Autodisplay technology can be used to facilitate enzyme inhibitors and library screening. Typical enzyme inhibitors have a high affinity for their target enzymes. Based on this basic principle, autodisplay technology can be developed into a drug discovery tool. In terms of Creative BioMart's autodisplay platform, we display the peptide library on the surface of E. coli cells, then label single cells with inhibitor structure by binding target enzymes, and finally select and classify labeled cells by FACS.
We conjugate the enzyme with fluorescent dyes and label the E. coli cells that display inhibitor activity through the affinity between the inhibitor and its target enzyme. Then flow cytometry will be used to sort the single cells expressing high-affinity inhibitors. The selected cells can then be used for cloning to produce enough cells for analysis or preparation purposes. Benefitting from the high copy number of E.coli surface molecules and the good viability and integrity of cells, E.coli-based autodisplay system has congenital advantages.
A peptide that is known to be an inhibitor (the lead) is expressed at the cell surface by autodisplay and tested for functionality.
Random libraries are generated by standard genetic engineering tools, where each cell of E. coli displays one distinct variant in high numbers.
The library of E. coli cells with different variants is screened by target enzyme labeling. Since an enzyme inhibitor has a high affinity to its target enzyme and as a consequence the enzyme has a high affinity to the inhibitor as well, the target enzyme will bind to an inhibiting structure expressed at the cell surface. If the target enzyme is coupled to a fluorescent dye (e.g., FITC), the cell displaying the appropriate variant can be sorted by FACS.
The cell selected by this procedure can be used for clonal production of cell quantities sufficient for, e.g., DNA sequence analysis and hence for the identification of a new lead structure.
Cathepsin G: related to the local destruction of connective tissue protein. Its inhibitors are expected to treat rheumatoid arthritis and other chronic inflammatory diseases. We modified the known peptide cathepsin G inhibitor P15. Firstly, we constructed an automatic display random database containing different p15 variants. Through the binding of inhibitors to target enzymes, fluorescent probes were used to specifically label potential inhibitors. After FACS identification, different new inhibitory lead structures of cathepsin G may be selected.
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