In-silico-based Investigation of the Inhibitory Potential of Compounds Obtained from High Performance Liquid Chromatography Analysis of Tobacco against β-Secretase-1

Abstract

Alzheimer’s disease (AD) has been a huge health threat to the human community from time immemorial, especially among individuals who are at an advanced age. Over the years, there has been no specific therapeutic regimen to cure the disease; however, the available drugs can only manage its symptoms, necessitating the development of better therapeutic regimens. This study aims to investigate the inhibitory potential of phytochemical constituents of Tobacco plant (Nicotiana tabacum) obtained by High Performance Liquid Chromatography (HPLC) analysis against βeta-secretase-1 using an in-silico-based approach. Herein, we used an in-silico-based approach involving virtual screening-based molecular docking and Molecular Dynamics (MD) simulation studies to investigate the inhibitory potential of compounds obtained from HPLC analysis of Tobacco plant against βeta-secretase-1. Our molecular docking campaign revealed that nicotelline had a higher binding affinity for the receptor than the standard compound (AZD 3293). A MD simulation run of 100 nanoseconds (ns) demonstrated that Nicotelline had better overall stability and a lesser fluctuation degree than AZD 3293. Our molecular docking and MD simulation studies demonstrated that Nicotelline can putatively bind to the active site of βeta-secretase-1 and inhibit the biological action of the enzyme more than AZD 3293, suggesting Nicotelline as a promising drug candidate. However, further studies (preclinical, clinical, and toxicity) are needed to evaluate and confirm the therapeutic potential of Nicotelline against βeta-secretase-1 towards the development of therapy for AD.