Synthesis of 5,6-Dihydropyran-2-ones as Potential Inhibitors of HIV-1 Protease

Presenter Information

Kristín Sigurjonsson
Jesse Nye

Document Type

Oral Presentation

Campus where you would like to present

SURC 135

Start Date

17-5-2012

End Date

17-5-2012

Abstract

Drug discovery and development for HIV/AIDS has led to groundbreaking anti-retroviral therapies including HIV-1 protease inhibitors. However, the rise in resistance to current treatments as well as issues regarding drug toxicity and affinity, generate a need for more effective inhibitory structures. This synthetic chemistry research builds on a previous research effort, in which HIV-1 protease inhibiting structures were designed using molecular modeling methods. Quantitative Structure-Activity Relationship (QSAR) was implemented using a fuzzy neural network to predict the biological activity for these compounds. We are synthesizing the novel structures through known methodologies. The inhibitory values of the target compounds will be determined and compared to the values predicted by the neural networks. We hope that the target compounds will possess better inhibitory properties, increased bioavailability and decreased toxicity compared to currently available inhibitors.

Faculty Mentor(s)

Levente Fabry-Asztalos

Additional Mentoring Department

Chemistry

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May 17th, 1:30 PM May 17th, 1:50 PM

Synthesis of 5,6-Dihydropyran-2-ones as Potential Inhibitors of HIV-1 Protease

SURC 135

Drug discovery and development for HIV/AIDS has led to groundbreaking anti-retroviral therapies including HIV-1 protease inhibitors. However, the rise in resistance to current treatments as well as issues regarding drug toxicity and affinity, generate a need for more effective inhibitory structures. This synthetic chemistry research builds on a previous research effort, in which HIV-1 protease inhibiting structures were designed using molecular modeling methods. Quantitative Structure-Activity Relationship (QSAR) was implemented using a fuzzy neural network to predict the biological activity for these compounds. We are synthesizing the novel structures through known methodologies. The inhibitory values of the target compounds will be determined and compared to the values predicted by the neural networks. We hope that the target compounds will possess better inhibitory properties, increased bioavailability and decreased toxicity compared to currently available inhibitors.