3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity

© 2016 The Authors The data is obtained from exploring the modulatory activities of bioflavonoids on P-glycoprotein function by ligand-based approaches. Multivariate Linear-QSAR models for predicting the induced/inhibitory activities of the flavonoids were created. Molecular descriptors were initial...

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Main Authors: Pathomwat Wongrattanakamon, Vannajan Sanghiran Lee, Piyarat Nimmanpipug, Supat Jiranusornkul
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/56349
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-563492018-09-05T03:15:22Z 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity Pathomwat Wongrattanakamon Vannajan Sanghiran Lee Piyarat Nimmanpipug Supat Jiranusornkul Multidisciplinary © 2016 The Authors The data is obtained from exploring the modulatory activities of bioflavonoids on P-glycoprotein function by ligand-based approaches. Multivariate Linear-QSAR models for predicting the induced/inhibitory activities of the flavonoids were created. Molecular descriptors were initially used as independent variables and a dependent variable was expressed as pFAR. The variables were then used in MLR analysis by stepwise regression calculation to build the linear QSAR data. The entire dataset consisted of 23 bioflavonoids was used as a training set. Regarding the obtained MLR QSAR model, R of 0.963, R2=0.927, Radj2=0.900, SEE=0.197, F=33.849 and q2=0.927 were achieved. The true predictabilities of QSAR model were justified by evaluation with the external dataset (Table 4). The pFARs of representative flavonoids were predicted by MLR QSAR modelling. The data showed that internal and external validations may generate the same conclusion. 2018-09-05T03:15:22Z 2018-09-05T03:15:22Z 2016-12-01 Journal 23523409 2-s2.0-85020256412 10.1016/j.dib.2016.08.004 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020256412&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/56349
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Multidisciplinary
spellingShingle Multidisciplinary
Pathomwat Wongrattanakamon
Vannajan Sanghiran Lee
Piyarat Nimmanpipug
Supat Jiranusornkul
3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
description © 2016 The Authors The data is obtained from exploring the modulatory activities of bioflavonoids on P-glycoprotein function by ligand-based approaches. Multivariate Linear-QSAR models for predicting the induced/inhibitory activities of the flavonoids were created. Molecular descriptors were initially used as independent variables and a dependent variable was expressed as pFAR. The variables were then used in MLR analysis by stepwise regression calculation to build the linear QSAR data. The entire dataset consisted of 23 bioflavonoids was used as a training set. Regarding the obtained MLR QSAR model, R of 0.963, R2=0.927, Radj2=0.900, SEE=0.197, F=33.849 and q2=0.927 were achieved. The true predictabilities of QSAR model were justified by evaluation with the external dataset (Table 4). The pFARs of representative flavonoids were predicted by MLR QSAR modelling. The data showed that internal and external validations may generate the same conclusion.
format Journal
author Pathomwat Wongrattanakamon
Vannajan Sanghiran Lee
Piyarat Nimmanpipug
Supat Jiranusornkul
author_facet Pathomwat Wongrattanakamon
Vannajan Sanghiran Lee
Piyarat Nimmanpipug
Supat Jiranusornkul
author_sort Pathomwat Wongrattanakamon
title 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
title_short 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
title_full 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
title_fullStr 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
title_full_unstemmed 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity
title_sort 3d-qsar modelling dataset of bioflavonoids for predicting the potential modulatory effect on p-glycoprotein activity
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020256412&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/56349
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