The HaploInsufficiency Profiling (HIP) assay discovers protein targets of medically relevant compounds in a comprehensive and unbiased fashion. To determine the molecular target of a bioactive compound, a pool of approximately 6,000 yeast deletion strains is grown in the presence vs. absence of compound. Identifying the strains that are hypersensitive to a drug provides valuable information about the drug's mechanism of action. The power of the highly multiplexed HIP assay is that it provides a comprehensive systems-level analysis of how a drug impacts the biology of a eukaryotic cell. This project aims to develop a high-throughput commercial system that is flexible, scalable, and seamlessly integrates hardware, software and assay methods for HaploInsufficiency Profiling. The system will incorporate innovations and improvements in all three areas. It will allow the HIP assay to be run accurately, reliably and inexpensively. The ability to screen many thousands of compounds efficiently will allow the generation of large, high-quality datasets. This will enable more comprehensive analysis of structure-function relationships, and aid the discovery of important interactions between small molecules and proteins. This information is invaluable for basic scientific research and early-stage drug development. The new system will also make the assay much more accessible to the scientific community and will allow powerful new variations of the assay to be developed and new applications to be explored. Traditional approaches to drug development are inefficient, and there is a pressing human health need for new information-rich technologies that can improve the process of identifying and validating targets and developing new drugs for important human diseases. This powerful and cost-effective chemical genomics technology has the potential to play a significant enabling role in basic research in systems biology and in drug development. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
2R44HG003788-02
Application #
7219097
Study Section
Special Emphasis Panel (ZRG1-GGG-J (10))
Program Officer
Ozenberger, Bradley
Project Start
2005-09-25
Project End
2008-08-31
Budget Start
2006-09-25
Budget End
2007-08-31
Support Year
2
Fiscal Year
2006
Total Cost
$502,394
Indirect Cost
Name
Prognosys Biosciences, Inc.
Department
Type
DUNS #
170943737
City
La Jolla
State
CA
Country
United States
Zip Code
92121
Smith, Andrew M; Heisler, Lawrence E; Mellor, Joseph et al. (2009) Quantitative phenotyping via deep barcode sequencing. Genome Res 19:1836-42