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，通过前所未有的精度的量子力学-分子力学组合计算来准确预测酶的催化能力。精确的QM势将使用局域关联方法[LMP2，L-CCSD，L-CCSD(TO)]和一种新的基于局域耦合团簇能量外推到完全基组极限的组合从头算方法来计算。这一外推程序将使用一组小分子进行校准，以允许将外推的局部关联能量与应用于传统从头计算方法的已建立的外推方法的结果进行显式比较。所提出的QM/MM方法将通过与大量实验确定的野生型和突变的分支酸变位酶和枯草杆菌蛋白的动力学数据进行比较来验证和改进。DFT/MM方法也将根据这个实验测试集进行基准测试，利用新的DFT功能，这些功能应该会对历史悠久的B3LYP提供实质性的改进。一旦通过与实验数据的广泛比较进行验证和微调，这些计算工具将被用于对新的酶设计进行排名，以催化合成有用的羟醛缩合。此外，开发的QM/MM方法将使酶催化的最终定量研究成为可能，包括对ODCase和其他催化机制仍未确定的酶的最终研究。通过结合量子力学和经典力学方法，将开发出准确模拟酶催化效率的计算工具。这些强大的计算工具的直接应用将是设计催化自然界中没有发现的反应的新酶。这些酶将在新的合成途径以及基于酶的疗法的发展中发挥作用。

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.