RNA language model and graph attention network for RNA and small molecule binding sites prediction.

ABSTRACT:

Motivation

The structural complexities enable RNA to serve as a versatile molecular scaffold capable of binding small molecules with high specificity. Understanding these interactions is essential for elucidating RNA's role in disease mechanisms and developing RNA-targeted therapeutics. However, predicting RNA-small molecule binding sites remains a significant challenge due to their conformational flexibility, structural diversity, and the limited availability of high-resolution structural data.

Results

In this study, we propose RLsite, a novel computational framework integrating pre-trained RNA language models with graph attention networks (GAT) to predict small-molecule binding sites on RNA. Our method effectively captures both sequential and structural features of RNA by

SUBMITTER: Sun S 

PROVIDER: S-EPMC12417085 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature