Diversity Supplement: Computational and Experimental Studies of Protein Structure and Design

多样性补充：蛋白质结构和设计的计算和实验研究

• 批准号: 10579649
• 负责人: Bruce R. Donald
• 金额: $ 3.95万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10579649
• 关键词: 3-Dimensional; Algorithm Design; Algorithmic Software; Algorithms; Antibodies; Antigens; Area; Binding; Biochemical; Biological; Cells; Computer Models; Computing Methodologies; Disease; Disease Resistance; Drug Design; Drug Targeting; Drug resistance; Future; Generations; Goals; Human; In Vitro; Investigation; Measurement; Measures; Methodology; Methods; Modeling; Molecular; Morbidity - disease rate; Mutation; Pharmacology; Probability; Process; Program Sustainability; Protein Dynamics; Protein Engineering; Proteins; Research; Research Project Grants; Resistance; Structure; System; Testing; Therapeutic; Therapeutic Intervention; Viral Antibodies; base; biophysical properties; computer studies; data modeling; design; drug candidate; experimental study; improved; in vivo; inhibitor; mortality; neutralizing antibody; new therapeutic target; novel; novel therapeutics; open source; parent grant; protein protein interaction; protein structure; resistance mutation; response

Abstract. Diversity Supplement to EI MIRA R35. Parent Grant Summary: The determination of three-dimensional protein structures is essential for revealing molecular mechanism of disease processes, and also for structure-based drug design. Concomitantly, technological advances in protein design could revolutionize therapeutic treatment. With these advances, proteins and other molecules can be designed to act on today’s undruggable proteins or tomorrow’s drug- resistant diseases. This proposed MIRA research project focuses on computational and experimental studies of protein structure and design (PS&D). The interlocking goals are to (A) determine protein structure and dynamics in systems of biomedical importance; and (B) design proteins, inhibitors, and their molecular interactions, especially to predict and overcome resistance. We will also (C) continue to develop free, open-source algorithms and software not only for challenging problems in the design of proteins and their interactions, but also to determine difficult protein structures and characterize their dynamics. We will use structural data and computational models to understand molecular mechanism and the basis of therapeutic interventions, and perform detailed experimental measurements in vitro and in vivo to confirm, iterate, and improve both our understanding of protein structure and molecular designs. The resulting models of protein structures and dynamics, together with our novel design methodology, will illuminate targets of biochemical and pharmacological significance. We will also advance PS&D by making algorithmic and modeling advances. We will test our methods and predictions by creating designed protein and inhibitor constructs, solving empirical structures, and performing in vitro experiments to measure enhanced biophysical properties on purified components, and in-cell experiments to measure biological efficacy. We will apply our PS&D algorithms to several areas of biomedical importance. We will solve structures of systems under our investigation and further develop the paradigm of protein structure as a continuous probability distribution. A set of synergistic research thrusts is proposed, in which, for example, we will (1) predict future resistance mutations in protein targets of novel drugs, (2) design protein-protein interaction (PPI) inhibitors that target “undruggable” proteins, and (3) use our PS&D methodology to characterize and design antibody:antigen constructs, with the ultimate goal of creating pan-neutralizing antibodies for viral targets. Our sustained program in developing novel computational methods to accurately predict potential drug target mutations in response to early-stage leads should drive the design of more resilient and durable first-generation drug candidates.

抽象的。 EI Mira R35的多样性补充。父授予摘要：三维蛋白的确定 结构对于揭示疾病过程的分子机制以及基于结构的药物设计至关重要。 同时，蛋白质设计的技术进步可以彻底改变治疗治疗。与这些 可以设计进步，蛋白质和其他分子，以对当今的不良蛋白质或明天的药物作用 - 抗性疾病。该提出的MIRA研究项目着重于蛋白质的计算和实验研究 结构和设计（PS＆D）。互锁的目标是（a）确定的蛋白质结构和动力学 生物医学重要性； （b）设计蛋白质，抑制剂及其分子相互作用，尤其是用于预测和 克服抵抗力。 我们还将（c）继续开发免费的开源算法和软件，不仅是针对挑战问题 蛋白质及其相互作用的设计，但也确定困难的蛋白质结构并表征其 动力学。 我们将使用结构数据和计算模型来了解分子机制和治疗的基础 干预措施，并在体外和体内进行详细的实验测量，以确认，迭代并改进 我们对蛋白质结构和分子设计的理解。由此产生的蛋白质结构模型和 动力学以及我们的新设计方法将阐明生化和药理学的靶标 意义。我们还将通过实现算法和建模进步来推进PS＆D。我们将测试我们的方法， 通过创建设计的蛋白质和抑制剂结构，解决经验结构并在体外进行预测 测量纯化成分上增强的生物物理特性的实验，以及测量的细胞内实验 生物效率。 我们将将PS＆D算法应用于生物医学重要性的几个领域。我们将解决系统的结构 我们的投资并进一步发展为蛋白质结构的范式作为连续的概率分布。一组 提出了协同研究推力，例如，我们将（1）预测蛋白质的未来抗性突变 新药物的靶标，（2）设计蛋白质蛋白质相互作用（PPI）抑制剂，靶向“不良”蛋白，（3） 使用我们的PS＆D方法来表征和设计抗体：抗原构建体，其最终目标是创建 病毒靶标的泛中和抗体。我们在开发新型计算方法方面持续的计划 准确地预测潜在的药物靶突变，以响应早期铅的响应，应推动更多的设计 弹性和耐用的第一代药物候选物。