BIOMOLECULAR INTERACTIONS AND ENZYMATIC PROCESSES

一个旨在发展理论能力的研究项目， 生物分子相互作用和酶促反应的表征 解决方案中的机制。 计算方法中心 在原子水平上使用Monte Carlo方法对生物聚合物进行计算机模拟 卡洛和分子动力学技术。 提供准确的 肽-肽和肽-溶剂相互作用的描述， 蛋白质的可极化分子间势函数 正在开发中。 除了复制实验 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，联合 量子力学和分子力学（QM/MM）势将是 在蒙特卡罗模拟中用于评估部分电荷，感应 水溶液中有机溶质的偶极矩和极化能 溶液 这些结果将与使用 PIPF功能。 通过对PIPF参数化的过程 函数，将研究各种有趣的问题， 疏水相互作用到离子溶剂化。 此外，我们研究的一个主要重点是研究结构， 乳酸脱氢酶催化反应机理。 最初，活性位点区域和基底中的结构特征 结合特异性将使用统计扰动理论建模 和分子动力学模拟。 接下来是一个完整的 催化剂的反应曲线的表征 乳酸脱氢酶中乳酸和丙酮酸相互转化 水溶液中使用的经验势函数和 最新的QM/MM组合方法。 除了这些洞察力之外， 计算可以提供在理解的原则， 酶的反应性和功能，这样的比较研究将 对于检验当前的理论方法和未来的 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.