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.

项目概要 最先进的高性能计算使研究人员能够模拟 现在可以定量生产数百万个相互作用的原子。 对蛋白质生物学功能的预测是原子论的“确定性” 在这个项目中，研究人员建议本质上是随机的相互作用和运动。 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。 从原子开始构建水通道蛋白及其生物环境，模拟它们的随机性 动力学，并阐明它们在各种可控条件下的确定性功能行为 具体来说，他们的目标是找到两种水通道（AQP1 和 AQP5）和一种水通道的抑制剂。 通过准确量化数十种候选物的结合亲和力来检测甘油通道 (GlpF) 抑制剂。 为此，PI 开发了一种新方法，即混合引导分子动力学 (hSMD) 方法 使用hSMD，研究人员将摆脱这个项目和相关研究的问题。 现有文献方法中固有的系统误差放大为5%。 输入将转化为 他们将能够充分利用结合亲和力的最终结果中的 5% 错误。 高分辨率蛋白质结构和成熟的CHARMM力场参数。 利用当今的大规模并行计算能力来改进当前研究的 候选抑制剂并以定量预测的方式寻找新的抑制剂。 项目完成后，两种类型的水通道蛋白抑制剂，细胞外通道进入 阻滞剂和深通道堵塞剂，将准备作为治疗以下疾病的药物进行临床试验 麻醉期间高血压、难治性水肿和气道粘液分泌增多。