Specificity and Selectivity in Protein-Ion Binding

总结 超过30%的所有蛋白质结合金属离子，包括过渡金属，用于结构和功能。 功能目的。尽管有丰富的实验结构和 蛋白质离子复合物的热力学信息，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。有 对精确的物理模型和高效的仿真软件的巨大需求， 蛋白质离子系统的计算研究。我们建议开发下一代 经典力场AMOEBA+，基于现有的AMOEBA潜力， 系统地模拟永久静电、排斥、色散、电荷 量子化后的穿透、极化、电荷转移和配体场效应 机械能分解和实验数据。新的潜力和高- 性能分子模拟软件（CPU和GPU系统的Tinker）将允许 我们理解的结构，物理和热力学驱动力的基础 蛋白质离子识别的分子动力学模拟。鉴于基本的 蛋白质与过渡金属（包括Zn、Cu、Ni、Co、Fe和 嗯，这项研究将对推进我们的科学知识产生广泛的影响， 离子在生物分子结构和功能，并导致新的计算工具， 加速设计新的诊断和治疗分子靶向蛋白质离子 交互.

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.