Computational inhibitor design to target protein-protein interactions

针对蛋白质-蛋白质相互作用的计算抑制剂设计

• 批准号: 9341364
• 负责人: Paramjit S Arora
• 金额: $ 37.12万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9341364
• 关键词: Affinity; Antineoplastic Agents; Binding; Binding Proteins; Bioinformatics; Biological; Biological Assay; Biological Process; Cell Culture Techniques; Cells; Complex; Computing Methodologies; Development; Disease; Docking; Drug Targeting; Enzymes; Free Energy; Gene Expression Regulation; Goals; Grant; Human Herpesvirus 8; Lead; Length; MDM2 gene; Malignant Neoplasms; Mediating; Membrane Proteins; Methodology; Methods; Modeling; Modification; Molecular Conformation; Molecular Models; Nature; Oncogenic; Pathogenesis; Phenotype; Play; Protein Engineering; Protein Inhibition; Proteins; Proteome; Ras Inhibitor; Reagent; Regulation; Resolution; Role; Signal Transduction; Site; Specificity; Surface; TP53 gene; Techniques; Tertiary Protein Structure; Testing; Therapeutic; Thermodynamics; Toxic effect; Tumor Suppressor Proteins; Work; base; computer studies; computerized tools; design; drug development; drug discovery; inhibitor/antagonist; innovation; mimetics; molecular dynamics; molecular modeling; novel; protein protein interaction; screening; simulation; small molecule; tool

Abstract: Protein-protein interactions (PPIs) are central factors in all cellular signaling and gene regulation protein networks, and their misregulation has been associated with a variety of diseases, notably cancer. Inevitably, many PPIs are biologically compelling targets for drug discovery. However, PPIs feature large, flat binding surfaces, lacking the tight-binding cavities that define typical drug targets. Accordingly, many PPIs pose a fundamental thermodynamic challenge to the development of conventional small molecule modulators. A promising PPI inhibitor discovery strategy is to use miniature protein domain mimetics (PDMs) to reproduce the key interface contacts utilized by nature. PDMs are advantageous as medium-sized molecules with high surface complementarity and a broader set of contact points than typical small molecules, but are still limited because—by definition—only a portion of the total PPI binding energy is captured in the interaction. The binding affinity of the synthetic domains is often lower than the cognate full-length proteins. Targeted covalent inhibition is an orthogonal therapeutic approach traditionally employed to enhance binding affinities of small molecules, but the approach has a potential drawback as the high reactivity of typical covalent warheads may lead to nonspecific interactions and toxicity. Here we propose to develop computational methods for a new design strategy that will leverage the strengths of these two methods—PDMs and covalent inhibition— while simultaneously mitigating their respective limitations. The focus of the effort is to rationally discover potent inhibitors that will non-covalently recognize and then covalently target protein- protein binding interfaces with exquisite specificity.

摘要： 蛋白质-蛋白质相互作用（PPIs）是所有细胞信号传导和基因调控的核心因素 蛋白质网络，它们的失调与各种疾病有关， 尤其是癌症。不可避免的是，许多PPI是药物发现的生物学强制性靶点。 然而，PPI的特点是大而平的结合表面，缺乏定义结合的紧密结合腔。 典型的药物靶点因此，许多PPI对生物学和生物化学构成了基本的热力学挑战。 常规小分子调节剂的开发。一种有前景的PPI抑制剂发现 一种策略是使用微型蛋白质结构域模拟物（PDM）来复制关键界面 接触自然。PDM是有利的，因为中等大小的分子具有高分子量。 表面互补性和比典型的小分子更广泛的接触点， 仍然是有限的，因为-根据定义-只有一部分的总PPI结合能是 在互动中捕捉。合成结构域的结合亲和力通常低于合成结构域。 同源全长蛋白质。靶向共价抑制是一种正交治疗方法 传统上用于增强小分子的结合亲和力，但该方法具有 潜在的缺点，因为典型的共价弹头的高反应性可能导致非特异性 相互作用和毒性。在这里，我们建议开发一种新的设计计算方法 该策略将利用这两种方法的优势-PDM和共价抑制- 同时减轻它们各自的局限性。努力的重点是合理地 发现有效的抑制剂，将非共价识别，然后共价靶向蛋白质- 蛋白质结合界面具有精确的特异性。