The University of North Carolina at Chapel Hill proposes to establish the Carolina Exploratory Center for Cheminformatics Research (CECCR, or Center) to promote multidisciplinary, multi-institutional collaboration among researchers in computational chemistry, chemical biology, datamining, computer science, and statistics to address critical issues in Cheminformatics in the context of Molecular Libraries Initiative (MLI) at NIH This multi-investigator effort will be coordinated by the Laboratory of Molecular Modeling and the Cheminformatics Research Resource at UNC-Chapel Hill, led by Professor Alexander Tropsha. In the course of the planning stage, we shall develop technical strategies and administrative infrastructure for CECCR integrating most essential components of Cheminformatics resources. These components include the procedures to calculate molecular descriptors, biologically relevant diversity and similarity metrics, data analytical tools and specialized methodologies for chemical library design and virtual screening, and rigorously validated biological and ADMETox property predictors. Incorporating these components, the CECCR will establish and maintain an integrated publicly available Cheminformatics Workbench (ChemBench) to support experimental chemists in the Chemical Synthesis Centers and quantitative biologists in the Molecular Libraries Screening Centers Network (MLSCN). The Workbench which is intended as an data analytical extension to the PubChem ( will enable researchers to mine available chemical and biological data to rationally design new compounds or compound libraries with significantly enhanced hit rates in the corresponding screening experiments. To begin the implementation of current and developing best practices in Cheminformatics research and translate them into advanced computational tools, the planning stage for the CECCR will focus on the following Specific Aims: ? 1. Establish Productive Collaborating Environment for Participating Laboratories; ? 2. Investigate Multidisciplinary Approaches to Key Cheminformatics Issues; ? 3. Build a Prototypic Web Based Cheminformatics Workbench (ChemBench) ? ? ?

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Exploratory Grants (P20)
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Special Emphasis Panel (ZHG1-HGR-N (O))
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Ajay, Ajay
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University of North Carolina Chapel Hill
Schools of Pharmacy
Chapel Hill
United States
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Tang, Hao; Wang, Xiang Simon; Hsieh, Jui-Hua et al. (2012) Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening? Proteins 80:1503-21
Dong, Xialan; Ebalunode, Jerry O; Yang, Sheng-Yong et al. (2011) Receptor-based pharmacophore and pharmacophore key descriptors for virtual screening and QSAR modeling. Curr Comput Aided Drug Des 7:181-9
Baker, Nancy C; Hemminger, Bradley M (2010) Mining connections between chemicals, proteins, and diseases extracted from Medline annotations. J Biomed Inform 43:510-9
Walker, Theo; Grulke, Christopher M; Pozefsky, Diane et al. (2010) Chembench: a cheminformatics workbench. Bioinformatics 26:3000-1
Hajjo, Rima; Grulke, Christopher M; Golbraikh, Alexander et al. (2010) Development, validation, and use of quantitative structure-activity relationship models of 5-hydroxytryptamine (2B) receptor ligands to identify novel receptor binders and putative valvulopathic compounds among common drugs. J Med Chem 53:7573-86
Tang, Hao; Wang, Xiang S; Huang, Xi-Ping et al. (2009) Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation. J Chem Inf Model 49:461-76
Peterson, Yuri K; Wang, Xiang S; Casey, Patrick J et al. (2009) Discovery of geranylgeranyltransferase-I inhibitors with novel scaffolds by the means of quantitative structure-activity relationship modeling, virtual screening, and experimental validation. J Med Chem 52:4210-20
Ebalunode, Jerry Osagie; Zheng, Weifan (2009) Unconventional 2D shape similarity method affords comparable enrichment as a 3D shape method in virtual screening experiments. J Chem Inf Model 49:1313-20
Wang, Xiang S; Tang, Hao; Golbraikh, Alexander et al. (2008) Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F. J Chem Inf Model 48:997-1013
Ebalunode, Jerry Osagie; Ouyang, Zheng; Liang, Jie et al. (2008) Novel approach to structure-based pharmacophore search using computational geometry and shape matching techniques. J Chem Inf Model 48:889-901

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