ANTICANCER DRUG DESIGN USING REDUCED VARIABLE DYNAMICS

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The purpose of this proposal is to apply innovative reduced variable simulation techniques to the design of novel molecular entities capable of specifically targeting DNA sequences of oncogenes and tumor suppressor genes. By reducing the time of each conformational study by better than an order of magnitude, many more molecules may be screened in a given period of time and more complete studies can be made correlating the discrete chemical transformations with pharmacologic data. This will result in a speed up in the formulation of a sound chemical rationale for the biochemical behavior of these drugs. Both the information gathered and the software methodologies developed will be of great scientific and commercial interest. There are currently no commercial molecular mechanics simulation packages that have the unique combination of speed, flexibility, and scaleability that these reduced variable algorithms possess. The ability to study more realistic systems will lead to an enhanced ability to design better anticancer drugs.