In silico-driven identification of potent CDK9 inhibitors through bioisosteric replacement and multi-stage virtual screening.

Cyclin-dependent kinase 9 (CDK9) is a serine/threonine kinase crucial for transcriptional elongation via phosphorylation of the C-terminal domain (CTD) of RNA polymerase II, thereby enabling productive mRNA synthesis. Given its pivotal role in gene expression, CDK9 represents a validated therapeutic target in cancer research. This study employed a sequential bioisosteric replacement strategy to identify novel CDK9 inhibitors. Initially, a library of 17,633 compounds was generated by replacing the core scaffold of 134 known inhibitors. Pharmacophore-based virtual screening reduced this set to 3,754 candidates, from which a highly predictive QSAR model identified compound 50224760_85 as the most promising lead. A second round of bioisosteric substitution yielded 66,966 novel structures, increasing chemical diversity and predicted bioactivity. QSAR analysis highlighted compounds 9550, 9724, and 31801 as representative molecules with favorable predicted properties and structural novelty. Density functional theory (DFT) calculations further revealed distinct electronic and chemical reactivity profiles across these top-ranked ligands. Molecular dynamics simulations demonstrated that all three ligands maintained enhanced stability within the ATP-binding pocket of CDK9 relative to the parent compound. Consistently, binding free energy and per-residue decomposition analyses confirmed robust interactions with catalytically relevant residues, supporting their potential as potential CDK9 inhibitors. Overall, this integrative strategy identified a rich dataset of CDK9-targeting ligands with predicted K