<i>De Novo</i> Design of Peptide Binders to Conformationally Diverse Targets with Contrastive Language Modeling.

ABSTRACT: Designing binders to target undruggable proteins presents a formidable challenge in drug discovery, requiring innovative approaches to overcome the lack of putative binding sites. Recently, generative models have been trained to design binding proteins via three-dimensional structures of target proteins, but as a result, struggle to design binders to disordered or conformationally unstable targets. In this work, we provide a generalizable algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model, and subsequently screen these novel linear sequence

SUBMITTER: Bhat S 

PROVIDER: S-EPMC11291000 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature