2D-QSAR, molecular docking and MD simulation based virtual screening of the herbal molecules against Alzheimer’s disorder: an approach to predict CNS activity

Abstract

Acetylcholinesterase (AChE) is one of the key enzyme targets that have been used clinically for the management of Alzheimer’s Disorder (AD). Numerous reports in the literature predict and demonstrate in-vitro, and in-silico anticholinergic activity of herbal molecules, however, majority of them failed to find clinical application. To address these issues, we developed a 2D-QSAR model that could efficiently predict the AChE inhibitory activity of herbal molecules along with predicting their potential to cross the blood-brain-barrier (BBB) to exert their beneficial effects during AD. Virtual screening of the herbal molecules was performed and amentoflavone, asiaticoside, astaxanthin, bahouside, biapigenin, glycyrrhizin, hyperforin, hypericin, and tocopherol were predicted as the most promising herbal molecules for inhibiting AChE. Results were validated through molecular docking, atomistic molecular dynamics simulations and Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) studies against human AChE (PDB ID: 4EY7). To determine whether or not these molecules can cross BBB to inhibit AChE within the central nervous system (CNS) for being beneficial for the management of AD, we determined a CNS Multi-parameter Optimization (MPO) score, which was found in the range of 1 to 3.76. Overall, the best results were observed for amentoflavone and our results demonstrated a PIC₅₀ value of 7.377 nM, molecular docking score of −11.5 kcal/mol, and CNS MPO score of 3.76. In conclusion, we successfully developed a reliable and efficient 2D-QSAR model and predicted amentoflavone to be the most promising molecule that could inhibit human AChE enzyme within the CNS and could prove beneficial for the management of AD.

Communicated by Ramaswamy H. Sarma

Keywords:

• 2D-QSAR
• molecular docking
• acetylcholine
• Alzheimer’s disorder
• blood brain barrier
• acetylcholinesterase
• CADD
• drug discovery
• drug designing

Acknowledgements

The authors acknowledge Govt. College of Pharmacy, Rohru for providing the facilities to conduct this study. Authors acknowledge the generous support of Dr. Rituraj Purohit, Principal Scientist, Structural Bioinformatics Lab, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP, 176061 for providing lab space for conducting MD Simulation studies. BS acknowledges the Department of Biotechnology, New Delhi, India for providing junior research fellowship File No: DBTHRDPMU/JRF/BET-20/I/2020/AL/36.

Author’s contributions

AT contributed to designing the study, performed QSAR and docking studies, and prepared the first draft of the manuscript. BS performed the simulation studies, compiled and analysed the data. AP, VS, and AK contributed to the study desigining, technical inputs, and manuscript editing. VM contributed to designing the study, molecular docking, manuscript preparation, and editing analysis of the results.

Disclosure statement

The authors are not having any conflict of interest concerning any part of this study.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.