Human germline antibody gene segments encode polyspecific antibodies

Prediction of polyspecificity from antibody sequence data by machine learning

Antibodies are generated with great diversity in nature resulting in a set of molecules, each optimized to bind a specific target. Taking advantage of their diversity and specificity, antibodies make up for a large part of recently developed biologic drugs. For therapeutic use antibodies need to fulfill several criteria to be safe and efficient. Polyspecific antibodies can bind structurally unrelated molecules in addition to their main target, which can lead to side effects and decreased efficacy in a therapeutic setting, for example via reduction of effective drug levels. Therefore, we created a neural-network-based model to predict polyspecificity of antibodies using the heavy chain variable region sequence as input. We devised a strategy for enriching antibodies from an immunization campaign either for antigen-specific or polyspecific binding properties, followed by generation of a large sequencing data set for training and cross-validation of the model. We identified important physico-chemical features influencing polyspecificity by investigating the behaviour of this model. This work is a machine-learning-based approach to polyspecificity prediction and, besides increasing our understanding of polyspecificity, it might contribute to therapeutic antibody development.

Surface patches induce nonspecific binding and phase separation of antibodies

Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.

Application of germline antibody features to vaccine development, antibody discovery, antibody optimization and disease diagnosis

Although the efficacy and commercial success of vaccines and therapeutic antibodies have been tremendous, designing and discovering new drug candidates remains a labor-, time- and cost-intensive endeavor with high risks. The main challenges of vaccine development are inducing a strong immune response in broad populations and providing effective prevention against a group of highly variable pathogens. Meanwhile, antibody discovery faces several great obstacles, especially the blindness in antibody screening and the unpredictability of the developability and druggability of antibody drugs. These challenges are largely due to poorly understanding of germline antibodies and the antibody responses to pathogen invasions. Thanks to the recent developments in high-throughput sequencing and structural biology, we have gained insight into the germline immunoglobulin (Ig) genes and germline antibodies and then the germline antibody features associated with antigens and disease manifestation. In this review, we firstly outline the broad associations between germline antibodies and antigens. Moreover, we comprehensively review the recent applications of antigen-specific germline antibody features, physicochemical properties-associated germline antibody features, and disease manifestation-associated germline antibody features on vaccine development, antibody discovery, antibody optimization, and disease diagnosis. Lastly, we discuss the bottlenecks and perspectives of current and potential applications of germline antibody features in the biotechnology field.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Selective Recognition of Carbohydrate Antigens by Germline Antibodies Isolated from AID Knockout Mice

Germline antibodies, the initial set of antibodies produced by the immune system, are critical for host defense, and information about their binding properties can be useful for designing vaccines, understanding the origins of autoantibodies, and developing monoclonal antibodies. Numerous studies have found that germline antibodies are polyreactive with malleable, flexible binding pockets. While insightful, it remains unclear how broadly this model applies, as there are many families of antibodies that have not yet been studied. In addition, the methods used to obtain germline antibodies typically rely on assumptions and do not work well for many antibodies. Herein, we present a distinct approach for isolating germline antibodies that involves immunizing activation-induced cytidine deaminase (AID) knockout mice. This strategy amplifies antigen-specific B cells, but somatic hypermutation does not occur because AID is absent. Using synthetic haptens, glycoproteins, and whole cells, we obtained germline antibodies to an assortment of clinically important tumor-associated carbohydrate antigens, including Lewis Y, the Tn antigen, sialyl Lewis C, and Lewis X (CD15/SSEA-1). Through glycan microarray profiling and cell binding, we demonstrate that all but one of these germline antibodies had high selectivity for their glycan targets. Using molecular dynamics simulations, we provide insights into the structural basis of glycan recognition. The results have important implications for designing carbohydrate-based vaccines, developing anti-glycan monoclonal antibodies, and understanding antibody evolution within the immune system.

Public Immunity: Evolutionary Spandrels for Pathway-Amplifying Protective Antibodies

Humoral immunity is seeded by affinity between the B cell receptor (BCR) and cognate antigen. While the BCR is a chimeric display of diverse antigen engagement solutions, we discuss its functional activity as an ‘innate-like’ immune receptor, wherein genetically hardwired antigen complementarity can serve as reproducible templates for pathway-amplifying otherwise immunologically recessive antibody responses. We propose that the capacity for germline reactivity to new antigen emerged as a set of evolutionary spandrels or coupled traits, which can now be exploited by rational vaccine design to focus humoral immunity upon conventionally immune-subdominant antibody targets. Accordingly, we suggest that evolutionary spandrels account for the necessary but unanticipated antigen reactivity of the germline antibody repertoire.

Antibody VH domain sequence analysis by a bioinformatics approach based on electronic amino acid properties may help to predict paratop location

Gene as the basic functional unit of DNA encodes information about the product such as protein. The majority of proteins realize function through protein-protein interactions involving short protein motifs. However, some proteins such as antibodies are established by the rearrangement of several (V-D-J) gene segments with the potential addition of nontemplated nucleotides that may change information encoded by the respective gene segment used. Antibody VH domain sequence analysis by ISM bioinformatics approach that is based on amino acids physicochemical features, enable to distinguish the contribution of the information encoded by VH gene or generated during VDJ gene recombination for antibody-antigen interaction. The data presented in this report revealed the significance of CDRH3 for the interaction of antibody specific for immunogenic molecules while CDRH3 contribution is minor for antibody interaction with nonimmunogenic molecules such as haptens and native mammalian dsDNA. Thus, paratopes might be located in the CDRH3 or VH regions.

Delicate balance among thermal stability, binding affinity, and conformational space explored by single-domain VHH antibodies

The high binding affinities and specificities of antibodies have led to their use as drugs and biosensors. Single-domain V_HH antibodies exhibit high specificity and affinity but have higher stability and solubility than conventional antibodies as they are single-domain proteins. In this work, based on physicochemical measurements and molecular dynamics (MD) simulations, we have gained insight that will facilitate rational design of single-chain V_HH antibodies. We first assessed two homologous V_HH antibodies by differential scanning calorimetry (DSC); one had a high (64.8 °C) and the other a low (58.6 °C) melting temperature. We then generated a series of the variants of the low stability antibody and analyzed their thermal stabilities by DSC and characterized their structures through MD simulations. We found that a single mutation that resulted in 8.2 °C improvement in melting temperature resulted in binding affinity an order of magnitude lower than the parent antibody, likely due to a shift of conformational space explored by the single-chain V_HH antibody. These results suggest that the delicate balance among conformational stability, binding capability, and conformational space explored by antibodies must be considered in design of fully functional single-chain V_HH antibodies.

Engineering an Antibody V Gene-Selective Vaccine

The ligand-binding surface of the B cell receptor (BCR) is formed by encoded and non-encoded antigen complementarity determining regions (CDRs). Genetically reproducible or ‘public’ antibodies can arise when the encoded CDRs play deterministic roles in antigen recognition, notably within human broadly neutralizing antibodies against HIV and influenza virus. We sought to exploit this by engineering virus-like-particle (VLP) vaccines that harbor multivalent affinity against gene-encoded moieties of the BCR antigen binding site. As proof of concept, we deployed a library of RNA bacteriophage VLPs displaying random peptides to identify a multivalent antigen that selectively triggered germline BCRs using the human V_H gene IGVH1-2*02. This VLP selectively primed IGHV1-2*02 BCRs that were present within a highly diversified germline antibody repertoire within humanized mice. Our approach thus provides methodology to generate antigens that engage specific BCR configurations of interest, in the absence of structure-based information.

A Single Human VH-gene Allows for a Broad-Spectrum Antibody Response Targeting Bacterial Lipopolysaccharides in the Blood

B cell receptors (BCRs) display a combination of variable (V)-gene-encoded complementarity determining regions (CDRs) and adaptive/hypervariable CDR3 loops to engage antigens. It has long been proposed that the former tune for recognition of pathogens or groups of pathogens. To experimentally evaluate this within the human antibody repertoire, we perform immune challenges in transgenic mice that bear diverse human CDR3 and light chains but are constrained to different human V_H-genes. We find that, of six commonly deployed V_H sequences, only those CDRs encoded by IGHV1-2^∗02 enable polyclonal antibody responses against bacterial lipopolysaccharide (LPS) when introduced to the bloodstream. The LPS is from diverse strains of gram-negative bacteria, and the V_H-gene-dependent responses are directed against the non-variable and universal saccrolipid substructure of this antigen. This reveals a broad-spectrum anti-LPS response in which germline-encoded CDRs naturally hardwire the human antibody repertoire for recognition of a conserved microbial target.

Parameters and determinants of responses to selection in antibody libraries

The sequences of antibodies from a given repertoire are highly diverse at few sites located on the surface of a genome-encoded larger scaffold. The scaffold is often considered to play a lesser role than highly diverse, non-genome-encoded sites in controlling binding affinity and specificity. To gauge the impact of the scaffold, we carried out quantitative phage display experiments where we compare the response to selection for binding to four different targets of three different antibody libraries based on distinct scaffolds but harboring the same diversity at randomized sites. We first show that the response to selection of an antibody library may be captured by two measurable parameters. Second, we provide evidence that one of these parameters is determined by the degree of affinity maturation of the scaffold, affinity maturation being the process by which antibodies accumulate somatic mutations to evolve towards higher affinities during the natural immune response. In all cases, we find that libraries of antibodies built around maturated scaffolds have a lower response to selection to other arbitrary targets than libraries built around germline-based scaffolds. We thus propose that germline-encoded scaffolds have a higher selective potential than maturated ones as a consequence of a selection for this potential over the long-term evolution of germline antibody genes. Our results are a first step towards quantifying the evolutionary potential of biomolecules.

Antibodies in the immune system consist of a genetically encoded scaffold that exposes a few highly diverse, non-genetically encoded sites. This focused diversity is sufficient to produce antibodies that bind to any target molecule. To understand the role of the scaffold, which acquires hypermutations during the immune response, over the selective response, we analyze quantitative in vitro experiments where large antibody populations based on different scaffolds are selected against different targets. We show that selective responses are described statistically by two parameters, one of which depends on prior evolution of the scaffold as part of a previous response. Our work provides methods to assay whether naïve antibody scaffolds are endowed with a distinctively high selective potential.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Discovery of Marburg virus neutralizing antibodies from virus-naïve human antibody repertoires using large-scale structural predictions

Marburg virus (MARV) disease is lethal, with fatality rates up to 90%. Neutralizing antibodies (Abs) are promising drug candidates to prevent or treat the disease. Current efforts are focused in part on vaccine development to induce such MARV-neutralizing Abs. We analyzed the antibody repertoire from healthy unexposed and previously MARV-infected individuals to assess if naïve repertoires contain suitable precursor antibodies that could become neutralizing with a limited set of somatic mutations. We computationally searched the human Ab variable gene repertoire for predicted structural homologs of the neutralizing Ab MR78 that is specific to the receptor binding site (RBS) of MARV glycoprotein (GP). Eight Ab heavy-chain complementarity determining region 3 (HCDR3) loops from MARV-naïve individuals and one from a previously MARV-infected individual were selected for testing as HCDR3 loop chimeras on the MR78 Ab framework. Three of these chimerized antibodies bound to MARV GP. We then tested a full-length native Ab heavy chain encoding the same 17-residue-long HCDR3 loop that bound to the MARV GP the best among the chimeric Abs tested. Despite only 57% amino acid sequence identity, the Ab from a MARV-naïve donor recognized MARV GP and possessed neutralizing activity against the virus. Crystallization of both chimeric and full-length native heavy chain-containing Abs provided structural insights into the mechanism of binding for these types of Abs. Our work suggests that the MARV GP RBS is a promising candidate for epitope-focused vaccine design to induce neutralizing Abs against MARV.

Why blood group A individuals are at risk whereas blood group O individuals are protected from SARS-CoV-2 (COVID-19) infection: A hypothesis regarding how the virus invades the human body via ABO(H) blood group-determining carbohydrates

While the angiotensin converting enzyme 2 (ACE2) protein is defined as the primary severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor, the viral serine molecule might be mobilized by the host's transmembrane protease serine subtype 2 (TMPRSS2) enzyme from the viral spike (S) protein and hijack the host’s N-acetyl-D-galactosamine (GalNAc) metabolism. The resulting hybrid, serologically A-like/Tn (T nouvelle) structure potentially acts as a host–pathogen functional molecular bridge. In humans, this intermediate structure will hypothetically be replaced by ABO(H) blood group-specific, mucin-type structures, in the case of infection hybrid epitopes, implicating the phenotypically glycosidic accommodation of plasma proteins. The virus may, by mimicking the synthetic pathways of the ABO(H) blood groups, bind to the cell surfaces of the blood group O(H) by formation of a hybrid H-type antigen as the potential precursor of hybrid non-O blood groups, which does not affect the highly anti-glycan aggressive anti-A and anti-B isoagglutinin activities, exerted by the germline-encoded nonimmune immunoglobulin M (IgM). In the non-O blood groups, which have developed from the H-type antigen, these IgM activities are downregulated by phenotypic glycosylation, while adaptive immunoglobulins might arise in response to the hybrid A and B blood group structures, bonds between autologous carbohydrates and foreign peptides, suggesting the exertion of autoreactivity. The non-O blood groups thus become a preferred target for the virus, whereas blood group O(H) individuals, lacking the A/B phenotype-determining enzymes and binding the virus alone by hybrid H-type antigen formation, have the least molecular contact with the virus and maintain the critical anti-A and anti-B isoagglutinin activities, exerted by the ancestral IgM, which is considered the humoral spearhead of innate immunity.

Structural and functional analysis of protective antibodies targeting the threefold plateau of enterovirus 71

Enterovirus 71 (EV71)-neutralizing antibodies correlate with protection and have potential as therapeutic agents. We isolate and characterize a panel of plasmablast-derived monoclonal antibodies from an infected child whose antibody response focuses on the plateau epitope near the icosahedral 3-fold axes. Eight of a total of 19 antibodies target this epitope and three of these potently neutralize the virus. Representative neutralizing antibodies 38-1-10A and 38-3-11A both confer effective protection against lethal EV71 challenge in hSCARB2-transgenic mice. The cryo-electron microscopy structures of the EV71 virion in complex with Fab fragments of these potent and protective antibodies reveal the details of a conserved epitope formed by residues in the BC and HI loops of VP2 and the BC and HI loops of VP3 spanning the region around the 3-fold axis. Remarkably, the two antibodies interact with the epitope in quite distinct ways. These plateau-binding antibodies provide templates for promising candidate therapeutics.

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.

The Innate Biologies of Adaptive Antigen Receptors

Nonclonal innate immune responses mediated by germ line-encoded receptors, such as Toll-like receptors or natural killer receptors, are commonly contrasted with diverse, clonotypic adaptive responses of lymphocyte antigen receptors generated by somatic recombination. However, the Variable (V) regions of antigen receptors include germ line-encoded motifs unaltered by somatic recombination, and theoretically available to mediate nonclonal, innate responses, that are independent of or largely override clonotypic responses. Recent evidence demonstrates that such responses exist, underpinning the associations of particular γδ T cell receptors (TCRs) with specific anatomical sites. Thus, TCRγδ can make innate and adaptive responses with distinct functional outcomes. Given that αβ T cells and B cells can also make nonclonal responses, we consider that innate responses of antigen receptor V-regions may be more widespread, for example, inducing states of preparedness from which adaptive clones are better selected. We likewise consider that potent, nonclonal T cell responses to microbial superantigens may reflect subversion of physiologic innate responses of TCRα/β chains.

Multi-state design of flexible proteins predicts sequences optimal for conformational change

Computational protein design of an ensemble of conformations for one protein–i.e., multi-state design–determines the side chain identity by optimizing the energetic contributions of that side chain in each of the backbone conformations. Sampling the resulting large sequence-structure search space limits the number of conformations and the size of proteins in multi-state design algorithms. Here, we demonstrated that the REstrained CONvergence (RECON) algorithm can simultaneously evaluate the sequence of large proteins that undergo substantial conformational changes. Simultaneous optimization of side chain conformations across all conformations increased sequence conservation when compared to single-state designs in all cases. More importantly, the sequence space sampled by RECON MSD resembled the evolutionary sequence space of flexible proteins, particularly when confined to predicting the mutational preferences of limited common ancestral descent, such as in the case of influenza type A hemagglutinin. Additionally, we found that sequence positions which require substantial changes in their local environment across an ensemble of conformations are more likely to be conserved. These increased conservation rates are better captured by RECON MSD over multiple conformations and thus multiple local residue environments during design. To quantify this rewiring of contacts at a certain position in sequence and structure, we introduced a new metric designated ‘contact proximity deviation’ that enumerates contact map changes. This measure allows mapping of global conformational changes into local side chain proximity adjustments, a property not captured by traditional global similarity metrics such as RMSD or local similarity metrics such as changes in φ and ψ angles.

Multi-state design can be used to engineer proteins that need to exist in multiple conformations or that bind to multiple partner molecules. In essence, multi-state design selects a compromise of protein sequences that allow for an ensemble of protein conformations, or states, associated with a particular biological function. In this paper, we used the REstrained CONvergence (RECON) algorithm with Rosetta to show that multi-state design of flexible proteins predicts sequences optimal for conformational change, mimicking mutation preferences sampled in evolution. Modeling optimal local side chain physicochemical environments within an ensemble selected significantly more native-like sequences than selections performed when all conformations states are designed independently. This outcome was particularly true for amino acids whose local side chain environment change between conformations. To quantify such contact map changes, we introduced a novel metric to show that sequence conservation is dependent on protein flexibility, i.e., changes in local side chain environments between stated limit the space of tolerated mutations. Additionally, such positions in sequence and structure are more likely to be energetically frustrated, at least in some states. Importantly, we showed that multi-state design over an ensemble of conformations (space) can explore evolutionary tolerated sequence space (time), thus enabling RECON to not only design proteins that require multiple states for function but also predict mutations that might be tolerated in native proteins but have not yet been explored by evolution. The latter aspect can be important to anticipate escape mutations, for example in pathogens or oncoproteins.

Diagnostic Profiling of the Human Public IgM Repertoire With Scalable Mimotope Libraries

Specific antibody reactivities are routinely used as biomarkers, but the antibody repertoire reactivity (igome) profiles are still neglected. Here, we propose rationally designed peptide arrays as efficient probes for these system level biomarkers. Most IgM antibodies are characterized by few somatic mutations, polyspecificity, and physiological autoreactivity with housekeeping function. Previously, probing this repertoire with a set of immunodominant self-proteins provided a coarse analysis of the respective repertoire profiles. In contrast, here, we describe the generation of a peptide mimotope library that reflects the common IgM repertoire of 10,000 healthy donors. In addition, an appropriately sized subset of this quasi-complete mimotope library was further designed as a potential diagnostic tool. A 7-mer random peptide phage display library was panned on pooled human IgM. Next-generation sequencing of the selected phage yielded 224,087 sequences, which clustered in 790 sequence clusters. A set of 594 mimotopes, representative of the most significant sequence clusters, was shown to probe symmetrically the space of IgM reactivities in patients' sera. This set of mimotopes can be easily scaled including a greater proportion of the mimotope library. The trade-off between the array size and the resolution can be explored while preserving the symmetric sampling of the mimotope sequence and reactivity spaces. BLAST search of the non-redundant protein database with the mimotopes sequences yielded significantly more immunoglobulin J region hits than random peptides, indicating a considerable idiotypic connectivity of the targeted igome. The proof of principle predictors for random diagnoses was represented by profiles of mimotopes. The number of potential reactivity profiles that can be extracted from this library is estimated at more than 10⁷⁰. Thus, a quasi-complete IgM mimotope library and a scalable representative subset thereof are found to address very efficiently the dynamic diversity of the human public IgM repertoire, providing informationally dense and structurally interpretable IgM reactivity profiles.

Affinity Maturation Enhances Antibody Specificity but Compromises Conformational Stability

Monoclonal antibodies (mAbs) have recently emerged as one of the most promising classes of biotherapeutics. A potential advantage of B cell-derived mAbs as therapeutic agents is that they have been subjected to natural filtering mechanisms, which may enrich for B cell receptors (BCRs) with favorable biophysical properties. Here, we evaluated 400 human mAbs for polyreactivity, hydrophobicity, and thermal stability using high-throughput screening assays. Overall, mAbs derived from memory B cells and long-lived plasma cells (LLPCs) display reduced levels of polyreactivity, hydrophobicity, and thermal stability compared with naive B cell-derived mAbs. Somatic hypermutation (SHM) is inversely associated with all three biophysical properties, as well as BCR expression levels. Finally, the developability profiles of the human B cell-derived mAbs are comparable with those observed for clinical mAbs, suggesting their high therapeutic potential. The results provide insight into the biophysical consequences of affinity maturation and have implications for therapeutic antibody engineering and development.

Tau-Reactive Endogenous Antibodies: Origin, Functionality, and Implications for the Pathophysiology of Alzheimer's Disease

In Alzheimer's disease (AD), tau pathology manifested by the accumulation of intraneuronal tangles and soluble toxic oligomers emerges as a promising therapeutic target. Multiple anti-tau antibodies inhibiting the formation and propagation of cytotoxic tau or promoting its clearance and degradation have been tested in clinical trials, albeit with the inconclusive outcome. Antibodies against tau protein have been documented both in the brain circulatory system and at the periphery, but their origin and role under normal conditions and in AD remain unclear. While it is tempting to assign them a protective role in regulating tau level and removal of toxic variants, the supportive evidence remains sporadic, requiring systematic analysis and critical evaluation. Herein, we review recent data showing the occurrence of tau-reactive antibodies in the brain and peripheral circulation and discuss their origin and significance in tau clearance. Based on the emerging evidence, we cautiously propose that impairments of tau clearance at the periphery by humoral immunity might aggravate the tau pathology in the central nervous system, with implication for the neurodegenerative process of AD.

Subtle Changes in the Combining Site of the Chlamydiaceae-Specific mAb S25-23 Increase the Antibody-Carbohydrate Binding Affinity by an Order of Magnitude

Murine antibodies S25-23, S25-26, and S25-5 derive from a common germ-line origin, and all bind the Chlamydiaceae family-specific epitope αKdo(2→8)αKdo(2→4)αKdo (where Kdo is 3-deoxy-α-d- manno-oct-2-ulosonic acid) with high affinity and specificity. These antibodies recognize the entire trisaccharide antigen in a linkage-dependent manner via a groove composed largely of germ-line residues. Despite sharing identical heavy and light chain genes, S25-23 binds the family-specific epitope with nanomolar affinity, which is an order of magnitude higher than that of S25-26, while S25-5 displays an affinity between those of S25-23 and S25-26. We determined the high-resolution crystal structures of S25-23 and S25-5 antigen binding fragments in complex with a pentasaccharide derived from the LPS of Chlamydia and measured the affinity of S25-5 for chlamydial LPS antigens using isothermal titration microcalorimetry. The 1.75 Å resolution structure of S25-23 shows how subtle conservative mutations Arg(L)-27E to lysine and Ser(H)-56 to threonine lead to an order of magnitude increase in affinity. Importantly, comparison between previous S25-26 structures and the 1.99 and 2.05 Å resolution liganded and unliganded structures of S25-5, respectively, shows how a Ser(L)-27E mutation results in an intermediate affinity due to the reduced enthalpic penalty associated with complex formation that would otherwise be required for arginine in this position. This strategy allows for subtle adjustments in the combining site via affinity maturation that have dramatic consequences for the affinity of an antibody for its antigen.

Multistate design of influenza antibodies improves affinity and breadth against seasonal viruses

Influenza is an annual threat to global public health, in part because of constant antigenic drift that facilitates evasion of the antibody response. Rapid changes in the influenza HA protein make it difficult for an antibody to achieve broad activity against different virus subtypes. We developed a computational method that can optimize an antibody sequence to be robust against seasonal variation. As a proof of concept, we tested this method by redesigning a known antibody against a set of diverse HA antigens and showed that the variant redesigned antibodies have improved activity against the virus panel, as predicted. This work shows that computational design can improve naturally occurring antibodies for recognition of different virus strains.

Influenza is a yearly threat to global public health. Rapid changes in influenza surface proteins resulting from antigenic drift and shift events make it difficult to readily identify antibodies with broadly neutralizing activity against different influenza subtypes with high frequency, specifically antibodies targeting the receptor binding domain (RBD) on influenza HA protein. We developed an optimized computational design method that is able to optimize an antibody for recognition of large panels of antigens. To demonstrate the utility of this multistate design method, we used it to redesign an antiinfluenza antibody against a large panel of more than 500 seasonal HA antigens of the H1 subtype. As a proof of concept, we tested this method on a variety of known antiinfluenza antibodies and identified those that could be improved computationally. We generated redesigned variants of antibody C05 to the HA RBD and experimentally characterized variants that exhibited improved breadth and affinity against our panel. C05 mutants exhibited improved affinity for three of the subtypes used in design by stabilizing the CDRH3 loop and creating favorable electrostatic interactions with the antigen. These mutants possess increased breadth and affinity of binding while maintaining high-affinity binding to existing targets, surpassing a major limitation up to this point.

Effective binding to protein antigens by antibodies from antibody libraries designed with enhanced protein recognition propensities

Antibodies provide immune protection by recognizing antigens of diverse chemical properties, but elucidating the amino acid sequence-function relationships underlying the specificity and affinity of antibody-antigen interactions remains challenging. We designed and constructed phage-displayed synthetic antibody libraries with enriched protein antigen-recognition propensities calculated with machine learning predictors, which indicated that the designed single-chain variable fragment variants were encoded with enhanced distributions of complementarity-determining region (CDR) hot spot residues with high protein antigen recognition propensities in comparison with those in the human antibody germline sequences. Antibodies derived directly from the synthetic antibody libraries, without affinity maturation cycles comparable to those in in vivo immune systems, bound to the corresponding protein antigen through diverse conformational or linear epitopes with specificity and affinity comparable to those of the affinity-matured antibodies from in vivo immune systems. The results indicated that more densely populated CDR hot spot residues were sustainable by the antibody structural frameworks and could be accompanied by enhanced functionalities in recognizing protein antigens. Our study results suggest that synthetic antibody libraries, which are not limited by the sequences found in antibodies in nature, could be designed with the guidance of the computational machine learning algorithms that are programmed to predict interaction propensities to molecules of diverse chemical properties, leading to antibodies with optimal characteristics pertinent to their medical applications.

Characterizing the Diversity of the CDR-H3 Loop Conformational Ensembles in Relationship to Antibody Binding Properties

We present an approach to assess antibody CDR-H3 loops according to their dynamic properties using molecular dynamics simulations. We selected six antibodies in three pairs differing substantially in their individual promiscuity respectively specificity. For two pairs of antibodies crystal structures are available in different states of maturation and used as starting structures for the analyses. For a third pair we chose two antibody CDR sequences obtained from a synthetic library and predicted the respective structures. For all three pairs of antibodies we performed metadynamics simulations to overcome the limitations in conformational sampling imposed by high energy barriers. Additionally, we used classic molecular dynamics simulations to describe nano- to microsecond flexibility and to estimate up to millisecond kinetics of captured conformational transitions. The methodology represents the antibodies as conformational ensembles and allows comprehensive analysis of structural diversity, thermodynamics of conformations and kinetics of structural transitions. Referring to the concept of conformational selection we investigated the link between promiscuity and flexibility of the antibodies' binding interfaces. The obtained detailed characterization of the binding interface clearly indicates a link between structural flexibility and binding promiscuity for this set of antibodies.

Deciphering evolution of immune recognition in antibodies

Background

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

Results

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

Conclusions

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

Electronic supplementary material

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

Antibody Epitope Specificity for dsDNA Phosphate Backbone Is an Intrinsic Property of the Heavy Chain Variable Germline Gene Segment Used

Analysis of protein sequences by the informational spectrum method (ISM) enables characterization of their specificity according to encoded information represented with defined frequency (F). Our previous data showed that F(0.367) is characteristic for variable heavy chain (VH) domains (a combination of variable (V), diversity (D) and joining (J) gene segments) of the anti-phosphocholine (PC) T15 antibodies and mostly dependent on the CDR2 region, a site for PC phosphate group binding. Because the T15 dsDNA-reactive U4 mutant also encodes F(0.367), we hypothesized that the same frequency may also be characteristic for anti-DNA antibodies. Data obtained from an analysis of 60 spontaneously produced anti-DNA antibody VH domain sequences supported our hypothesis only for antibodies, which use V gene segment in germline configuration, such as S57(VH31), MRL-DNA22, and VH11, members of the VH1 (J558) and VH7 (S107) gene families. The important finding is that out of seven V gene segments used by spontaneous anti-DNA antibodies, F(0.367) is only expressed by the germline configuration of these three V gene segments. The data suggest that antibody specificity for the phosphate group moiety delineated as F(0.367) is the intrinsic property of the V germline gene segments used, whereas paratope/epitope interaction with antigens bearing this epitope, such as PC or dsDNA, requires corresponding antibody VH conformation that is susceptible to somatic mutation(s).

ABO phenotype-protected reproduction based on human specific α1,2 L-fucosylation as explained by the Bombay type formation

The metabolic relationship between the formation of the ABO(H) blood group phenotype and human fertility is evident in the case of the (Oh) or Bombay blood type, which Charles Darwin would have interpreted as resulting from reduced male fertility in consanguinities, based on the history of his own family, the Darwin/Wedgwood Dynasty. The classic Bombay type occurs with the extremely rare, human-specific genotype (h/h; se/se), which (due to point mutations) does not encode fucosyltransferases 1(FUT1) and 2 (FUT2). These enzymes are the basis for ABO(H) phenotype formation on the cell surfaces and fucosylation of plasma proteins, involving neonatal immunoglobulin M (IgM). In the normal human blood group O(H), which is not protected by clonal selection with regard to environmental A/B immunization, the plasma contains a mixture of non-immune and adaptive anti-A/B reactive isoagglutinins, which in the O(h) Bombay type show extremely elevated levels, associated with decreased levels of fucosylation-dependent functional plasma proteins, suchs as the van Willebrand factor (vWF) and clotting factor VIII. In fact, while the involvement of adaptive immunoglobulins remains unknown, poor fucosylation may explain the polyreactivity in the Bombay type plasma, which exhibits pronounced complement-binding cross-reactive anti-A/Tn and anti-B IgM levels, with additional anti-H reactivity, acting over a wide range of temperatures, with an amplitude at 37 °C. This aggressive anti-glycan-reactive IgM molecule suggests the induction of ADCC (antibody-dependent) and/or complement-mediated cytotoxicity via overexpressed glycosidic bond sites against the embryogenic stem cell-to-germ cell transformation, which is characterized by fleeting appearances of A-like, developmental trans-species GalNAcα1-O-Ser/Thr-R glycan, also referred to as the Tn (T "nouvelle") antigen.

Position of human blood group O(H) and phenotype-determining enzymes in growth and infectious disease

The human ABO(H) blood group phenotypes arise from the evolutionarily oldest genetic system found in primate populations. While the blood group antigen A is considered the ancestral primordial structure, under the selective pressure of life‐threatening diseases blood group O(H) came to dominate as the most frequently occurring blood group worldwide. Non‐O(H) phenotypes demonstrate impaired formation of adaptive and innate immunoglobulin specificities due to clonal selection and phenotype formation in plasma proteins. Compared with individuals with blood group O(H), blood group A individuals not only have a significantly higher risk of developing certain types of cancer but also exhibit high susceptibility to malaria tropica or infection by Plasmodium falciparum. The phenotype‐determining blood group A glycotransferase(s), which affect the levels of anti‐A/Tn cross‐reactive immunoglobulins in phenotypic glycosidic accommodation, might also mediate adhesion and entry of the parasite to host cells via trans‐species O‐GalNAc glycosylation of abundantly expressed serine residues that arise throughout the parasite's life cycle, while excluding the possibility of antibody formation against the resulting hybrid Tn antigen. In contrast, human blood group O(H), lacking this enzyme, is indicated to confer a survival advantage regarding the overall risk of developing cancer, and individuals with this blood group rarely develop life‐threatening infections involving evolutionarily selective malaria strains.

Repertoire Analysis of Antibody CDR-H3 Loops Suggests Affinity Maturation Does Not Typically Result in Rigidification

Antibodies can rapidly evolve in specific response to antigens. Affinity maturation drives this evolution through cycles of mutation and selection leading to enhanced antibody specificity and affinity. Elucidating the biophysical mechanisms that underlie affinity maturation is fundamental to understanding B-cell immunity. An emergent hypothesis is that affinity maturation reduces the conformational flexibility of the antibody's antigen-binding paratope to minimize entropic losses incurred upon binding. In recent years, computational and experimental approaches have tested this hypothesis on a small number of antibodies, often observing a decrease in the flexibility of the complementarity determining region (CDR) loops that typically comprise the paratope and in particular the CDR-H3 loop, which contributes a plurality of antigen contacts. However, there were a few exceptions and previous studies were limited to a small handful of cases. Here, we determined the structural flexibility of the CDR-H3 loop for thousands of recent homology models of the human peripheral blood cell antibody repertoire using rigidity theory. We found no clear delineation in the flexibility of naïve and antigen-experienced antibodies. To account for possible sources of error, we additionally analyzed hundreds of human and mouse antibodies in the Protein Data Bank through both rigidity theory and B-factor analysis. By both metrics, we observed only a slight decrease in the CDR-H3 loop flexibility when comparing affinity matured antibodies to naïve antibodies, and the decrease was not as drastic as previously reported. Further analysis, incorporating molecular dynamics simulations, revealed a spectrum of changes in flexibility. Our results suggest that rigidification may be just one of many biophysical mechanisms for increasing affinity.

Integrating linear optimization with structural modeling to increase HIV neutralization breadth

Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.

In this article, we report a new approach for protein design, which combines traditional structural modeling with machine learning and integer programming. Using this method, we are able to design antibodies that are predicted to bind large panels of antigenically diverse HIV variants. The combination of methods from these fields allows us to surpass protein design limitations that have been seen up to this point. We predict that if we tested these modified antibodies against HIV variants they would have greater neutralization breadth than any antibodies seen to this point.

Antibody side chain conformations are position-dependent

Side chain prediction is an integral component of computational antibody design and structure prediction. Current antibody modelling tools use backbone-dependent rotamer libraries with conformations taken from general proteins. Here we present our antibody-specific rotamer library, where rotamers are binned according to their immunogenetics (IMGT) position, rather than their local backbone geometry. We find that for some amino acid types at certain positions, only a restricted number of side chain conformations are ever observed. Using this information, we are able to reduce the breadth of the rotamer sampling space. Based on our rotamer library, we built a side chain predictor, position-dependent antibody rotamer swapper (PEARS). On a blind test set of 95 antibody model structures, PEARS had the highest average χ₁ and χ1+2 accuracy (78.7% and 64.8%) compared to three leading backbone-dependent side chain predictors. Our use of IMGT position, rather than backbone ϕ/ψ, meant that PEARS was more robust to errors in the backbone of the model structure. PEARS also achieved the lowest number of side chain-side chain clashes. PEARS is freely available as a web application at http://opig.stats.ox.ac.uk/webapps/pears.

Towards a universal influenza vaccine: different approaches for one goal

Influenza virus infection is an ongoing health and economic burden causing epidemics with pandemic potential, affecting 5–30% of the global population annually, and is responsible for millions of hospitalizations and thousands of deaths each year. Annual influenza vaccination is the primary prophylactic countermeasure aimed at limiting influenza burden. However, the effectiveness of current influenza vaccines are limited because they only confer protective immunity when there is antigenic similarity between the selected vaccine strains and circulating influenza isolates. The major targets of the antibody response against influenza virus are the surface glycoprotein antigens hemagglutinin (HA) and neuraminidase (NA). Hypervariability of the amino acid sequences encoding HA and NA is largely responsible for epidemic and pandemic influenza outbreaks, and are the consequence of antigenic drift or shift, respectively. For this reason, if an antigenic mismatch exists between the current vaccine and circulating influenza isolates, vaccinated people may not be afforded complete protection. There is currently an unmet need to develop an effective “broadly-reactive” or “universal” influenza vaccine capable of conferring protection against both seasonal and newly emerging pre-pandemic strains. A number of novel influenza vaccine approaches are currently under evaluation. One approach is the elicitation of an immune response against the “Achille’s heel” of the virus, i.e. conserved viral proteins or protein regions shared amongst seasonal and pre-pandemic strains. Alternatively, other approaches aim toward eliciting a broader immune response capable of conferring protection against the diversity of currently circulating seasonal influenza strains.

In this review, the most promising under-development universal vaccine approaches are discussed with an emphasis on those targeting the HA glycoprotein. In particular, their strengths and potential short-comings are discussed. Ultimately, the upcoming clinical evaluation of these universal vaccine approaches will be fundamental to determine their effectiveness against preventing influenza virus infection and/or reducing transmission and disease severity.

Polyreactive natural antibodies in transplantation

PURPOSE OF REVIEW

Antibody-mediated rejection (ABMR), especially in its chronic manifestation, is increasingly recognized as a leading cause of late graft loss following solid organ transplantation. In recent years, autoantibodies have emerged as a significant component of the humoral response to allografts alongside anti-human leukocyte antigen antibodies. These include polyreactive antibodies also known as natural antibodies (Nabs) secreted by innate B cells. A hallmark of Nabs is their capacity to bind altered self such as oxidized lipids on apoptotic cells. This review provides an overview of these overlooked antibodies and their implication in the pathophysiology of ABMR.

RECENT FINDINGS

New evidence reported in the past few years support a contribution of immunoglobulin (Ig) G Nabs to ABMR. Serum IgG Nabs levels are significantly higher in patients with ABMR compared with control kidney transplant recipients with stable graft function. Pretransplant IgG Nabs are also associated with ABMR and late graft loss. IgG Nabs are almost exclusively of the IgG1 and IgG3 subclasses and have the capacity to activate complement.

SUMMARY

In conclusion, Nabs are important elements in host immune responses to solid organ grafts. The recent description of their implication in ABMR and late kidney graft loss warrants further investigation into their pathogenic potential.

Early ovariectomy reveals the germline encoding of natural anti-A- and Tn-cross-reactive immunoglobulin M (IgM) arising from developmental O-GalNAc glycosylations. (Germline-encoded natural anti-A/Tn cross-reactive IgM)

While native blood group A-like glycans have not been demonstrated in prokaryotic microorganisms as a source of human "natural" anti-A isoagglutinin production, and metazoan eukaryotic N-acetylgalactosamine O-glycosylation of serine or threonine residues (O-GalNAc-Ser/Thr-R) does not occur in bacteria, the O-GalNAc glycan-bearing ovarian glycolipids, discovered in C57BL/10 mice, are complementary to the syngeneic anti-A-reactive immunoglobulin M (IgM), which is not present in animals that have undergone ovariectomy prior to the onset of puberty. These mammalian ovarian glycolipids are complementary also to the anti-A/Tn cross-reactive Helix pomatia agglutinin (HPA), a molluscan defense protein, emerging from the coat proteins of fertilized eggs and reflecting the snail-intrinsic, reversible O-GalNAc glycosylations. The hexameric structure of this primitive invertebrate defense protein gives rise to speculation regarding an evolutionary relationship to the mammalian nonimmune, anti-A-reactive immunoglobulin M (IgM) molecule. Hypothetically, this molecule obtains its complementarity from the first step of protein glycosylations, initiated by GalNAc via reversible O-linkages to peptides displaying Ser/Thr motifs, whereas the subsequent transferase depletion completes germ cell maturation and cell renewal, associated with loss of glycosidic bonds and release of O-glycan-depleted proteins, such as complementary IgM revealing the structure of the volatilely expressed "lost" glycan carrier through germline Ser residues. Consequently, the evolutionary/developmental first glycosylations of proteins appear metabolically related or identical to that of the mucin-type, potentially "aberrant" monosaccharide GalNAcα1-O-Ser/Thr-R, also referred to as the Tn (T "nouvelle") antigen, and explain the anti-Tn cross-reactivity of human innate or "natural" anti-A-specific isoagglutinin and the pronounced occurrence of cross-reactive anti-Tn antibody in plasma from humans with histo-blood group O. In fact, A-allelic, phenotype-specific GalNAc glycosylation of plasma proteins does not occur in human blood group O, affecting anti-Tn antibody levels, which may function as a growth regulator that contributes to a potential survival advantage of this group in the overall risk of developing cancer when compared with non-O blood groups.

Polyspecificity of Anti-lipid A Antibodies and Its Relevance to the Development of Autoimmunity

The process of natural selection favours germ-line gene segments that encode CDRs that have the ability to recognize a range of structurally related antigens. This presents an immunological advantage to the host, as it can confer protection against a common pathogen and still cope with new or changing antigens. Cross-reactive and polyspecific antibodies also play a central role in autoimmune responses, and a link has been shown to exist between auto-reactive B cells and certain bacterial infections. Bacterial DNA, lipids, and carbohydrates have been implicated in the progression of autoimmune diseases such as systemic lupus erythematosus. As well, reports of anti-lipid A antibody polyspecificity towards single-stranded DNA together with the observed sequence homology amongst isolated auto- and anti-lipid A antibodies has prompted further study of this phenomenon. Though the lipid A epitope appears cryptic during Gram-negative bacterial infection, there have been several reported instances of lipid A-specific antibodies isolated from human sera, some of which have exhibited polyspecificity for single stranded DNA. In such cases, the breakdown of negative selection through polyspecificity can have the unfortunate consequence of autoimmune disease. This review summarizes current knowledge regarding such antibodies and emphasizes the features of S1-15, A6, and S55-5, anti-lipid A antibodies whose structures were recently determined by X-ray crystallography.

Human B-cell memory is shaped by age- and tissue-specific T-independent and GC-dependent events

Switched and IgM memory B cells execute different and noninterchangeable functions. We studied memory B cells in children of different ages, in peripheral blood and spleen and compared them with those of children born asplenic or unable to build germinal centers. We show that, whereas switched memory B cells are mostly generated in the germinal centers at all ages, IgM memory B cells can be distinct in three types with different developmental history. Innate IgM memory B cells, the largest pool in infants, are generated in the spleen by a germinal center-independent mechanism. With age, if the spleen is present and germinal centers are functional, innate IgM memory B cells are remodelled and accumulate somatic mutations. The third type of IgM memory B cell is a by-product of the germinal center reaction. Our data suggest that the B-cell memory developmental program is implemented during the first 5-6 years of life.

Protocols for Molecular Modeling with Rosetta3 and RosettaScripts

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987–2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

Computationally Designed Bispecific Antibodies using Negative State Repertoires

A challenge in the structure-based design of specificity is modeling the negative states, i.e., the complexes that you do not want to form. This is a difficult problem because mutations predicted to destabilize the negative state might be accommodated by small conformational rearrangements. To overcome this challenge, we employ an iterative strategy that cycles between sequence design and protein docking in order to build up an ensemble of alternative negative state conformations for use in specificity prediction. We have applied our technique to the design of heterodimeric CH3 interfaces in the Fc region of antibodies. Combining computationally and rationally designed mutations produced unique designs with heterodimer purities greater than 90%. Asymmetric Fc crystallization was able to resolve the interface mutations; the heterodimer structures confirmed that the interfaces formed as designed. With these CH3 mutations, and those made at the heavy-/light-chain interface, we demonstrate one-step synthesis of four fully IgG-bispecific antibodies.

A subset of AID-dependent B-1a cells initiates hypersensitivity and pneumococcal pneumonia resistance

We propose that there is a special B-1a B cell subset ("sB-1a" cells) that mediates linked processes very early after immunization to initiate cutaneous contact sensitivity (CS), delayed-type hypersensitivity (DTH), and immune resistance to pneumococcal pneumonia. Our published data indicate that in CS and DTH, these initiating processes are required for elicitation of the delayed onset and late-occurring classical T cell-mediated responses. sB-1a cells resemble memory B2 cells, as they are stimulated within 1 h of immunization and depend on T helper cytokines-uniquely IL-4 from hepatic iNKT cells--for activation and rapid migration from the peritoneal cavity to the spleen to secrete IgM antibody (Ab) and Ab-derived free light chains (FLCs) by only 1 day after immunization. Unlike conventional B-1a (cB-1a) cell-produced IgM natural Ab, IgM Ab produced by sB-1a cells has high Ag affinity owing to immunoglobulin V-region mutations induced by activation-induced cytidine deaminase (AID). The dominant cB-1a cells are increased in immunized AID-deficient mice but do not mediate initiation, CS, or pneumonia resistance because natural Ab has relatively low Ag affinity because of unmutated germ-line V regions. In CS and DTH, sB-1a IgM Ag affinity is sufficiently high to mediate complement activation for generation of C5a that, together with vasoactive mediators such as TNF-α released by FLC-sensitized mast cells, activate local endothelium for extravascular recruitment of effector T cells. We conclude by discussing the possibility of functional sB-1 cells in humans.

Deciphering the human immunome

Technological advances in next-generation DNA sequencing offer great potential to probe the human immune system. On 3 April 2015, leading immunologists and bioinformatics scientists met to consider how best to harness these advances for decoding the human immunome.

Vaccine-elicited antibody that neutralizes H5N1 influenza and variants binds the receptor site and polymorphic sites

Antigenic drift of circulating seasonal influenza viruses necessitates an international vaccine effort to reduce the impact on human health. A critical feature of the seasonal vaccine is that it stimulates an already primed immune system to diversify memory B cells to recognize closely related, but antigenically distinct, influenza glycoproteins (hemagglutinins). Influenza pandemics arise when hemagglutinins to which no preexisting adaptive immunity exists acquire the capacity to infect humans. Hemagglutinin 5 is one subtype to which little preexisting immunity exists and is only a few acquired mutations away from the ability to transmit efficiently between ferrets, and possibly humans. Here, we describe the structure and molecular mechanism of neutralization by H5.3, a vaccine-elicited antibody that neutralizes hemagglutinin 5 viruses and variants with expanded host range. H5.3 binds in the receptor-binding site, forming contacts that recapitulate many of the sialic acid interactions, as well as multiple peripheral interactions, yet is not sensitive to mutations that alter sialic acid binding. H5.3 is highly specific for a subset of H5 strains, and this specificity arises from interactions to the periphery of the receptor-binding site. H5.3 is also extremely potent, despite retaining germ line-like conformational flexibility.

Biological messiness vs. biological genius: Mechanistic aspects and roles of protein promiscuity

In contrast to the traditional biological paradigms focused on 'specificity', recent research and theoretical efforts have focused on functional 'promiscuity' exhibited by proteins and enzymes in many biological settings, including enzymatic detoxication, steroid biochemistry, signal transduction and immune responses. In addition, divergent evolutionary processes are apparently facilitated by random mutations that yield promiscuous enzyme intermediates. The intermediates, in turn, provide opportunities for further evolution to optimize new functions from existing protein scaffolds. In some cases, promiscuity may simply represent the inherent plasticity of proteins resulting from their polymeric nature with distributed conformational ensembles. Enzymes or proteins that bind or metabolize noncognate substrates create 'messiness' or noise in the systems they contribute to. With our increasing awareness of the frequency of these promiscuous behaviors it becomes interesting and important to understand the molecular bases for promiscuous behavior and to distinguish between evolutionarily selected promiscuity and evolutionarily tolerated messiness. This review provides an overview of current understanding of these aspects of protein biochemistry and enzymology.

Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences

Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD) paradigm. Multi-specificity design (MSD), on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON). The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain) an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.

Rigidity Emerges during Antibody Evolution in Three Distinct Antibody Systems: Evidence from QSFR Analysis of Fab Fragments

The effects of somatic mutations that transform polyspecific germline (GL) antibodies to affinity mature (AM) antibodies with monospecificity are compared among three GL-AM Fab pairs. In particular, changes in conformational flexibility are assessed using a Distance Constraint Model (DCM). We have previously established that the DCM can be robustly applied across a series of antibody fragments (VL to Fab), and subsequently, the DCM was combined with molecular dynamics (MD) simulations to similarly characterize five thermostabilizing scFv mutants. The DCM is an ensemble based statistical mechanical approach that accounts for enthalpy/entropy compensation due to network rigidity, which has been quite successful in elucidating conformational flexibility and Quantitative Stability/Flexibility Relationships (QSFR) in proteins. Applied to three disparate antibody systems changes in QSFR quantities indicate that the VH domain is typically rigidified, whereas the VL domain and CDR L2 loop become more flexible during affinity maturation. The increase in CDR H3 loop rigidity is consistent with other studies in the literature. The redistribution of conformational flexibility is largely controlled by nonspecific changes in the H-bond network, although certain Arg to Asp salt bridges create highly localized rigidity increases. Taken together, these results reveal an intricate flexibility/rigidity response that accompanies affinity maturation.

Antibodies are protective proteins used by the immune system to recognize and neutralize foreign objects through interactions with a specific part of the target, called an antigen. Antibody structures are Y-shaped, contain multiple protein chains, and include two antigen-binding sites. The binding sites are located at the end of the Fab fragments, which are the upward facing arms of the Y-structure. The Fab fragments maintain binding affinity by themselves, and are thus often used as surrogates to student antibody-antigen interactions. High affinity antibodies are produced during the course of an immune response by successive mutations to germline gene-encoded antibodies. Germline antibodies are more likely to be polyspecific, whereas the affinity maturation process yields monoclonal antibodies that bind specifically to the target antigen. In this work, we use a computational Distance Constraint Model to characterize how mechanical properties change as three disparate germline antibodies are converted to affinity mature. Our results reveal a rich set of mechanical responses throughout the Fab structure. Nevertheless, increased rigidity in the VH domain is consistently observed, which is consistent with the transition from polyspecificity to monospecificity. That is, flexible antibody structures are able to recognize multiple antigens, while increased affinity and specificity is achieved—in part—by structural rigidification.

Redesigned HIV antibodies exhibit enhanced neutralizing potency and breadth

Several HIV envelope-targeting (Env-targeting) antibodies with broad and potent neutralizing activity have been identified and shown to have unusual features. Of these, the PG9 antibody has a long heavy chain complementarity determining region 3 (HCDR3) and possesses unique structural elements that interact with protein and glycan features of the HIV Env glycoprotein. Here, we used the Rosetta software suite to design variants of the PG9 antibody HCDR3 loop with the goal of identifying variants with increased potency and breadth of neutralization for diverse HIV strains. One variant, designated PG9_N100(F)Y, possessed increased potency and was able to neutralize a diverse set of PG9-resistant HIV strains, including those lacking the Env N160 glycan, which is critical for PG9 binding. An atomic resolution structure of the PG9_N100(F)Y fragment antigen binding (Fab) confirmed that the mutated residue retains the paratope surface when compared with WT PG9. Differential scanning calorimetry experiments revealed that the mutation caused a modest increase in thermodynamic stability of the Fab, a feature predicted by the computational model. Our findings suggest that thermodynamic stabilization of the long HCDR3 in its active conformation is responsible for the increased potency of PG9_N100(F)Y, and strategies aimed at stabilizing this region in other HIV antibodies could become an important approach to in silico optimization of antibodies.