Auto QSAR-based Active learning docking for hit identification of potential inhibitors ofPlasmodium falciparumHsp90 as antimalarial agents

Abstract

AbstractMalaria which is mainly caused byPlasmodium falciparumparasite remains a devastating public health concern, necessitating the need to develop new antimalarial agents.P. falciparumheat shock protein 90 (Hsp90), is indispensable for parasite survival and a promising drug target. Inhibitors targeting the ATP-binding pocket of the N-terminal domain have anti-Plasmodiumeffects. We proposed ade novoactive learning (AL) driven method in tandem with docking to predict inhibitors with unique scaffolds and preferential selectivity towards PfHsp90. Reference compounds, predicted to bind PfHsp90 at the ATP-binding pocket and possessing anti-Plasmodiumactivities, were used to generate 10,000 unique derivatives and to build the Auto-quantitative structures activity relationships (QSAR) models. Glide docking was performed to predict the docking scores of the derivatives and > 15,000 compounds obtained from the ChEMBL database. Re-iterative training and testing of the models was performed until the optimum Kennel-based Partial Least Square (KPLS) regression model with a regression coefficient R2 = 0.75 for the training set and squared correlation prediction Q2 = 0.62 for the test set reached convergence. Rescoring using induced fit docking and molecular dynamics simulations enabled us to prioritize 15 ATP/ADP-like design ideas for purchase. The compounds exerted moderate activity towardsP. falciparumNF54 strain with IC50values of ≤ 6μM and displayed moderate to weak affinity towards PfHsp90 (KDrange: 13.5-19.9μM) comparable to the reported affinity of ADP. The most potent compound was FTN-T5 (PfN54 IC50:1.44μM; HepG2/CHO cells SI≥ 29) which bound to PfHsp90 with moderate affinity (KD:7.7μM), providing a starting point for optimization efforts. Our work demonstrates the great utility of AL for the rapid identification of novel molecules for drug discovery (i.e., hit identification). The potency of FTN-T5 will be critical for designing species-selective inhibitors towards developing more efficient agents against malaria.