Interplay of inherent promiscuity and specificity in protein biochemical function with applications to drug discovery and exome analysis

蛋白质生化功能固有的混杂性和特异性与药物发现和外显子组分析应用的相互作用

• 批准号: 9270553
• 负责人: JEFFREY SKOLNICK
• 金额: $ 48.97万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-06 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9270553
• 关键词: Active Sites; Adverse effects; Amino Acids; Binding; Binding Sites; Biochemical; Cell physiology; Cells; Chemicals; Disease; Enzymes; FDA approved; Failure; Genetic Variation; Human; Ligand Binding; Ligands; Mendelian disorder; Missense Mutation; Mutation; Pharmaceutical Preparations; Property; Proteins; Specificity; Structure; Tertiary Protein Structure; Testing; Variant; Wit; Work; base; design; disease diagnosis; drug discovery; exome; human disease; insight; protein function; protein structure; public health relevance; screening; small molecule; tool; virtual

 DESCRIPTION (provided by applicant): A gap exists as to how to interpret the information in the enormous number of sequenced human exomes in terms of the functional consequences of the observed variations in amino acids and their connection to human diseases. This gap also underlies the failure to develop drugs, without side effects, to treat these diseases. This failureis exacerbated by the fact that a given drug molecule binds to different proteins involved in numerous cellular processes. This proposal lays out the details as to how and why these problems occur, and in the context of protein structure, how our existing and proposed progress can help surmount them. We first elucidate the design principles underlying protein structure and function and then apply them to repurpose FDA approved drugs to treat Mendelian diseases and to identify the genetic variations underlying such diseases. We begin by examining whether the stereo chemical space of small molecule drugs and endogenous metabolites is complete and also the differences in the properties of drugs and metabolites. From these analyses, we will suggest how binding specificity might emerge from a highly promiscuous background. This might enable the design of better drugs with minimal side effects and a better understanding of how cells work. Employing these insights, we then develop better structure-based approaches to virtual ligand screening and enzyme function inference. The ability to predict enzymatic function is particularly essential as residue mutations associated wit loss of enzymatic function are the most important missense mutations associated with Mendelian disease. These approaches will use the conservation of ligand-protein microenvironments in stereochemically similar ligand binding sites or active sites in different proteins, regardless of their evolutionary relationship. We will explore the biochemical consequences of a class of enzymes that we discovered - dizymes, single domain proteins that perform two different enzymatic activities at two different active sites. For representative cases, we will experimentally test our predictions of ligand binding and enzymatic activity and their influence on cellular biochemical function. All developed tools will be combined in a comprehensive exome annotation approach. First, it will identify disease associated residue variations. Then, it will predict diseases a protein might be associated with and suggest the best protein targets. Finally, it will suggest what might be the best drugs to treat the disease.

 描述（由申请人提供）：关于如何根据观察到的氨基酸变异的功能后果及其与人类疾病的联系来解释大量已测序的人类外显子组中的信息，存在着差距。由于特定药物分子与参与众多细胞过程的不同蛋白质结合，因此未能开发出无副作用的药物来治疗这些疾病。该提案详细说明了这些问题如何以及为何发生。 ，并且在上下文中我们现有的和拟议的进展如何帮助克服这些问题，首先阐明蛋白质结构和功能的设计原理，然后将它们应用于重新利用 FDA 批准的药物来治疗孟德尔疾病，并开始识别此类疾病的遗传变异。通过检查小分子药物和内源性代谢物的立体化学空间是否完整以及药物和代谢物性质的差异，我们将建议如何从混杂的背景中出现结合特异性。设计出副作用最小的更好的药物，并更好地了解细胞的工作原理，然后我们开发出更好的基于结构的虚拟配体筛选和酶功能推断的方法，作为残留物，预测酶功能尤其重要。与酶功能丧失相关的突变是与孟德尔疾病相关的最重要的错义突变，这些方法将利用不同蛋白质中立体化学相似的配体结合位点或活性位点的配体-蛋白质微环境的保守性，无论它们的进化关系如何。探索生物化学我们发现的一类酶的结果 - 双酶，单域蛋白质，在两个不同的活性位点执行两种不同的酶活性 对于代表性案例， 我们将通过实验测试我们对配体结合和酶活性的预测及其对细胞生化功能的影响。首先，它将识别疾病相关的残留变异。最后，它将建议治疗该疾病的最佳药物。