Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

ABSTRACT: High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in these large datasets, in particular the identification of therapeutic antibodies (Abs) or those associated with disease exposure and protection. Here, we describe our efforts to use artificial intelligence (AI)-based image-analyses for prospective classification of Abs based solely on sequence information. We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that

SUBMITTER: Ripoll DR 

PROVIDER: S-EPMC8032195 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature