RUI: Collaborative Research: CDS&E: Theory and Methods for Implicit Molecular Solvation in Ligand and Ion Binding

加州州立大学北岭分校(CSUN)的Tyler Luchko和罗格斯大学的David Case获得了化学部化学理论、模型和计算方法项目的支持，以降低计算小分子和离子与蛋白质、DNA和RNA结合的计算成本。计算机模型能够准确地定量预测分子在液体环境中如何有效地相互结合(或粘合)，这是理解生物系统的健康功能或先进材料的结构和稳定性的关键。但是，达到预期精度所需的模型往往伴随着不切实际的计算成本。为了解决这个问题，Luchko博士和Case博士将开发方法来提高预测类药物分子与生物和非生物靶标的紧密结合以及DNA和RNA周围离子的扩散(云状)结合的计算效率。他们将寻求在所需计算中提供高度精度的新算法，同时通过利用先进的硬件选项(如GPU)来加快计算速度，从而降低计算成本。这两个方面都需要反复测试和调整，以达到最大的效果。这些方法和软件将作为AmberTools分子建模套件的一部分免费提供给广泛的应用。这项工作将直接涉及CSUN的学生，其中超过50%来自传统上服务不足的群体，从而为培训不同的STEM(科学、技术、工程和数学)劳动力做出贡献。将开发的方法的核心是分子液体的3D参考相互作用部位模型(3D-RISM)。3D-RISM是一种潜在的强有力的分子模拟工具，因为它快速地提供了平衡的溶剂密度分布和准确的溶剂化自由能，但是它的计算成本对于目前的许多分子结合应用来说太高了。为了在降低整体计算负担的同时保持3D-RISM的优势，Luchko博士和Case博士将开发方法来解决小分子、类药物分子的紧密结合以及DNA和RNA周围离子的扩散结合等具体挑战。对于小的类药物分子，他和他的团队将创建一个热力学循环，使用快速隐式溶剂方法来有效地包括采样，然后进行3D棱镜校正。对于扩散离子结合，他们将优化离子力场参数和3D-rism求解器，以预测DNA和RNA在不同浓度的二价离子下的稳定性。此外，他们将在GPU上实现3D-RISM，以直接降低这些和所有其他应用程序的所有3D-RISM模型的计算成本。这些目标结合在一起，有可能提供简单易用的工具和溶剂模型来计算结合自由能，而不会牺牲速度或准确性。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。

Tyler Luchko of California State University, Northridge (CSUN) and David Case of Rutgers University are supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to reduce the computational cost of calculating the binding of small molecules and ions to proteins, DNA and RNA. The ability of computer models to make accurate quantitative predictions about how effectively molecules bind with (or “stick” to) each other in a liquid environment is key to understanding the healthy functioning of biological systems or the structure and stability of advanced materials. But the models required to achieve the desired accuracy often come with impractical computational costs. To address this, Drs. Luchko and Case will develop methods to improve the computational efficiency of predicting the tight binding of drug-like molecules to biological and non-biological targets and also the diffuse (“cloud-like”) binding of ions around DNA and RNA. They will be pursuing new algorithms that offer a high degree of accuracy in the required calculations while also lowering the computational cost, by taking advantage of advancing hardware options, like GPUs, to speed up calculations. Both aspects will require iterative testing and tailoring to achieve maximum effectiveness. These methods and software will be freely available for broad application as part of the AmberTools molecular modeling suite. This work will directly involve students at CSUN, of whom over 50% are from traditionally underserved groups, thereby contributing to the training of a diverse STEM (science, technology, engineering and mathematics) workforce.Central to the methods that will be developed is the 3D reference interaction site model (3D-RISM) of molecular liquids. 3D-RISM is a potentially powerful tool for molecular modeling, as it rapidly provides equilibrium solvent density distributions and accurate solvation free energies; however, its computational cost is too high for many molecular binding applications at present. To preserve the strengths of 3D-RISM while reducing the overall computational load, Drs. Luchko and Case will develop methods to address the specific challenges of the tight binding of small, drug-like molecules and the diffuse binding of ions around DNA and RNA. For small, drug-like molecules, he and his group will create a thermodynamic cycle that employs fast implicit solvent methods to efficiently include sampling, followed by a 3D-RISM correction. For diffuse ion binding, they will optimize ion force field parameters and solvers for 3D-RISM to predict the stability of DNA and RNA at different concentrations of divalent ions. In addition, they will implement 3D-RISM on GPUs, to directly reduce the computational cost of the model for all 3D-RISM for these and all other applications. When combined, these objectives have the potential to provide easy-to-use tools and solvent models for calculating binding free energies that do not sacrifice speed or accuracy.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.