Backbone flexibility of CDR3 and immune recognition of antigens

Distinct types of VHHs in Alpaca

Introduction

VHHs (VH of heavy-chain-only antibodies) represent a unique alternative to Q7 conventional antibodies because of their smaller size, comparable binding affinity and biophysical properties.

Method

In this study, we systematically analyzed VHH NGS sequences from 22 Alpacas and structure data from public database.

Results

VHHs in Alpaca can be grouped into five main types with multiple distinct sequence and structure features. Based on the existence of hallmark residues in FR2 region, VHHs can be classified into two groups: nonclassical VHHs (without hallmark residues) and classical VHHs (with hallmark residues). Based on VHH hallmark residues at 42 position (IMGT numbering, FR2 region) and number of cysteines, we found that Alpaca classical VHHs can be further separated into three main types: F_C2 VHHs with F (phenylalanine) at position 42 and having 2 cysteines within sequences, Y_C2 VHHs with Y (tyrosine) at position 42 and having 2 cysteines, and F_C4 with F at position 42 and having 4 cysteines. Non-classical VHHs can be further separated into 2 types based on germlines mapped: N_V3 for VHHs mapped to V3 germlines and N_V4 for V4 germlines. Based on whether FR2 residues are involved in binding, two kinds of paratopes can be identified. Different types of VHHs showed distinct associations with these two paratopes and displayed significant differences in paratope size, residue usage and other structure features.

Discussion

Such results will have significant implications in VHH discovery, engine e ring, and design for innovative therapeutics.

Proscan: a structure-based proline design web server

The ability to control protein conformations and dynamics through structure-based design has been useful in various scenarios, including engineering of viral antigens for vaccines. One effective design strategy is the substitution of residues to proline amino acids, which due to its unique cyclic side chain can favor and rigidify key backbone conformations. To provide the community with a means to readily identify and explore proline designs for target proteins of interest, we developed the Proscan web server. Proscan provides assessment of backbone angles, energetic and deep learning-based favorability scores, and other parameters for proline substitutions at each position of an input structure, along with interactive visualization of backbone angles and candidate substitution sites on structures. It identifies known favorable proline substitutions for viral antigens, and was benchmarked against datasets of proline substitution stability effects from deep mutational scanning and thermodynamic measurements. This tool can enable researchers to identify and prioritize designs for prospective vaccine antigen targets, or other designs to favor stability of key protein conformations. Proscan is available at: https://proscan.ibbr.umd.edu.

Ligand-Directed GPCR Antibody Discovery

Developing affinity reagents recognizing and modulating G-protein coupled receptors (GPCR) function by traditional animal immunization or in vitro screening methods is challenging. Some anti-GPCR antibodies exist on the market, but the success rate of development is still poor compared with antibodies targeting soluble or peripherally anchored proteins. More importantly, most of these antibodies do not modulate GPCR function. The current pipeline for antibody development primarily screens for overall affinity rather than functional epitope recognition. We developed a new strategy utilizing natural ligand affinity to generate a library of antibody variants with an inherent bias toward the active site of the GPCR. Instead of using phage libraries displaying antibodies with random CDR sequences at polymorphism sites observed in natural immune repertoire sequences, we generated focused antibody libraries with a natural ligand encoded within or conjugated to one of the CDRs or the N-terminus. To tailor antibody binding to the active site, we limited the sequence randomization of the antibody in regions holstering the ligand while leaving the ligand-carrying part unaltered in the first round of randomization. With hits from the successful first round, the second round of randomization of the ligand-carrying part was then performed to eliminate the bias of the ligand. Based on our results on three different GPCR targets, the proposed pipeline will enable the rapid generation of functional antibodies (both agonists and antagonists) against high-value targets with poor function epitope exposures including GPCR, channels, transporters as well as cell surface targets whose binding site is heavily masked by glycosylation.

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83-98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

Validation of Methods to Assess the Immunoglobulin Gene Repertoire in Tissues Obtained from Mice on the International Space Station

Spaceflight is known to affect immune cell populations. In particular, splenic B-cell numbers decrease during spaceflight and in ground-based physiological models. Although antibody isotype changes have been assessed during and after spaceflight, an extensive characterization of the impact of spaceflight on antibody composition has not been conducted in mice. Next Generation Sequencing and bioinformatic tools are now available to assess antibody repertoires. We can now identify immunoglobulin gene-segment usage, junctional regions, and modifications that contribute to specificity and diversity. Due to limitations on the International Space Station, alternate sample collection and storage methods must be employed. Our group compared Illumina MiSeq® sequencing data from multiple sample preparation methods in normal C57Bl/6J mice to validate that sample preparation and storage would not bias the outcome of antibody repertoire characterization. In this report, we also compared sequencing techniques and a bioinformatic workflow on the data output when we assessed the IgH and Igκ variable gene usage. Our bioinformatic workflow has been optimized for Illumina HiSeq® and MiSeq® datasets, and is designed specifically to reduce bias, capture the most information from Ig sequences, and produce a data set that provides other data mining options.

Tuning antiviral CD8 T-cell response via proline-altered peptide ligand vaccination

Viral escape from CD8+ cytotoxic T lymphocyte responses correlates with disease progression and represents a significant challenge for vaccination. Here, we demonstrate that CD8+ T cell recognition of the naturally occurring MHC-I-restricted LCMV-associated immune escape variant Y4F is restored following vaccination with a proline-altered peptide ligand (APL). The APL increases MHC/peptide (pMHC) complex stability, rigidifies the peptide and facilitates T cell receptor (TCR) recognition through reduced entropy costs. Structural analyses of pMHC complexes before and after TCR binding, combined with biophysical analyses, revealed that although the TCR binds similarly to all complexes, the p3P modification alters the conformations of a very limited amount of specific MHC and peptide residues, facilitating efficient TCR recognition. This approach can be easily introduced in peptides restricted to other MHC alleles, and can be combined with currently available and future vaccination protocols in order to prevent viral immune escape.

The Immunogenicity of a Proline-Substituted Altered Peptide Ligand toward the Cancer-Associated TEIPP Neoepitope Trh4 Is Unrelated to Complex Stability

Human cancers frequently display defects in Ag processing and presentation allowing for immune evasion, and they therefore constitute a significant challenge for T cell-based immunotherapy. We have previously demonstrated that the antigenicity of tumor-associated Ags can be significantly enhanced through unconventional residue modifications as a novel tool for MHC class I (MHC-I)-based immunotherapy approaches. We have also previously identified a novel category of cancer neo-epitopes, that is, T cell epitopes associated with impaired peptide processing (TEIPP), that are selectively presented by MHC-I on cells lacking the peptide transporter TAP. In this study, we demonstrate that substitution of the nonanchoring position 3 into a proline residue of the first identified TEIPP peptide, the murine Trh4, results in significantly enhanced recognition by antitumor CTLs toward the wild-type epitope. Although higher immunogenicity has in most cases been associated with increased MHC/peptide complex stability, our results demonstrate that the overall stability of H-2D^b in complex with the highly immunogenic altered peptide ligand Trh4-p3P is significantly reduced compared with wild-type H-2D^b/Trh4. Comparison of the crystal structures of the H-2D^b/Trh4-p3P and H-2D^b/Trh4 complexes revealed that the conformation of the nonconventional methionine anchor residue p5M is altered, deleting its capacity to form adequate sulfur-π interactions with H-2D^b residues, thus reducing the overall longevity of the complex. Collectively, our results indicate that vaccination with Thr4-p3P significantly enhances T cell recognition of targets presenting the wild-type TEIPP epitope and that higher immunogenicity is not necessarily directly related to MHC/peptide complex stability, opening for the possibility to design novel peptide vaccines with reduced MHC/peptide complex stability.

Molecular Basis for Necitumumab Inhibition of EGFR Variants Associated with Acquired Cetuximab Resistance

Acquired resistance to cetuximab, an antibody that targets the EGFR, impacts clinical benefit in head and neck, and colorectal cancers. One of the mechanisms of resistance to cetuximab is the acquisition of mutations that map to the cetuximab epitope on EGFR and prevent drug binding. We find that necitumumab, another FDA-approved EGFR antibody, can bind to EGFR that harbors the most common cetuximab-resistant substitution, S468R (or S492R, depending on the amino acid numbering system). We determined an X-ray crystal structure to 2.8 Å resolution of the necitumumab Fab bound to an S468R variant of EGFR domain III. The arginine is accommodated in a large, preexisting cavity in the necitumumab paratope. We predict that this paratope shape will be permissive to other epitope substitutions, and show that necitumumab binds to most cetuximab- and panitumumab-resistant EGFR variants. We find that a simple computational approach can predict with high success which EGFR epitope substitutions abrogate antibody binding. This computational method will be valuable to determine whether necitumumab will bind to EGFR as new epitope resistance variants are identified. This method could also be useful for rapid evaluation of the effect on binding of alterations in other antibody/antigen interfaces. Together, these data suggest that necitumumab may be active in patients who are resistant to cetuximab or panitumumab through EGFR epitope mutation. Furthermore, our analysis leads us to speculate that antibodies with large paratope cavities may be less susceptible to resistance due to mutations mapping to the antigen epitope. Mol Cancer Ther; 17(2); 521-31. ©2017 AACR.

A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces

T-cell receptors (TCRs) have emerged as a new class of therapeutics, most prominently for cancer where they are the key components of new cellular therapies as well as soluble biologics. Many studies have generated high affinity TCRs in order to enhance sensitivity. Recent outcomes, however, have suggested that fine manipulation of TCR binding, with an emphasis on specificity may be more valuable than large affinity increments. Structure-guided design is ideally suited for this role, and here we studied the generality of structure-guided design as applied to TCRs. We found that a previous approach, which successfully optimized the binding of a therapeutic TCR, had poor accuracy when applied to a broader set of TCR interfaces. We thus sought to develop a more general purpose TCR design framework. After assembling a large dataset of experimental data spanning multiple interfaces, we trained a new scoring function that accounted for unique features of each interface. Together with other improvements, such as explicit inclusion of molecular flexibility, this permitted the design new affinity-enhancing mutations in multiple TCRs, including those not used in training. Our approach also captured the impacts of mutations and substitutions in the peptide/MHC ligand, and recapitulated recent findings regarding TCR specificity, indicating utility in more general mutational scanning of TCR-pMHC interfaces.

Differential utilization of binding loop flexibility in T cell receptor ligand selection and cross-reactivity

Complementarity determining region (CDR) loop flexibility has been suggested to play an important role in the selection and binding of ligands by T cell receptors (TCRs) of the cellular immune system. However, questions remain regarding the role of loop motion in TCR binding, and crystallographic structures have raised questions about the extent to which generalizations can be made. Here we studied the flexibility of two structurally well characterized αβ TCRs, A6 and DMF5. We found that the two receptors utilize loop motion very differently in ligand binding and cross-reactivity. While the loops of A6 move rapidly in an uncorrelated fashion, those of DMF5 are substantially less mobile. Accordingly, the mechanisms of binding and cross-reactivity are very different between the two TCRs: whereas A6 relies on conformational selection to select and bind different ligands, DMF5 uses a more rigid, permissive architecture with greater reliance on slower motions or induced-fit. In addition to binding site flexibility, we also explored whether ligand-binding resulted in common dynamical changes in A6 and DMF5 that could contribute to TCR triggering. Although binding-linked motional changes propagated throughout both receptors, no common features were observed, suggesting that changes in nanosecond-level TCR structural dynamics do not contribute to T cell signaling.

Platform for high-throughput antibody selection using synthetically-designed antibody libraries

Synthetic humanized antibody libraries are frequently generated by random incorporation of changes at multiple positions in the antibody hypervariable regions. Although these libraries have very large theoretical diversities (>10(20)), the practical diversity that can be achieved by transformation of Escherichia coli is limited to about 10(10). To constrain the practical diversity to sequences that more closely mimic the diversity of natural human antibodies, we generated a scFv phage library using entirely pre-defined complementarity determining regions (CDR). We have used this library to select for novel antibodies against four human protein targets and demonstrate that identification of enriched sequences at each of the six CDRs in early selection rounds can be used to reconstruct a consensus antibody with selectivity for the target.

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.