Towards the ab Initio Prediction of Catalytic Proficiencies of Enzymes

描述（由申请人提供）：将开发和验证一套强大的工具，用于通过前所未有的精确度的组合量子力学-分子力学计算准确预测酶的催化活性。精确的QM势将使用局部相关方法[LMP 2、L-CCSD、L-CCSD（TO）]并通过使用基于局部耦合团簇能量外推到完整基组极限的新复合从头算方法来计算。将使用一组小分子校准此外推程序，以允许外推局部相关能与应用于常规从头算方法的已建立外推方法的结果进行明确比较。建议的QM/MM方法将通过与野生型和突变的分支酸酯酶和枯草杆菌蛋白酶蛋白质的实验确定的动力学数据的广泛的一组比较进行验证和改进。DFT/MM方法也将针对这个实验测试集进行基准测试，利用新的DFT函数，这些函数将对古老的B3 LYP进行实质性改进。一旦通过与实验数据的广泛比较进行验证和微调，这些计算工具将用于对新型酶设计进行排序以催化合成有用的羟醛缩合。此外，QM/MM方法的开发将允许确定的定量研究的酶催化，包括确定的研究ODCase和其他酶的催化机制仍然是不确定的。将通过结合量子力学和经典力学方法开发精确模拟酶催化功效的计算工具。这些强大的计算工具的直接应用将是设计新的酶，催化自然界中没有发现的反应。这种酶将有助于新的合成途径以及基于酶的治疗方法的发展。

DESCRIPTION (provided by applicant): A robust suite of tools will be developed and validated for the accurate prediction of catalytic proficiencies of enzymes through combined quantum mechanical-molecular mechanical computations of unprecedented accuracy. Accurate QM potentials will be computed using local correlation methods [LMP2, L-CCSD, L- CCSD(TO)] and through the use of a new composite ab initio approach based on the extrapolation of local coupled cluster energies to the complete basis set limit. This extrapolation procedure will be calibrated using a set of small molecules, to allow for the explicit comparison of extrapolated local correlation energies with results from established extrapolation approaches applied to conventional ab initio methods. The proposed QM/MM approaches will be validated and refined through comparison with an extensive set of experimentally determined kinetic data for wild type and mutated chorismate mutase and subtilisin proteins. DFT/MM methods will also be benchmarked against this experimental test set, utilizing new DFT functions that should offer substantial improvements to the venerable B3LYP. Once validated and fine- tuned through extensive comparisons with experimental data, these computational tools will be utilized in the ranking of novel enzyme designs to catalyze synthetically useful aldol condensations. Further, the QM/MM methods developed will allow for definitive quantitative studies of enzyme catalysis, including definitive studies of ODCase and other enzymes for which the catalytic mechanism is still unsettled. Computational tools to accurately model the catalytic efficacy of enzymes will be developed by combining quantum mechanical and classical mechanical methods. The immediate applications of these powerful computational tools will be in the design of new enzymes that catalyze reactions not found in nature. Such enzymes will be instrumental in novel synthetic pathways as well as for the development of enzyme-based therapeutics.