Machine Learning-Based Virtual Screening for the Identification of Novel CDK-9 Inhibitors.

ABSTRACT: Cyclin-dependent kinase 9 (CDK9) is a key regulator of transcriptional elongation and DNA repair, supporting cancer cell survival by sustaining the expression of oncogenes and anti-apoptotic proteins. Its overexpression in multiple malignancies makes it an attractive target for anticancer therapy. Here, we report a machine learning (ML) based approach to identify novel CDK9 inhibitors. Through systematic data collection and preprocessing, seventy predictive models were developed using five algorithms, two classification settings, and seven molecular representations. The best-performing model was employed to guide a virtual screening (VS) campaign, resulting in the identification of 14 compounds promising for their potential inhibitory effect. Upon enzymatic assays, two molecules with inhib

SUBMITTER: Piazza L 

PROVIDER: S-EPMC12839014 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature