The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies

Shin Hua Lu, Josephine W. Wu, Hsuan Liang Liu, Jian Hua Zhao, Kung Tien Liu, Chih Kuang Chuang, Hsin Yi Lin, Wei Bor Tsai, Yih Ho

研究成果: 雜誌貢獻文章

86 引文 (Scopus)

摘要

Background: Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. Methods. In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. Results: The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high Güner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from A toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. Conclusions: The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.

原文英語
文章編號8
期刊Journal of Biomedical Science
18
發行號1
DOIs
出版狀態已發佈 - 2011

指紋

Cholinesterase Inhibitors
Acetylcholinesterase
Screening
Cholinergic Agents
Alzheimer Disease
Workflow
Studios
Bioactivity
Neurons
Toxicity
Dementia
Hydrogen
Catalytic Domain
Consensus
Hydrogen bonds
Binding Sites
Tissue Donors
Databases
Molecules

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Molecular Biology
  • Cell Biology
  • Biochemistry, medical
  • Endocrinology, Diabetes and Metabolism
  • Pharmacology (medical)

引用此文

The discovery of potential acetylcholinesterase inhibitors : A combination of pharmacophore modeling, virtual screening, and molecular docking studies. / Lu, Shin Hua; Wu, Josephine W.; Liu, Hsuan Liang; Zhao, Jian Hua; Liu, Kung Tien; Chuang, Chih Kuang; Lin, Hsin Yi; Tsai, Wei Bor; Ho, Yih.

於: Journal of Biomedical Science, 卷 18, 編號 1, 8, 2011.

研究成果: 雜誌貢獻文章

Lu, Shin Hua ; Wu, Josephine W. ; Liu, Hsuan Liang ; Zhao, Jian Hua ; Liu, Kung Tien ; Chuang, Chih Kuang ; Lin, Hsin Yi ; Tsai, Wei Bor ; Ho, Yih. / The discovery of potential acetylcholinesterase inhibitors : A combination of pharmacophore modeling, virtual screening, and molecular docking studies. 於: Journal of Biomedical Science. 2011 ; 卷 18, 編號 1.
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abstract = "Background: Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. Methods. In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. Results: The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high G{\"u}ner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from A toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. Conclusions: The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.",
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AU - Zhao, Jian Hua

AU - Liu, Kung Tien

AU - Chuang, Chih Kuang

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N2 - Background: Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. Methods. In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. Results: The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high Güner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from A toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. Conclusions: The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.

AB - Background: Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. Methods. In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. Results: The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high Güner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from A toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. Conclusions: The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.

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