Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: The diverse structures and functions inherent in RNAs present a wealth of potential drug targets. Some small molecules are anticipated to serve as leading compounds, providing guidance for the development of novel RNA-targeted therapeutics. Consequently, the determination of RNA-small molecule binding affinity is a critical undertaking in the landscape of RNA-targeted drug discovery and development. Nevertheless, to date, only one computational method for RNA-small molecule binding affinity prediction has been proposed. The prediction of RNA-small molecule binding affinity remains a significant challenge. The development of a computational model is deemed essential to effectively extract relevant features and predict RNA-small molecule binding affinity accurately.

Authors

  • Saisai Sun
    School of Mathematical Sciences, Nankai University, Tianjin, China.
  • Lin Gao