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KMID : 0043320170400101146
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Archives of Pharmacal Research
2017 Volume.40 No. 10 p.1146 ~ p.1155
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Adaptive neuro-fuzzy inference system-applied QSAR with bond dissociation energy for antioxidant activities of phenolic compounds
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Jhin Chang-Ho
Nho Chu-Won
Hwang Keum-Taek
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Abstract
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The aim of this study was to develop quantitative structure?activity relationship (QSAR) models for predicting antioxidant activities of phenolic compounds. The bond dissociation energy of O?H bond (BDE) was calculated by semi-empirical quantum chemical methods. As a new parameter for QSAR models, sum of reciprocals of BDE of enol and phenol groups (XBDE) was calculated. Significant correlations were observed between XBDE and antioxidant activities, and XBDE was introduced as a parameter for developing QSAR models. Linear regression-applied QSAR models and adaptive neuro-fuzzy inference system (ANFIS)-applied QSAR models were developed. QSAR models by both of linear regression and ANFIS achieved high prediction accuracies. Among the developed models, ANFIS-applied models achieved better prediction accuracies than linear regression-applied models. From these results, the proposed parameter of XBDE was confirmed as an appropriate variable for predicting and analysing antioxidant activities of phenolic compounds. Also, the ANFIS could be applied on QSAR models to improve prediction accuracy.
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KEYWORD
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Chinese medicinal plants, QSAR, Phenolic compounds, Antioxidants
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