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Specificity and Selectivity in Protein-Ion Binding

蛋白质-离子结合的特异性和选择性

基本信息

批准号：
10609424
负责人：
JAY PONDER
金额：
$ 31.29万
依托单位：
UNIVERSITY OF TEXAS AT AUSTIN
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10609424
关键词：
Acceleration Algorithms Binding Binding Proteins Biological Biological Process C2 Domain Charge Communicable Diseases Communities Complex Data Development Diagnostic EF Hand Motifs Educational workshop Electrostatics Free Energy Future Geometry Goals Heart Diseases Infrastructure Ions Knowledge Ligands Malignant Neoplasms Mediating Metabolism Metal Ion Binding Metalloproteins Metals Modeling Molecular Movement Neurodegenerative Disorders Penetration Performance Physics Play Potential Energy Proteins Public Health Quantum Mechanics Research Role Science Signal Transduction Site Sodium Chloride Specificity Structure System Therapeutic Thermodynamics Time Training Transition Elements computer studies computerized tools design diagnostic strategy driving force improved inhibitor innovation inorganic phosphate insight mechanical energy models and simulation molecular dynamics molecular mechanics next generation novel diagnostics novel therapeutics physical model protonation response simulation simulation software small molecule therapeutic protein therapeutic target treatment fees

项目摘要

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.

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.

项目成果

期刊论文数量（59）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

An Efficient Approach to Large-Scale Ab Initio Conformational Energy Profiles of Small Molecules.

DOI：
10.3390/molecules27238567
发表时间：
2022-12-05
期刊：
Molecules (Basel, Switzerland)
影响因子：
0
作者：
Wang Y;Walker BD;Liu C;Ren P
通讯作者：
Ren P

Calculating protein-ligand binding affinities with MMPBSA: Method and error analysis.

DOI：
10.1002/jcc.24467
发表时间：
2016-10-15
期刊：
JOURNAL OF COMPUTATIONAL CHEMISTRY
影响因子：
3
作者：
Wang, Changhao;Nguyen, Peter H.;Pham, Kevin;Huynh, Danielle;Le, Thanh-Binh Nancy;Wang, Hongli;Ren, Pengyu;Luo, Ray
通讯作者：
Luo, Ray

Calculating binding free energies of host-guest systems using the AMOEBA polarizable force field.