Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.

Autor: Lima MNN; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil., Borba JVB; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil.; Laboratory of Tropical Diseases - Prof. Dr. Luiz Jacintho da Silva, Department of Genetics Evolution, Microbiology and Immunology, Institute of Biology, 13083-970, Campinas, SP, Brazil., Cassiano GC; Laboratory of Tropical Diseases - Prof. Dr. Luiz Jacintho da Silva, Department of Genetics Evolution, Microbiology and Immunology, Institute of Biology, 13083-970, Campinas, SP, Brazil.; Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal., Mottin M; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil., Mendonça SS; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil., Silva AC; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil., Tomaz KCP; Laboratory of Tropical Diseases - Prof. Dr. Luiz Jacintho da Silva, Department of Genetics Evolution, Microbiology and Immunology, Institute of Biology, 13083-970, Campinas, SP, Brazil., Calit J; Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, 05508-000, São Paulo, SP, Brazil., Bargieri DY; Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, 05508-000, São Paulo, SP, Brazil., Costa FTM; Laboratory of Tropical Diseases - Prof. Dr. Luiz Jacintho da Silva, Department of Genetics Evolution, Microbiology and Immunology, Institute of Biology, 13083-970, Campinas, SP, Brazil., Andrade CH; LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Rua 240, qd. 87, Goiânia, GO, 74605-170, Brazil.; Laboratory of Tropical Diseases - Prof. Dr. Luiz Jacintho da Silva, Department of Genetics Evolution, Microbiology and Immunology, Institute of Biology, 13083-970, Campinas, SP, Brazil.
Jazyk: angličtina
Zdroj: ChemMedChem [ChemMedChem] 2021 Apr 08; Vol. 16 (7), pp. 1093-1103. Date of Electronic Publication: 2021 Mar 16.
DOI: 10.1002/cmdc.202000685
Abstrakt: 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 in 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.
(© 2020 Wiley-VCH GmbH.)
Databáze: MEDLINE
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