Learning the Language of Antibody Hypervariability

Abstract excerpt

Protein language models (PLMs) based on machine learning have demon-strated impressive success in predicting protein structure and function. However, general-purpose (“foundational”) PLMs have limited performance in predicting antibodies due to the latter’s hypervariable regions, which do not conform to the evolutionary conservation principles that such models rely on. In this study, we propose a new transfer lear...

Topics

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• Amino Acid Sequence
• Antibodies
• Computational Biology
• Germ-Line Mutation
• Monoclonal and Polyclonal Antibodies Research
• Mutation
• RNA and protein synthesis mechanisms
• vaccines and immunoinformatics approaches

Identifiers and source

Literature Corpus work

b45292a6-796d-531b-85b2-ecb8a4d907dd

DOI

10.1101/2023.04.26.538476