Developing a machine learning model to identify protein-protein interaction hotspots to facilitate drug discovery.

ABSTRACT: Throughout the history of drug discovery, an enzymatic-based approach for identifying new drug molecules has been primarily utilized. Recently, protein-protein interfaces that can be disrupted to identify small molecules that could be viable targets for certain diseases, such as cancer and the human immunodeficiency virus, have been identified. Existing studies computationally identify hotspots on these interfaces, with most models attaining accuracies of ~70%. Many studies do not effectively integrate information relating to amino acid chains and other structural information relating to the complex. Herein, (1) a machine learning model has been created and (2) its ability to integrate multiple features, such as those associated with amino-acid chains, has been evaluated to enhance the abi

SUBMITTER: Nandakumar R 

PROVIDER: S-EPMC7727375 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature