TITLE:

COMPUTATIONAL APPROACHES IN HIV-PROTEASE DRUG DESIGN (No. 143)

DATE:

Friday, February 9th, 2007

TIME:

3:30 PM

LOCATION:

GMCS 214

SPEAKER:

Rajni Garg, Chemistry and Biochemistry Department,, Cal State, San Marcos, CA

ABSTRACT:

Acquired Immunodeficiency Syndrome (AIDS) and its related disorders, caused by retrovirus Human Immunodeficiency Virus (HIV) Type 1, are a major health concern worldwide. HIV Protease enzyme (protein) is one of the major viral targets for the development of new chemotherapeutics. Currently, many HIV protease inhibitor drugs are used in combination with other drugs. However, the use of current drug regimens has several shortcomings, such as adherence, tolerability, long-term toxicity, and drug- and cross-resistance (mutation). Therefore, the development of new HIV protease inhibitors that are less toxic, more tolerable, convenient and active against drug-resistant mutant viruses is highly desirable.
Computational approaches play a major role in lead optimization in drug discovery, design and development, which significantly reduces the time and cost. Some of these approaches involve quantitative structure-activity relationships (QSAR), molecular modeling (docking), pharmacophore mapping, structure/substructure searching, database development and data mining for predicting biological activity and other properties from chemical structure. Lately neural networks, pattern recognition, shape analysis and 3D graphics techniques are also being increasingly employed for multi-modality data analysis in order to understand the drug-receptor (drug-protein) interaction. In the first part of the talk I will present my current research using QSAR, neural network/machine learning, and molecular modeling techniques. The second part of the talk will focus on role of some of the emerging computational approaches in HIV drug design and development, including the design of Smart (mutant-resistant) drugs active against HIV.

HOST:

Jose Castillo

DOWNLOAD: