Literature DB >> 24325852

Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer's agents.

Pravin Ambure1, Supratik Kar1, Kunal Roy2.   

Abstract

Alzheimer's disease (AD) is turning out to be one of the lethal diseases in older people. Acetylcholinesterase (AChE) is a crucial target in designing of drugs against AD. The present in silico study was carried out to explore natural compounds as potential AChE inhibitors. Virtual screening, via drug-like ADMET filter, best pharmacophore model and molecular docking analyses, has been utilized to identify putative novel AChE inhibitors. The InterBioScreen's Natural Compound (NC) database was first filtered by applying drug-like ADMET properties and then with the pharmacophore-based virtual screening followed by molecular docking analyses. Based on docking score, interaction patterns and calculated activity, the final hits were selected and these consist of coumarin and non-coumarin classes of compounds. Few hits were found to have been already reported for their AChE inhibitory activity in different literatures confirming reliability of our pharmacophore model. The remaining hits are suggested to be potential AChE inhibitors for AD.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Acetylcholinesterase inhibitor; Alzheimer's disease; Molecular docking; Pharmacophore mapping; QSAR; Virtual screening

Mesh:

Substances:

Year:  2013        PMID: 24325852     DOI: 10.1016/j.biosystems.2013.12.002

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  8 in total

1.  2D-SAR and 3D-QSAR analyses for acetylcholinesterase inhibitors.

Authors:  Bing Niu; Manman Zhao; Qiang Su; Mengying Zhang; Wei Lv; Qin Chen; Fuxue Chen; Dechang Chu; Dongshu Du; Yuhui Zhang
Journal:  Mol Divers       Date:  2017-03-09       Impact factor: 2.943

2.  Combined 3D-QSAR, molecular docking, and molecular dynamics study of tacrine derivatives as potential acetylcholinesterase (AChE) inhibitors of Alzheimer's disease.

Authors:  An Zhou; Jianping Hu; Lirong Wang; Guochen Zhong; Jian Pan; Zeyu Wu; Ailing Hui
Journal:  J Mol Model       Date:  2015-10-05       Impact factor: 1.810

3.  Virtual Screening and Hit Selection of Natural Compounds as Acetylcholinesterase Inhibitors.

Authors:  Mariyana Atanasova; Ivan Dimitrov; Stefan Ivanov; Borislav Georgiev; Strahil Berkov; Dimitrina Zheleva-Dimitrova; Irini Doytchinova
Journal:  Molecules       Date:  2022-05-13       Impact factor: 4.927

4.  2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors.

Authors:  Manman Zhao; Lin Wang; Linfeng Zheng; Mengying Zhang; Chun Qiu; Yuhui Zhang; Dongshu Du; Bing Niu
Journal:  Biomed Res Int       Date:  2017-05-29       Impact factor: 3.411

5.  Multiple 3D-QSAR modeling, e-pharmacophore, molecular docking, and in vitro study to explore novel AChE inhibitors.

Authors:  Srabanti Jana; Ankit Ganeshpurkar; Sushil Kumar Singh
Journal:  RSC Adv       Date:  2018-11-26       Impact factor: 4.036

6.  Integrating transcriptome and chemical analyses to reveal the anti-Alzheimer's disease components in Verbena officinalis Linn.

Authors:  Shuhuan Peng; Fangyi Li; Kuo Yu; Fengshu Zhou; Heshui Yu; Hui Liu; Jialiang Guo; Guoqiang Li; Chunhua Wang; Xiaohui Yan; Zheng Li
Journal:  Front Plant Sci       Date:  2022-08-04       Impact factor: 6.627

7.  Dual binding site and selective acetylcholinesterase inhibitors derived from integrated pharmacophore models and sequential virtual screening.

Authors:  Shikhar Gupta; C Gopi Mohan
Journal:  Biomed Res Int       Date:  2014-06-25       Impact factor: 3.411

8.  Guided Evolution of Recombinant Bombyx mori Acetylcholinesterase II by Homology Modeling to Change Pesticide Sensitivity.

Authors:  Jun Cai; Bingfeng Wang; Jiadong Li; Zijian Chen; Meifang Rao; Serge Muyldermans; Xiude Hua; Xi Xie; Hong Wang; Jinyi Yang; Zhenlin Xu; Yudong Shen; Yuanming Sun
Journal:  Int J Mol Sci       Date:  2018-10-27       Impact factor: 5.923

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.