DNDi T. cruzi fenarimol series dataset from which preclinical candidate EPL-BS0967 was identified (see also related datasets: CHEMBL3137386 and CHEMBL...
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ID: ALA3137440
Title: DNDi T. cruzi fenarimol series dataset from which preclinical candidate EPL-BS0967 was identified (see also related datasets: CHEMBL3137386 and CHEMBL2448688)
Authors: Martine Keenan, Paul W. Alexander, Jason H Chaplin, Michael J Abbott, Hugo Diao, Zhisen Wang, Wayne M Best, Catherine J Perez, Scott MJ Cornwall, Sarah K Keatley, RC Andrew Thompson, Susan A Charman, Karen L White, Eileen Ryan, Gong Chen, Jean-Robert Ioset, Thomas W von Geldern, Eric Chatelain
Abstract: Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. Results: We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. Conclusion: High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process. This is the dataset from which preclinical candidate EPL-BS0967 was identified.
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