May 25, 2012
For millennia, mankind has discovered new drugs either through educated guesswork or blind luck. But with the proliferation of advanced computing, a new paradigm has emerged whereby one can find drug targets through simulation and modeling.
Chandrajit Bajaj, professor of computer science at The University of Texas at Austin has been integrally involved in these efforts for more than 20 years. Computational and Applied Mathematics chair in Visualization and director of the Computational Visualization Center at UT's Institute for Computational Engineering and Sciences (ICES), over his career Bajaj has systematically attacked each step of the drug discovery process, improving the speed and accuracy of the algorithms involved in computational drug discovery. The research has been sponsored by the National Institute of Health, the National Science Foundation, and the Texas Institute of Drug and Diagnostic Development.
A combination of modeling, simulation, analysis and visualization, the process is accomplished through the expert application of biophysical algorithms and the high-performance, parallel-processing supercomputers of the Texas Advanced Computing Center's (TACC).
"Computers are a good way to accelerate the process of drug design," said Bajaj. "It takes 10 years to proof out a drug, and a billion dollars or more. Hence computational drug discovery is not only timesaving, but economics tells you this is the way we should be going."
For the rest of the story, visit http://www.tacc.utexas.edu/news/feature-stories/2012/molecular-matchmaking.
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Source: TTexas Advanced Computing Center (TACC)
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