The HIV-1 (Human Immunodeficiency Virus) is a member of the retroviral family which contains a single- stranded RNA genome and is considered the major etiological agent involved in the development of acquired immunodeficiency syndrome or AIDS. The World Health Organization now estimates that in 2011 over 40 million people worldwide are infected and that this number is projected to increase. While there has been much progress over the past decade, there continues to be a significant need for new therapeutic strategies, new drugs and new drug combinations to combat this disease. There are a number of potential steps in the life cycle of the HIV virus that have been targeted with major efforts centered around HIV reverse transcriptase (RT), HIV protease, and more recently viral entry, attachment, and integration. The drugs that target HIV-1 RT are divided into two classes: nucleoside inhibitors (NRTIs) and non- nucleoside inhibitors (NNRTIs). Drugs targeting RT remain a cornerstone of AIDS therapy as approximately 90% of conventional therapeutic regimens include either NRTIs and/or NNRTIs. The rapid development of drug resistance by the error prone RT and issues of viral versus host polymerase selectivity necessitate the discovery of more effective NRTIs and NNRTIs with improved safety, pharmacological, and drug resistance profiles. The PIs lab, along with an established set of collaborators, has developed a distinctive and successful computationally and mechanistically guided approach for the discovery of new HIV RT inhibitors. This partnership of computational and detailed experimental methodologies is a unique strategy that builds optimal physiochemical and pharmacological parameters into the design. These molecules are then experimentally tested and the design iteratively refined through mechanistic, structural and cellular evaluation. This multidisciplinary effort has lead to the identification of a number of potent new NNRTIs including one class that has a novel mode of binding, picomolar antiviral activity, and a wide margin of cellular safety. These compounds are now poised for more comprehensive lead optimization, preclinical studies, and evaluation in a humanized HIV-infected mouse model.
The World Health Organization estimates that at end of 2011 over 30 million people worldwide are infected and this number is growing. There continues to be a significant need for new drugs and drug combinations to combat this disease. A great deal of effort to develop drugs against HIV has centered around the molecular target, HIV reverse transcriptase (RT). The studies outlined in this proposal will combine mechanistic studies with computational guidance to design more effective therapies that have improved therapeutic properties.
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