BindingSiteDTI: differential-scale binding site modelling for drug-target interaction prediction.

ABSTRACT:

Motivation

Enhanced by contemporary computational advances, the prediction of drug-target interactions (DTIs) has become crucial in developing de novo and effective drugs. Existing deep learning approaches to DTI prediction are frequently beleaguered by a tendency to overfit specific molecular representations, which significantly impedes their predictive reliability and utility in novel drug discovery contexts. Furthermore, existing DTI networks often disregard the molecular size variance between macro molecules (targets) and micro molecules (drugs) by treating them at an equivalent scale that undermines the accurate elucidation of their interaction.

Results

We propose a novel DTI network with a differential-scale scheme to model the binding site for enhancing DTI prediction

SUBMITTER: Pan F 

PROVIDER: S-EPMC11256917 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature