Quantitatively predictive biology of aquaporins 1, 5, and GlpF

水通道蛋白 1、5 和 GlpF 的定量预测生物学

• 批准号: 9753012
• 负责人: LIAO Y CHEN
• 金额: $ 35.36万
• 依托单位: UNIVERSITY OF TEXAS SAN ANTONIO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9753012
• 关键词: AQP1 gene; AQP9 gene; Acetazolamide; Affinity; Anesthesia procedures; Area; Behavior; Binding; Biological; Biological Assay; Biological Process; Biology; Biomedical Research; Cattle; Cells; Clinical Trials; Collaborations; Computing Methodologies; Diuresis; Drug Design; Drug Targeting; Edema; Environment; Erythrocytes; Escherichia coli; Free Energy; Glycerol; Goals; Head; Health; Height; High Performance Computing; Human; Hybrids; Hydrocarbons; Hydrogen Bonding; Hydrophobicity; Hypertension; In Vitro; Knockout Mice; Life; Light; Literature; Medical; Membrane Proteins; Methazolamide; Methods; Motion; Mucous body substance; Names; Nature; Organ; Organism; Performance; Pharmacotherapy; Physics; Physiological; Plumbing; Procedures; Propylene Glycols; Proteins; Refractory; Research; Research Personnel; Resolution; Science; Sea; Structural Protein; Structure; Sum; Supercomputing; System; Testing; Therapeutic; Thiadiazoles; Translating; Validation; Vestibule; Water; analog; aquaporin 3; aquaporin 5; base; extracellular; flexibility; foot; hypertension treatment; improved; inhibitor/antagonist; man; membrane model; molecular dynamics; parallel computer; prevent; protein complex; protein expression; protein structure; simulation; supercomputer; water channel; water flow

Project Summary The state-of-the-art high performance computing enables researchers to simulate the motions of millions of atoms interacting with one another. Now it is feasible to produce quantitative predictions of biological functions of a protein that are “deterministic” out of the atomistic interactions and motions that are stochastic in nature. In this project, the researchers propose to study the functions of two human aquaporins and look for ways to modulate/inhibit them. They will build the aquaporins and their biological environments from atoms up, simulate their stochastic dynamics, and elucidate their deterministic functional behaviors under various controllable conditions. Specifically, they aim to find inhibitors of two water channels (AQP1 and AQP5) and one glycerol channel (GlpF) by accurately quantifying the binding affinities of dozens of candidate inhibitors. The PI developed a new method, the hybrid steered molecular dynamics (hSMD) method, for the purpose of this project and related research. Using hSMD, the researchers will be free from the problem of systematic error amplifications inherent in the current methods of the literature. 5% errors in the input will translate into 5% errors in the final results for binding affinities. They will be able to take full advantage of the high resolution protein structures and the mature CHARMM force field parameters. They will harness the massively parallel computing power of the day to improve the currently investigated candidate inhibitors and to find new inhibitors in a quantitatively predictive manner. Upon completion of the project, two types of aquaporin inhibitors, the extracellular channel entry blockers and the deep channel cloggers, will be ready for clinical trials as drugs for treatment of hypertension, refractory edema, and elevated airway mucus secretion during anesthesia.

项目摘要 最先进的高性能计算使研究人员能够模拟 数以百万计的原子相互作用。现在，量化生产是可行的 对蛋白质生物学功能的预测是原子论之外的“确定性” 本质上是随机的相互作用和运动。在这个项目中，研究人员提议 研究两种人类水通道蛋白的功能，并寻找调节/抑制它们的方法。他们会 从原子上构建水通道蛋白及其生物环境，模拟其随机性 动力学，并阐明了它们在各种可控条件下的确定性功能行为 条件。具体地说，他们的目标是找到两种水通道(AQP1和AQP5)的抑制剂和一种 通过准确定量数十个候选分子的结合亲和力来实现甘油通道(GlpF) 抑制剂。 为此，PI开发了一种新的方法，即混合导向分子动力学(HSMD)方法 本项目及相关研究的进展情况。使用hSMD，研究人员将摆脱 文献中现有方法固有的系统性误差放大。5%的错误 输入将转换为 结合亲和力的最终结果有5%的误差。他们将能够充分利用 高分辨率的蛋白质结构和成熟的CHARMM力场参数。他们会 利用当今的大规模并行计算能力来改进当前正在研究的 并以定量预测的方式寻找新的抑制剂。 项目完成后，两种类型的水通道抑制剂，细胞外通道进入 阻滞剂和深通道阻滞剂将作为治疗高血压的药物进行临床试验 麻醉期间出现高血压、顽固性浮肿和呼吸道粘液分泌增加。