Deconstructing Best-in-Class Neoglycoclusters as a Tool for Dissecting Key Multivalent Processes in Glycosidase Inhibition.

Yan Liang,Rosaria Schettini,Nicolas Kern, Luca Manciocchi,Irene Izzo, Martin Spichty,Anne Bodlenner,Philippe Compain

Chemistry (Weinheim an der Bergstrasse, Germany)(2024)

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摘要
Multivalency represents an appealing option to modulate selectivity in enzyme inhibition and transform moderate glycosidase inhibitors into highly potent ones. The rational design of multivalent inhibitors is however challenging because global affinity enhancement relies on several interconnected local mechanistic events, whose relative impact is unknown. So far, the largest multivalent effects ever reported for a non-polymeric glycosidase inhibitor have been obtained with cyclopeptoid-based inhibitors of Jack bean α-mannosidase (JBα-man). Here, we report a structure-activity relationship (SAR) study based on the top-down deconstruction of best-in-class multivalent inhibitors. This approach provides a valuable tool to understand the complex interdependent mechanisms underpinning the inhibitory multivalent effect. Combining SAR experiments, binding stoichiometry assessments, thermodynamic modelling and atomistic simulations allowed us to establish the significant contribution of statistical rebinding mechanisms and the importance of several key parameters, including inhitope accessibility, topological restrictions, and electrostatic interactions. Our findings indicate that strong chelate-binding, resulting from the formation of a cross-linked complex between a multivalent inhibitor and two dimeric JBα-man molecules, is not a sufficient condition to reach high levels of affinity enhancements. The deconstruction approach thus offers unique opportunities to better understand multivalent binding and provides important guidelines for the design of potent and selective multiheaded inhibitors.
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关键词
atomistic simulations,glycosidase,iminosugar,multivalency,thermodynamic modeling
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