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Molecular design of cysteine protease reversible covalent inhibitors

Grant number: 17/13344-0
Support type:Research Grants - Visiting Researcher Grant - International
Duration: September 01, 2017 - November 01, 2017
Field of knowledge:Physical Sciences and Mathematics - Chemistry
Principal Investigator:Carlos Alberto Montanari
Grantee:Carlos Alberto Montanari
Visiting researcher: Peter Wedderburn Kenny
Visiting researcher institution: AstraZeneca, United Kingdom, England
Home Institution: Instituto de Química de São Carlos (IQSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:13/18009-4 - Molecular design, synthesis and trypanocidal activity of cruzain reversible covalent inhibitors, AP.TEM

Abstract

Cysteine proteases are important therapeutic targets in a range of human diseases, including Chagas disease (cruzain) and various cancers (cathepsins). We have an established research program for developing covalent cruzain inhibitors as novel trypanocidal agents. This program recently delivered a series of new potent chemical entities against cruzain. Two of the best compounds, Neq0593 and Neq0594, are better to one of the only two approved drugs for Chagas disease, albeit do not properly inhibit cruzain. Moreover, we discovered that Neq0643 (a Neq0594 analogue) also inhibits cathepsin L (CatL), a promising target for the prevention of metastasis in various cancers. Though these are promising leads, there is considerable room for optimisation, as well as for new chemotypes. Here we propose to combine our knowledge and expertise in covalent cruzain inhibition, with novel computational methods for hypothesis driven molecular design, for the discovery of new reversible covalent inhibitors of cruzain and CatL. We will focus on compounds containing an activated nitrile, an electrophile that is able to form a reversible covalent bond with the catalytic cysteine in the protease active site. The reversibility can alleviate risks of "off-target" binding that are present in most irreversible covalent inhibitors. We will design new libraries of nitriles, as well as focused libraries based on our inhibitors. We will computationally screen these libraries to select putative candidates designed for improved potency and specificity using our new state-of-art machine learning tools. The compounds will be assessed experimentally in vitro and in cell based assays and may lead to the first selective reversible covalent cruzain inhibitors. (AU)