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.

BACKGROUND: Vertebrate immune systems generate diverse repertoires of antibodies capable of mediating response to a variety of antigens. Next generation sequencing methods provide unique approaches to a number of immuno-based research areas including antibody discovery and engineering, disease surveillance, and host immune response to vaccines. In particular, single-molecule circular consensus sequencing permits the sequencing of antibody repertoires at previously unattainable depths of coverage and accuracy. We approached the bovine immunoglobulin G (IgG) repertoire with the objective of characterizing diversity of expressed IgG transcripts. Here we present single-molecule real-time sequencing data of expressed IgG heavy-chain repertoires of four individual cattle. We describe the diversity observed within antigen binding regions and visualize this diversity using a network-based approach.
RESULTS: We generated 49,945 high quality cDNA sequences, each spanning the entire IgG variable region from four Bos taurus calves. From these sequences we identified 49,521 antigen binding regions using the automated Paratome web server. Approximately 9% of all unique complementarity determining 2 (CDR2) sequences were of variable lengths. A bimodal distribution of unique CDR3 sequence lengths was observed, with common lengths of 5-6 and 21-25 amino acids. The average number of cysteine residues in CDR3s increased with CDR3 length and we observed that cysteine residues were centrally located in CDR3s. We identified 19 extremely long CDR3 sequences (up to 62 amino acids in length) within IgG transcripts. Network analyses revealed distinct patterns among the expressed IgG antigen binding repertoires of the examined individuals.
CONCLUSIONS: We utilized circular consensus sequencing technology to provide baseline data of the expressed bovine IgG repertoire that can be used for future studies important to livestock research. Somatic mutation resulting in base insertions and deletions in CDR2 further diversifies the bovine antibody repertoire. In contrast to previous studies, our data indicate that unusually long CDR3 sequences are not unique to IgM antibodies in cattle. Centrally located cysteine residues in bovine CDR3s provide further evidence that disulfide bond formation is likely of structural importance. We hypothesize that network or cluster-based analyses of expressed antibody repertoires from controlled challenge experiments will help identify novel natural antigen binding solutions to specific pathogens of interest.

The Complementarity Determining Regions (CDRs) of antibodies are assumed to account for the antigen recognition and binding and thus to contain also the antigen binding site. CDRs are typically discerned by searching for regions that are most different, in sequence or in structure, between different antibodies. Here, we show that ~20% of the antibody residues that actually bind the antigen fall outside the CDRs. However, virtually all antigen binding residues lie in regions of structural consensus across antibodies. Furthermore, we show that these regions of structural consensus which cover the antigen binding site are identifiable from the sequence of the antibody. Analyzing the predicted contribution of antigen binding residues to the stability of the antibody-antigen complex, we show that residues that fall outside of the traditionally defined CDRs are at least as important to antigen binding as residues within the CDRs, and in some cases, they are even more important energetically. Furthermore, antigen binding residues that fall outside of the structural consensus regions but within traditionally defined CDRs show a marginal energetic contribution to antigen binding. These findings allow for systematic and comprehensive identification of antigen binding sites, which can improve the understanding of antigenic interactions and may be useful in antibody engineering and B-cell epitope identification.

Even though the results of current therapy are improved for B-cell acute lymphoblastic leukemia (B-ALL) and Burkitt\'s lymphoma (BL), prognosis of relapsed mature B-ALL and BL still remain extremely poor. In this study, we investigated the possibility of applying the use of non-radiolabelled PCR consensus primers and automatic sequencing for the rapid identification of the tumor-specific V(H) CDR3 nucleotide sequence, in mature B-ALL and BL. RNA was extracted from four consecutive, unselected samples from BL cases and three consecutive, unselected samples from mature B-ALL cases. The feasibility of the identification of the tumor-specific V(H) CDR3 nucleotide sequence was then assessed by using non-radiolabelled PCR consensus primers with automatic sequencing. The tumor-specific V(H) CDR3 nucleotide sequence was successfully identified for all seven patients (3 mature B-ALL and BL). The time required was substantially lower than that of the other methods previously published, despite the poor quality of some of the samples. The procedure showed rapidity, reliability and reproducibility. The characteristics of the methodology applied widen the possibility of developing anti-idiotypic therapeutic strategies, even in these B-cell malignancies.