Deep learning-driven prediction of drug mechanism of action from large-scale chemical-genetic interaction profiles.

ABSTRACT:

Motivation

Chemical-genetic interaction profiling is a genetic approach that quantifies the susceptibility of a set of mutants depleted in specific gene product(s) to a set of chemical compounds. With the recent advances in artificial intelligence, chemical-genetic interaction profiles (CGIPs) can be leveraged to predict mechanism of action of compounds. This can be achieved by using machine learning, where the data from a CGIP is fed into the machine learning platform along with the chemical descriptors to develop a chemogenetically trained model. As small molecules can be considered non-structural data, graph convolutional neural networks, which can learn from the chemical structures directly, can be used to successfully predict molecular properties. Clustering analysis, on the o

SUBMITTER: Liu C 

PROVIDER: S-EPMC8917716 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature