Analysis of 5518 unique, productively rearranged human VH3-23*01 gene sequences reveals CDR-H3 length-dependent usage of the IGHD2 gene family

A window into the human immune system: comprehensive characterization of the complexity of antibody complementary-determining regions in functional antibodies

The human immune system uses antibodies to neutralize foreign antigens. They are composed of heavy and light chains, both with constant and variable regions. The variable region has six hypervariable loops, also known as complementary-determining regions (CDRs) that determine antibody diversity and antigen specificity. Knowledge of their significance, and certain residues present in these areas, is vital for antibody therapeutics development. This study includes an analysis of more than 11,000 human antibody sequences from the International Immunogenetics information system (IMGT). The analysis included parameters such as length distribution, overall amino acid diversity, amino acid frequency per CDR and residue position within antibody chains. Overall, our findings confirm existing knowledge, such as CDRH3's high length diversity and amino acid variability, increased aromatic residue usage, particularly tyrosine, charged and polar residues like aspartic acid, serine, and the flexible residue glycine. Specific residue positions within each CDR influence these occurrences, implying a unique amino acid type distribution pattern. We compared amino acid type usage in CDRs and non-CDR regions, both in globular and transmembrane proteins, which revealed distinguishing features, such as increased frequency of tyrosine, serine, aspartic acid, and arginine. These findings should prove useful for future optimization, improvement of affinity, synthetic antibody library design, or the creation of antibodies de-novo in silico.

Antibody heavy chain CDR3 length-dependent usage of human IGHJ4 and IGHJ6 germline genes

Therapeutic antibody discovery using synthetic diversity has been proved productive, especially for target proteins not suitable for traditional animal immunization-based antibody discovery approaches. Recently, many lines of evidences suggest that the quality of synthetic diversity design limits the development success of synthetic antibody hits. The aim of our study is to understand the quality limitation and to properly address the challenges with a better design. Using VH3–23 as a model framework, we observed and quantitatively mapped CDR-H3 loop length-dependent usage of human IGHJ4 and IGHJ6 germline genes in the natural human immune repertoire. Skewed usage of DH2-JH6 and DH3-JH6 rearrangements was quantitatively determined in a CDR-H3 length-dependent manner in natural human antibodies with long CDR-H3 loops. Structural modeling suggests choices of JH help to stabilize antibody CDR-H3 loop and JH only partially contributes to the paratope. Our observations shed light on the design of next-generation synthetic diversity with improved probability of success.

Landscape of Non-canonical Cysteines in Human VH Repertoire Revealed by Immunogenetic Analysis

Human antibody repertoire data captured through next-generation sequencing (NGS) has enabled deeper insights into B cell immunogenetics and paratope diversity. By analyzing large public NGS datasets, we map the landscape of non-canonical cysteines in human variable heavy-chain domains (V_Hs) at the repertoire level. We identify remarkable usage of non-canonical cysteines within the heavy-chain complementarity-determining region 3 (CDR-H3) and other CDRs and framework regions. Furthermore, our study reveals the diversity and location of non-canonical cysteines and their associated motifs in human V_Hs, which are reminiscent of and more complex than those found in other non-human species such as chicken, camel, llama, shark, and cow. These results explain how non-canonical cysteines strategically occur in the human antibodyome to expand its paratope space. This study will guide the design of human antibodies harboring disulfide-stabilized long CDR-H3s to access difficult-to-target epitopes and influence a paradigm shift in developability involving non-canonical cysteines.

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NGS-based non-canonical cysteine landscape in human V_Hs

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1 to 8 non-canonical cysteines and up to 30% in long CDR-H3s

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An array of potential disulfide motifs adds paratope diversity

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Non-canonical cysteines in human V_Hs are reminiscent of lower animals

ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning

Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in generating antibody-based inhibitors is the lack of fundamental information relating sequences of antibodies to their unique properties as inhibitors. We develop a pipeline, Antibody Sequence Analysis Pipeline using Statistical testing and Machine Learning (ASAP-SML), to identify features that distinguish one set of antibody sequences from antibody sequences in a reference set. The pipeline extracts feature fingerprints from sequences. The fingerprints represent germline, CDR canonical structure, isoelectric point and frequent positional motifs. Machine learning and statistical significance testing techniques are applied to antibody sequences and extracted feature fingerprints to identify distinguishing feature values and combinations thereof. To demonstrate how it works, we applied the pipeline on sets of antibody sequences known to bind or inhibit the activities of matrix metalloproteinases (MMPs), a family of zinc-dependent enzymes that promote cancer progression and undesired inflammation under pathological conditions, against reference datasets that do not bind or inhibit MMPs. ASAP-SML identifies features and combinations of feature values found in the MMP-targeting sets that are distinct from those in the reference sets.