Specificity and Selectivity in Protein-Ion Binding

蛋白质-离子结合的特异性和选择性

• 批准号: 10569447
• 负责人: JAY PONDER
• 金额: $ 17.99万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10569447
• 关键词: Binding; Binding Proteins; Charge; Complex; Data; Diagnostic; Electrostatics; Ions; Knowledge; Lead; Ligands; Metal Ion Binding; Modeling; Molecular; Penetration; Performance; Proteins; Public Health; Research; Specificity; Structure; System; Thermodynamics; Transition Elements; base; computer studies; computerized tools; design; driving force; mechanical energy; molecular dynamics; next generation; novel diagnostics; novel therapeutics; physical model; quantum; simulation software; therapeutic protein

SUMMARY Over 30% of all proteins bind metal ions, including transition metals, for structural and functional purposes. Even though there are rich experimental structural and thermodynamic information on protein-ion complexes, our understanding of the physical basis for the specificity and selectivity in protein-ion recognition remains lacking. There is a great need for accurate physical models and efficient simulation software to enable computational study of protein-ion systems. We propose to develop a next generation classical force field AMOEBA+, based on the existing AMOEBA potential, to systematically model permanent electrostatics, repulsion, dispersion, charge penetration, polarization, charge transfer, and ligand field effect after quantum mechanical energy decomposition and experimental data. The new potential and high- performance molecular simulation software (Tinker for CPU & GPU systems) will allow us to comprehend the structural, physical and thermodynamic driving forces underlying protein-ion recognition using molecular dynamics simulations. Given the fundamental importance of protein interaction with transition metals including Zn, Cu, Ni, Co, Fe, and Mn, this research will have a broad impact on advancing our scientific knowledge about ions in biomolecular structure and function, and lead to new computational tools to accelerate the design of new diagnostic and therapeutic molecules targeting protein-ion interactions.

摘要 超过30%的蛋白质结合金属离子，包括过渡金属，用于结构和 功能用途。尽管有丰富的实验性结构和 关于蛋白质-离子络合物的热力学信息，我们对物理的理解 蛋白质-离子识别的特异性和选择性的基础仍然缺乏。的确有 非常需要精确的物理模型和高效的模拟软件来实现 蛋白质-离子体系的计算研究。我们计划发展下一代 经典力场阿米巴+，基于现有的阿米巴势能， 系统地模拟永久静电、斥力、色散、电荷 量子后的穿透、极化、电荷转移和配位场效应 机械能分解和实验数据。新的潜力和高度- 性能分子模拟软件(用于CPU和GPU系统的Tinker)将允许 美国将理解潜在的结构、物理和热力学驱动力 基于分子动力学模拟的蛋白质离子识别。在给定的基本情况下 蛋白质与过渡金属包括锌、铜、镍、钴、铁和 MN，这项研究将对促进我们对 离子在生物分子结构和功能中的作用，并导致新的计算工具 加速设计新的针对蛋白质离子的诊断和治疗分子 互动。