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Comparative QSAR as a Cheminformatics Tool in the Design of Dihydro- Pyranone Based HIV-1 Protease Inhibitors

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Protease is a key viral enzyme in the life cycle of retrovirus HIV-1. Different drug cocktails of HIV-1 protease inhibitors (HIV-PI) along with other drugs have improved the survival rate for HIV-1 infected patients. However, the difficult treatment schedule, adverse side effects & emergence of drug-resistant viral mutations make these drugs less efficient and have led to therapeutic failures. Quantitative Structure Activity Relationship (QSAR) studies are successfully used in drug design and development. In the present study, a cheminformatics analysis of simple QSAR models laterally validated via comparative QSAR approach is used to understand the inherent relationships between the dihydro-pyranone based HIV-1 protease inhibitors (HIV-PI) and their biological activity. This work focuses on the development history of more than 500 dihydro-pyranones based HIV-PIs from available literature to extract vital information. This cumulative quantitative study of the various substituents that were studied in this scaffold provides valuable mechanistic insight regarding its substituents' interaction with protease enzyme binding pockets. We hope this study will contribute significantly in understanding the binding patterns of drug-resistant mutants with Tipranavir, a recently FDA approved dihydropyranone based HIV-PI. In addition, it will be useful in the design of new inhibitors.





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Keywords: AIDS; Cheminformatics; HIV-1 protease inhibitors; QSAR; dihydropyranone; drug-resistant mutant HIV-1 protease; tipranavir

Document Type: Research Article

Publication date: December 1, 2008

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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