Development and experimental validation of computational methods for human antibody affinity enhancement.

ABSTRACT: High affinity is crucial for the efficacy and specificity of antibody. Due to involving high-throughput screens, biological experiments for antibody affinity maturation are time-consuming and have a low success rate. Precise computational-assisted antibody design promises to accelerate this process, but there is still a lack of effective computational methods capable of pinpointing beneficial mutations within the complementarity-determining region (CDR) of antibodies. Moreover, random mutations often lead to challenges in antibody expression and immunogenicity. In this study, to enhance the affinity of a human antibody against avian influenza virus, a CDR library was constructed and evolutionary information was acquired through sequence alignment to restrict the mutation positions and type

SUBMITTER: Li J 

PROVIDER: S-EPMC11446602 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature