The generation of Plasmodium falciparum Hsp90 selective inhibitors using rational drug design.

Abstract

Malaria, which is mainly caused by Plasmodium falciparum parasite, remains a devastating disease that poses a significant burden on the public health systems and socio-economic development of countries globally. This is particularly true in regions with limited resources, such as sub-Saharan Africa. Drug-resistant strains of the P. falciparum parasite have significantly restricted effective treatment options, necessitating the development of new and effective antimalarial drugs that can overcome drug resistance. The molecular chaperone, heat shock protein 90 (Hsp90), plays a critical role in parasite survival and proliferation. Therefore, it is a promising target for the development of new antimalarial drugs. The generation of selective inhibitors is important for target specificity, therapeutic efficacy, safety, and drug tolerability. Using rational drug design strategies, this study aimed to generate selective inhibitors of P. falciparum Hsp90 (PfHsp90) through molecular modelling, facilitated by an active learning approach, followed by biochemical and biophysical assays.. This study used a combination of computational techniques, namely reaction-based enumeration, active learning, induced fit docking, molecular dynamics simulations, absorption, distribution, metabolism, excretion, and toxicity (ADME/T) predictions, and molecular mechanics with generalized born surface area (MM-GBSA) to generate a total of 10 000 drug-like design ideas. Furthermore, a large compound library from chEMBL was used to identify compounds with high affinity and selectivity for the target protein. A total of 13 models were built using active learning autoQSAR, which achieved good statistical results of R2 = 0.69, Q2 = 0.61, and RMSE = 0.44, on average for all models. The current study then assessed the ability of a subset of the purchased compound to inhibit the ATPase activity of PfHsp90 using an ATPase assay and protein-ligand interaction measured using surface plasmon resonance (SPR). Compounds FTN-T4 and FTN-T10 brought the most robust inhibition of PfHsp90's ATPase activity, greater than that of the positive control harmine, which is in correlation with the in-silico data, while the majority of the compounds displayed a similar inhibition of the ATPase activity to harmine. In the biophysical study, compound FTN-T2 displayed moderate binding with a KD of 7µM, while FTN-T10 and FTN-T5 displayed binding affinities comparable to that of ADP, at KD values of 13 µM and 19 µM, respectively. The results presented in this study demonstrate the great potential of active learning models to generate novel P. falciparum Hsp90 inhibitors. The identified compounds were found to disrupt the ATPase activity of PfHsp90, form sufficient interactions between the protein and ligand, possess a good safety profile and selectivity, and represent promising candidates for further lead optimization. By targeting PfHsp90, these inhibitors offer potential avenues for overcoming drug resistance and improving the efficacy of antimalarial therapies.