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. ? ? ?
| Smith, Andrew M; Heisler, Lawrence E; Mellor, Joseph et al. (2009) Quantitative phenotyping via deep barcode sequencing. Genome Res 19:1836-42 |
