Mimicking the secondary structures of proteins and peptides to modulate Protein-Protein Interactions

模仿蛋白质和肽的二级结构来调节蛋白质-蛋白质相互作用

• 批准号: RGPIN-2022-04028
• 负责人: Boudreault, PierreLuc
• 金额: $ 1.82万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=762064
• 关键词: Mimicking; secondary; structures; proteins; peptides

The human genome encodes for approximately 20,000 different proteins creating a vast network of potential protein-protein interactions (PPI), which is only partially characterized. The protein-protein interactome (network involving PPIs) is central to intracellular pathways and determines any given protein's role in physiology. Modulation of such PPI promises to shed light on the key molecular mechanisms within a biological system and is crucial to understanding how proteins perform cellular functions. At the heart of the program is the development of peptidomimetic molecules, i.e., molecules capable of mimicking the structure of peptides while advantageously adjusting their undesirable properties and the exploitation of computational sciences to analyze the dynamics of such scaffolds and to prioritize compounds to synthesize. 1. Diversity-oriented synthesis of hot-spot enriched PPI inhibitor library Meticulous analysis of the anatomy of PPIs has allowed to characterize the molecular features involved in recognition. We will take advantage of recent findings and our expertise in solid phase-support synthesis to develop a library of novel peptidomimetic PPI modulators designed to expose the same molecular recognition elements as over-represented side chains in hot-spots. These elements will be on scaffolds that provide a chemical space and shape appropriate for the PPI chemical space enriched with molecular recognition elements over-abundant in known PPI inhibitors. We performed a thorough in silico analysis to produce a class of compounds that possess the proper profile in terms of topology and molecular descriptors 2. Rational design and synthesis of secondary structures at PPI interface using 3D prediction approach. Recent advances in structural biology now allow us to elucidate, at the molecular level, the structure of complex macromolecular assemblies and characterize the interactions interface between proteins. Using an innovative and powerful 3D conformation prediction approach combining molecular dynamics, independent component analysis (tICA), and a Gaussian Mixture Hidden Markov Model (GM HMM) recently developed in our group, we will rationally design and synthesize epitope and secondary structures at PPI interfaces mimicking one of the two proteins of interest. This multidisciplinary research program at the interface of chemistry, biology, and computational science is expected to give superior hit rates compared to standard HTS libraries on PPI targets. Association of computational sciences and experimental evaluation will provide insights on the key interactions needed to access highly selective and efficient PPI modulators. Libraries are expected to become a versatile chemical biology set of tools used in phenotypic assays to decipher critical PPI pathways.

人类基因组编码大约20，000种不同的蛋白质，形成了一个巨大的潜在蛋白质-蛋白质相互作用（PPI）网络，这只是部分特征。蛋白质-蛋白质相互作用组（涉及PPI的网络）是细胞内途径的核心，并决定任何给定蛋白质在生理学中的作用。这种PPI的调节有望揭示生物系统中的关键分子机制，并且对于理解蛋白质如何执行细胞功能至关重要。该计划的核心是肽模拟分子的开发，即，能够模拟肽的结构同时有利地调节其不期望的性质的分子，以及利用计算科学来分析这种支架的动力学并优先考虑要合成的化合物。1.热点富集PPI抑制剂库的多样性导向合成PPI的解剖结构的METERY分析已经允许表征参与识别的分子特征。我们将利用最近的研究结果和我们在固相支持合成方面的专业知识，开发一个新的拟肽PPI调节剂库，该调节剂旨在暴露与热点中过度代表的侧链相同的分子识别元件。这些元件将位于支架上，所述支架提供适合于PPI化学空间的化学空间和形状，所述PPI化学空间富含在已知PPI抑制剂中过量的分子识别元件。我们进行了彻底的计算机分析，以产生一类在拓扑结构和分子描述符2方面具有适当特征的化合物。利用三维预测方法合理设计和合成PPI界面二级结构。结构生物学的最新进展使我们能够在分子水平上阐明复杂大分子组装体的结构，并表征蛋白质之间的相互作用界面。使用一种创新的和强大的三维构象预测方法，结合分子动力学，独立成分分析（tICA），和高斯混合隐马尔可夫模型（GM HMM）最近在我们的小组开发，我们将合理地设计和合成表位和二级结构在PPI接口模仿两个感兴趣的蛋白质之一。这个多学科的研究计划在化学，生物学和计算科学的接口，预计将提供上级命中率相比，标准的HTS库PPI目标。计算科学和实验评估协会将提供有关获得高度选择性和有效的PPI调节剂所需的关键相互作用的见解。文库有望成为表型分析中用于破译关键PPI途径的多功能化学生物学工具集。