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Rapid identification of substrates for novel proteases using a combinatorial peptide library
1Preclinical Research, Pharma Division, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland. Gerard.Rosse@Aventis.com
Journal of Combinatorial Chemistry
|October 13, 2000
Summary
Rapidly identify novel enzyme substrates using a novel solid-phase combinatorial assay. This technology accelerates drug discovery by enabling faster development of high-throughput screening assays for proteases.
Area of Science:
- Biochemistry
- Enzymology
- Drug Discovery
Background:
- Proteolytic enzymes play crucial roles in biological processes.
- Identifying specific substrates for novel proteases is essential for understanding their function and for drug development.
- Existing methods for substrate identification can be time-consuming and inefficient.
Purpose of the Study:
- To develop and validate a rapid, solid-phase combinatorial assay for identifying fluorogenic substrates of novel proteolytic enzymes.
- To demonstrate the utility of this technology for discovering substrates for enzymes of pharmaceutical relevance, such as human napsin A.
Main Methods:
- Utilized a solid-phase combinatorial assay technology with intramolecularly quenched fluorogenic peptide libraries.
- Validated the methodology using leader peptidase from Escherichia coli.
- Extended the technique to screen peptide libraries against extracts of cells expressing recombinant human napsin A.
Main Results:
- Successfully identified potent fluorogenic substrates for leader peptidase and human napsin A.
- Demonstrated the efficiency of using cell extracts expressing recombinant enzymes for screening.
- Validated the rapid optimization of protease substrates using this approach.
Conclusions:
- The developed solid-phase combinatorial assay is an effective and rapid method for identifying novel protease substrates.
- This technology significantly facilitates drug discovery by accelerating the development of high-throughput screening assays.
- The approach enables better utilization of genomic and combinatorial chemistry data for enzyme-targeted drug development.