? The long-term objective of this project is to develop computational algorithms and software to gain theoretical and empirical insights in the use of chemical diversity for determining quantitative structure-activity relationships (QSARs). In addition to addressing scientific and technical goals with respect to QSAR modeling, planning-period tasks will include specific activities to bring together the researchers and to facilitate inter-disciplinary communication. ? ? Specific Aim 1 is to develop and enhance collaborations between three broad disciplines: statistics, computer science, and chemistry. This will be accomplished primarily through several intense workshops per year and regularly scheduled status meetings. ? ? Specific Aim 2 is to initiate a benchmarking study to compare structural descriptors, modeling strategies, and methods of model assessment. Through a web server, results will be posted from analyzing several datasets using many QSAR modeling techniques, a variety of molecular descriptors, and a number of assessment criteria. ? ? Specific Aim 3 is to design and beta-test web-accessibility of modeling software. PowerMV, a cheminformatics software tool created at the National Institute of Statistical Sciences, will be upgraded and made web-accessible. ? ? And Specific Aim 4 is to develop a broad view of cheminformatics tools based on the singular value decomposition and other similar decompositions where computations take advantage of the high degree of sparseness often exhibited by HTS data sets. ? ? The significance of these specific aims, in support of the long-term objective, is to reduce resource requirements for, and thus streamline, the process of drug discovery. ? ?
? By reducing resource requirements for Lead Identification and Lead Optimization, which are two of the five phases of drug discovery, this project will help to streamline the entire discovery process. As a result, the nation's health and well-being will be improved because of the increased returns on research expenditures. These returns include decreasing the time for finding effective cures and/or treatments for diseases already being studied as well as increasing the number of diseases being studied. ? ?
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