Antibody design using LSTM based deep generative model from phage display library for affinity maturation.

ABSTRACT: Molecular evolution is an important step in the development of therapeutic antibodies. However, the current method of affinity maturation is overly costly and labor-intensive because of the repetitive mutation experiments needed to adequately explore sequence space. Here, we employed a long short term memory network (LSTM)-a widely used deep generative model-based sequence generation and prioritization procedure to efficiently discover antibody sequences with higher affinity. We applied our method to the affinity maturation of antibodies against kynurenine, which is a metabolite related to the niacin synthesis pathway. Kynurenine binding sequences were enriched through phage display panning using a kynurenine-binding oriented human synthetic Fab library. We defined binding antibodies using

SUBMITTER: Saka K 

PROVIDER: S-EPMC7955064 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature