho group, located near the peptide's N-terminus is mandatory for antibody binding when placed on the peptide surface at a precise distance to the C-terminally located positively charged ε-amino group of a lysinyl residue. (ii) A bulky amino acid residue, such as the tyrosinyl residue at the N-terminal position of the (phospho-) threoninyl residue, abolishes antibody binding. (iii) Two closely spaced phospho groups negatively interfere with the surface polarity pattern and abolish antibody binding as well. (iv) Non-phosphorylated peptides are not binding partners of the anti-HpTGEKP antibody.

Analysis of conformational stability of interacting residues in protein binding interfaces

After approximately 60 years of work, the protein folding problem has recently seen rapid advancement thanks to the inventions of AlphaFold and RoseTTAFold, which are machine-learning algorithms capable of reliably predicting protein structures from their sequences. A key component in their success was the inclusion of pairwise interaction information between residues. As research focus shifts towards developing algorithms to design and engineer binding proteins, it is likely that knowledge of interaction features at protein interfaces can improve predictions. Here, 574 protein complexes were analyzed to identify the stability features of their pairwise interactions, revealing that interactions between pre-stabilized residues are a selected feature in protein binding interfaces. In a retrospective analysis of 475 de novo designed binding proteins with an experimental success rate of 19%, inclusion of pairwise interaction pre-stabilization parameters increased the frequency of identifying experimentally successful binders to 40%.

Significance of antibody numbering systems in the development of antibody engineering

Immunotherapy has become increasingly popular in recent years for treating a variety of diseases including inflammatory, neurological, oncological, and auto-immune disorders. The significant interest in antibody development is due to the high binding affinity and specificity of an antibody against a specific antigen. Recent advances in antibody engineering have provided a different view on how to engineer antibodies in silico for therapeutic and diagnostic applications. In order to improve the clinical utility of therapeutic antibodies, it is of paramount importance to understand the various molecular properties which impact antigen targeting and its potency. In antibody engineering, antibody numbering (AbN) systems play an important role to identify the complementarity determining regions (CDRs) and the framework regions (FR). Hence, it is crucial to accurately define and understand the CDR, FR and the crucial residues of heavy and light chains that aid in the binding of the antibody to the antigenic site. Detailed understanding of amino acids positions are useful for modifying the binding affinity, specificity, physicochemical features, and half-life of an antibody. In this review, we have summarized the different antibody numbering systems that are widely used in antibody engineering and highlighted their significance. Here, we have systematically explored and mentioned the various tools and servers that harness different AbN systems.

Binding affinity prediction for antibody-protein antigen complexes: A machine learning analysis based on interface and surface areas

Specific antibodies can bind to protein antigens with high affinity and specificity, and this property makes them one of the best protein-based therapeutics. Accurate prediction of antibody‒protein antigen binding affinity is crucial for designing effective antibodies. The current predictive methods for protein‒protein binding affinity usually fail to predict the binding affinity of an antibody‒protein antigen complex with a comparable level of accuracy. Here, new models specific for antibody‒antigen binding affinity prediction are developed according to the different types of interface and surface areas present in antibody‒antigen complex. The contacts-based descriptors are also employed to construct or train different models specific for antibody‒protein antigen binding affinity prediction. The results of this study show that (i) the area-based descriptors are slightly better than the contacts-based descriptors in terms of the predictive power; (ii) the new models specific for antibody‒protein antigen binding affinity prediction are superior to the previously-used general models for predicting the protein‒protein binding affinities; (iii) the performances of the best area-based and contacts-based models developed in this work are better than the performances of a recently-developed graph-based model (i.e., CSM-AB) specific for antibody‒protein antigen binding affinity prediction. The new models developed in this work would not only help understand the mechanisms underlying antibody‒protein antigen interactions, but would also be of some applicable utility in the design and virtual screening of antibody-based therapeutics.

Learned features of antibody-antigen binding affinity

Defining predictors of antigen-binding affinity of antibodies is valuable for engineering therapeutic antibodies with high binding affinity to their targets. However, this task is challenging owing to the huge diversity in the conformations of the complementarity determining regions of antibodies and the mode of engagement between antibody and antigen. In this study, we used the structural antibody database (SAbDab) to identify features that can discriminate high- and low-binding affinity across a 5-log scale. First, we abstracted features based on previously learned representations of protein-protein interactions to derive 'complex' feature sets, which include energetic, statistical, network-based, and machine-learned features. Second, we contrasted these complex feature sets with additional 'simple' feature sets based on counts of contacts between antibody and antigen. By investigating the predictive potential of 700 features contained in the eight complex and simple feature sets, we observed that simple feature sets perform comparably to complex feature sets in classification of binding affinity. Moreover, combining features from all eight feature-sets provided the best classification performance (median cross-validation AUROC and F1-score of 0.72). Of note, classification performance is substantially improved when several sources of data leakage (e.g., homologous antibodies) are not removed from the dataset, emphasizing a potential pitfall in this task. We additionally observe a classification performance plateau across diverse featurization approaches, highlighting the need for additional affinity-labeled antibody-antigen structural data. The findings from our present study set the stage for future studies aimed at multiple-log enhancement of antibody affinity through feature-guided engineering.

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.

Epitope Fine Mapping by Mass Spectrometry: Investigations of Immune Complexes Consisting of Monoclonal Anti-HpTGEKP Antibody and Zinc Finger Protein Linker Phospho-Hexapeptides

Accurate formation of antibody-antigen complexes has been relied on in both, multitudes of scientific projects and ample therapeutic and diagnostic applications. Mass spectrometrically determined dissociation behavior of immune complexes with the anti-HpTGEKP antibody revealed that the ten most frequently occurring phospho-hexapeptide linker sequences from C2H2 zinc finger proteins could be divided into two classes: orthodox binders, where strong noncovalent interactions developed as anticipated, and unorthodox binders with deviating structures and weaker binding. Phosphorylation of threonine was compulsory for antibody binding in an orthodox manner. Gas phase dissociation energy determinations of seven C2H2 zinc finger protein linker phospho-hexapeptides with orthodox binding properties revealed a bipolar binding motif of the antibody paratope. Epitope peptides, which in addition to the negatively charged phospho-threonine residue were C-terminally flanked by positively charged residues provided stronger binding, i. e. dissociation was endothermic, than peptides with acidic amino acid residues at these positions, for which dissociation was exothermic.

Antibody homotypic interactions are encoded by germline light chain complementarity determining region 2

Weak transient interactions are fundamental to immune responses, enabling avidity-driven triggers for pathogen neutralization and cellular regulation. In contrast to obligate binding interactions that can be directly investigated structurally, the low or transitory abundance of weak interactions make them difficult to identify and characterize. This study leverages receptor agonism systems that are sensitive to oligomerization to investigate transient homotypic interfaces between antibody Fab regions. Our results show that self-association determinants are encoded naturally by the antibody germline through light chain complementarity determining region 2 (CDRL2), and these determinants can be engineered into antibodies to enhance their therapeutic properties. Insights into avidity-driven interactions create opportunities for optimization, and accordingly this work expands the engineering toolbox for antibody-based drugs.

The utilization of avidity to drive and tune functional responses is fundamental to antibody biology and often underlies the mechanisms of action of monoclonal antibody drugs. There is increasing evidence that antibodies leverage homotypic interactions to enhance avidity, often through weak transient interfaces whereby self-association is coupled with target binding. Here, we comprehensively map the Fab–Fab interfaces of antibodies targeting DR5 and 4-1BB that utilize homotypic interaction to promote receptor activation and demonstrate that both antibodies have similar self-association determinants primarily encoded within a germline light chain complementarity determining region 2 (CDRL2). We further show that these determinants can be grafted onto antibodies of distinct target specificity to substantially enhance their activity. An expanded characterization of all unique germline CDRL2 sequences reveals additional self-association sequence determinants encoded in the human germline repertoire. Our results suggest that this phenomenon is unique to CDRL2, and is correlated with the less frequent antigen interaction and lower somatic hypermutation associated with this loop. This work reveals a previously unknown avidity mechanism in antibody native biology that can be exploited for the engineering of biotherapeutics.

Camelid Single-Domain Antibodies: Promises and Challenges as Lifesaving Treatments

Since the discovery of camelid heavy-chain antibodies in 1993, there has been tremendous excitement for these antibody domains (VHHs/sdAbs/nanobodies) as research tools, diagnostics, and therapeutics. Commercially, several patents were granted to pioneering research groups in Belgium and the Netherlands between 1996–2001. Ablynx was established in 2001 with the aim of exploring the therapeutic applications and development of nanobody drugs. Extensive efforts over two decades at Ablynx led to the first approved nanobody drug, caplacizumab (Cablivi) by the EMA and FDA (2018–2019) for the treatment of rare blood clotting disorders in adults with acquired thrombotic thrombocytopenic purpura (TPP). The relatively long development time between camelid sdAb discovery and their entry into the market reflects the novelty of the approach, together with intellectual property restrictions and freedom-to-operate issues. The approval of the first sdAb drug, together with the expiration of key patents, may open a new horizon for the emergence of camelid sdAbs as mainstream biotherapeutics in the years to come. It remains to be seen if nanobody-based drugs will be cheaper than traditional antibodies. In this review, I provide critical perspectives on camelid sdAbs and present the promises and challenges to their widespread adoption as diagnostic and therapeutic agents.

Identification of single domain antibodies with insect cytotoxicity using phage-display antibody library screening and Plutella xylostella ATP-binding cassette transporter subfamily C member 2 (ABCC2) -based insect cell expression system

It is extremely imminent to study a new strategy to manage agricultural pest like Plutella xylostella (P. xylostella) which is currently resistant to most of pesticides, including three domain-Cry toxins from Bacillus thuringiensis (Bt). In this study, we reported a phage displayed single domain antibody screening from human domain antibody (DAb) library targeted on Spodoptera frugiperda 9 (Sf9) cells expressed Cry1Ac toxin receptor, ATP-dependent binding cassette transporter C2 in P. xylostella (PxABCC2). After three rounds of panning, three cytotoxic antibodies (1D2, 2B7, 3C4) were obtained from thirty-eight antibodies and displayed high binding ability towards PxABCC2-expressed Sf9 cells. Through homology modeling and molecular docking, the interaction mode indicated that the most cytotoxic 1D2 of the three antibodies presented the lowest binding free energy required and had the most hydrogen bond formed with PxABCC2 in molecular docking analysis. Functional assay of key regions in 1D2 via Alanine replacement indicated that complementarity-determining region (CDR) 3 played a crucial role in antibody exerts binding activity and cytotoxicity. This study provides the first trial for discovering of potential cytotoxic antibodies from the human antibody library via specific receptor-expressed insect cell system biopanning.

CSM-AB: graph-based antibody-antigen binding affinity prediction and docking scoring function

MOTIVATION

Understanding antibody-antigen interactions is key to improving their binding affinities and specificities. While experimental approaches are fundamental for developing new therapeutics, computational methods can provide quick assessment of binding landscapes, guiding experimental design. Despite this, little effort has been devoted to accurately predicting the binding affinity between antibodies and antigens and to develop tailored docking scoring functions for this type of interaction. Here, we developed CSM-AB, a machine learning method capable of predicting antibody-antigen binding affinity by modelling interaction interfaces as graph-based signatures.

RESULTS

CSM-AB outperformed alternative methods achieving a Pearson's correlation of up to 0.64 on blind tests. We also show CSM-AB can accurately rank near-native poses, working effectively as a docking scoring function. We believe CSM-AB will be an invaluable tool to assist in the development of new immunotherapies.

AVAILABILITY AND IMPLEMENTATION

CSM-AB is freely available as a user-friendly web interface and API at http://biosig.unimelb.edu.au/csm_ab/datasets.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Agonist antibody discovery: Experimental, computational, and rational engineering approaches

Agonist antibodies that activate cellular signaling have emerged as promising therapeutics for treating myriad pathologies. Unfortunately, the discovery of rare antibodies with the desired agonist functions is a major bottleneck during drug development. Nevertheless, there has been important recent progress in discovering and optimizing agonist antibodies against a variety of therapeutic targets that are activated by diverse signaling mechanisms. Herein, we review emerging high-throughput experimental and computational methods for agonist antibody discovery as well as rational molecular engineering methods for optimizing their agonist activity.

Secondary Structure and Conformational Stability of the Antigen Residues Making Contact with Antibodies

Antibodies are crucial biomolecules that bring high therapeutic efficacy in medicine and accurate molecular detection in diagnosis. Many studies have been devoted to analyzing the antigen-antibody interaction from the importance of understanding the antibody recognition mechanism. However, most of the previous studies examined the characteristic of the antibody for interaction. It is also informative to clarify the significant antigen residues contributing to the binding. To characterize the molecular interaction of antigens, we computationally analyzed 350 antigen-antibody complex structures by molecular mechanics (MM) calculations and molecular dynamics (MD) simulations. Based on the MM calculations, the antigen residues contributing to the binding were extracted from all the 350 complexes. The extracted residues are located at the antigen-antibody interface and are responsible for making contact with the antibody. The appearances of the charged polar residues, Asp, Glu, Arg, and Lys, were noticeably large. In contrast, the populations of the hydrophobic residues, Leu, Val, and Ala, were relatively low. The appearance frequencies of the other amino acid residues were almost close to the abundance of general proteins of eukaryotes. The binding score indicated that the hydrophilic interaction was dominant at the antigen-antibody contact instead of the hydrophobic one. The positively charged residues, Arg and Lys, remarkably contributed to the binding compared to the negatively charged ones, Asp and Glu. Considerable contributions were also observed for the noncharged polar residues, Asn and Gln. The analysis of the secondary structures of the extracted antigen residues suggested that there was no marked difference in recognition by antibodies among helix, sheet, turn, and coil. A long helix of the antigen sometimes made contact with antibody complementarity-determining regions, and a large sheet also frequently covered the antibody heavy and light chains. The turn structure was the most popularly observed at the contact with antibody among 350 complexes. Three typical complexes were picked up for each of the four secondary structures. MD simulations were performed to examine the stability of the interfacial structures of the antigens for these 12 complex models. The alterations of secondary structures were monitored through the simulations. The structural fluctuations of the contact residues were low compared with the other domains of antigen molecules. No drastic conversion was observed for every model during the 100 ns simulation. The motions of the interfacial antigen residues were small compared to the other residues on the protein surface. Therefore, diverse molecular conformations are possible for antibody recognition as long as the target areas are polar, nonflexible, and protruding on the protein surface.

Analysis of Binding Modes of Antigen-Antibody Complexes by Molecular Mechanics Calculation

Antibodies are one of the most important protein molecules in biopharmaceutics. Due to the recent advance in technology for producing monoclonal antibodies, many structural data are available on the antigen-antibody complexes. To characterize the molecular interaction in antigen-antibody recognition, we computationally analyzed 500 complex structures by molecular mechanics calculations. The presence of Ser and Tyr is markedly large in the complementarity-determining regions (CDRs). Although Ser is abundant in CDRs, its contribution to the binding score is not large. Instead, Tyr, Asp, Glu, and Arg significantly contribute to the molecular interaction from the viewpoint of the binding score. The decomposition of the binding score suggests that the hydrophilic interaction is predominant in all CDRs compared with the hydrophobic one. The contribution of the heavy chain is larger than that of the light chain. In particular, H2 and H3 largely contribute to the binding interaction. Tyr is a main contributing residue both in H2 and H3. The positively charged residue Arg also significantly contributes to the binding score in H3, while the contribution of Lys is small. The appearance of Ser is remarkable in H2, and Asp is abundant in H3. The non-charged polar residues, Thr, Asn, and Gln, appear much in H2, compared to appearing in H3. The negatively charged residues Asp and Glu significantly contribute to the binding score in H3. The contributions of Phe and Trp are not large in spite that the aromatic residues are capable of making the π-π or CH-π interaction. Gly is commonly abundant both in H2 and H3. The average distance of the shortest direct hydrogen bond between the antigen and antibody is longer than that of the hydrogen bonds observed in the complexes between compounds and their target proteins. Therefore, the antigen-antibody interface is not so tight as the compound-target protein interface. The calculation of shape complementarity is consistent with the result of the hydrogen bonds in that the fitness of the antigen-antibody contact is not so high as that of the compound-target protein contact. There exist many water molecules at the antigen-antibody interface. These findings suggest that Tyr, Asp, Glu, and Arg are rich in H3 and work as major contributors for the interaction with the antigen. Ser, Thr, Asn, and Gln are rich in H2 and support the interaction with enhancing molecular fitness. Gly is helpful in increasing flexibility and geometrical diversity. Because the antigen-antibody binding is fundamentally hydrophilic-driven, the non-polar residues are unfavorable for mediating the contact even for the aromatic residues such as Phe and Trp.

IsAb: a computational protocol for antibody design

The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.

Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities

Immunoglobulin repertoires contain a fraction of antibodies that recognize low molecular weight compounds, including some enzymes' cofactors, such as heme. Here, by using a set of 113 samples with variable region sequences matching clinical-stage antibodies, we demonstrated that a considerable number of these antibodies interact with heme. Antibodies that interact with heme possess specific sequence traits of their antigen-binding regions. Moreover they manifest particular physicochemical and functional qualities i.e. increased hydrophobicity, higher propensity of self-binding, higher intrinsic polyreactivity and reduced expression yields. Thus, interaction with heme is a strong predictor of different molecular and functional qualities of antibodies. Notably, these qualities are of high importance for therapeutic antibodies, as their presence was associated with failure of drug candidates to reach clinic. Our study reveled an important facet of information about relationship sequence-function in antibodies. It also offers a convenient tool for detection of liabilities of therapeutic antibodies.

Construction, characterization and crystal structure of a fluorescent single-chain Fv chimera

In vitro display technologies based on phage and yeast have a successful history of selecting single-chain variable fragment (scFv) antibodies against various targets. However, single-chain antibodies are often unstable and poorly expressed in Escherichia coli. Here, we explore the feasibility of converting scFv antibodies to an intrinsically fluorescent format by inserting the monomeric, stable fluorescent protein named thermal green, between the light- and heavy-chain variable regions. Our results show that the scTGP format maintains the affinity and specificity of the antibodies, improves expression levels, allows one-step fluorescent assay for detection of binding and is a suitable reagent for epitope binning. We also report the crystal structure of an scTGP construct that recognizes phosphorylated tyrosine on FcεR1 receptor of the allergy pathway.

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

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

Modifying ADAMTS13 to modulate binding of pathogenic autoantibodies of patients with acquired thrombotic thrombocytopenic purpura

Antibodies that develop in patients with immune thrombotic thrombocytopenic purpura (iTTP) commonly target the spacer epitope R568/F592/R660/Y661/Y665 (RFRYY). In this study we present a detailed contribution of each residue in this epitope for autoantibody binding. Different panels of mutations were introduced here to create a large collection of full-length ADAMTS13 variants comprising conservative (Y←→F), semi-conservative (Y/F→L), non-conservative (Y/F→N) or alanine (Y/F/R→A) substitutions. Previously reported Gain-of-Function (GoF, KYKFF) and truncated 'MDTCS' variants were also included. Sera of 18 patients were screened against all variants. Conservative mutations of the aromatic residues did not reduce the binding of autoantibodies. Moderate resistance was achieved by replacing R568 and R660 by lysines or alanines. Semi-conservative mutations of aromatic residues show a moderate effectiveness in autoantibody resistance. Non-conservative asparagine or alanine mutations of aromatic residues are the most effective. In the mixtures of autoantibodies from the majority (89%) of patients screened, autoantibodies targeting the spacer RFRYY epitope have preponderance compared to other epitopes. Reductions in ADAMTS13 proteolytic activity were observed for all full-length mutant variants, in varying degrees. The greatest activity reductions were observed in the most autoantibody-resistant variants (15-35% residual activity in FRETS-VWF73). Among these, a triple-alanine mutant RARAA showed activity in a VWF multimer assay. This study shows that non-conservative and alanine modifications of residues within the exosite-3 spacer RFRYY epitope in full-length ADAMTS13 resist the binding of autoantibodies from iTTP patients, while retaining residual proteolytic activity. Our study provides a framework for the design of autoantibody-resistant ADAMTS13 variants for further therapeutic development.

Characterization of the Specific Interactions between Nanoparticles and Proteins at Residue-Resolution by Alanine Scanning Mutagenesis

The interaction between nanoparticles and proteins is a central problem in the nano-bio-fields. However, it is still a great challenge to characterize the specific interaction between nanoparticles and proteins in structural details. Using the Goldbodies, the artificial antibodies created by grafting complementary-determining regions (CDRs) of natural antibodies onto gold nanoparticles, as the models, we manage to identify the key residues of the CDR peptides on gold nanoparticles for the specific interactions by alanine scanning mutagenesis. Each and every residue of the CDR peptides on two Goldbodies (which specifically bind with hen egg white lysozyme and epidermal growth factor receptor, respectively) is mutated to alanine one by one, generating a total of 18 single-mutants of the two Goldbodies. Experimental results reveal that the key residues of the CDR peptides for the specific interactions between the two Goldbodies and the corresponding antigens are exactly the same as those in the natural antibodies, thus proving that the correct conformations of the CDRs of natural antibodies have been successfully reconstructed on AuNPs. This is the first residue-resolution structural illustration for the specific interaction between a designed nanoparticle and a protein.

Biasing human epidermal growth factor receptor 4 (HER4) tyrosine kinase signaling with antibodies: Induction of cell death by antibody-dependent HER4 intracellular domain trafficking

Human epidermal growth factor receptor 4 (HER4) isoforms have oncogenic or tumor suppressor functions depending on their susceptibility to proteolytic cleavage and HER4 intracellular domain (4ICD) translocation. Here, we report that the neuregulin 1 (NRG1) tumor suppressor mechanism through the HER4 JMa/CYT1 isoform can be mimicked by the agonist anti‐HER4 Ab C6. Neuregulin 1 induced cleavage of poly(ADP‐ribose) polymerase (PARP) and sub‐G₁ DNA fragmentation, and also reduced the metabolic activity of HER3⁻/HER4⁺ cervical (C‐33A) and ovarian (COV318) cancer cells. This effect was confirmed in HER4 JMa/CYT1‐, but not JMa/CYT2‐transfected BT549 triple‐negative breast cancer cells. Neuregulin 1 favored 4ICD cleavage and retention in mitochondria in JMa/CYT1‐transfected BT549 cells, leading to reactive oxygen species (ROS) production through mitochondrial depolarization. Similarly, the anti‐HER4 Ab C6, which binds to a conformational epitope located on a.a. 575‐592 and 605‐620 of HER4 domain IV, induced 4ICD cleavage and retention in mitochondria, and mimicked NRG1‐mediated effects on PARP cleavage, ROS production, and mitochondrial membrane depolarization in cancer cells. In vivo, C6 reduced growth of COV434 and HCC1187 tumor cell xenografts in nude mice. Biasing 4ICD trafficking to mitochondria with anti‐HER4 Abs to mimic NRG1 suppressor functions could be an alternative anticancer strategy.

Les formats alternatifs aux anticorps

Les anticorps sont désormais devenus d’une utilisation courante dans un large champ thérapeutique qui n’est plus restreint à la cancérologie et à l’inflammation. Cette explosion du domaine conduit à des besoins nouveaux qui peuvent être mieux remplis par des molécules inspirées mais différentes des anticorps classiques. En particulier, la molécule anticorps a de multiples fonctions qui ne sont pas toujours nécessaires, comme sa capacité à recruter les cellules du système immunitaire, à se lier de façon bivalente à sa cible ou à présenter une demi-vie plasmatique élevée. En revanche, dans la grande majorité des applications, sa remarquable capacité à reconnaître spécifiquement sa cible moléculaire et surtout sa diversité de reconnaissance doivent être conservées. De plus, les anticorps sont des molécules de très haut poids moléculaire, coûteuses à produire et qui présentent des propriétés physicochimiques limitées ne permettant pas leur utilisation dans des milieux agressifs. Finalement, dans certaines applications thérapeutiques, la grande taille de la molécule (environ 150 kDa) peut également limiter sa diffusion dans les tissus et empêcher la reconnaissance de certaines structures moléculaires peu accessibles. Pour répondre à ces limitations, de nombreux formats alternatifs aux anticorps entiers ont été développés au cours de ces vingt dernières années. Les applications couvrent les domaines de la biotechnologie, du diagnostic in vitro et in vivo et de la thérapie. Deux grandes familles de molécules permettent de couvrir ce champ et seront présentées dans cette mini-revue. Une première famille s’appuie sur la diversité naturelle des anticorps mais en en réduisant la taille, comme les fragments d’anticorps classiques (Fab, scFv) ou ceux provenant des camélidés ou des requins (VHH, V-NAR). La deuxième famille a été développée en partant des propriétés finales désirées et notamment la stabilité en milieu extrême et la productivité en système simple et économique de production comme l’utilisation de bactéries et en y greffant des propriétés de liaison comparables aux anticorps par des méthodes d’évolution moléculaire dirigée in vitro. Cette mini-revue se concentrera sur les molécules les plus avancées, mais le domaine est en très forte et rapide expansion. Il faut noter que beaucoup de ces molécules, voire ces approches, sont couvertes par des brevets et sont souvent développées dans le cadre de jeunes sociétés innovantes dont certaines ont déjà été rachetées par de grands groupes de la pharmacie.

Antigen-Antibody Complexes

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

'Characterization of monoclonal antibodies generated to the 287-302 amino acid loop of the human epidermal growth factor receptor'

BACKGROUND

The dysregulation of epidermal growth factor receptor (EGFR) has been implicated in the oncogenesis of various malignancies including glioblastoma and some epithelial cancers. Oncogenesis occurs from the overexpression of EGFR, often linked to gene amplification or receptor mutagenesis. The 287-302 loop in the extracellular domain is exposed completely on EGFR variant III (EGFRvIII), partially exposed on some cancers but cryptic on normal cells. We report on the generation of antibodies to this loop.

METHODS

The 286-303 peptide was coupled chemically to keyhole limpet hemocyanin. After immunizations, sera were assayed for reactivity to the peptide. Mice with high titers were used for hybridoma production. Purified antibodies were isolated from hybridoma supernatants, while V regions were cloned and sequenced. Receptor binding was characterized using enzyme-linked immunosorbent assay and flow cytometry. A recombinant immunotoxin was generated from the 40H3 antibody and its cytotoxic activity characterized on relevant cancer cell lines.

RESULTS

Seven monoclonal antibodies were generated to the 287-302 loop and characterized further. Each one reacted with EGFRvIII but not wild-type EGFR. Based on reactivity with the immunizing peptide, antibodies were mapped to one of three subgroups. One antibody, 40H3, also exhibited binding to MDA-MB-468 and A431 cells but not to non-cancerous WI-38 cells. Because of its unusual binding characteristics, a recombinant immunotoxin was generated from 40H3, which proved to be cytotoxic to MDA-MB-468, A431 and F98npEGFRvIII expressing cells.

CONCLUSIONS

Immunization with a peptide corresponding to a cryptic epitope from EGFR can produce tumor cell-binding antibodies. The 40H3 antibody was engineered as a cytotoxic recombinant immunotoxin and could be further developed as a therapeutic agent.

Novel Immune Microlens Imaging for Detection of Antigen and Antibody

Detection and analysis of antigen-antibody reaction is one of the most critical detection techniques in the fields of medicine, biology, environmental science, and food safety. Traditional and classical methods for detecting antigen and antibody encounter many problems, such as time-consuming, high cost, and low accuracy. A novel immune microsphere imaging technique by the microlens is used to test the changes of refractive index before and after antigen-antibody reaction. It can quickly perform qualitative and quantitative determination for antigen-antibody reaction without any labeling, premodification, postwashing, and expensive enzymes. Here, we feature and discuss its principle and advantages, structure of a microlens immunoassay instrument, and potential in measuring clinical samples. It is promising to be developed for application to diagnosis of clinical diseases.

Cognizance of Molecular Methods for the Generation of Mutagenic Phage Display Antibody Libraries for Affinity Maturation

Antibodies leverage on their unique architecture to bind with an array of antigens. The strength of interaction has a direct relation to the affinity of the antibodies towards the antigen. In vivo affinity maturation is performed through multiple rounds of somatic hypermutation and selection in the germinal centre. This unique process involves intricate sequence rearrangements at the gene level via molecular mechanisms. The emergence of in vitro display technologies, mainly phage display and recombinant DNA technology, has helped revolutionize the way antibody improvements are being carried out in the laboratory. The adaptation of molecular approaches in vitro to replicate the in vivo processes has allowed for improvements in the way recombinant antibodies are designed and tuned. Combinatorial libraries, consisting of a myriad of possible antibodies, are capable of replicating the diversity of the natural human antibody repertoire. The isolation of target-specific antibodies with specific affinity characteristics can also be accomplished through modification of stringent protocols. Despite the ability to screen and select for high-affinity binders, some 'fine tuning' may be required to enhance antibody binding in terms of its affinity. This review will provide a brief account of phage display technology used for antibody generation followed by a summary of different combinatorial library characteristics. The review will focus on available strategies, which include molecular approaches, next generation sequencing, and in silico approaches used for antibody affinity maturation in both therapeutic and diagnostic applications.

Analysis of interleukin 23 and 7G10 interactions for computational design of lead antibodies against immune-mediated inflammatory diseases

Wealth of structural data on theurapeutic targets in complex with monoclonal antibodies (mAbs) and advances in molecular modeling algorithms present exciting opportunities in the field of novel biologic design. Interleukin 23 (IL23), a well-known drug target for autoimmune diseases, in complex with mAb 7G10 offers prospect to design potent lead antibodies by traversing the complete epitope-paratope interface. Herein, key interactions aiding antibody-based neutralization in IL23-7G10 complex are resolute through PyMOL, LigPlot⁺, Antibody i-Patch, DiscoTope and FoldX. Six amino acids Ser31, Val33, Asn55, Lys59 in heavy chain and His34, Ser93 in light chain are subjected to in silico mutagenesis with residues Met, Trp, Ile, Leu and Arg. A set of 431 mutant macromolecules are outlined. Binding affinities of these molecules with IL23 are estimated through protein-protein docking by employing ZDOCK, ClusPro and RosettaDock. Subsequently, the macromolecules revealed comparable result with 7G10 are cross validated through binding free-energy calculations by applying Molecular Mechanics/Poisson Boltzman Surface Area method in CHARMM. Thirty nine designed theoretical antibodies showed improved outcome in all evaluations; from these, top 10 molecules showed at least nine unit better binding affinity compared to the known mAb. These molecules have the potential to act as lead antibodies. Subsequent molecular dynamics simulations too favored prospective of best ranked molecule to have therapeutic implications in autoimmune and inflammatory diseases. Abbreviations: IL23: interleukin 23; IL17: interleukin17; Ab: antibody; Ag: antigen; mAbs: monoclonal antibodies; STAT3: signal transducer and activator of transcription 3; STAT4: signal transducer and activator of transcription 4; PDB: protein databank; MM/PBSA: molecular mechanics Poisson-Boltzmann surface area; Ag-Ab: antigen- antibody complex; SPC/E: extended simple point charge; SD: steepest descents; PME: particle mesh ewald; dG: binding free energies; Fv: variable fragment.

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.