Identification of therapeutics against PfPK6 protein of Plasmodium falciparum: Structure and Deep Learning approach

Abstract

The Plasmodium falciparum Protein Kinase 6 (PfPK6) is a serine/threonine protein kinase categorized under the CMGC group, displaying both cyclin-dependent kinases (CDKs) and mitogen-activated protein kinases (MAPKs) activity. Previous research has indicated that PfPK6 is expressed during the trophozoite and schizont stages of the Plasmodium falciparum asexual blood stage. Unlike typical cyclin-dependent kinases, PfPK6 demonstrates kinase activity independent of cyclin, making it a promising target for drug identification. In this study, we utilized a computational approach to identify a novel PfPK6 inhibitor through virtual screening of small inhibitor compounds from diverse datasets, employing a structure-based approach and a Deep Learning (DL) model. The most promising inhibitor molecule, TCMDC-132409 from the Tres Cantos Antimalarial Set, exhibited a binding affinity of −13.553 kcal/mol against PfPK6. Additionally, a 200ns molecular dynamics simulation study confirmed the stability of the binding mode, indicating the potential of TCMDC-132409 as an antiplasmodial inhibitor for further investigation.