Predictive QSAR modeling on tetrahydropyrimidine-2-one derivatives as HIV-1 protease enzyme inhibitors
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Med Chem Res DOI 10.1007/s00044-012-0275-8
ORIGINAL RESEARCH
Predictive QSAR modeling on tetrahydropyrimidine-2-one derivatives as HIV-1 protease enzyme inhibitors Jimish R. Patel • Laxman M. Prajapati
Received: 14 June 2012 / Accepted: 9 October 2012 Ó Springer Science+Business Media New York 2012
Abstract QSAR model development of 51 tetrahydropyrimidine-2-one was carried out to predict HIV-1 protease receptors inhibitors activity. Physicochemical parameters were calculated using DRAGON descriptor software, version 5.5. Stepwise multiple linear regression analysis was applied to derive QSAR models, which were further evaluated for statistical significance and predictive power by internal and external validation. The best quantitative structure activity relationship model having a correlation coefficient (R2) of 0.824, cross-validated correlation coefficient (Q2) of 0.773, and R2pred of 0.910 was selected. The predictive ability of the selected model was also confirmed by leave-one-out cross-validation. The QSAR model indicates that the descriptors (RDF010u, RDF010m, TPSA (NO), F04[C–N]) play an important role in enzyme binding. The information derived from the present study may be useful in the design of more potent substituted tetrahydropyrimidine-2-one. Keywords QSAR Tetrahydropyrimidine-2-one HIV-1 protease inhibitors Multiple linear regressions HIV
Introduction Human immune deficiency virus (HIV) is the causative agent for acquired immune deficiency syndrome (AIDS)
J. R. Patel (&) L. M. Prajapati Department of Pharmaceutical Chemistry, Shri B M Shah College of Pharmaceutical Education and Research, College Campus, Modasa 383315, Gujarat, India e-mail: [email protected]
which causes loss of helper T lymphocytes and heavy damage to lymphatic tissues (WHO/UNAIDS, 2003). HIV drugs mainly can be classified into three classes: nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors (PIs) (Williams, 2003). PIs saquinavir, ritonavir, indinavir, nelfinavir, and amprenavir have been approved as anti AIDS drugs (Rang et al., 2007). These drugs were found to be very useful in reducing the viral load and improving the CD4 cell counts in AIDS patients. However, rapid emergence of drug resistance has been reported for all PIs currently in clinical use due to site specific mutation in the enzyme (Boden and Markowitz, 1998; Condra et al., 1995; Ala et al., 1997). PIs are potent antiretroviral drugs recommended as part of the ‘‘preferred regimen’’ for patients in the guidelines of the International AIDS Society-USA (IAS-USA) and the Department of Health and Human Services (DHHS) (Guidelines, 2011, Thompson et al., 2010). Inhibition of the HIV protease is one of the most important approaches for the therapeutic intervention in HIV infection (Chen, 2003), and their development is regarded as major success of structurebased drug design (Adachi, 2009). They are highly effective against HIV (Yanchunas, 2005). Further the intr
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