Multiscale modeling of (bio) catalytic systems

近年来，复杂系统的建模在化学、物理、生物、材料科学及相关交叉学科中取得了长足的进步。在这项提议感兴趣的领域，量子化学、分子力学和分子动力学、统计和随机方法以及动力学网络处理方面的进展正在合并。一种胚胎系统的方法正在出现。一些最有趣的前沿工作是跨学科和综合性的，需要跨越空间和时间尺度的大范围的理论和方法。我的研究计划的长期目标是为这种多尺度建模方法的发展做出贡献，以高效的计算机代码实现它们，并将它们应用于复杂生物和能源相关环境中的催化驱动过程。成功将导致更好地了解生物系统，了解生化反应如何与细胞组件的更大规模属性相结合，以及它们如何协同工作。在蛋白质之间的电子转移方面，我们已经成功地阐明了水在调节蛋白质MADH和氨基花青素之间的电子转移中的作用。我们开发了一种方法来计算量子退相干对速率的影响。在即将到来的资助周期中，我们将把这项工作扩展到其他蛋白质对的例子，并致力于方法学上的工作，以消除隧道途径方法的经验方面。我们将启动一个关于呼吸链中质子转移的新项目，这将需要核量子效应的方法学，并将该项目扩展到质子耦合电子转移。我们使用经验速率常数探索了生物转录和翻译的反应网络。对RNA聚合酶合成m-RNA的各个步骤进行了量子力学/分子力学(QM/MM)模拟。用快速半经验量子力学方法确定了构象变化，并绘制了化学反应图。该项目将扩展到重要的突变，以及用其他金属取代具有催化作用的重要镁离子对RNA反应的影响，从铁开始。这些方法也可用于在实际条件下理解石油化学，如在稠油或油砂中的石油化学。新的超分散催化剂将通过计算-实验相结合的方法(与佩雷拉的团队合作)来设计，这样一些重要的化学作用就可以在地下进行，而对环境的影响更小。到目前为止，我们已经用密度泛函理论结合周期模型和团簇模型研究了苯加氢的势能面。两种快速半经验方法(DFTB和TBQCMD)的模拟和基准测试正在进行中。对包括碳氢化合物、纳米催化剂和二氧化硅(沙)模型的初步DFTB模拟表明，Mo2C纳米粒子可以解离氢气并裂解十六烷。计划延长多环芳烃的加氢和裂解。所选反应的自由能分布的计算将采用QM/MM方法，使用DFTB/CHARMM和伞形抽样。作为我的研究计划(10%-15%的努力)中的一个高风险、投机性的元素，我正在与Stuart Kauffman和Gabor Vattay合作，使用分子的本征值谱将它们置于有轴的“稳定领域”，X从有序到临界再到混沌，Y测量量子退相干的程度。初步结果显示，生物分子往往是关键。

The modeling of complex systems in chemistry, physics, biology, materials science and related interdisciplines has taken great strides in recent years. In the areas of interest to this proposal, advances in quantum chemistry, in molecular mechanics and molecular dynamics, in statistical and stochastic methodologies and in the treatment of kinetic networks are merging. And an embryonic systems approach is emerging. Some of the most interesting frontier work is interdisciplinary and integrative in nature and requires theories and methodologies that span large ranges on spatial and temporal scales. The long-term goal of my research program is to contribute to the development of such multi-scale modeling methodologies, to their implementation in efficient computer codes, and their application to catalytically-driven processes in complex biological and energy-related environments. Success would lead to better understanding of biological systems, of how biochemical reactions are coupled to larger scale properties of cellular components and of how they work together. In the area of electron-transfer between proteins, we have successfully elucidated the role of water in modulating the electron transfer between the proteins MADH and Amicyanin. We have developed a methodology to compute the effects of quantum decoherence on the rates. In the upcoming grant cycle we will extend this work to other examples of protein pairs and also work on methodology to remove the empirical aspects of the tunneling pathway approach. We will start a new project on proton transfers in the respiratory chain, which will require methodology for nuclear quantum effects and extend the project to proton-coupled electron transfers. We have explored the reaction network for biological transcription and translation using empirical rate constants. Quantum Mechanical/Molecular Mechanical (QM/MM) simulations have been carried out for various steps in the formation of m-RNA by RNA Polymerase. Conformational changes have been identified and the chemical reaction has been mapped out using a rapid semi-empirical quantum mechanical method. The project will be extended to important mutants and also the effects on RNA reactions of substituting the catalytically important Mg ions by other metals, starting with Fe. The methods can also be used to understand petroleum chemistry under realistic conditions, such as those in heavy oil deposits or in the oil sands. New ultradispersed catalysts will be designed by a combined computational-experimental (in collaboration with Pereira's group) approach so that some of the important chemistry can be done underground, with less impact on the environment. So far, we have explored the potential energy surface for the hydrogenation of benzene as a model molecule using Density Functional Theory with both periodic and cluster models. Simulations and benchmarking of two rapid semiempirical methods (DFTB and TBQCMD) are ongoing. Preliminary DFTB simulations on a model including hydrocarbon, nanocatalyst and a silica (sand) model have shown that a Mo2C nanoparticle can dissociate hydrogen and crack hexadecane. Extensions to hydrogenation and cracking of polyaromatic hydrocarbons are planned. Calculations of the free energy profiles for selected reactions will be carried out with QM/MM methodology using DFTB/CHARMM and umbrella sampling. As a high-risk, speculative, element of my research program (10-15% effort) I am collaborating with Stuart Kauffman and Gabor Vattay on using the eigenvalue spectra of molecules to situate them in the "poised realm" which has axes, X going from ordered to critical to chaotic and Y measuring the extent of quantum decoherence. Preliminary results show that biological molecules tend to be critical.