Laboratoire d'Innovation Moléculaire et Applications (LIMA), University of Strasbourg|University of Haute-Alsace|CNRS (UMR 7042), Equipe de Synthèse Organique et Molécules Bioactives (SYBIO), ECPM, 25 Rue Becquerel, 67087, Strasbourg, France).
Dipartimento di Chimica e Biologia "A. Zambelli", Università degli Studi di, Salerno, 84084, Fisciano (Salerno), Italy.
Chemistry. 2024 Apr 2;30(19):e202304126. doi: 10.1002/chem.202304126. Epub 2024 Feb 13.
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.
多价性是调节酶抑制选择性并将中等糖苷酶抑制剂转化为高活性抑制剂的一种有吸引力的选择。然而,多价抑制剂的合理设计具有挑战性,因为全局亲和力增强依赖于几个相互关联的局部机制事件,其相对影响尚不清楚。到目前为止,报道的非聚合糖苷酶抑制剂获得的最大多价效应是用环缩肽基 Jack bean α-甘露糖苷酶 (JBα-man) 的抑制剂获得的。在这里,我们报告了一项基于顶级解构的最佳多价抑制剂的构效关系 (SAR) 研究。这种方法提供了一种有价值的工具,可以了解支持抑制多价效应的复杂相互依存机制。结合 SAR 实验、结合化学计量评估、热力学建模和原子模拟,使我们能够确定统计再结合机制的重要贡献以及几个关键参数的重要性,包括结合物的可及性、拓扑限制和静电相互作用。我们的研究结果表明,多价抑制剂与两个二聚体 JBα-man 分子之间形成交联复合物导致的强螯合结合并不是达到高亲和力增强水平的充分条件。因此,解构方法为更好地理解多价结合提供了独特的机会,并为设计有效和选择性的多头抑制剂提供了重要的指导方针。