RESUMEN
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making them interesting targets in many diseases. Protein kinase 7 (PK7) is an orphan kinase from the Plasmodium genus, essential for the sporogonic cycle of these parasites. Here, we applied a robust and integrative artificial intelligence-assisted virtual-screening (VS) approach using shape-based and machine learning models to identify new potential PK7 inhibitors with inâ vitro antiplasmodial activity. Eight virtual hits were experimentally evaluated, and compound LabMol-167 inhibited ookinete conversion of Plasmodium berghei and blood stages of Plasmodium falciparum at nanomolar concentrations with low cytotoxicity in mammalian cells. As PK7 does not have an essential role in the Plasmodium blood stage and our virtual screening strategy aimed for both PK7 and blood-stage inhibition, we conducted an in silico target fishing approach and propose that this compound might also inhibit P. falciparum PK5, acting as a possible dual-target inhibitor. Finally, docking studies of LabMol-167 with P. falciparum PK7 and PK5 proteins highlighted key interactions for further hit-to lead optimization.
Asunto(s)
Antimaláricos/farmacología , Inteligencia Artificial , Quinasas de Proteína Quinasa Activadas por Mitógenos/antagonistas & inhibidores , Plasmodium falciparum/efectos de los fármacos , Inhibidores de Proteínas Quinasas/farmacología , Proteínas Protozoarias/antagonistas & inhibidores , Antimaláricos/química , Relación Dosis-Respuesta a Droga , Evaluación Preclínica de Medicamentos , Quinasas de Proteína Quinasa Activadas por Mitógenos/metabolismo , Estructura Molecular , Pruebas de Sensibilidad Parasitaria , Plasmodium falciparum/metabolismo , Inhibidores de Proteínas Quinasas/química , Proteínas Protozoarias/metabolismo , Relación Estructura-ActividadRESUMEN
Virtual screening (VS) techniques are well-established tools in the modern drug discovery process, mainly used for hit finding in drug discovery. The availability of knowledge of structural information, which includes an increasing number of 3D protein structures and the readiness of free databases of commercially available smallmolecules, provides a broad platform for VS. This review summarizes the current developments in VS regarding chemical databases and highlights the achievements as well as the challenges with an emphasis on a recent example of the successful application for the identification of new hits for sterol 14α-demethylase (CYP51) of Trypanosoma cruzi.