Language models can identify enzymatic binding sites in protein sequences.

ABSTRACT: Recent advances in language modeling have had a tremendous impact on how we handle sequential data in science. Language architectures have emerged as a hotbed of innovation and creativity in natural language processing over the last decade, and have since gained prominence in modeling proteins and chemical processes, elucidating structural relationships from textual/sequential data. Surprisingly, some of these relationships refer to three-dimensional structural features, raising important questions on the dimensionality of the information encoded within sequential data. Here, we demonstrate that the unsupervised use of a language model architecture to a language representation of bio-catalyzed chemical reactions can capture the signal at the base of the substrate-binding site atomic intera

SUBMITTER: Nana Teukam YG 

PROVIDER: S-EPMC11087710 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature