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April Journal-2009.p65 - Association of Biotechnology and Pharmacy

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Current Trends in <strong>Biotechnology</strong> <strong>and</strong> <strong>Pharmacy</strong><br />

Vol. 3 (2) 149-154, <strong>April</strong> 2009. ISSN 0973-8916<br />

Prediction <strong>of</strong> HIV-1 Protease Inhibitory Activity <strong>of</strong> (4-Hydroxy-<br />

6-Phenyl-2-Oxo-2H-Pyran-3-yl) Thiomethanes: QSAR Study<br />

V. Ravich<strong>and</strong>ran a+ , Abhishek K. Jain a , V.K. Mourya b <strong>and</strong> R. K. Agrawal a *<br />

Department <strong>of</strong> Pharmaceutical Sciences, Dr. H. S. Gour University, Sagar (M.P.), India<br />

b<br />

Govt. College <strong>of</strong> <strong>Pharmacy</strong>, Osmanpura, Aurangabad, Maharashtra, India<br />

+Present Addres : Faculty <strong>of</strong> <strong>Pharmacy</strong>, AIMST University, Semeling - 08100, Kedah, Malaysia<br />

* For Correspondence - dragrawal2001@yahoo.co.in - phravi75@rediffmail.com<br />

Abstract<br />

In pursuit <strong>of</strong> better HIV-1 protease<br />

inhibitory agents, QSAR studies were performed<br />

on a series <strong>of</strong> (4-hydroxy-6-phenyl-2-oxo-2hpyran-3-yl)<br />

thiomethanes using WIN CAChe 6.1.<br />

Stepwise multiple linear regression analysis was<br />

performed to derive QSAR models which were<br />

further evaluated for statistical significance <strong>and</strong><br />

predictive power by internal <strong>and</strong> external<br />

validation. The best QSAR model was selected,<br />

having correlation coefficient (R) = 0.923 <strong>and</strong><br />

cross-validated squared correlation coefficient<br />

(q 2 ) = 0.743. The developed best QSAR model<br />

indicates that the hydrophobicity <strong>and</strong> ionization<br />

potential play an important role in the HIV-1<br />

protease inhibitory activities.<br />

Keywords: QSAR; HIV-1 protease inhibitory<br />

activity; multiple linear regressions;<br />

thiomethane.<br />

Introduction<br />

HIV- 1 (Human Immunodeficiency Virus<br />

Type-1) is the pathogenic retrovirus <strong>and</strong> causative<br />

agent <strong>of</strong> AIDS or AIDS- related complex (ARC)<br />

(1). When viral RNA is translated into a<br />

polypeptide sequence, it is assembled in a long<br />

polypeptide chain, which includes several<br />

individual proteins namely, reverse transcriptase,<br />

protease, integrase, etc. Before these enzymes<br />

become functional, they must be cut from the<br />

longer polypeptide chain.<br />

Acquired immune deficiency syndrome<br />

(AIDS) is a formidable p<strong>and</strong>emic that is still<br />

wreaking havoc world wide. The catastrophic<br />

potential <strong>of</strong> this virally caused disease may not<br />

have been fully realized. The causative moiety <strong>of</strong><br />

the disease is human immunodeficiency virus<br />

(HIV), which is a retrovirus <strong>of</strong> the lentivirus family<br />

(2). The three viral enzymes; reverse<br />

transcriptase, protease <strong>and</strong> integrase encoded by<br />

the group specific antigen <strong>and</strong> group specific<br />

antigen-polyprotein genes <strong>of</strong> HIV play an<br />

important role in the virus replication cycle.<br />

Among them, viral protease catalyzes the<br />

formation <strong>of</strong> viral functional enzymes <strong>and</strong> proteins<br />

necessary for its survival. The viral particles at<br />

this stage are called virions. The virus particles<br />

after the protease action have all the necessary<br />

constituents <strong>of</strong> mature virus <strong>and</strong> are capable <strong>of</strong><br />

invading other T4 cells <strong>and</strong> repeating the life cycle<br />

<strong>of</strong> proviral DNA from viral RNA, the key stage<br />

in viral replication. Its central role in virus<br />

maturation makes protease is a prime target for<br />

anti-HIV-therapy.<br />

Computational chemistry has developed<br />

into an important contributor to rational drug<br />

design. Quantitative structure activity relationship<br />

(QSAR) modeling results in a quantitative<br />

correlation between chemical structure <strong>and</strong><br />

biological activity. QSAR analyses <strong>of</strong> HIV-1<br />

reverse transcriptase inhibitors (3), HIV-1<br />

Prediction <strong>of</strong> HIV-1 Protease Inhibitory Activity

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