This proposal aims to develop software that will speed the optimization of lead candidates for new drugs. At present, high throughput screening enables pharmaceutical companies to discover rapidly and in significant number lead compounds for new medications. However, years of research and development are required to optimize these leads as suitable therapeutics. Our software will expedite this process by simulating the reactions of combinatorial chemistry that are used to optimize lead compounds and then using scoring functions to identify the most promising of the derivatives that are generated.
The software created in this research will accelerate the optimization of lead compounds for drug development by exploiting virtual combinatorial chemistry. The time savings in the development of any single drug will translate into millions of dollars. The market for this product includes anyone involved in drug discovery and development, ranging from established pharmaceutical companies to startup biotech concerns.
