Abstract
A structure-activity relationship (SAR) dataset was generated for a set of acetylcholinesterase inhibitors using Adaboost and physicochemical parameters. After calculation, it is found that the ACC of SAR model is 99.51 by using 10-fold cross-validation test, while 99.35% for independent test set. Based on the SAR prediction model, bakuchiol is predicted to be an acetylcholinesterase inhibitor. Fluorescence was used to investigate the binding between bakuchiol and acetylcholinesterase, which can provide valuable qualitative and quantitative information about the interaction between acetylcholinesterase and bakuchiol.
Keywords: Molecular descriptors, acetylcholinesterase, bakuchiol, Adaboost.
Current Bioinformatics
Title:Prediction of an Interaction between Bakuchiol and Acetylcholinesterase using Adaboost
Volume: 11 Issue: 1
Author(s): Can Zhang, Xueyuan Wang, Lei Gu, Li Jiang, Qiang Su, Manman Zhao, Linfeng Zheng, Ling Tang, Fuxue Chen and Bing Niu
Affiliation:
Keywords: Molecular descriptors, acetylcholinesterase, bakuchiol, Adaboost.
Abstract: A structure-activity relationship (SAR) dataset was generated for a set of acetylcholinesterase inhibitors using Adaboost and physicochemical parameters. After calculation, it is found that the ACC of SAR model is 99.51 by using 10-fold cross-validation test, while 99.35% for independent test set. Based on the SAR prediction model, bakuchiol is predicted to be an acetylcholinesterase inhibitor. Fluorescence was used to investigate the binding between bakuchiol and acetylcholinesterase, which can provide valuable qualitative and quantitative information about the interaction between acetylcholinesterase and bakuchiol.
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Cite this article as:
Zhang Can, Wang Xueyuan, Gu Lei, Jiang Li, Su Qiang, Zhao Manman, Zheng Linfeng, Tang Ling, Chen Fuxue and Niu Bing, Prediction of an Interaction between Bakuchiol and Acetylcholinesterase using Adaboost, Current Bioinformatics 2016; 11 (1) . https://dx.doi.org/10.2174/1574893611666151119220248
DOI https://dx.doi.org/10.2174/1574893611666151119220248 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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