Wei-Bor Tsai

Dr. Wei-Bor Tsai

Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

34Years (1993-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 January 1999 in Journal of Biomedical Materials Research
Verified
Journal Article
Closed access
PDF file
Wei-Bor TsaiWei-Bor Tsai
Wei-Bor Tsai
JGJohn M. Grunkemeier
John M. Grunkemeier
THThomas A. Horbett
Thomas A. Horbett

1 December 2011 in Acta Biomaterialia
Verified
Journal Article
Closed access
Wei-Bor TsaiWei-Bor Tsai
Wei-Bor Tsai
WCWen-Tung Chen
Wen-Tung Chen
HCHsiu-Wen Chien
Hsiu-Wen Chien
WKWei-Hsuan Kuo
Wei-Hsuan Kuo
MWMeng-Jiy Wang
Meng-Jiy Wang


6 February 2002 in Journal of Biomedical Materials Research
Verified
Journal Article
Closed access
PDF file
Wei-Bor TsaiWei-Bor Tsai
Wei-Bor Tsai
JGJohn M. Grunkemeier
John M. Grunkemeier
CMClive D. McFarland
Clive D. McFarland
THThomas A. Horbett
Thomas A. Horbett

21 January 2011 in Journal of Biomedical Science
Verified
Journal Article
Open access
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SLShin-Hua Lu
Shin-Hua Lu
JWJosephine W Wu
Josephine W Wu
HLHsuan-Liang Liu
Hsuan-Liang Liu
JZJian-Hua Zhao
Jian-Hua Zhao
KLKung-Tien Liu
Kung-Tien Liu
YHYih Ho
Yih Ho
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 Aβ 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.

1 September 2011 in Acta Biomaterialia
Verified
Journal Article
Closed access
PWPeng-Yuan Wang
Peng-Yuan Wang
Jiashing YuJiashing Yu
Jiashing Yu
JLJia-Hua Lin
Jia-Hua Lin
Wei-Bor TsaiWei-Bor Tsai
Wei-Bor Tsai