Development of multi-scale models for enzyme catalysis in complex environments

威斯康星州大学的Qiang Cui得到了化学系化学理论，模型和计算方法项目的支持，以开发新的计算方法，从而可以用理论技术有效地分析复杂环境中的酶催化。 第一个发展目标是涉及酶中复杂金属簇配体的化学反应。 Cui及其同事正在开发一种新的量子力学/分子力学（QM/MM）框架，其中只有反应性配体和其他明确参与化学的基团用QM处理，而其余的金属基序在MM水平上用高级价键力场处理。 QM配体和MM金属基序之间的相互作用在反应过程中的变化处理与化学势均衡的方法，这避免了明确治疗QM区域作为一个开放的系统相关的技术复杂性。 第二个主题涉及混合分辨率模拟的发展。 这一发展利用了Cui小组建立的水、脂质和氨基酸的粗粒度（CG）模型，该模型具有仔细处理静电的特点。 对于原子/CG相互作用的校准，除了使用全原子模拟作为参考的常见策略外，这种方法的独特之处在于还利用了多组分溶液的实验热力学数据，这些发展满足了与理解酶如何催化化学反应相关的计算和理论挑战。 通过避免明确的处理复杂的电子结构的金属簇，新的QM/MM框架允许计算化学家和生物学家研究化学反应的复杂系统的生物相关性。 它是特别强大的建模有趣的和重要的复杂过程，如发生在光合作用的质子耦合电子转移。 混合原子/CG方法需要在许多应用中，需要一个高分辨率的蛋白质和复杂的环境，如具有特定曲率的多组分脂质双层的真实描述。 这些方法在物理化学之外的广泛领域中找到应用，包括酶学，生物物理学/生物化学和生物无机化学。混合分辨率模型的发展极大地扩展了系统的规模和复杂性，这些系统可以通过计算进行有意义的处理，从而影响材料科学和细胞生物化学。在这个项目中开发的计算方法被实施到流行的分子模拟软件包，CHARMM，并可用于研究广泛的化学和生物学问题。 该项目的外联部分有助于强调理论和计算化学在理解自然方面的作用，并鼓励青年学生从事科学事业。

Qiang Cui of the University of Wisconsin is supported by the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop novel computational methods such that enzyme catalysis in complex environments can be effectively analyzed with theoretical techniques. The first development targets chemical reactions that involve ligands of complex metal clusters in enzymes. Cui and coworkers are developing a novel quantum mechanical/molecular mechanical (QM/MM) framework in which only the reactive ligand and other groups that explicitly participate the chemistry are treated with QM, while the rest of the metal motif is treated at a MM level with an advanced valence-bond force field. Variations in the interaction between the QM ligand and the MM metal motif during the reaction are treated with a chemical potential equalization approach, which avoids technical complications associated with explicitly treating the QM region as an open system. The second subject concerns the development of mixed-resolution simulations. This development takes advantage of a coarse-grained (CG) model established in the Cui group for water, lipids and amino acids that features a careful treatment of electrostatics. For the calibration of atomistic/CG interactions, in addition to the common strategy of using all-atom simulations as a reference, the unique aspect of this approach is to also take advantage of experimental thermodynamic data for multi-component solutions.These developments meet the computational and theoretical challenges associated with understanding how enzymes catalyze chemical reactions. By avoiding the explicit treatment of the complex electronic structure of metal clusters, the novel QM/MM framework allows computational chemists and biologists to study chemical reactions in complex systems of biological relevance. It is particularly powerful for modeling interesting and important complex processes such as the proton-coupled-electron-transfers that occur in photosynthesis. The mixed atomistic/CG approach is demanded in many applications that require a high-resolution description of the protein and a realistic description of the complex environment, such as a multi-component lipid bilayer with specific curvature. These methods find applications in broad areas that go beyond physical chemistry to include enzymology, biophysics/biochemistry and bio-inorganic chemistry. Development of mixed-resolution models greatly expand the scale and complexity of systems that can be meaningfully treated with computations, and thus impact materials science and cellular biochemistry. The computational methods developed in this project are implemented into the popular molecular simulation package, CHARMM, and can be used to study a broad range of problems in chemistry and biology. The outreach component of the project helps emphasize the role of theoretical and computational chemistry in understanding nature and stimulate young students to pursue careers in science.