BIOMOLECULAR INTERACTIONS AND ENZYMATIC PROCESSES

一项旨在发展理论能力的研究项目 生物分子相互作用和酶反应的表征 提出了解决该问题的机理。计算方法的中心是 用蒙特卡罗方法在原子水平上模拟生物聚合物 卡罗和分子动力学技术。为了提供准确的 多肽-多肽和多肽-溶剂相互作用的描述 蛋白质分子间极化势函数集(PIPF) 正在开发中。除了复制实验中的 模型液体和晶体的结构和能量性质 化合物和高水平从头计算的结果， 参数化还考虑了静电势 通过X-射线衍射实验得到。此外，合并后的 量子力学和分子力学(QM/MM)势将是 在蒙特卡罗模拟中用来评估部分电荷，诱导 有机溶质在水中的偶极矩和极化能 解决方案。这些结果将与使用 PIPF函数。通过PIPF的参数化过程 函数，将从以下方面研究各种有趣的问题 疏水作用对离子溶剂化的影响。 另外，我们研究的一个主要方向是研究结构， 乳酸脱氢酶的特性及其催化反应机理。 最初，活动部位区域和基质中的结构特征 结合专一性将使用统计微扰理论进行建模 和分子动力学模拟。这之后是完整的 催化剂反应谱线的表征 乳酸脱氢酶中乳酸和丙酮酸的相互转化 使用经验势函数和经验势函数的水溶液 最新的QM/MM组合方法。除了这些洞察力之外 计算可以提供对以下原理的理解 酶的反应性和功能，这样的比较研究将 对测试当前的理论方法和未来有价值 理论的发展。

A research project aimed at developing the capacity for theoretical characterization of biomolecular interactions and enzymatic reaction mechanisms in solution is proposed. The computational approach centers on computer simulations of biopolymers at the atomic level using Monte Carlo and molecular dynamics techniques. To provide an accurate description of the peptide-peptide and peptide-solvent interactions, a set of polarizable intermolecular potential functions (PIPF) for proteins is being developed. In addition to reproducing the experimental structural and energetic properties of liquids and crystals of model compounds and the results from high level ab initio calculations, the parameterization also takes into account the electrostatic potentials obtained by X-ray diffraction experiment. Furthermore, a combined quantum mechanical and molecular mechanical (QM/MM) potential will be used in Monte Carlo simulations to evaluate the partial charges, induce dipole moments and polarization energies for organic solutes in aqueous solution. These results will be compared with the predictions using the PIPF function. Through the course of parameterization of the PIPF functions, a variety of interesting problems will be studied ranging from hydrophobic interactions to ionic solvation. In addition, a major thrust of our research is to study the structure, specificity and catalytic reaction mechanism of lactate dehydrogenase. Initially, structural features in the active site region and substrate binding specificity will be modeled using statistical perturbation theory and molecular dynamics simulations. This is followed by a full characterization of the reaction profile for the catalytic interconversion of lactate and pyruvate in lactate dehydrogenase in aqueous solution using both the empirical potential function and the latest combined QM/MM approach. In addition t the insight these computations can provide in the understanding of the principles of enzymatic reactivity and function, such a comparative investigation will be valuable for testing current theoretical methodologies and for future development of theory.