In-Silico Identification of the Best Compound Against Leishmania infantum: High Throughput Screening of All FDA Approved Drugs

Objective: Current in-silico research was designed and administered for the screening of 20000 Food and Drug Administration-approved drug compounds with the goal of finding promising drugs against lipophosphoglycan (LPG) and γ-glutamylcysteine synthetase (γ-GCS) of Leishmania infantum. Methods: After the protein sequence of both targets was taken, the 3D structures of protein of interest were predicted and validated. Molecular docking was done among the two putative targets (LPG and γ-GCS) and approved compounds were selected using AutoDock 4.2 program to predict ligand-receptor interactions. Results: After docking experiment was done on 20000 drug compounds, a total number of seven ligands, two for γ-GCS receptor and five for LPG receptor, were assigned as novel, potent anti-leishmanial drugs based on their binding affinity and energy. Of those, five ligands possessed cytotoxic and anti-cancer characteristics and showed good binding capacity to LPG receptor with ΔGbinding up to 8.5 kcal/mol more negative; while two compounds showed good binding capacity to glutamyl receptor with ΔGbinding up to 7.8 kcal/mol more negative. Conclusion: The latest software-based methods are powerful tools for scanning and predicting new peptide templates specific to biological targets in organisms for new drug discovery. However, the use of in vitro and in vivo techniques is a requirement for better evaluation of the potential of projected ligands with the help of in-silico approaches, identifying molecular mechanism of action of the more active compounds is possible. This can help in defining the most likely molecular target, so that the subsequent optimization using in vitro and in vivo techniques can be undertaken.