Enzyme Catalysis & Bridged Bi-Metal Motif

描述（由申请人提供）：提出使用从头算（基于密度泛函理论）Car-Parinello分子动力学（CPMD）和混合量子CPMD/经典MD方法的计算机模拟，以补充宾夕法尼亚大学和其他地方专注于酶催化的实验计划。 本提案的目的是使用最先进的计算方法来详细探索利用桥连结构基序进行催化的酶的选定实例。 具体而言，气单胞菌解蛋白氨肽酶（AAP）和氨基肽酶的机械模型将被检查，以及仿生变体的结构和动力学特性。 计算研究将探讨水解酶（AAP）的金属和底物选择性，并比较锰过氧化氢酶和过氧化氢酶的氧化还原过氧化氢酶活性。 此外，还将沿着对甲烷单加氧酶（MMO）的催化机理进行探讨，并模拟MMO蛋白的过氧化氢还原和氧活化过程。 长期目标是深入了解氧化还原和水解酶催化中桥连结构基序的作用以及微调。 这种理解将基于对不同环境中存在的共同基序进行系统的比较，并促进不同的反应过程。 丰富的可用实验数据的p53基序本身的对照研究，其价值将进一步提高的可能性，建议新的实验，并最终有助于设计的治疗，靶向这些酶。

DESCRIPTION (provided by applicant): Computer simulations using ab initio (density functional theory based) Car-Parinello molecular dynamics (CPMD) and hybrid quantum CPMD / classical MD methodologies are proposed to complement experimental programs at the University of Pennsylvania and elsewhere that focus on enzyme catalysis. The objective of the present proposal is to use state-of-the-art computational methods to explore in detail selected examples of enzymes that exploit the bridged bimetal motif for catalysis. Specifically, mechanistic models of Aeromonas proteolytica aminopeptidase (AAP) and arginase will be examined, as well as the structural and dynamical properties of biomimetic variants. The computational studies will investigate the metal and substrate selectivity of hydrolytic enzymes (AAP), and compare the redox catalase activity of manganese catalase and arginase. In addition, the catalytic mechanism of methane monooxygenase (MMO) will be explored along with modeling the hydrogen peroxide disproportionation and oxygen activation processes at the bimetal core of a biomimetic MMO protein. The long-term goal is to reach a deep understanding of the role of, as well as the fine tuning at, the bridged bimetal motif in redox and hydrolytic enzymatic catalysis. This understanding will be based on a systematic comparative approach to a common motif present in different environments and promoting different reaction processes. The wealth of available experimental data on the bimetal motif lends itself to a controlled study, whose value will be further enhanced by the possibility of suggesting new experiments and ultimately contributing to the design of therapies that target such enzymes.