Computational Exploration of gp63: Unlocking Potential Inhibitors for Leishmaniasis

Abstract

Leishmaniasis is an infection caused by protozoa of the genus Leishmania, which belongs to a neglected group of diseases. Limited treatment options and emerging drug resistance has contributed towards morbidity and mortality due to leishmaniasis. Therefore, exploring new therapeutic targets responsible for the pathogen's virulence is a priority to combat the disease. One of the contributing molecular factors to Leishmania virulence and pathogenesis is the metalloprotease glycoprotein 63 (gp63), also known as leishmanolysin or major surface protease (MSP). This metalloprotease is abundant on the parasite's surface in both promastigote and amastigote Leishmania stages. The present study focuses on finding the inhibitors of gp63 using the ChEMBL database, which includes a large, diverse set of 12,00,000 compounds. This study pipeline includes homology modeling, virtual screening, free energy analysis and molecular dynamic simulations to identify the with potential inhibitors of gp63, an important virulence factor of Leishmania species. Fourteen compounds were identified with good docking scores (-11 to -9 kcal/mol) compared to the control Gly2. The stability of the protein-ligand complex was later determined by free energy, which was computed using MM/GBSA. Moreover, molecular dynamic simulations validated the stability of the top seven compounds (Compound 2, Compound 3, Compound 6, Compound 7, Compound 9, Compound 10 and Compound 13 using parameters like root mean square deviation (RMSD), root mean square fluctuation (RMSF) and protein-ligand interactions. Thus, these compounds may serve as leads for further in-vitro studies in order to develop potential leishmaniasis chemotherapeutics.