Transformer neural network for protein-specific de novo drug generation as a machine translation problem.

ABSTRACT: Drug discovery for a protein target is a very laborious, long and costly process. Machine learning approaches and, in particular, deep generative networks can substantially reduce development time and costs. However, the majority of methods imply prior knowledge of protein binders, their physicochemical characteristics or the three-dimensional structure of the protein. The method proposed in this work generates novel molecules with predicted ability to bind a target protein by relying on its amino acid sequence only. We consider target-specific de novo drug design as a translational problem between the amino acid "language" and simplified molecular input line entry system representation of the molecule. To tackle this problem, we apply Transformer neural network architecture, a state-of-th

SUBMITTER: Grechishnikova D 

PROVIDER: S-EPMC7801439 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature