Fast Algorithm for Interface Relaxation and Efficient Computational Modeling of Molecular Binding and Unbinding

界面松弛的快速算法以及分子结合和解离的高效计算模型

• 批准号: 1913144
• 负责人: Li-Tien Cheng
• 金额: $ 32.5万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1913144&HistoricalAwards=false
• 关键词: Fast; Algorithm; Interface; Relaxation; Efficient

This project develops rigorous scientific theories and powerful computational tools to investigate the principal mechanisms by which drug and protein molecules associate and dissociate. Often, a drug molecule moves around in a crowded environment, and finds a spot of the surface of a protein to bind to, stays there, and can also leave, unbinding from the protein. During such binding and unbinding events, often repeated, both molecules constantly change their internal atomic positions. They also interact with other molecules, particularly the water molecules, in the surrounding environment. There are two key scientific questions on such complex processes that are characterized by multiple spatiotemporal scales and many-body effects. One is how stable the drug-protein bound unit is. Such thermodynamic stability severs as a criterion for searching drug molecules capable of binding to targeted proteins. The other is how fast or slow the binding and unbinding can occur. Such kinetics has been found recently in experiments and computer simulations to be critical to the drug effectiveness and efficacy. For decades, the scientific communities have made an enormous amount of effect, searching the quantitative answers to these questions to guide the computer-aided drug design and discovery. A recent assessment by the National Institutes of Health of the existing such computer programs, however, has concluded that advanced scientific theories are needed urgently to improve the practice. The success of this project can therefore provide a solid theoretical foundation as well as computational algorithms for drug design and discovery, potentially helping reduce the very high cost often needed for laboratory experiments and speed up the process of drug discovery. In addition, this highly interdisciplinary research project provides unique opportunities for students at different levels to receive training at the interface of mathematical, computational, and biological sciences, keeping our nation's strength in scientific research in a highly competitive international environment.To tackle the extreme complex problem of molecular association and dissociation, the investigators design, implement, and analyze a very fast binary level-set method for interface relaxation to capture the molecular interfacial structures in the framework of an advanced, variational molecular solvation theory. The new method combines the strength of the threshold dynamics and the binary level-set representation, and utilizes the locality of the underlying energy landscape, and new pixel-flipping techniques to achieve very high efficiency. They also develop a new and hybrid computational approach to the kinetics of interface stochastic dynamics, coupling the interfacial energy minimization by the fast algorithm, the string method for transition pathways, and a novel, multi-state Brownian dynamics simulations. All these are applied specifically to investigating the molecular binding and unbinding kinetics for which, some of the conventional methods such as the standard Brownian dynamics simulations may fail. It is expected that this project will advance significantly the basic research in scientific computing and numerical analysis, particularly those of the interface dynamics and stochastic modeling. If successful, this research can help resolve some of the bottle-neck issues in solving very complex scientific problems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个项目开发了严谨的科学理论和强大的计算工具来研究药物和蛋白质分子结合和解离的主要机制。通常，药物分子在拥挤的环境中四处移动，找到蛋白质表面的一点结合，停留在那里，也可以离开，脱离蛋白质。在这种通常重复发生的结合和解离过程中，两个分子都会不断地改变其内部原子位置。它们还与周围环境中的其他分子，特别是水分子相互作用。对于这种以多时空尺度和多体效应为特征的复杂过程，有两个关键的科学问题。其一是药物与蛋白质结合的单位有多稳定。这种热力学稳定性是寻找能够与目标蛋白质结合的药物分子的标准。另一个是绑定和解绑发生的快慢程度。最近在实验和计算机模拟中发现，这种动力学对药物的有效性和疗效至关重要。几十年来，科学界取得了巨大的成就，寻找这些问题的定量答案来指导计算机辅助药物的设计和发现。然而，美国国立卫生研究院最近对现有的这类计算机程序进行的一项评估得出结论，迫切需要先进的科学理论来改进实践。因此，该项目的成功可以为药物设计和发现提供坚实的理论基础和计算算法，潜在地有助于降低实验室实验经常需要的非常高的成本，并加快药物发现的进程。此外，这一高度跨学科的研究项目为不同水平的学生提供了在数学、计算和生物科学的界面上接受培训的独特机会，使我国在竞争激烈的国际环境中保持了科研实力。为了解决极端复杂的分子缔合和解离问题，研究人员设计、实现和分析了一种非常快速的二进制水平集方法，用于界面松弛，在先进的变分分子溶剂化理论框架下捕捉分子界面结构。新方法结合了阈值动态和二值水平集表示的优点，并利用了底层能量景观的局部性，以及新的像素翻转技术来实现非常高的效率。他们还发展了一种新的混合计算方法来研究界面随机动力学动力学，将快速算法的界面能量最小化、用于过渡路径的弦方法和一种新的多态布朗动力学模拟相结合。所有这些都特别适用于研究分子的结合和解离动力学，对于这些动力学，一些传统的方法，如标准的布朗动力学模拟可能会失败。预计该项目将大大促进科学计算和数值分析的基础研究，特别是界面动力学和随机建模的基础研究。如果成功，这项研究可以帮助解决一些瓶颈问题，解决非常复杂的科学问题。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Coupling Monte Carlo, Variational Implicit Solvation, and Binary Level-Set for Simulations of Biomolecular Binding.

• DOI: 10.1021/acs.jctc.0c01109
• 发表时间: 2021-04-13
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Zhang Z;Ricci CG;Fan C;Cheng LT;Li B;McCammon JA
• 通讯作者: McCammon JA

Passing from Discrete to Continuum Models of Electrostatic Energy

从静电能量的离散模型过渡到连续模型

• DOI: 10.1137/20m1345530
• 发表时间: 2021
• 期刊: SIAM Journal on Mathematical Analysis
• 影响因子: 2
• 作者: Ciotti, Benjamin;Li, Bo
• 通讯作者: Li, Bo

A GENERALIZED RAYLEIGH-PLESSET EQUATION FOR IONS WITH SOLVENT FLUCTUATIONS

• DOI: 10.1137/20m1360268
• 发表时间: 2021-01-01
• 期刊: SIAM JOURNAL ON APPLIED MATHEMATICS
• 影响因子: 1.9
• 作者: Fan，Chao;Li，Bo;White，Michael R.
• 通讯作者: White，Michael R.

The Calculus of Boundary Variations and the Dielectric Boundary Force in the Poisson–Boltzmann Theory for Molecular Solvation

• DOI: 10.1007/s00332-021-09749-7
• 发表时间: 2020-10
• 期刊: Journal of Nonlinear Science
• 影响因子: 3
• 作者: Bo Li;Zhengfang Zhang;Shenggao Zhou