Utilization of Molecular Simulation in Drug Discovery: Using Computational Approaches to Find the Best Inhibitor of Nicotinamide Phosphoribotyltransferase (NAMPT) For Cancer Drug Candidate

Abstract

The critical role of nicotinamide phosphoribotyltransferase (NAMPT) in nicotinamide adenine dinucleotide biosynthesis makes it an attractive target for the development of new anticancer agents. Many attempts have been made to explore this field, and it is also known that two of NAMPT inhibitors have entered clinical trials. The aim of this study is to explore the utilization of molecular simulation and structural validation, optimizing the use of computational approaches to find the best inhibitor of NAMPT. Thus, the steps will be proven to help target identification and target validation steps in drug discovery development. In this study, a total of seven NAMPT-ligand complexes were docked using AutoDock Vina. The binding affinity of six of was compared to curcumin as the new potential NAMPT inhibitor. Visualization was done using Structural Validation using wwPDB Validation Service and WHAT_CHECK were also performed in order to validate the previously available NAMPT-ligand in Protein Data Bank to explore the information provided. This study showed that molecular simulation provided a lot of useful information before doing the real research. Molecular Docking revealed that 1QR ligand has the highest binding affinity to NAMPT with -11.5 kcal/mol, meanwhile, CHS-828 that has entered clinical trials, exhibited the lowest binding affinity with -6.9 kcal/mol. Therefore, the poor performance of clinical trials was suggested because of the lack of in silico study that predicted the ability be the inhibitor. The findings of this study provide a new insight of utilizing the provided molecular simulation tools to reduce the drug development cost and future studies including molecular dynamics using High Performance Computer are needed.