TY - JOUR
T1 - 3D-QSAR studies on chromone derivatives as HIV-1 protease inhibitors: application of molecular field analysis
AU - Nunthanavanit, Patcharawee
AU - Anthony, N.G.
AU - Johnston, B.F.
AU - Mackay, S.P.
AU - Ungwitayatorn, Jiraporn
PY - 2008/4/28
Y1 - 2008/4/28
N2 - 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 (r2cv), conventional r2, and predictive r2 (r2pred) 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.
AB - 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 (r2cv), conventional r2, and predictive r2 (r2pred) 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.
KW - alignment
KW - chromone derivatives
KW - HIV-1 protease
KW - molecular field analysis (MFA)
KW - 3D-QSAR
KW - Machine Learning
UR - http://dx.doi.org/10.1002/ardp.200700229
U2 - 10.1002/ardp.200700229
DO - 10.1002/ardp.200700229
M3 - Article
SN - 0365-6233
VL - 341
SP - 357
EP - 364
JO - Archiv der Pharmazie
JF - Archiv der Pharmazie
IS - 6
ER -