Explicit ions in implicit solvent: fast and accurate.

隐式溶剂中的显式离子：快速、准确。

基本信息

批准号：
9808072
负责人：
ALEXEY VLAD ONUFRIEV
金额：
$ 17.18万
依托单位：
VIRGINIA POLYTECHNIC INST AND ST UNIV
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2021-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9808072
关键词：
Address Adoption Algorithms Area Atmosphere Behavior Binding Biological Biological Process Biological Response Modifier Therapy Biomedical Research Charge Chromatin Communities Complex DNA Diffuse Double-Stranded RNA Drug Design Foundations Gene Expression Regulation Goals Health Human Biology Individual Ion Channel Ion Exchange Ion Pumps Ion Transport Ions Ligands Mathematics Medical Medicine Membrane Methodology Methods Minority Modeling Modernization Molecular Molecular Conformation Nucleic Acids Peptides Pharmaceutical Preparations Physical condensation Play Polyamines Process Property Protein Dynamics Proteins RNA Roentgen Rays Role Sampling Science Site Sodium Chloride Solvents Speed Structure System Testing Time Water Work aqueous base design drug discovery ds-DNA experimental study fundamental research gene therapy improved models and simulation molecular dynamics molecular modeling novel novel therapeutics open source protein folding prototype simulation solute structural biology technology research and development theories tool virtual

项目摘要

Project Summary. This proposal responds to PAR-17-046 “Exploratory Research for Technology Development (R21)”. The goal of the proposal is to design and test in a pilot implementation of a novel “GB- ION” model that will allow fast and accurate atomistic simulations of dynamics of biologically relevant structures such as proteins and DNA in implicit water with explicit ions. Progress in modern bio-molecular sciences, from structural biology to structure-based drug design, is greatly accelerated by methods of atomic-level modeling and simulations that bridge the gap between theory and experiment. The so-called implicit solvation model provides critical advantages of speed and versatility through representing the effects of water – often the most computationally expensive part of such simulations – in an approximate manner. The resulting speed-up of modeling efforts is critical in many areas, from fundamental research in human biology to design of novel medicines; fast implicit solvent methodology can make possible simulations that are otherwise prohibitively expensive within the traditional explicit solvent approach. However, the version of the methodology best suited for atomistic simulations – the so-called generalized Born (GB) model – has a critical flaw in its foundation that precludes its use on systems and problems where explicit treatment of biologically relevant ions is needed. In fact, the majority of bio-medically relevant applications is out of reach to current GB for this reason – these are most of systems where multi- valent ions such as Mg2+ or Ca2+ play a critical role, or where binding of mono-valent ions to specific sites is important. Ion transport or compaction of nucleic acids and chromatin are just two examples out of a long list. This serious limitation of the GB model will be addressed in a novel, systematic way; advantages of the new implicit solvation model will be demonstrated through a pilot implementation and testing on biologically relevant structures. We will develop a novel model, GB-ION, similar in spirit to the generalized Born, that treats ions explicitly, at the same level of accuracy and efficiency as the current fast analytical GB models. Specifically, the GB will be extended to work for multiple, disconnected dielectric boundaries, beyond the singly-connected spherical topology that the current model assumes. The new prototype model will be parametrized for representative examples of mono-, di-, and tri-valent ions. We will test the model on several biologically relevant structures and processes, and implement its prototype in an open source package, widely used (AmberTools or/and OpenMM.) Results will benefit the entire biomolecular modeling community by establishing validity of an approach to carry out fast implicit solvent atomistic simulations in situations where explicit treatment of ions is necessary, which is the majority of bio-medically relevant simulations.

该提案响应 PAR-17-046“技术探索性研究”。该提案的目标是设计和测试新型“GB-开发（R21）”。 ION”模型将允许对生物相关的动力学进行快速、准确的原子模拟具有显式离子的隐式水中的蛋白质和 DNA 等结构。现代生物分子科学的进展，从结构生物学到基于结构的药物设计，正在取得进展通过原子级建模和模拟方法极大地加速了理论之间的差距所谓的隐式溶剂化模型提供了速度和多功能性的关键优势。通过表示水的影响——通常是此类模拟中计算成本最高的部分—— 以近似的方式，由此产生的建模工作速度在许多领域都至关重要。人类生物学的基础研究可以设计新的药物；使传统显式溶剂中的模拟变得可能，否则成本高昂然而，该方法的版本最适合原子模拟——所谓的。广义 Born (GB) 模型 – 其基础存在严重缺陷，无法在系统和系统上使用事实上，大多数生物医学问题都需要对生物学相关的离子进行明确的处理。由于这个原因，相关应用程序对于当前的 GB 来说是遥不可及的——这些是大多数系统，其中多 Mg2+ 或 Ca2+ 等价离子起着关键作用，或者单价离子与特定位点的结合离子传输或核酸和染色质的压缩只是一长串例子中的两个例子。 GB 模型的这一严重局限性将以一种新颖、系统的方式得到解决；新的隐式溶剂化模型将通过试点实施和生物测试来证明我们将开发一种新颖的模型，GB-ION，其精神类似于广义的 Born，它处理明确离子，其精度和效率与当前快速分析 GB 模型相同。具体来说，GB 将扩展到适用于多个、断开的电介质边界，超出了当前模型采用的单连接球形拓扑结构。针对单价、二价和三价离子的代表性示例进行参数化，我们将在几个上测试该模型。生物学相关的结构和过程，并在开源包中广泛实现其原型使用（AmberTools 或/和 OpenMM。）通过建立方法的有效性，结果将使整个生物分子建模界受益在需要对离子进行显式处理的情况下进行快速隐式溶剂原子模拟，这是大多数生物医学相关的模拟。