Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models.

ABSTRACT: The development of selective inhibitors of the clinically relevant human Carbonic Anhydrase (hCA) isoforms IX and XII has become a major topic in drug research, due to their deregulation in several types of cancer. Indeed, the selective inhibition of these two isoforms, especially with respect to the homeostatic isoform II, holds great promise to develop anticancer drugs with limited side effects. Therefore, the development of in silico models able to predict the activity and selectivity against the desired isoform(s) is of central interest. In this work, we have developed a series of machine learning classification models, trained on high confidence data extracted from ChEMBL, able to predict the activity and selectivity profiles of ligands for human Carbonic Anhydrase isoforms II, IX and

SUBMITTER: Tinivella A 

PROVIDER: S-EPMC7937250 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature