After beginning scientific operations in 2005, the NCGC reached full staffing and production during the reporting year. The Center is now working with over 100 researchers worldwide, and during the year performed over 50 high-throughput screens on molecular targets and cellular phenotypes important for virtually every area of biology and disease, including cancer, heart disease, infectious diseases, and neurological disorders. During this year, the NCGC fully operationalized its titration-based Quantitative High Throughput Screening (qHTS) paradigm, and demonstrated that it significantly improves the efficiency of screening over conventional methods. The NCGC Informatics Division built an entirely new infrastructure to process and extract automated conclusions from the vast amount of data qHTS produces (routinely producing 2-5 million data points in a single experiment), and is preparing those programs for publication and dissemination. Also during the year, the NCGCs Chemistry Division reached full staffing, allowing the rich screening and informatics data to be used in medicinal chemistry optimization campaigns to develop and publish a variety of new chemical probes. Among these were a group of new chaperone leads for Gaucher Disease, a human lysosomal storage disease (published in PNAS 104:13192-7), Alzheimer Diease (published in Neurobiology of Disease doi:10.1016/j.nbd.2007.07.018), and Schistosomiasis (publication in press). In all, production metrics included >18,000,000 compounds screened, >2,250,000 concentration-response profiles generated, >233 million data points generated, and >21,000,000 data fields deposited into PubChem. ? ? The NCGC expanded its already-extensive outreach program during the year, in order to both educate the academic community about chemical genomics methods and capabilities, and assist researchers in their assay development efforts. NCGC staff delivered over 60 invited lectures worldwide during the year, from New York and Los Angeles to Japan, Germany, and Spain. In order to extend its educational reach further, the NCGC Assay Development Manual was updated and reached version 4.1 on the NCGC website (www.ncgc.nih.gov), and the NCGC published a comprehensive review of assay development for HTS in Nature Chemical Biology (3:466-79).

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Intramural Research (Z01)
Project #
1Z01HG200319-04
Application #
7594329
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
2007
Total Cost
$17,834,863
Indirect Cost
Name
National Human Genome Research Institute
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Capuzzi, Stephen J; Sun, Wei; Muratov, Eugene N et al. (2018) Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors. J Med Chem 61:3582-3594
Nilubol, Naris; Boufraqech, Myriem; Zhang, Lisa et al. (2018) Synergistic combination of flavopiridol and carfilzomib targets commonly dysregulated pathways in adrenocortical carcinoma and has biomarkers of response. Oncotarget 9:33030-33042
Slavov, Svetoslav; Stoyanova-Slavova, Iva; Li, Shuaizhang et al. (2017) Why are most phospholipidosis inducers also hERG blockers? Arch Toxicol :
Li, Hao; Sun, Wei; Huang, Xiuli et al. (2017) Efficient Synthesis of 1,9-Substituted Benzo[h][1,6]naphthyridin-2(1H)-ones and Evaluation of their Plasmodium falciparum Gametocytocidal Activities. ACS Comb Sci 19:748-754
Lal-Nag, Madhu; McGee, Lauren; Guha, Rajarshi et al. (2017) A High-Throughput Screening Model of the Tumor Microenvironment for Ovarian Cancer Cell Growth. SLAS Discov 22:494-506
Torimoto-Katori, Nao; Huang, Ruili; Kato, Harutoshi et al. (2017) In Silico Prediction of hPXR Activators Using Structure-Based Pharmacophore Modeling. J Pharm Sci 106:1752-1759
Wu, Leihong; Liu, Zhichao; Auerbach, Scott et al. (2017) Integrating Drug's Mode of Action into Quantitative Structure-Activity Relationships for Improved Prediction of Drug-Induced Liver Injury. J Chem Inf Model 57:1000-1006
Sun, Hongmao; Huang, Ruili; Xia, Menghang et al. (2017) Prediction of hERG Liability - Using SVM Classification, Bootstrapping and Jackknifing. Mol Inform 36:
Fuller, John A; Berlinicke, Cynthia A; Inglese, James et al. (2016) Use of a Machine Learning-Based High Content Analysis Approach to Identify Photoreceptor Neurite Promoting Molecules. Adv Exp Med Biol 854:597-603
Sakamuru, Srilatha; Attene-Ramos, Matias S; Xia, Menghang (2016) Mitochondrial Membrane Potential Assay. Methods Mol Biol 1473:17-22

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