Identifying Potential Drug Candidates against Plasmodium falciparum (Isolate 3D7) through Targeting ADP-dependent DNA Helicase RecQ: An in silico Approach

Abstract:

Background: The malarial scenario has significantly varied in the past few decades; whether it is funding or the range of sophisticated life-saving tools that have been improved, the disease burden has reduced, and even a few nations are on the verge of their elimination. Despite these, drug resistance is the major hurdle in the fight against malaria. Aim: Identifying new drug candidates with negligible toxicity are imperative to overcome the existing problem. The proposed study aims to identify new potential lead molecules via targeting the ADP-dependent DNA helicase RecQ of Plasmodium falciparum (isolate 3D7) using Target-Based Virtual Screening (TBVS), molecular docking, and dynamics simulations. Materials and Methods: Ligand molecules were retrieved from a comprehensive digital library of the MCULE database having millions of investigational compounds. Pfizer’s rule of five and the number of halogen atoms (3-5) were considered the basic primary filters of TBVS. The AutoDockVina (ADV) and GROningenMAchine for Chemical Simulations software were used to assess the molecular interactions and stability of protein-ligand complexes, respectively. Results: The primary filters of the TBVS work-pipeline depicted 2,597,040 chemical hits from over a hundred million small molecules. The toxicity tool sifted twenty-one molecules whose HIA and BBB permeation were evaluated through the Egan-Egg model. Five ligand hits were shortlisted with zero violation of drug-likeness and contain three or more hydrogen bonds. ADME, docking, and MD parameters depicted a molecule MCULE-1255186442-0-1 as a promising drug candidate. Conclusion: Druggable properties of identified ligands are inferred purely from the in silico experiments, so before its therapeutic implications, wet-lab validations are imperative.

Keywords: Malaria, Plasmodium falciparum, DNA helicase, PfWrn, Docking, MD simulation.