Computational studies on HIV-1 protease inhibitors: Influence of calculated inhibitor-enzyme binding affinities on the statistical quality of 3D-QSAR CoMFA models
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作者:
Jayatilleke, PRN
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机构:Univ Missouri, Dept Chem, St Louis, MO 63121 USA
Jayatilleke, PRN
Nair, AC
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机构:Univ Missouri, Dept Chem, St Louis, MO 63121 USA
Nair, AC
Zauhar, R
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机构:Univ Missouri, Dept Chem, St Louis, MO 63121 USA
Zauhar, R
Welsh, WJ
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Univ Missouri, Dept Chem, St Louis, MO 63121 USAUniv Missouri, Dept Chem, St Louis, MO 63121 USA
Welsh, WJ
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机构:
[1] Univ Missouri, Dept Chem, St Louis, MO 63121 USA
[2] Univ Missouri, Ctr Mol Elect, St Louis, MO 63121 USA
[3] Univ Sci Philadelphia, Dept Chem & Biochem, Philadelphia, PA 19104 USA
A theoretical study was performed on a set of 38 human immunodeficiency type 1 (HIV-1) protease inhibitors that are structurally similar to the AIDS drug Indinavir. Comparison between the computed binding energies and experimental activity data (pIC(50)) found a high degree of correlation (r(2) = 0.82). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) yielded predicted activities that were in excellent agreement with the corresponding experimentally determined values. Inclusion of the calculated enzyme-inhibitor binding energy as an additional descriptor in the CoMFA model yielded a significant improvement in the internal predictive ability of our model (q(2) = 0.45 to q(2) = 0.69). Separate CoMFA models were constructed to evaluate the influence of different alignment schemes (Atom Fit and Field Fit) and different partial atomic charge assignment schemes (Discover CVFF, Gasteiger-Marsili, and AM1-ESP) on the statistical quality of the models.