DeepRSMA: a cross-fusion-based deep learning method for RNA-small molecule binding affinity prediction.

ABSTRACT:

Motivation

RNA is implicated in numerous aberrant cellular functions and disease progressions, highlighting the crucial importance of RNA-targeted drugs. To accelerate the discovery of such drugs, it is essential to develop an effective computational method for predicting RNA-small molecule affinity (RSMA). Recently, deep learning-based computational methods have been promising due to their powerful nonlinear modeling ability. However, the leveraging of advanced deep learning methods to mine the diverse information of RNAs, small molecules, and their interaction still remains a great challenge.

Results

In this study, we present DeepRSMA, an innovative cross-attention-based deep learning method for RSMA prediction. To effectively capture fine-grained features from RNA and sma

SUBMITTER: Huang Z 

PROVIDER: S-EPMC11646567 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature