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DC Field | Value | Language |
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dc.contributor.author | Nunthanavanit P. | |
dc.contributor.author | Anthony N.G. | |
dc.contributor.author | Johnston B.F. | |
dc.contributor.author | Mackay S.P. | |
dc.contributor.author | Ungwitayatorn J. | |
dc.date.accessioned | 2021-04-05T04:31:58Z | - |
dc.date.available | 2021-04-05T04:31:58Z | - |
dc.date.issued | 2008 | |
dc.identifier.issn | 3656233 | |
dc.identifier.other | 2-s2.0-50949092681 | |
dc.identifier.uri | https://ir.swu.ac.th/jspui/handle/123456789/14850 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-50949092681&doi=10.1002%2fardp.200700229&partnerID=40&md5=2a49c59d1f6f111004e25d0b3640205e | |
dc.description.abstract | Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for chromone derivatives against HIV-1 protease using molecular field analysis (MFA) with genetic partial least square algorithms (G/PLS). Three different alignment methods: field fit, pharmacophore-based, and receptor-based were used to derive three MFA models. All models produced good predictive ability with high cross-validated r2 (r2 cv), conventional r2, and predictive r2 (r 2pred) values. The receptor-based MFA showed the best statistical results with r2cv = 0.789, r2 = 0.886, and r2pred = 0.995. The result obtained from the receptor-based model was compared with the docking simulation of the most active compound 21 in this chromone series to the binding pocket of HIV-1 protease (PDB entry 1AJX). It was shown that the MFA model related well with the binding structure of the complex and can provide guidelines to design more potent HIV-1 protease inhibitors. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA. | |
dc.subject | chromone derivative | |
dc.subject | proteinase inhibitor | |
dc.subject | chromone derivative | |
dc.subject | p16 protease, Human immunodeficiency virus 1 | |
dc.subject | proteinase | |
dc.subject | proteinase inhibitor | |
dc.subject | article | |
dc.subject | drug protein binding | |
dc.subject | molecular model | |
dc.subject | pharmacophore | |
dc.subject | predictive validity | |
dc.subject | priority journal | |
dc.subject | quantitative structure activity relation | |
dc.subject | simulation | |
dc.subject | three dimensional imaging | |
dc.subject | algorithm | |
dc.subject | binding site | |
dc.subject | chemical structure | |
dc.subject | chemistry | |
dc.subject | conformation | |
dc.subject | drug design | |
dc.subject | regression analysis | |
dc.subject | Algorithms | |
dc.subject | Binding Sites | |
dc.subject | Chromones | |
dc.subject | Drug Design | |
dc.subject | HIV Protease | |
dc.subject | HIV Protease Inhibitors | |
dc.subject | Least-Squares Analysis | |
dc.subject | Models, Molecular | |
dc.subject | Molecular Conformation | |
dc.subject | Quantitative Structure-Activity Relationship | |
dc.title | 3D-QSAR studies on chromone derivatives as HIV-1 protease inhibitors: Application of molecular field analysis | |
dc.type | Article | |
dc.rights.holder | Scopus | |
dc.identifier.bibliograpycitation | Archiv der Pharmazie. Vol 341, No.6 (2008), p.357-364 | |
dc.identifier.doi | 10.1002/ardp.200700229 | |
Appears in Collections: | Scopus 1983-2021 |
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