Generating interacting protein sequences using domain-to-domain translation.

ABSTRACT:

Motivation

Being able to artificially design novel proteins of desired function is pivotal in many biological and biomedical applications. Generative statistical modeling has recently emerged as a new paradigm for designing amino acid sequences, including in particular models and embedding methods borrowed from natural language processing (NLP). However, most approaches target single proteins or protein domains, and do not take into account any functional specificity or interaction with the context. To extend beyond current computational strategies, we develop a method for generating protein domain sequences intended to interact with another protein domain. Using data from natural multidomain proteins, we cast the problem as a translation problem from a given interactor domain to t

SUBMITTER: Meynard-Piganeau B 

PROVIDER: S-EPMC10329493 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature