Improving generalizability of drug-target binding prediction by pre-trained multi-view molecular representations.

ABSTRACT:

Motivation

Most drugs start on their journey inside the body by binding the right target proteins. This is the reason that numerous efforts have been devoted to predicting the drug-target binding during drug development. However, the inherent diversity among molecular properties, coupled with limited training data availability, poses challenges to the accuracy and generalizability of these methods beyond their training domain.

Results

In this work, we proposed a neural networks construction for high accurate and generalizable drug-target binding prediction, named Pre-trained Multi-view Molecular Representations (PMMR). The method uses pre-trained models to transfer representations of target proteins and drugs to the domain of drug-target binding prediction, mitigating the is

SUBMITTER: Ouyang X 

PROVIDER: S-EPMC11751634 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature