Molecular scaffold recognition of drug molecules against essential genes of Leishmania donovani using biocomputing approach

Abstract

• Essential genes (Pyridoxal kinase and sterol alpha-14 demethylase) are drug targets. • Discerned the atomistic interactions of small molecules with target proteins through Molecular Docking and MD Simulations. • Non-bonded contacts and MM-PBSA calculations aided in deciphering nitazoxanide and artemisinin dynamic interactions with the target proteins. • This biocomputing study identified plausible drug inhibitors against essential leishmanial genes. Leishmania donovani , an obligatory intracellular flagellate pathogen, is the underlying cause of visceral leishmaniasis (VL), a fatal disease that poses a significant challenge to existing therapeutic approaches and leads to human mortality. In an endeavor to find an antileishmanial drug to combat VL, we aimed to assess the approved drug molecules against the specific drug targets of VL. In this study, a theoretical method was used to select two essential therapeutic targets (pyridoxal kinase [PK] and sterol alpha-14 demethylase [SDM]) which were present in both the data set of essential genes and drug target proteins. The selected PK and SDM proteins in L. donovani play pivotal roles as essential enzymes in the crucial vitamin B6 salvage and sterol biosynthesis pathways, respectively, leading to pathogenicity in humans. In addition to that drugs were gathered from the DrugBank and Drug Central databases and 325 (out of 4867) compounds having anti-parasitic properties were screened by PASS analysis. Consequently, three ligands (referred to as Lig_1, Lig_2, and Lig_3) were chosen based on their elevated Pa values, docking scores, and notable medicinal applications. Moreover, the result obtained from MD simulation suggests Lig_1 [Nitazoxanide (PubChem ID-41684)] does not affect the structural integrity of both targets. Additionally, evaluation of total binding energies by MMPBSA analysis showed stronger binding of Lig_1 with PK and SDM is -100.71 and -175.61 kJ/mol, respectively compared to others. As a whole, the methodology employed in this research involves the simultaneous identification of suitable protein targets and potential inhibitors. Through this investigation, we have demonstrated that compounds derived from a biocomputing approach exhibit interaction mechanisms as inhibitors against drug targets, offering a promising avenue for addressing VL.

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