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Merck

An efficient assay for identification and quantitative evaluation of potential polysialyltransferase inhibitors.

The Analyst (2020-05-16)
Xiaoxiao Guo, Jodie R Malcolm, Marrwa M Ali, Goreti Ribeiro Morais, Steven D Shnyder, Paul M Loadman, Laurence H Patterson, Robert A Falconer
RÉSUMÉ

The polysialyltransferases (polySTs) catalyse the polymerisation of polysialic acid, which plays an important role in tumour metastasis. While assays are available to assess polyST enzyme activity, there is no methodology available specifically optimised for identification and quantitative evaluation of potential polyST inhibitors. The development of an HPLC-fluorescence-based enzyme assay described within includes a comprehensive investigation of assay conditions, including evaluation of metal ion composition, enzyme, substrate and acceptor concentrations, temperature, pH, and tolerance to DMSO, followed by validation using known polyST inhibitors. Thorough analysis of each of the assay components provided a set of optimised conditions. Under these optimised conditions, the experimentally observed Ki value for CMP, a competitive polyST inhibitor, was strongly correlated with the predicted Ki value, based on the classical Cheng-Prusoff equation [average fold error (AFE) = 1.043]. These results indicate that this assay can provide medium-throughput analysis for enzyme inhibitors with high accuracy, through determining the corresponding IC50 values with substrate concentration at the KM, without the need to perform extensive kinetic studies for each compound. In conclusion, an in vitro cell-free assay for accurate assessment of polyST inhibition is described. The utility of the assay for routine identification of potential polyST inhibitors is demonstrated, allowing quantitative measurement of inhibition to be achieved, and exemplified through assessment of full competitive inhibition. Given the considerable and growing interest in the polySTs as important anti-metastatic targets in cancer drug discovery, this is a vital tool to enable preclinical identification and evaluation of novel polyST inhibitors.

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