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Division of Program Coordination, Planning, and Strategic Initiatives (DPCPSI) National Institutes of Health  •  U.S. Department of Health and Human Services

NIH Challenge Grants in Health and Science Research (RFA-OD-09-003)

(15) Translational Science

Topics in the table below that are marked with an asterisk (*) have been designated as the Institute, Center or Office’s highest priority; however, applicants may apply to any of the topics.

Challenge Topic ID Specific Challenge Topic Contact
15-OD-101 Mouse and Metabolic profiling of MLPCN Probes. Metabolic profiling of probes identified through the Molecular Libraries program (https://mli.nih.gov/mli/mlp-probes/). Probes produced by the Molecular Libraries Probe Production Centers Network have the potential to be important research tools. Often, however, a barrier standing in the way of utilization of the probe is the need for optimization and/or characterization to enhance its effects on physiology and pathophysiology. The challenge is to optimize the probes to achieve adequate bioavailability for use in animal models of disease to allow phenotypic profiling to assess the efficacy of the probe against an important target. The results of the work would increase the utility of the probes for identifying underlying mechanisms of disease, new potential therapeutic targets, and changes in gene expression in affected tissues. Dr. Ron Margolis (NIDDK)
301-594-8819
margolisr@mail.nih.gov
and
Dr. Dan Zaharevitz (NCI)
301-435-9172
ZaharevD@mail.nih.gov
15-OD-102 Analysis of PubChem data sets. The Molecular Libraries Probe Production Centers Network (MLPCN) implements high throughput screens for a number of biological targets and develops probe compounds from the results. The emphasis is on finding useful probes for a wide variety of targets rather than on an in depth investigation of each target or the interactions between them. The NIH will support projects based on MLPCN data available through Pub Chem (http://pubchem.ncbi.nlm.nih.gov) that combine informatics, chemical synthesis and non-high-throughput biological testing to enable the scientific community to take full advantage of the ML resources. Ajay
ajaydr@mail.nih.gov
National Human Genome Research Institute

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This page last reviewed: March 2, 2009