Insights into the Structural Basis of Antibody Affinity Maturation from Next-Generation Sequencing

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.

Biparatopic binding of ISB 1442 to CD38 in trans enables increased cell antibody density and increased avidity

ISB 1442 is a bispecific biparatopic antibody in clinical development to treat hematological malignancies. It consists of two adjacent anti-CD38 arms targeting non-overlapping epitopes that preferentially drive binding to tumor cells and a low-affinity anti-CD47 arm to enable avidity-induced blocking of proximal CD47 receptors. We previously reported the pharmacology of ISB 1442, designed to reestablish synthetic immunity in CD38+ hematological malignancies. Here, we describe the discovery, optimization and characterization of the ISB 1442 antigen binding fragment (Fab) arms, their assembly to 2 + 1 format, and present the high-resolution co-crystal structures of the two anti-CD38 Fabs, in complex with CD38. This, with biophysical and functional assays, elucidated the underlying mechanism of action of ISB 1442. In solution phase, ISB 1442 forms a 2:2 complex with CD38 as determined by size-exclusion chromatography with multi-angle light scattering and electron microscopy. The predicted antibody-antigen stoichiometries at different CD38 surface densities were experimentally validated by surface plasmon resonance and cell binding assays. The specific design and structural features of ISB 1442 enable: 1) enhanced trans binding to adjacent CD38 molecules to increase Fc density at the cancer cell surface; 2) prevention of avid cis binding to monomeric CD38 to minimize blockade by soluble shed CD38; and 3) greater binding avidity, with a slower off-rate at high CD38 density, for increased specificity. The superior CD38 targeting of ISB 1442, at both high and low receptor densities, by its biparatopic design, will enhance proximal CD47 blockade and thus counteract a major tumor escape mechanism in multiple myeloma patients.

Using Short Molecular Dynamics Simulations to Determine the Important Features of Interactions in Antibody-Protein Complexes

The last few years have seen the rapid proliferation of machine learning methods to design binding proteins. Although these methods have shown large increases in experimental success rates compared to prior approaches, the majority of their predictions fail when they are experimentally tested. It is evident that computational methods still struggle to distinguish the features of real protein binding interfaces from false predictions. Short molecular dynamics simulations of 20 antibody-protein complexes were conducted to identify features of interactions that should occur in binding interfaces. Intermolecular salt bridges, hydrogen bonds, and hydrophobic interactions were evaluated for their persistences, energies, and stabilities during the simulations. It was found that only the hydrogen bonds where both residues are stabilized in the bound complex are expected to persist and meaningfully contribute to binding between the proteins. In contrast, stabilization was not a requirement for salt bridges and hydrophobic interactions to persist. Still, interactions where both residues are stabilized in the bound complex persist significantly longer and have significantly stronger energies than other interactions. Two hundred and twenty real antibody-protein complexes and 8194 decoy complexes were used to train and test a random forest classifier using the features of expected persistent interactions identified in this study and the macromolecular features of interaction energy (IE), buried surface area (BSA), IE/BSA, and shape complementarity. It was compared to a classifier trained only on the expected persistent interaction features and another trained only on the macromolecular features. Inclusion of the expected persistent interaction features reduced the false positive rate of the classifier by two- to five-fold across a range of true positive classification rates.

What does AlphaFold3 learn about antigen and nanobody docking, and what remains unsolved?

Antibody therapeutic development is a major focus in healthcare. To accelerate drug development, significant efforts have been directed towards the in silico design and screening of antibodies for which high modeling accuracy is necessary. To probe AlphaFold3's (AF3) capabilities and limitations, we tested AF3's ability to capture the fine details and interplay between antibody structure prediction and antigen docking accuracy. With one seed, AF3 achieves an 11.0% and 11.4% high-accuracy docking success rate for antibodies and nanobodies, respectively, and a median unbound CDR H3 RMSD accuracy of 2.73 Å and 2.30 Å. CDR H3 accuracy boosts complex prediction accuracy, with antigen context improving CDR H3 accuracy, particularly for loops longer than 15 residues. Combining I-pLDDT with Δ G B improves discriminative power for correctly docked complexes. However, AF3's 60% failure rate for antibody and nanobody docking (with single seed sampling) demonstrates necessary refinement to improve antibody design endeavors.

ANTIPASTI: Interpretable prediction of antibody binding affinity exploiting normal modes and deep learning

The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network model that achieves state-of-the-art performance in the prediction of antibody binding affinity using as input a representation of antibody-antigen structures in terms of normal mode correlation maps derived from elastic network models. This representation captures not only structural features but energetic patterns of local and global residue fluctuations. The learnt representations are interpretable: they reveal similarities of binding patterns among antibodies targeting the same antigen type, and can be used to quantify the importance of antibody regions contributing to binding affinity. Our results show the importance of the antigen imprint in the normal mode landscape, and the dominance of cooperative effects and long-range correlations between antibody regions to determine binding affinity.

Determining key residues of engineered scFv antibody variants with improved MMP-9 binding using deep sequencing and machine learning

Given the crucial role of specific matrix metalloproteinases (MMPs) in the extracellular matrix, an imbalance in the regulation of activation of matrix metalloproteinase-9 (MMP-9) zymogen and inhibition of the enzyme can result in various diseases, such as cancer, neurodegenerative, and gynecological diseases. Thus, developing novel therapeutics that target MMP-9 with single-chain antibody fragments (scFvs) is a promising approach. We used fluorescent-activated cell sorting (FACS) to screen a synthetic scFv antibody library displayed on yeast for enhanced binding to MMP-9. The screened scFv mutants demonstrated improved binding to MMP-9 compared to the natural inhibitor of MMPs, tissue inhibitor of metalloproteinases (TIMPs). To identify the molecular determinants of these engineered scFv variants that affect binding to MMP-9, we used next-generation DNA sequencing and computational protein structure analysis. Additionally, a deep-learning language model was trained on the screened scFv library of variants to predict the binding affinities of scFv variants based on their CDR-H3 sequences.

Structure-guided mutations in CDRs for enhancing the affinity of neutralizing SARS-CoV-2 nanobody

The optimization of antibodies to attain the desired levels of affinity and specificity holds great promise for the development of next generation therapeutics. This study delves into the refinement and engineering of complementarity-determining regions (CDRs) through in silico affinity maturation followed by binding validation using isothermal titration calorimetry (ITC) and pseudovirus-based neutralization assays. Specifically, it focuses on engineering CDRs targeting the epitopes of receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. A structure-guided virtual library of 112 single mutations in CDRs was generated and screened against RBD to select the potential affinity-enhancing mutations. Protein-protein docking analysis identified 32 single mutants of which nine mutants were selected for molecular dynamics (MD) simulations. Subsequently, biophysical ITC studies provided insights into binding affinity, and consistent with in silico findings, six mutations that demonstrated better binding affinity than native nanobody were further tested in vitro for neutralization activity against SARS-CoV-2 pseudovirus. Leu106Thr mutant was found to be most effective in virus-neutralization with IC50 values of ∼0.03 μM, as compared to the native nanobody (IC50 ∼0.77 μM). Thus, in this study, the developed computational pipeline guided by structure-aided interface profiles and thermodynamic analysis holds promise for the streamlined development of antibody-based therapeutic interventions against emerging variants of SARS-CoV-2 and other infectious pathogens.

A library-on-library screen reveals the breadth expansion landscape of a broadly neutralizing betacoronavirus antibody

Broadly neutralizing antibodies (bnAbs) typically evolve cross-reactivity breadth through acquiring somatic hypermutations. While evolution of breadth requires improvement of binding to multiple antigenic variants, most experimental evolution platforms select against only one antigenic variant at a time. In this study, a yeast display library-on-library approach was applied to delineate the affinity maturation of a betacoronavirus bnAb, S2P6, against 27 spike stem helix peptides in a single experiment. Our results revealed that the binding affinity landscape of S2P6 varies among different stem helix peptides. However, somatic hypermutations that confer general improvement in binding affinity across different stem helix peptides could also be identified. We further showed that a key somatic hypermutation for breadth expansion involves long-range interaction. Overall, our work not only provides a proof-of-concept for using a library-on-library approach to analyze the evolution of antibody breadth, but also has important implications for the development of broadly protective vaccines.

Structural and genetic basis for the binding of a mouse monoclonal antibody to Flavobacterium psychrophilum lipopolysaccharide

A mouse monoclonal antibody (mAb FL100A) previously prepared against Flavobacterium psychrophilum (Fp) CSF259-93 has now been examined for binding to lipopolysaccharides (LPS) of this strain and Fp 950106-1/1. The corresponding O-polysaccharides (O-PS) of these strains are formed by identical trisaccharide repeats composed of l-Rhamnose (l-Rha), 2-acetamido-2-deoxy-l-fucose (l-FucNAc) and 2-acetamido-4-R1-2,4-dideoxy-d-quinovose (d-Qui2NAc4NR1) where R1 represents a dihydroxyhexanamido moiety. The O-PS loci of these strains are also identical except for the gene (wzy1 or wzy2) that encodes the polysaccharide polymerase. Accordingly, adjacent O-PS repeats are joined through d-Qui2NAc4NR1 and l-Rha by wzy2-dependent α(1-2) linkages in Fp CSF259-93 versus wzy1-dependent β(1-3) linkages in Fp 950106-1/1. mAb FL100A reacted strongly with Fp CSF259-93 O-PS and LPS but weakly or not at all with Fp 950106-1/1 LPS and O-PS. Importantly, it also labelled cell surface blebs on the former but not the latter strain. Additionally, mAb binding was approximately 5-times stronger to homologous Fp CSF259-93 LPS than to LPS from a strain with a different R-group gene. A conformational epitope for mAb FL100A binding was suggested from molecular dynamic simulations of each O-PS. Thus, Fp CSF259-93 O-PS formed a stable well-defined compact helix in which the R1 groups were displayed in a regular pattern on the helix exterior while unreactive Fp 950106-1/1 O-PS adopted a flexible extended linear conformation. Taken together, the findings establish the specificity of mAb FL100A for Wzy2-linked F. psychrophilum O-PS and LPS.

Overview of AlphaFold2 and breakthroughs in overcoming its limitations

Predicting three-dimensional (3D) protein structures has been challenging for decades. The emergence of AlphaFold2 (AF2), a deep learning-based machine learning method developed by DeepMind, became a game changer in the protein folding community. AF2 can predict a protein's three-dimensional structure with high confidence based on its amino acid sequence. Accurate prediction of protein structures can dramatically accelerate our understanding of biological mechanisms and provide a solid foundation for reliable drug design. Although AF2 breaks through the barriers in predicting protein structures, many rooms remain to be further studied. This review provides a brief historical overview of the development of protein structure prediction, covering template-based, template-free, and machine learning-based methods. In addition to reviewing the potential benefits (Pros) and considerations (Cons) of using AF2, this review summarizes the diverse applications, including protein structure predictions, dynamic changes, point mutation, integration of language model and experimental data, protein complex, and protein-peptide interaction. It underscores recent advancements in efficiency, reliability, and broad application of AF2. This comprehensive review offers valuable insights into the applications of AF2 and AF2-inspired AI methods in structural biology and its potential for clinically significant drug target discovery.

B cell somatic hypermutation following COVID-19 vaccination with Ad26.COV2.S

The viral vector-based COVID-19 vaccine Ad26.COV2.S has been recommended by the WHO since 2021 and has been administered to over 200 million people. Prior studies have shown that Ad26.COV2.S induces durable neutralizing antibodies (NAbs) that increase in coverage of variants over time, even in the absence of boosting or infection. Here, we studied humoral responses following Ad26.COV2.S vaccination in individuals enrolled in the initial Phase 1/2a trial of Ad26.COV2.S in 2020. Through 8 months post vaccination, serum NAb responses increased to variants, including B.1.351 (Beta) and B.1.617.2 (Delta), without additional boosting or infection. The level of somatic hypermutation, measured by nucleotide changes in the VDJ region of the heavy and light antibody chains, increased in Spike-specific B cells. Highly mutated mAbs from these sequences neutralized more SARS-CoV-2 variants than less mutated comparators. These findings suggest that the increase in NAb breadth over time following Ad26.COV2.S vaccination is mediated by affinity maturation.

Comparison of Non B-Ig and B-Ig

Immunoglobulin (Ig) has been widely acknowledged to be produced solely by B-lineage cells. However, growing evidence has demonstrated the expression of Ig in an array of cancer cells, as well as normal cells including epithelial cells, epidermal cells, mesangial cells, monocytes, and neutrophils. Ig has even been found to be expressed in non-B cells at immune-privileged sites such as neurons and spermatogenic cells. Despite these non-B cell-derived Igs (non-B-Igs) sharing the same symmetric structures with conventional Igs (B-Igs), further studies have revealed unique characteristics of non-B-Ig, such as restricted variable region and aberrant glycosylation. Moreover, non-B-Ig exhibits properties of promoting malignant behaviours of cancer cells, therefore it could be utilised in the clinic as a potential therapeutic biomarker or target. The elucidation of the generation and regulation of non-B-Ig will certainly broaden our understanding of immunology.

Peptides From the Variable Domain of Immunoglobulin G as Biomarkers in Chronic Inflammatory Demyelinating Polyradiculoneuropathy

BACKGROUND AND OBJECTIVES

Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a clinically heterogeneous immune-mediated disease. Diagnostic biomarkers for CIDP are currently lacking. Peptides derived from the variable domain of circulating immunoglobulin G (IgG) have earlier been shown to be shared among patients with the same immunologic disease. Because humoral immune factors are hypothesized to be involved in the pathogenesis of CIDP, we evaluated IgG variable domain-derived peptides as diagnostic biomarkers in CIDP (primary objective) and whether IgG-derived peptides could cluster objective clinical entities in CIDP (secondary objective).

METHODS

IgG-derived peptides were determined in prospectively collected sera of patients with CIDP and neurologic controls by means of mass spectrometry. Peptides of interest were selected through statistical analysis in a discovery cohort followed by sequence determination and confirmation. Diagnostic performance was evaluated for individual selected peptides and for a multipeptide model incorporating selected peptides, followed by performance reassessment in a validation cohort. Clustering of patients with CIDP based on IgG-derived peptides was evaluated through unsupervised sparse principal component analysis followed by k-means clustering.

RESULTS

Sixteen peptides originating from the IgG variable domain were selected as candidate biomarkers in a discovery cohort of 44 patients with CIDP and 29 neurologic controls. For all 16 peptides, univariate logistic regressions and ROC curve analysis demonstrated increasing peptide abundances to associate with increased odds for CIDP (area under the curves [AUCs] ranging from 64.6% to 79.6%). When including age and sex in the logistic regression models, this remained the case for 13/16 peptides. A model composed of 5/16 selected peptides showed strong discriminating performance between patients with CIDP and controls (AUC 91.5%; 95% CI 84.6%-98.4%; p < 0.001). In the validation cohort containing 45 patients and 43 controls, 2/16 peptides demonstrated increasing abundances to associate with increased odds for CIDP, while the five-peptide model demonstrated an AUC of 61.2% (95% CI 49.3%-73.2%; p = 0.064). Peptide-based patient clusters did not associate with clinical features.

DISCUSSION

IgG variable domain-derived peptides showed a valid source for diagnostic biomarkers in CIDP, albeit with challenges toward replication. Our proof-of-concept findings warrant further study of IgG-derived peptides as biomarkers in more homogeneous cohorts of patients with CIDP and controls.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that the pattern of serum IgG-derived peptide clusters may help differentiate between patients with CIDP and those with other peripheral neuropathies.

Enhanced antibody-antigen structure prediction from molecular docking using AlphaFold2

Predicting the structure of antibody-antigen complexes has tremendous value in biomedical research but unfortunately suffers from a poor performance in real-life applications. AlphaFold2 (AF2) has provided renewed hope for improvements in the field of protein-protein docking but has shown limited success against antibody-antigen complexes due to the lack of co-evolutionary constraints. In this study, we used physics-based protein docking methods for building decoy sets consisting of low-energy docking solutions that were either geometrically close to the native structure (positives) or not (negatives). The docking models were then fed into AF2 to assess their confidence with a novel composite score based on normalized pLDDT and pTMscore metrics after AF2 structural refinement. We show benefits of the AF2 composite score for rescoring docking poses both in terms of (1) classification of positives/negatives and of (2) success rates with particular emphasis on early enrichment. Docking models of at least medium quality present in the decoy set, but not necessarily highly ranked by docking methods, benefitted most from AF2 rescoring by experiencing large advances towards the top of the reranked list of models. These improvements, obtained without any calibration or novel methodologies, led to a notable level of performance in antibody-antigen unbound docking that was never achieved previously.

Experimentally Observed Conformational Changes in Antibodies Due to Binding and Paratope-epitope Asymmetries

Understanding binding related changes in antibody conformations is important for epitope prediction and antibody refinement. The increase of available data in the PDB allowed a more detailed investigation of the conformational landscape for free and bound antibodies. A dataset containing a total of 835 unique PDB entries of antibodies that were crystallized in complex with their antigen and in a free state was constructed. It was examined for binding related conformation changes. We present further evidence supporting the theory of a pre-existing-equilibrium in experimental data. Multiple sequence alignments did not show binding induced tendencies in the solvent accessibility of residues in any specific position. Evaluating the changes in solvent accessibility per residue revealed a certain binding induced increase for several amino acids. Antibody-antigen interaction statistics were established and quantify a significant directional asymmetry between many interacting antibody and antigen residue pairs, especially a richness in tyrosine in the antibody epitope compared to its paratope. This asymmetry could potentially facilitate an increase in the success rate of computationally guided antibody refinement.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

Producing amyloid fibrils in vitro: A tool for studying AL amyloidosis

Amyloid light-chain (AL) amyloidosis is the second most common form of systemic amyloidosis which is characterized by a high level of mortality and no effective treatment to remove fibril deposition. This disorder is caused by malfunctioning of B-cells resulting in production of abnormal protein fibrils composed of immunoglobulin light chain fragments that tend to deposit on various organs and tissues. AL amyloidosis is set apart from other forms of amyloidosis in that no specific sequences have been identified in the immunoglobulin light chains that are amyloid fibril formation causative and patient specific. This unusual feature hinders the therapeutic progress and requires either direct access to patient samples (which is not always possible) or a source of in vitro produced fibrils. While isolated reports of successful AL amyloid fibril formation from various patient-specific protein sequences can be found in literature, no systematic research on this topic was performed since 1999. In the present study we have developed a generalized approach to in vitro fibril production from various types of previously reported [[1], [2], [3]] amyloidogenic immunoglobulin light chains and their fragments. We describe the procedure from selection and generation of starting material, through finding of optimal assay conditions, to applying a panel of methods to confirm successful fibril formation. Procedure details are discussed in the light of the most recent findings and theories on amyloid fibril formation. The reported protocol produces high quality AL amyloid fibrils that can subsequently be used in the development of the much-needed amyloid-targeting diagnostic and therapeutic approaches.

Obesity Is Associated with an Impaired Baseline Repertoire of Anti-Influenza Virus Antibodies

Obesity is a risk factor for severe disease and mortality for both influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While previous studies show that individuals with obesity generate antibody responses following influenza vaccination, infection rates within the obese group were twice as high as those in the healthy-weight group. The repertoire of antibodies raised against influenza viruses following previous vaccinations and/or natural exposures is referred to here as baseline immune history (BIH). To investigate the hypothesis that obesity impacts immune memory to infections and vaccines, we profiled the BIH of obese and healthy-weight adults vaccinated with the 2010-2011 seasonal influenza vaccine in response to conformational and linear antigens. Despite the extensive heterogeneity of the BIH profiles in both groups, there were striking differences between obese and healthy subjects, especially with regard to A/H1N1 strains and the 2009 pandemic virus (Cal09). Individuals with obesity had lower IgG and IgA magnitude and breadth for a panel of A/H1N1 whole viruses and hemagglutinin proteins from 1933 to 2009 but increased IgG magnitude and breadth for linear peptides from the Cal09 H1 and N1 proteins. Age was also associated with A/H1N1 BIH, with young individuals with obesity being more likely to have reduced A/H1N1 BIH. We found that individuals with low IgG BIH had significantly lower neutralizing antibody titers than individuals with high IgG BIH. Taken together, our findings suggest that increased susceptibility of obese participants to influenza infection may be mediated in part by obesity-associated differences in the memory B-cell repertoire, which cannot be ameliorated by current seasonal vaccination regimens. Overall, these data have vital implications for the next generation of influenza virus and SARS-CoV-2 vaccines. IMPORTANCE Obesity is associated with increased morbidity and mortality from influenza and SARS-CoV-2 infection. While vaccination is the most effective strategy for preventing influenza virus infection, our previous studies showed that influenza vaccines fail to provide optimal protection in obese individuals despite reaching canonical correlates of protection. Here, we show that obesity may impair immune history in humans and cannot be overcome by seasonal vaccination, especially in younger individuals with decreased lifetime exposure to infections and seasonal vaccines. Low baseline immune history is associated with decreased protective antibody responses. Obesity potentially handicaps overall responses to vaccination, biasing it toward responses to linear epitopes, which may reduce protective capacity. Taken together, our data suggest that young obese individuals are at an increased risk of reduced protection by vaccination, likely due to altered immune history biased toward nonprotective antibody responses. Given the worldwide obesity epidemic coupled with seasonal respiratory virus infections and the inevitable next pandemic, it is imperative that we understand and improve vaccine efficacy in this high-risk population. The design, development, and usage of vaccines for and in obese individuals may need critical evaluation, and immune history should be considered an alternate correlate of protection in future vaccine clinical trials.

Structural basis for breadth development in the HIV-1 V3-glycan targeting DH270 antibody clonal lineage

Antibody affinity maturation enables adaptive immune responses to a wide range of pathogens. In some individuals broadly neutralizing antibodies develop to recognize rapidly mutating pathogens with extensive sequence diversity. Vaccine design for pathogens such as HIV-1 and influenza has therefore focused on recapitulating the natural affinity maturation process. Here, we determine structures of antibodies in complex with HIV-1 Envelope for all observed members and ancestral states of the broadly neutralizing HIV-1 V3-glycan targeting DH270 antibody clonal B cell lineage. These structures track the development of neutralization breadth from the unmutated common ancestor and define affinity maturation at high spatial resolution. By elucidating contacts mediated by key mutations at different stages of antibody development we identified sites on the epitope-paratope interface that are the focus of affinity optimization. Thus, our results identify bottlenecks on the path to natural affinity maturation and reveal solutions for these that will inform immunogen design aimed at eliciting a broadly neutralizing immune response by vaccination.

Antibodies gone bad - the molecular mechanism of light chain amyloidosis

Light chain amyloidosis (AL) is a systemic disease in which abnormally proliferating plasma cells secrete large amounts of mutated antibody light chains (LCs) that eventually form fibrils. The fibrils are deposited in various organs, most often in the heart and kidney, and impair their function. The prognosis for patients diagnosed with AL is generally poor. The disease is set apart from other amyloidoses by the huge number of patient-specific mutations in the disease-causing and fibril-forming protein. The molecular mechanisms that drive the aggregation of mutated LCs into fibrils have been enigmatic, which hindered the development of efficient diagnostics and therapies. In this review, we summarize our current knowledge on AL amyloidosis and discuss open issues.

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%.

Research progress on unique paratope structure, antigen binding modes, and systematic mutagenesis strategies of single-domain antibodies

Single-domain antibodies (sdAbs) showed the incredible advantages of small molecular weight, excellent affinity, specificity, and stability compared with traditional IgG antibodies, so their potential in binding hidden antigen epitopes and hazard detection in food, agricultural and veterinary fields were gradually explored. Moreover, its low immunogenicity, easy-to-carry target drugs, and penetration of the blood-brain barrier have made sdAbs remarkable achievements in medical treatment, toxin neutralization, and medical imaging. With the continuous development and maturity of modern molecular biology, protein analysis software and database with different algorithms, and next-generation sequencing technology, the unique paratope structure and different antigen binding modes of sdAbs compared with traditional IgG antibodies have aroused the broad interests of researchers with the increased related studies. However, the corresponding related summaries are lacking and needed. Different antigens, especially hapten antigens, show distinct binding modes with sdAbs. So, in this paper, the unique paratope structure of sdAbs, different antigen binding cases, and the current maturation strategy of sdAbs were classified and summarized. We hope this review lays a theoretical foundation to elucidate the antigen-binding mechanism of sdAbs and broaden the further application of sdAbs.

General Theory of Specific Binding: Insights from a Genetic-Mechano-Chemical Protein Model

Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. However, despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present such a model that combines chemistry, mechanics, and genetics and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving molecular discrimination-by varying degrees of flexibility and shape/chemistry complementarity-but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces, and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine-tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is enabled by increasing the protein size, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. The model makes testable, specific predictions about the role of flexibility and shape mismatch in discrimination, and how evolution can independently tune affinity and specificity. Thus, the proposed theory of specific binding addresses the natural question of "why are proteins so big?". A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.

COVID-19 diverse outcomes: Aggravated reinfection, type I interferons and antibodies

SARS-CoV-2 infection intrigued medicine with diverse outcomes ranging from asymptomatic to severe acute respiratory syndrome (SARS) and death. After more than two years of pandemic, reports of reinfection concern researchers and physicists. Here, we will discuss potential mechanisms that can explain reinfections, including the aggravated ones. The major topics of this hypothesis paper are the disbalance between interferon and antibodies responses, HLA heterogeneity among the affected population, and increased proportion of cytotoxic CD4+ T cells polarization in relation to T follicular cells (Tfh) subtypes. These features affect antibody levels and hamper the humoral immunity necessary to prevent or minimize the viral burden in the case of reinfections.

Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes

Understanding the structural principles that determine the binding affinity of nanobodies to the spike protein of severe acute respiratory syndrome coronavirus 2 has been difficult. We analyzed electron microscopy maps of nanobody-spike complexes and quantified the conformational entropy of binding. This informed the design of an engineered nanobody with improved binding to the spike protein. This result offers a guiding principle for the rational maturation of nanobodies directed against the spike. High-binding potency nanobodies have been shown to be effective in animal models; thus, this technology could have application in future pandemics.

Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure–activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein–nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.

Somatic Hypermutation and Framework Mutations of Variable Region Contribute to Anti-Zika Virus-Specific Monoclonal Antibody Binding and Function

Zika virus (ZIKV) is a global public health concern due to its ability to cause congenital Zika syndrome and lack of approved vaccine, therapeutic, or other control measures. We discovered eight novel rabbit monoclonal antibodies (MAbs) that bind to distinct ZIKV envelope protein epitopes. The majority of the MAbs were ZIKV specific and targeted the lateral ridge of the envelope (E) protein domain III, while the MAb with the highest neutralizing activity recognized a putative quaternary epitope spanning E protein domains I and III. One of the non-neutralizing MAbs specifically recognized ZIKV precursor membrane protein (prM). Somatic hypermutation of immunoglobulin variable regions increases antibody affinity maturation and triggers antibody class switching. Negative correlations were observed between the somatic hypermutation rate of the immunoglobulin heavy-chain variable region and antibody binding parameters such as equilibrium dissociation constant, dissociation constant, and half-maximal effective concentration value of MAb binding to ZIKV virus-like particles. Complementarity-determining regions recognize the antigen epitopes and are scaffolded by canonical framework regions. Reversion of framework region amino acids to the rabbit germ line sequence decreased anti-ZIKV MAb binding activity of some MAbs. Thus, antibody affinity maturation, including somatic hypermutation and framework region mutations, contributed to the binding and function of these anti-ZIKV MAbs. IMPORTANCE ZIKV is a global health concern against which no vaccine or therapeutics are available. We characterized eight novel rabbit monoclonal antibodies recognizing ZIKV envelope and prM proteins and studied the relationship between somatic hypermutation of complementarity-determining regions, framework regions, mutations, antibody specificity, binding, and neutralizing activity. The results contribute to understanding structural features and somatic mutation pathways by which potent Zika virus-neutralizing antibodies can evolve, including the role of antibody framework regions.

Evolutionary Landscapes of Host-Virus Arms Races

Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.

Natural Barcodes for Longitudinal Single Cell Tracking of Leukemic and Immune Cell Dynamics

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.

Leveraging Sequential and Spatial Neighbors Information by Using CNNs Linked With GCNs for Paratope Prediction

Antibodies consisting of variable and constant regions, are a special type of proteins playing a vital role in immune system of the vertebrate. They have the remarkable ability to bind a large range of diverse antigens with extraordinary affinity and specificity. This malleability of binding makes antibodies an important class of biological drugs and biomarkers. In this article, we propose a method to identify which amino acid residues of an antibody directly interact with its associated antigen based on the features from sequence and structure. Our algorithm uses convolution neural networks (CNNs) linked with graph convolution networks (GCNs) to make use of information from both sequential and spatial neighbors to understand more about the local environment of target amino acid residue. Furthermore, we process the antigen partner of an antibody by employing an attention layer. Our method improves on the state-of-the-art methodology.

Heavy chain-only antibody genes in fish evolved to generate unique CDR3 repertoire

In addition to conventional immunoglobulin, camelids and cartilaginous fish express a special class of antibody that consists only of heavy (H) chain (HCAbs). In the holocephalan elephantfish, there are two HCAb classes, one of which has evolved surprising features. The H-chain genes in cartilaginous fish are organized as 20-200 minigenes, or clusters, each consisting of VH, 1-3 DH, JH gene segments with one set of constant region exons. We report that HHC2 (holocephalan H-chain antibody 2) evolved from IgM H-chain clusters, but its DH gene segments have diverged considerably. The three DH in HHC2 clusters are A-rich, so that one to three potential reading frames for each DH encode lysine and arginine. All three are incorporated into the rearranged VDJ, ensuring that the ligand-binding site carries multiple basic residues, as cDNA sequences demonstrate. The electropositive character in HHC2 CDR3 is accompanied by a paucity of aromatic amino acids, the latter feature at variance to the established, interactive role of tyrosine not only in ligand-binding but generally at interfaces of protein complexes. The selection for these divergent HHC2 features challenges currently accepted ideas on what determines antibody reactivity and molecular recognition.

Immunosuppression in Glomerular Diseases: Implications for SARS-CoV-2 Vaccines and COVID-19

BACKGROUND

Glomerular diseases (GD) are chronic conditions that often involve immune dysfunction and require immunosuppressive therapy (IST) to control underlying pathogenesis. Unfortunately, such diseases appear to heighten risks of severe outcomes in COVID-19 and predispose to other infections that may be life-threatening. Thus, averting preventable infections is imperative in GD patients.

SUMMARY

The advent of vaccines demonstrated to be safe and efficacious against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has favorably impacted the COVID-19 pandemic epidemiology. However, patients on ISTs were excluded from initial vaccine clinical trials. Thus, only limited and incomplete data are available currently regarding the potential impact of immunosuppression on immune response to or efficacy of the SARS-CoV-2 vaccines. However, new insights are emerging from SARS-CoV-2 vaccine studies, and impacts of ISTs on conventional vaccines are useful to consider. Mechanisms of immunosuppressive agents commonly used in the treatment of GD are reviewed with respect to implications for immune responses induced by SARS-CoV-2 vaccines. ISTs discussed include corticosteroids; alkylating agents; antimetabolites; calcineurin or mammalian target of rapamycin inhibitors; CD38+, CD20+, or CD19+ cell depletion; and complement protein C5 inhibition.

KEY MESSAGES

Many immunosuppressive therapies may potentially attenuate or impair protective immunity of the SARS-CoV-2 vaccines. However, as vaccines currently in use employ mRNA or nonreplicative viral vectors, they appear to be safe in patients on immunosuppression, further favoring vaccination. Moreover, predominant SARS-CoV-2 vaccines are likely to afford at least partial protective immunity through one or more immune mechanisms even in patients on IST. Guidelines and emerging strategies are also considered to optimize vaccine protection from COVID-19.

Genomics and Inflammation in Cardiovascular Disease

Chronic cardiovascular diseases are associated with inflammatory responses within the blood vessels and end organs. The origin of this inflammation has not been certain, and neither is its relationship to disease clear. There is a need to determine whether this association is causal or coincidental to the processes leading to cardiovascular disease. These processes are themselves complex: many cardiovascular diseases arise in conjunction with the presence of sustained elevation of blood pressure. Inflammatory processes have been linked to hypertension, and causality has been suggested. Evidence of causality poses the difficult challenge of linking the integrated and multifaceted biology of blood pressure regulation with vascular function and complex elements of immune system function. These include both, innate and adaptive immunity, as well as interactions between the host immune system and the omnipresent microorganisms that are encountered in the environment and that colonize and exist in commensal relationship with the host. Progress has been made in this task and has drawn on experimental approaches in animals, much of which have focused on hypertension occurring with prolonged infusion of angiotensin II. These laboratory studies are complemented by studies that seek to inform disease mechanism by examining the genomic basis of heritable disease susceptibility in human populations. In this realm too, evidence has emerged that implicates genetic variation affecting immunity in disease pathogenesis. In this article, we survey the genetic and genomic evidence linking high blood pressure and its end-organ injuries to immune system function and examine evidence that genomic factors can influence disease risk. © 2021 American Physiological Society. Compr Physiol 11:1-22, 2021.

Immune Prophylaxis and Therapy for Human Cytomegalovirus Infection

Human Cytomegalovirus (HCMV) infection is widespread and can result in severe sequelae in susceptible populations. Primary HCMV infection of naïve individuals results in life-long latency characterized by frequent and sporadic reactivations. HCMV infection elicits a robust antibody response, including neutralizing antibodies that can block the infection of susceptible cells in vitro and in vivo. Thus, antibody products and vaccines hold great promise for the prevention and treatment of HCMV, but to date, most attempts to demonstrate their safety and efficacy in clinical trials have been unsuccessful. In this review we summarize publicly available data on these products and highlight new developments and approaches that could assist in successful translation of HCMV immunotherapies.

Antibody Repertoire Analysis of Tumor-Infiltrating B Cells Reveals Distinct Signatures and Distributions Across Tissues

The role of B cells in the tumor microenvironment (TME) has largely been under investigated, and data regarding the antibody repertoire encoded by B cells in the TME and the adjacent lymphoid organs are scarce. Here, we utilized B cell receptor high-throughput sequencing (BCR-Seq) to profile the antibody repertoire signature of tumor-infiltrating lymphocyte B cells (TIL−Bs) in comparison to B cells from three anatomic compartments in a mouse model of triple-negative breast cancer. We found that TIL-Bs exhibit distinct antibody repertoire measures, including high clonal polarization and elevated somatic hypermutation rates, suggesting a local antigen-driven B-cell response. Importantly, TIL-Bs were highly mutated but non-class switched, suggesting that class-switch recombination may be inhibited in the TME. Tracing the distribution of TIL-B clones across various compartments indicated that they migrate to and from the TME. The data thus suggests that antibody repertoire signatures can serve as indicators for identifying tumor-reactive B cells.

Rapid generation of potent antibodies by autonomous hypermutation in yeast

The predominant approach for antibody generation remains animal immunization, which can yield exceptionally selective and potent antibody clones owing to the powerful evolutionary process of somatic hypermutation. However, animal immunization is inherently slow, not always accessible and poorly compatible with many antigens. Here, we describe 'autonomous hypermutation yeast surface display' (AHEAD), a synthetic recombinant antibody generation technology that imitates somatic hypermutation inside engineered yeast. By encoding antibody fragments on an error-prone orthogonal DNA replication system, surface-displayed antibody repertoires continuously mutate through simple cycles of yeast culturing and enrichment for antigen binding to produce high-affinity clones in as little as two weeks. We applied AHEAD to generate potent nanobodies against the SARS-CoV-2 S glycoprotein, a G-protein-coupled receptor and other targets, offering a template for streamlined antibody generation at large.

Comparison of Two Strategies to Generate Antigen-Specific Human Monoclonal Antibodies: Which Method to Choose for Which Purpose?

Human monoclonal antibodies (mAbs) are valuable tools to link genetic information with functional features and to provide a platform for conformational epitope mapping. Additionally, combined data on genetic and functional features provide a valuable mosaic for systems immunology approaches. Strategies to generate human mAbs from peripheral blood have been described and used in several studies including single cell sequencing of antigen-binding B cells and the establishment of antigen-specific monoclonal Epstein-Barr Virus (EBV) immortalized lymphoblastoid cell lines (LCLs). However, direct comparisons of these two strategies are scarce. Hence, we sought to set up these two strategies in our laboratory using peanut 2S albumins (allergens) and the autoantigen anti-Rho guanosine diphosphate dissociation inhibitor 2 (RhoGDI2, alternatively 'ARHGDIB') as antigen targets to directly compare these strategies regarding costs, time expenditure, recovery, throughput and complexity. Regarding single cell sequencing, up to 50% of corresponding V(D)J gene transcripts were successfully amplified of which 54% were successfully cloned into expression vectors used for heterologous expression. Seventy-five percent of heterologously expressed mAbs showed specific binding to peanut 2S albumins resulting in an overall recovery of 20.3%, which may be increased to around 29% by ordering gene sequences commercially for antibody cloning. In comparison, the establishment of monoclonal EBV-LCLs showed a lower overall recovery of around 17.6%. Heterologous expression of a mAb carrying the same variable region as its native counterpart showed comparable concentration-dependent binding abilities. By directly comparing those two strategies, single cell sequencing allows a broad examination of antigen-binding mAbs in a moderate-throughput manner, while the establishment of monoclonal EBV-LCLs is a powerful tool to select a small number of highly reactive mAbs restricted to certain B cell subpopulations. Overall, both strategies, initially set-up for peanut 2S albumins, are suitable to obtain human mAbs and they are easily transferrable to other target antigens as shown for ARHGDIB.

Optimal evolutionary decision-making to store immune memory

The adaptive immune system provides a diverse set of molecules that can mount specific responses against a multitude of pathogens. Memory is a key feature of adaptive immunity, which allows organisms to respond more readily upon re-infections. However, differentiation of memory cells is still one of the least understood cell fate decisions. Here, we introduce a mathematical framework to characterize optimal strategies to store memory to maximize the utility of immune response over an organism's lifetime. We show that memory production should be actively regulated to balance between affinity and cross-reactivity of immune receptors for an effective protection against evolving pathogens. Moreover, we predict that specificity of memory should depend on the organism's lifespan, and shorter lived organisms with fewer pathogenic encounters should store more cross-reactive memory. Our framework provides a baseline to gauge the efficacy of immune memory in light of an organism's coevolutionary history with pathogens.

B Cell Response to Vaccination

As one of the most important weapons against infectious diseases, vaccines have saved countless lives since their first use in the late eighteenth century. Antibodies produced by effector B cells upon vaccination play a critical role in mediating protection. The past several decades of research have led to a revolution in our understanding of B cell response to vaccination. Vaccines against SARS-CoV-2 coronavirus were developed at an unprecedented speed to power our global fight against COVID-19 pandemic. Nevertheless, we still face many challenges in the development of vaccines against many other deadly viruses, such as human immunodeficiency virus (HIV) and influenza virus. In this review, we summarize the latest findings on B cell response to vaccination and pathogen infection. We also discuss the current challenges in the field and the potential strategies targeting B cell response to improve vaccine efficacy.Key abbreviations box: BCR: B cell receptor; bNAb: broadly neutralizing antibody; DC: dendritic cells; DZ: dark zone; EF response: extrafollicular response; FDC: follicular dendritic cell; GC: germinal center; HIV: human immunodeficiency virus; IC: immune complex; LLPC: long-lived plasma cell; LZ: light zone; MBC: memory B cell; SLPB: short-lived plasmablast; TFH: T follicular helper cells; TLR: Toll-like receptor.

Affinity maturation: highlights in the application of in vitro strategies for the directed evolution of antibodies

Affinity maturation is a key technique in protein engineering which is used to improve affinity and binding interactions in vitro, a process often required to fulfil the therapeutic potential of antibodies. There are many available display technologies and maturation methods developed over the years, which have been instrumental in the production of therapeutic antibodies. However, due to the inherent limitations in display capacity of these technologies, accommodation of expansive and complex library builds is still a challenge. In this article, we discuss our recent efforts in the affinity maturation of a difficult antibody lineage using an unbiased approach, which sought to explore a larger sequence space through the application of DNA recombination and shuffling techniques across the entire antibody region and selections using ribosome display. We also highlight the key features of several display technologies and diversification methods, and discuss the strategies devised by different groups in response to different challenges. Particular attention is drawn to examples which are aimed at the expansion of sequence, structural or experimental diversity through different means and approaches. Here, we provide our perspectives on these methodologies and the considerations involved in the design of effective strategies for the directed evolution of antibodies.

Progress toward improved understanding of antibody maturation

Upon encountering an antigen, antibodies mature through various rounds of somatic mutations, resulting in higher affinities and specificities to the particular antigen. We review recent progress in four areas of antibody maturation studies. (1) Next-generation and single-cell sequencing have revolutionized the analysis of antibody repertoires by dramatically increasing the sequences available to study the state and evolution of the immune system. Computational methods, including machine learning tools, have been developed for reconstituting antibody clonal lineages and for general repertoire analysis. (2) The availability of X-ray structures, thermodynamic and kinetic data, and molecular dynamics simulations provide information on the biophysical mechanisms responsible for improved affinity. (3) In addition to improved binding to a specific antigen, providing affinity-independent diversity and self/nonself discrimination are fundamental functions of the immune system. Recent studies, including X-ray structures, yield improved understanding of both mechanisms. (4) Results from in vivo maturation help to develop methods of in vitro maturation to improve antibody properties for therapeutic applications, frequently combining computational and experimental approaches.

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

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

Local and Global Rigidification Upon Antibody Affinity Maturation

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

Extensive sequence and structural evolution of Arginase 2 inhibitory antibodies enabled by an unbiased approach to affinity maturation

Affinity maturation is a powerful technique in antibody engineering for the in vitro evolution of antigen binding interactions. Key to the success of this process is the expansion of sequence and combinatorial diversity to increase the structural repertoire from which superior binding variants may be selected. However, conventional strategies are often restrictive and only focus on small regions of the antibody at a time. In this study, we used a method that combined antibody chain shuffling and a staggered-extension process to produce unbiased libraries, which recombined beneficial mutations from all six complementarity-determining regions (CDRs) in the affinity maturation of an inhibitory antibody to Arginase 2 (ARG2). We made use of the vast display capacity of ribosome display to accommodate the sequence space required for the diverse library builds. Further diversity was introduced through pool maturation to optimize seven leads of interest simultaneously. This resulted in antibodies with substantial improvements in binding properties and inhibition potency. The extensive sequence changes resulting from this approach were translated into striking structural changes for parent and affinity-matured antibodies bound to ARG2, with a large reorientation of the binding paratope facilitating increases in contact surface and shape complementarity to the antigen. The considerable gains in therapeutic properties seen from extensive sequence and structural evolution of the parent ARG2 inhibitory antibody clearly illustrate the advantages of the unbiased approach developed, which was key to the identification of high-affinity antibodies with the desired inhibitory potency and specificity.

The Effects of Framework Mutations at the Variable Domain Interface on Antibody Affinity Maturation in an HIV-1 Broadly Neutralizing Antibody Lineage

Understanding affinity maturation of antibodies that can target many variants of HIV-1 is important for vaccine development. While the antigen-binding site of antibodies is known to mutate throughout the co-evolution of antibodies and viruses in infected individuals, the roles of the mutations in the antibody framework region are not well understood. Throughout affinity maturation, the CH103 broadly neutralizing antibody lineage, from an individual designated CH505, altered the orientation of one of its antibody variable domains. The change in orientation was a response to insertions in the variable loop 5 (V5) of the HIV envelope. In this study, we generated CH103 lineage antibody variants in which residues in the variable domain interface were mutated, and measured the binding to both autologous and heterologous HIV-1 envelopes. Our data show that very few mutations in an early intermediate antibody of the lineage can improve binding toward both autologous and heterologous HIV-1 envelopes. We also crystallized an antibody mutant to show that framework mutations alone can result in a shift in relative orientations of the variable domains. Taken together, our results demonstrate the functional importance of residues located outside the antigen-binding site in affinity maturation.

Learning context-aware structural representations to predict antigen and antibody binding interfaces

MOTIVATION

Understanding how antibodies specifically interact with their antigens can enable better drug and vaccine design, as well as provide insights into natural immunity. Experimental structural characterization can detail the 'ground truth' of antibody-antigen interactions, but computational methods are required to efficiently scale to large-scale studies. To increase prediction accuracy as well as to provide a means to gain new biological insights into these interactions, we have developed a unified deep learning-based framework to predict binding interfaces on both antibodies and antigens.

RESULTS

Our framework leverages three key aspects of antibody-antigen interactions to learn predictive structural representations: (i) since interfaces are formed from multiple residues in spatial proximity, we employ graph convolutions to aggregate properties across local regions in a protein; (ii) since interactions are specific between antibody-antigen pairs, we employ an attention layer to explicitly encode the context of the partner; (iii) since more data are available for general protein-protein interactions, we employ transfer learning to leverage this data as a prior for the specific case of antibody-antigen interactions. We show that this single framework achieves state-of-the-art performance at predicting binding interfaces on both antibodies and antigens, and that each of its three aspects drives additional improvement in the performance. We further show that the attention layer not only improves performance, but also provides a biologically interpretable perspective into the mode of interaction.

AVAILABILITY AND IMPLEMENTATION

The source code is freely available on github at https://github.com/vamships/PECAN.git.

Occupation of a thermoresistant-scaffold (αRep) at SP1-NC cleavage site disturbs the function of HIV-1 protease

HIV-1 nucleocapsid (NC) becomes an attractive target for the development of novel anti-HIV-1 agents. Discovering of non-antibody scaffolds that disrupt the function of NC will be a potential aspect for disturbing viral maturation process. Correspondingly, we explored the specific binding site of the thermoresistant-scaffold protein, αRep9A8 which formerly demonstrated the inhibitory effect on HIV-1 replication. The portion of Gag, CA₂₁-SP1-NC has been used as a template for designing nine overlapping peptides (P4–P12). The P9 peptide showed the strongest binding activity followed by P8 and P12 respectively. The amino acid sequences on those peptides resemble the N-terminal domain of the NC proximity to the SP1-NC initial cleavage site and across the conserved CCHC zinc finger 1 (ZF1) of NC. The interaction K_D between αRep9A8 with its target was 224.9 ± 57.4 nM. Consequently, αRep9A8 demonstrated the interference of the HIV-1 protease function by hindering a protease cleavage site. The released NC product from CA₂₁-SP1-NC was diminished. The present study provided an additional information of αRep9A8 function in interfering of viral maturation processes resulting in the decremental efficiency of viral infectivity.

São Paulo School of Advanced Sciences on Vaccines: an overview

Two years ago, we held an exciting event entitled the São Paulo School of Advanced Sciences on Vaccines (SPSASV). Sixty-eight Ph.D. students, postdoctoral fellows and independent researchers from 37 different countries met at the Mendes Plaza Hotel located in the city of Santos, SP - Brazil to discuss the challenges and the new frontiers of vaccinology. The SPSASV provided a critical and comprehensive view of vaccine research from basics to the current state-of-the-art techniques performed worldwide. For 10 days, we discussed all the aspects of vaccine development in 36 lectures, 53 oral presentations and 2 poster sessions. At the end of the course, participants were further encouraged to present a model of a grant proposal related to vaccine development against individual pathogens. Among the targeted pathogens were viruses (Chikungunya, HIV, RSV, and Influenza), bacteria (Mycobacterium tuberculosis and Streptococcus pyogenes), parasites (Plasmodium falciparum or Plasmodium vivax), and the worm Strongyloides stercoralis. This report highlights some of the knowledge shared at the SPSASV.

T-Cell Receptor Variable β Domains Rigidify During Affinity Maturation

We investigated T-cell receptor variable β chains binding to the superantigen staphylococcal enterotoxin C3 (SEC 3) with structure information in different stages of affinity maturation. Metadynamics in combination with molecular dynamics simulations allow to access the micro-to-millisecond timescale and reveal a strong effect of energetically significant mutations on the flexibility of the antigen-binding site. The observed changes in dynamics of the complementarity determining region (CDR) loops, especially the CDR 2, and HV 4 loop on this specific pathway of affinity maturation are reflected in their structural diversity, thermodynamics of conformations and kinetics of structural transitions. In addition, this affinity maturation pathway follows the concept of conformational selection, because even without the presence of the antigen the binding competent state is present in this pre-existing ensemble of conformations. In all stages of this affinity maturation process we observe a link between specificity and reduced flexibility.

Proteome of thymus and spleen reveals that 10-hydroxydec-2-enoic acid could enhance immunity in mice

Objectives: 10-hydroxydec-2-enoic acid (10-HDA), a unique component of royal jelly existing only in nature, has the potential to promote human health. Knowledge of 10-HDA in regulating immuno-activity, however, is lacking. The aim of our work is to gain a novel understanding of 10-HDA in promoting immunity.Methods: Immuno-suppressed mice were generated by cyclophosphamide injection, After 10-HDA supplementation to the mice to rescue their immunity, the proteomes of the thymus and spleen were analyzed.Results: The weight of the body, thymus, and spleen in cyclophosphamide-induced mice recovered by 10-HDA indicate its potential role in immuno-organ protection. In the thymus, the enhanced activity of pathways associated with DNA/RNA/protein activities may be critical for T-lymphocyte proliferation/differentiation, and cytotoxicity. In the spleen, the induced pathways involved in DNA/RNA/protein activities, and cell proliferative stimulation suggest their vital role in B-lymphocyte affinity maturation, antigen presentation, and macrophage activity. The up-regulated proteins highly connected in networks modulated by 10-HDA indicate that the mice may evolve tactics to respond to immuno-organ impairment by activating critical physiological processes.Conclusion: Our data constitute a proof-of-concept that 10-HDA is a potential agent to improve immunity in the thymus and spleen and offer a new venue for applying natural products to the therapy for hypoimmunity.

Robustness of Serologic Investigations for Chikungunya and Mayaro Viruses following Coemergence

Geographically overlapping transmission of Chikungunya virus (CHIKV) and Mayaro virus (MAYV) in Latin America challenges serologic diagnostics and epidemiologic surveillance, as antibodies against the antigenically related viruses can be cross-reactive, potentially causing false-positive test results. We examined whether widely used ELISAs and plaque reduction neutralization testing allow specific antibody detection in the scenario of CHIKV and MAYV coemergence. For this purpose, we used 37 patient-derived MAYV-specific sera from Peru and 64 patient-derived CHIKV-specific sera from Brazil, including longitudinally collected samples. Extensive testing of those samples revealed strong antibody cross-reactivity in ELISAs, particularly for IgM, which is commonly used for patient diagnostics. Cross-neutralization was also observed, albeit at lower frequencies. Parallel testing for both viruses and comparison of ELISA reactivities and neutralizing antibody titers significantly increased diagnostic specificity. Our data provide a convenient and practicable solution to ensure robust differentiation of CHIKV- and MAYV-specific antibodies.

Since 2013, the arthropod-borne Chikungunya virus (CHIKV) has cocirculated with the autochthonous Mayaro virus (MAYV) in Latin America. Both belong to the same alphavirus serocomplex, termed the Semliki Forest serocomplex. The extent of antibody cross-reactivity due to the antigenic relatedness of CHIKV and MAYV in commonly used serologic tests remains unclear. By testing 64 CHIKV- and 37 MAYV-specific sera from cohort studies conducted in Peru and Brazil, we demonstrate about 50% false-positive test results using commercially available enzyme-linked immunosorbent assays (ELISAs) based on structural antigens. In contrast, combining ELISAs for CHIKV and MAYV significantly increased positive predictive values (PPV) among all cohorts from 35.3% to 88.2% for IgM and from 61.3% to 96.8% for IgG (P < 0.0001). Testing of longitudinally collected CHIKV-specific patient sera indicated that ELISA specificity is highest for IgM testing at 5 to 9 days post-onset of symptoms (dpo) and for IgG testing at 10 to 14 dpo. IgG cross-reactivity in ELISA was asymmetric, occurring in 57.9% of MAYV-specific sera compared to 29.5% of CHIKV-specific sera. Parallel plaque reduction neutralization testing (PRNT) for CHIKV and MAYV increased the PPV from 80.0% to 100% (P = 0.0053). However, labor-intense procedures and delayed seroconversion limit PRNT for patient diagnostics. In sum, individual testing for CHIKV or MAYV only is prone to misclassifications that dramatically impact patient diagnostics and sero-epidemiologic investigation. Parallel ELISAs for both CHIKV and MAYV provide an easy and efficient solution to differentiate CHIKV from MAYV infections. This approach may provide a template globally for settings in which alphavirus coemergence imposes similar problems.

IMPORTANCE Geographically overlapping transmission of Chikungunya virus (CHIKV) and Mayaro virus (MAYV) in Latin America challenges serologic diagnostics and epidemiologic surveillance, as antibodies against the antigenically related viruses can be cross-reactive, potentially causing false-positive test results. We examined whether widely used ELISAs and plaque reduction neutralization testing allow specific antibody detection in the scenario of CHIKV and MAYV coemergence. For this purpose, we used 37 patient-derived MAYV-specific sera from Peru and 64 patient-derived CHIKV-specific sera from Brazil, including longitudinally collected samples. Extensive testing of those samples revealed strong antibody cross-reactivity in ELISAs, particularly for IgM, which is commonly used for patient diagnostics. Cross-neutralization was also observed, albeit at lower frequencies. Parallel testing for both viruses and comparison of ELISA reactivities and neutralizing antibody titers significantly increased diagnostic specificity. Our data provide a convenient and practicable solution to ensure robust differentiation of CHIKV- and MAYV-specific antibodies.