Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking

Author:

Simeon Saw1,Anuwongcharoen Nuttapat1,Shoombuatong Watshara1,Malik Aijaz Ahmad1,Prachayasittikul Virapong2,Wikberg Jarl E.S.3,Nantasenamat Chanin1

Affiliation:

1. Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand

2. Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand

3. Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

Abstract

Alzheimer’s disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values of 0.92 ± 0.01, 0.78 ± 0.06 and 0.78 ± 0.05, respectively. Furthermore, Y-scrambling was applied to evaluate the possibility of chance correlation of the predictive model. Subsequently, a thorough analysis of the substructure fingerprint count was conducted to provide informative insights on the inhibitory activity of AChE inhibitors. Moreover, Kennard–Stone sampling of the actives were applied to select 30 diverse compounds for further molecular docking studies in order to gain structural insights on the origin of AChE inhibition. Site-moiety mapping of compounds from the diversity set revealed three binding anchors encompassing both hydrogen bonding and van der Waals interaction. Molecular docking revealed that compounds13,5and28exhibited the lowest binding energies of −12.2, −12.0 and −12.0 kcal/mol, respectively, against human AChE, which is modulated by hydrogen bonding,ππstacking and hydrophobic interaction inside the binding pocket. These information may be used as guidelines for the design of novel and robust AChE inhibitors.

Funder

Thailand Research Fund

Swedish Research Council

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference72 articles.

1. QSAR in reactions of organophosphorus inhibitors with acetylcholinesterase;Aaviksaar;Phosphorus, Sulfur, and Silicon and the Related Elements,1990

2. Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase;Andersson;Journal of Computer-Aided Molecular Design,2014

3. Aging, energy, and oxidative stress in neurodegenerative diseases;Beal;Annals of Neurology,1995

4. Lead identification of acetylcholinesterase inhibitors-histamine H3 receptor antagonists from molecular modeling;Bembenek;Bioorganic & Medicinal Chemistry,2008

5. Cholinesterase inhibitors for Alzheimer’s disease;Birks;Cochrane Database of Systematic Reviews,2006

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3