Literature DB >> 11831910

Computational studies on tetrahydropyrimidine-2-one HIV-1 protease inhibitors: improving three-dimensional quantitative structure-activity relationship comparative molecular field analysis models by inclusion of calculated inhibitor- and receptor-based properties.

Anil C Nair1, Philippa Jayatilleke, Xia Wang, Stanislav Miertus, William J Welsh.   

Abstract

A computational chemistry study has been performed on a series of tetrahydropyrimidine-2-ones (THPs) as HIV-1 protease (HIV-1 PR) inhibitors. The present investigation focuses on the correlation of inhibitor-enzyme complexation energies (E(compl)), inhibitor solvation energies E(solv)[I], and both polar and nonpolar buried surface areas (BSAs) with the observed values of the binding affinity (pK(I)). Various combinations of these specific inhibitor- and receptor-based properties were also evaluated as additional descriptors to three-dimensional quantitative structure-activity relationship (3D-QSAR) models constructed using comparative molecular field analysis (CoMFA). Linear regression of the observed pK(I) values with E(compl), E(solv)[I], and the BSAs yielded a strong correlation in terms of both self-consistency (r(2) approximately equal to 0.90) and internal predictive ability (r(cv)(2) > 0.50). The 3D-QSAR models obtained from CoMFA using standard partial least-squares (PLS) analysis also yielded a strong correlation between the CoMFA fields and the experimental pK(i) (r(2) = 0.96; r(cv)(2) = 0.58). Various "enhanced" 3D-QSAR models were constructed in which different combinations of the E(compl), E(solv)[I], and BSAs were added as additional descriptors to the default steric-electrostatic CoMFA fields. Inclusion of E(solv)[I] in particular yielded significant improvement in the predictive ability (r(cv)(2) approximately equal to 0.80) of the resultant 3D-QSAR model.

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Year:  2002        PMID: 11831910     DOI: 10.1021/jm010417v

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  7 in total

1.  Structure-based phenotyping predicts HIV-1 protease inhibitor resistance.

Authors:  Mark D Shenderovich; Ron M Kagan; Peter N R Heseltine; Kal Ramnarayan
Journal:  Protein Sci       Date:  2003-08       Impact factor: 6.725

2.  3D-QSAR illusions.

Authors:  Arthur M Doweyko
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

3.  Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis.

Authors:  Anna Maria Almerico; Marco Tutone; Antonino Lauria
Journal:  J Comput Aided Mol Des       Date:  2008-02-14       Impact factor: 3.686

4.  Quantitative structure-activity relationship by CoMFA for cyclic urea and nonpeptide-cyclic cyanoguanidine derivatives on wild type and mutant HIV-1 protease.

Authors:  Speranta Avram; Cristian Bologa; Maria-Luiza Flonta
Journal:  J Mol Model       Date:  2005-02-16       Impact factor: 1.810

5.  Optimal drug cocktail design: methods for targeting molecular ensembles and insights from theoretical model systems.

Authors:  Mala L Radhakrishnan; Bruce Tidor
Journal:  J Chem Inf Model       Date:  2008-05-27       Impact factor: 4.956

6.  Correlation between the predicted and the observed biological activity of the symmetric and nonsymmetric cyclic urea derivatives used as HIV-1 protease inhibitors. A 3D-QSAR-CoMFA method for new antiviral drug design.

Authors:  Speranta Avram; I Svab; C Bologa; Maria-Luiza Flonta
Journal:  J Cell Mol Med       Date:  2003 Jul-Sep       Impact factor: 5.310

7.  Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties.

Authors:  Dipankar Sengupta; Deeptak Verma; Pradeep K Naik
Journal:  J Biosci       Date:  2007-12       Impact factor: 1.826

  7 in total

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