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Artificial Intelligence (AI) techniques have made great advances in assisting antibody design. However, antibody design still heavily relies on isolating antigen-specific antibodies from serum, which is a resource-intensive and time-consuming process. To address this issue, we propose a Pre-trained Antibody generative large Language Model (PALM-H3) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 (CDRH3) with desired antigen-binding specificity, reducing the reliance on natural antibodies. We also build a high-precision model antigen-antibody binder (A2binder) that pairs antigen epitope sequences with antibody sequences to predict binding specificity and affinity. PALM-H3-generated antibodies exhibit binding ability to SARS-CoV-2 antigens, including the emerging XBB variant, as confirmed through in-silico analysis and in-vitro assays. The in-vitro assays validate that PALM-H3-generated antibodies achieve high binding affinity and potent neutralization capability against spike proteins of SARS-CoV-2 wild-type, Alpha, Delta, and the emerging XBB variant. Meanwhile, A2binder demonstrates exceptional predictive performance on binding specificity for various epitopes and variants. Furthermore, by incorporating the attention mechanism inherent in the Roformer architecture into the PALM-H3 model, we improve its interpretability, providing crucial insights into the fundamental principles of antibody design. Antibody design still heavily relies on isolating antigen-specific antibodies from serum. Here the authors report a Pre-trained Antibody generative large Language Model (PALM-H3) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 with desired antigen-binding specificity.

The vertebrate adaptive immune system modifies the genome of individual B cells to encode antibodies that bind particular antigens 1 . In most mammals, antibodies are composed of heavy and light chains that are generated sequentially by recombination of V, D (for heavy chains), J and C gene segments. Each chain contains three complementarity-determining regions (CDR1–CDR3), which contribute to antigen specificity. Certain heavy and light chains are preferred for particular antigens 2 – 22 . Here we consider pairs of B cells that share the same heavy chain V gene and CDRH3 amino acid sequence and were isolated from different donors, also known as public clonotypes 23 , 24 . We show that for naive antibodies (those not yet adapted to antigens), the probability that they use the same light chain V gene is around 10%, whereas for memory (functional) antibodies, it is around 80%, even if only one cell per clonotype is used. This property of functional antibodies is a phenomenon that we call light chain coherence. We also observe this phenomenon when similar heavy chains recur within a donor. Thus, although naive antibodies seem to recur by chance, the recurrence of functional antibodies reveals surprising constraint and determinism in the processes of V(D)J recombination and immune selection. For most functional antibodies, the heavy chain determines the light chain.  Among naturally occurring antibodies that have adapted to antigen, those with similar heavy chains usually have similar light chains.

Therapeutic mAbs must not only bind to their target but must also be free from “developability issues” such as poor stability or high levels of aggregation. While small-molecule drug discovery benefits from Lipinski’s rule of five to guide the selection of molecules with appropriate biophysical properties, there is currently no in silico analog for antibody design. Here, we model the variable domain structures of a large set of post-phase-I clinical-stage antibody therapeutics (CSTs) and calculate in silico metrics to estimate their typical properties. In each case, we contextualize the CST distribution against a snapshot of the human antibody gene repertoire. We describe guideline values for five metrics thought to be implicated in poor developability: the total length of the complementarity-determining regions (CDRs), the extent and magnitude of surface hydrophobicity, positive charge and negative charge in the CDRs, and asymmetry in the net heavy- and light-chain surface charges. The guideline cutoffs for each property were derived from the values seen in CSTs, and a flagging system is proposed to identify nonconforming candidates. On two mAb drug discovery sets, we were able to selectively highlight sequences with developability issues. We make available the Therapeutic Antibody Profiler (TAP), a computational tool that builds downloadable homology models of variable domain sequences, tests them against our five developability guidelines, and reports potential sequence liabilities and canonical forms. TAP is freely available at opig.stats.ox.ac.uk/webapps/sabdab-sabpred/TAP.php.

Defects in T cell receptor (TCR) repertoire are proposed to predispose to autoimmunity. Here we show, by analyzing >2 × 10 8 TCRB sequences of circulating naive, central memory, regulatory and stem cell-like memory CD4 + T cell subsets from patients with type 1 diabetes and healthy donors, that patients have shorter TCRB complementarity-determining region 3s (CDR3), in all cell subsets, introduced by increased deletions/reduced insertions during VDJ rearrangement. High frequency of short CDR3s is also observed in unproductive TCRB sequences, which are not subjected to thymic culling, suggesting that the shorter CDR3s arise independently of positive/negative selection. Moreover, TCRB CDR3 clonotypes expressed by autoantigen-specific CD4 + T cells are shorter compared with anti-viral T cells, and with those from healthy donors. Thus, early events in thymic T cell development and repertoire generation are abnormal in type 1 diabetes, which suggest that short CDR3s increase the potential for self-recognition, conferring heightened risk of autoimmune disease. T cell receptors are generated by somatic gene recombination, and are normally selected against autoreactivity. Here the authors show that CD4 T cells from patients with autoimmune type 1 diabetes have shorter TCRβ sequences, broader repertoire diversity, and more repertoire sharing than those from healthy individuals.

Tumor-infiltrating B cells are an important component in the microenvironment but have unclear anti-tumor effects. We enhanced our previous computational algorithm TRUST to extract the B cell immunoglobulin hypervariable regions from bulk tumor RNA-sequencing data. TRUST assembled more than 30 million complementarity-determining region 3 sequences of the B cell heavy chain (IgH) from The Cancer Genome Atlas. Widespread B cell clonal expansions and immunoglobulin subclass switch events were observed in diverse human cancers. Prevalent somatic copy number alterations in the MICA and MICB genes related to antibody-dependent cell-mediated cytotoxicity were identified in tumors with elevated B cell activity. The IgG3–1 subclass switch interacts with B cell–receptor affinity maturation and defects in the antibody-dependent cell-mediated cytotoxicity pathway. Comprehensive pancancer analyses of tumor-infiltrating B cell–receptor repertoires identified novel tumor immune evasion mechanisms through genetic alterations. The IgH sequences identified here are potentially useful resources for future development of immunotherapies. This comprehensive pancancer analysis of RNA-sequencing data from bulk tumors defines the landscape of tumor-infiltrating B cell–receptor repertoires and highlights new mechanisms of tumor immune evasion through genetic alterations.

Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called “ideal” folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes.

The development of recombinant antibody binders against phosphorothioate-modified antisense oligonucleotides (PS-ASOs) remains challenging due to the highly polyanionic character and structural flexibility of the phosphorothioate backbone. Here, we applied a next-generation sequencing (NGS)-guided phage display strategy to determine whether selection against PS-modified ASOs induces reproducible repertoire remodeling and the emergence of shared CDR3 physicochemical signatures associated with PS-ASO recognition. Two independent two-round phage display biopanning strategies against biotinylated PS-ASO targets were coupled to targeted amplicon sequencing of VH and VL FR3-CDR3-FR4 regions on the Illumina MiSeq platform. CDR3 clonotypes were reconstructed using a dedicated bioinformatic pipeline including quality filtering, read merging, in-frame translation, clonotype counting, CPM normalization, enrichment analysis, and physicochemical descriptor profiling. Representative enriched scFv clones were further evaluated by ELISA-based binding and competition assays and by fluorescence microscopy in ASO-treated cells. Deep sequencing revealed a marked reduction in repertoire diversity from Round 1 to Round 2, associated with reproducible clonal dominance across independent selection strategies. These changes were already evident at early stages of selection. A shared enriched set of 113 CDR3-VH clonotypes was identified and displayed a defined physicochemical profile, including increased positive charge, recurrent aromatic residue patterns, constrained CDR3-VH length distribution, higher theoretical pI, and reduced hydrophobicity. Representative functional assays further supported the relevance of this signature: among the selected recombinant scFv clones, 12F2 showed preferential binding to both PS1-ASO and PS2-ASO, with reduced reactivity toward the phosphodiester-backbone oligonucleotide used as control. In ASO-treated cells, 12F2 produced a detectable intracellular signal after PS-ASO transfection, whereas PO-ASO-treated cells showed absent or nearly absent signal. These results define an NGS-guided framework for identifying early-stage repertoire focusing and physicochemical signatures associated with recognition of modified nucleic acid backbones. The common property-level features suggest convergent binding solutions compatible with recognition of phosphorothioate-associated molecular features, supporting the rational prioritization of candidate binders against challenging polyanionic targets.

Immune recognition of protein antigens relies on the combined interaction of multiple antibody loops, which provide a fairly large footprint and constrain the size and shape of protein surfaces that can be targeted. Single protein loops can mediate extremely high-affinity binding, but it is unclear whether such a mechanism is available to antibodies. Here we report the isolation and characterization of an antibody called C05, which neutralizes strains from multiple subtypes of influenza A virus, including H1, H2 and H3. X-ray and electron microscopy structures show that C05 recognizes conserved elements of the receptor-binding site on the haemagglutinin surface glycoprotein. Recognition of the haemagglutinin receptor-binding site is dominated by a single heavy-chain complementarity-determining region 3 loop, with minor contacts from heavy-chain complementarity-determining region 1, and is sufficient to achieve nanomolar binding with a minimal footprint. Thus, binding predominantly with a single loop can allow antibodies to target small, conserved functional sites on otherwise hypervariable antigens. The crystal structure of an influenza antibody that recognizes a small, conserved site in the variable receptor-binding domain of HA is described; this antibody shows broad neutralization across multiple subtypes of influenza A virus through an antibody–antigen interaction dominated by a single heavy-chain complementarity-determining region 3 loop. An effective anti-influenza antibody This manuscript reports the identification and structural characterization of a novel anti-influenza antibody, C05, that recognizes a small conserved site in the variable receptor-binding domain of haemagglutinin. The antibody achieves broad neutralization by the insertion of a single loop of the heavy-chain complementarity-determining region 3 into the small conserved site amplified by the avidity of additional binding interactions. This finding highlights loop insertion into the receptor-binding pocket of haemagglutinin as a possible strategy to achieve broad neutralization of influenza by vaccines and therapeutic antibodies.

Since the COVID-19 pandemic onset, the antibody response to SARS-CoV-2 has been extensively characterized. Antibodies to the receptor binding domain (RBD) on the spike protein are frequently encoded by IGHV3-53/3-66 with a short complementarity-determining region (CDR) H3. Germline-encoded sequence motifs in heavy chain CDRs H1 and H2 have a major function, but whether any common motifs are present in CDR H3, which is often critical for binding specificity, is not clear. Here, we identify two public clonotypes of IGHV3-53/3-66 RBD antibodies with a 9-residue CDR H3 that pair with different light chains. Distinct sequence motifs on CDR H3 are present in the two public clonotypes that seem to be related to differential light chain pairing. Additionally, we show that Y58F is a common somatic hypermutation that results in increased binding affinity of IGHV3-53/3-66 RBD antibodies with a short CDR H3. These results advance understanding of the antibody response to SARS-CoV-2. Public antibody clonotypes that recognize SARS-CoV-2 spike protein are important for protection against COVID-19. Here, the authors characterize sequence motifs in the heavy chain complementarity-determining region (CDR) H3s of two public clonotypes and their association with light chain identity.

Despite the fact that HPV vaccines are likely to lead to a significant reduction in cervical cancer occurrence, there remains cervical cancer incidence independent of the vaccine and cervical cancer arising in the absence of vaccination. Thus, continued efforts are needed to address the potential parameters of cervical cancer that could impact therapy and could lead to additional ways of reducing cervical cancer death rates. Adaptive immune receptor recombinations were obtained from the cancer genome atlas (TCGA) cervical cancer database through tumor exome and RNAseq files as well as from the independent Cancer Genome Characterization Initiative (CGCI) cervical cancer dataset. T-cell receptor (TCR) complementarity determining region-3’s (CDR3s) were then assessed, based on chemical complementarity to human papillomavirus (HPV) T-cell epitopes. Results indicated increased overall survival probabilities consistently across the three TCR datasets with TCR CDR3 chemical complementarity to the same HPV epitopes, specifically immune epitope database (IEDB) designations: IEDB-1625373, IEDB-174148, and IEDB-110943. Among other potential applications of these results, the results may indicate HPV epitopes that could be useful targets for immunotherapy.