Abstract
The main challenge in the control of malaria has been the emergence of drug-resistant parasites. The presence of drug-resistant Plasmodium sp. has raised the need for new antimalarial drugs. Molecular modelling techniques have been used as tools to develop new drugs. In this study, we employed virtual screening of a pyrazol derivative (Tx001) against four malaria targets: plasmepsin-IV, plasmepsin-II, falcipain-II, and PfATP6. The receiver operating characteristic curves and area under the curve (AUC) were established for each molecular target. The AUC values obtained for plasmepsin-IV, plasmepsin-II, and falcipain-II were 0.64, 0.92, and 0.94, respectively. All docking simulations were carried out using AutoDock Vina software. The ligand Tx001 exhibited a better interaction with PfATP6 than with the reference compound (-12.2 versus -6.8 Kcal/mol). The Tx001-PfATP6 complex was submitted to molecular dynamics simulations in vacuum implemented on an NAMD program. The ligand Tx001 docked at the same binding site as thapsigargin, which is a natural inhibitor of PfATP6. Compound TX001 was evaluated in vitro with a P. falciparum strain (W2) and a human cell line (WI-26VA4). Tx001 was discovered to be active against P. falciparum (IC50 = 8.2 µM) and inactive against WI-26VA4 (IC50 > 200 µM). Further ligand optimisation cycles generated new prospects for docking and biological assays.
Highlights
Malaria continues to the leading cause of mortality among all infectious diseases in the world; the current chemotherapeutic arsenal has limited clinical response owing to parasite resistance
Octopus carries out docking simulations of the prepared ligands against each molecular target set via AutoDock Vina
We describe the successful case of Tx001, which is a potential compound identified via virtual screening (VS) against four malaria targets: plasmepsin-IV, plasmepsinII, falcipain-II, and PfATP6
Summary
Computational methods: evaluation of docking methodologies - Initially, AutoDock Vina was evaluated by re-docking, which removes the crystallographic ligand with subsequent docking. The active compounds 3, 5, and 6 were selected from ChemBL for plasmepsin-IV (2ANL), plasmepsin-II (1LF3), and falcipain-II (3BPF), respectively, and none for PfATP6 (Gaulton et al 2012). False-positive compounds were obtained from a directory of useful decoys using the DUD-E database (Mysinger et al 2012). DUD-E could generate 150, 250, and 300 decoys for plasmepsin-IV, plasmepsin-II, and falcipain-II, respectively. Decoy and active ligands were submitted to the docking process in their default protonation states. All docking simulations were carried out using AutoDock Vina (Trott & Olson 2010). The grid box was generated by AutoDock Tools (Morris & Huey 2009).
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