Tuning antibody stability and function by rational designs of framework mutations.

ABSTRACT: Artificial intelligence and machine learning models have been developed to engineer antibodies for specific recognition of antigens. These approaches, however, often focus on the antibody complementarity-determining region (CDR) whilst ignoring the immunoglobulin framework (FW), which provides structural rigidity and support for the flexible CDR loops. Here we present an integrated computational-experimental workflow, combining static structure analyses, molecular dynamics simulations and in vitro physicochemical and functional assays to generate rational designs of FW mutations for modulating antibody stability and activity. We first showed that recent antibody-specific language models lacked insights in FW mutagenesis, in comparison to approaches that use antibody structure inform

SUBMITTER: Ng JCF 

PROVIDER: S-EPMC12269682 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature