Multi-PLI: interpretable multi-task deep learning model for unifying protein-ligand interaction datasets.

ABSTRACT: The assessment of protein-ligand interactions is critical at early stage of drug discovery. Computational approaches for efficiently predicting such interactions facilitate drug development. Recently, methods based on deep learning, including structure- and sequence-based models, have achieved impressive performance on several different datasets. However, their application still suffers from a generalizability issue because of insufficient data, especially for structure based models, as well as a heterogeneity problem because of different label measurements and varying proteins across datasets. Here, we present an interpretable multi-task model to evaluate protein-ligand interaction (Multi-PLI). The model can run classification (binding or not) and regression (binding affinity) tasks concu

SUBMITTER: Hu F 

PROVIDER: S-EPMC8051026 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature