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基于热力学的药物设计:抑制蛋白-蛋白相互作用的策略。

Thermodynamics-based drug design: strategies for inhibiting protein-protein interactions.

机构信息

Department of Biology, The Johns Hopkins University, Baltimore, Maryland 21218, USA.

出版信息

Future Med Chem. 2011 Jul;3(9):1129-37. doi: 10.4155/fmc.11.81.

Abstract

The inhibition of protein-protein interactions and their ensuing signaling processes play an increasingly important role in modern medicine. Small molecular-weight inhibitors that can be administered orally are the preferred approach but efficient strategies for developing them are not yet generally available. Due to the large size difference between the protein-protein interface and the small molecule, inhibitor interactions are expected to extend to only a small region of the interface. If this is the case, classical competitive inhibition may be hard to achieve. In addition, competitive inhibition wastes binding energy that can be effectively used to inhibit signaling. The best and most energy-efficient approach would be the development of small molecules that bind at the protein-protein interface and inhibit the signaling process without displacing the protein ligand. This approach seems feasible knowing that the binding energy is not evenly distributed within the binding interface but concentrated in discrete hotspots, and that the initiation of signaling may not overlap with those hotspots. We outline a general protein-protein inhibition model that extends from competitive to noncompetitive scenarios and apply it to the development of HIV-1 gp120-CD4 inhibitors. This rigorous model can be easily applied to the analysis of protein-protein inhibition data and used as a tool in the optimization of inhibitor molecules.

摘要

蛋白质-蛋白质相互作用及其随后的信号转导过程在现代医学中起着越来越重要的作用。可口服的小分子抑制剂是首选方法,但开发它们的有效策略尚未普遍可用。由于蛋白质-蛋白质界面与小分子之间的大小差异很大,预计抑制剂的相互作用仅延伸到界面的一小部分区域。如果是这样,经典的竞争性抑制可能很难实现。此外,竞争性抑制浪费了可以有效用于抑制信号转导的结合能。最佳和最节能的方法是开发小分子,这些小分子结合在蛋白质-蛋白质界面上,并在不置换蛋白质配体的情况下抑制信号转导过程。考虑到结合能并非均匀分布在结合界面内,而是集中在离散的热点上,并且信号转导的启动可能与这些热点不重叠,我们概述了一个从竞争性到非竞争性情况的通用蛋白质-蛋白质抑制模型,并将其应用于 HIV-1 gp120-CD4 抑制剂的开发。这个严格的模型可以很容易地应用于蛋白质-蛋白质抑制数据的分析,并作为优化抑制剂分子的工具。

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