The Prediction and Interpretation of Protein pKa's Using QM/MM

该项目的目标是建立一种质量管理/MM方法，用于预测和解释具有不寻常值和/或难以用当前方法建模的蛋白质pKa。该方法将应用于三种蛋白质（火鸡卵泡样蛋白第三结构域、泛素和木聚糖酶），并对影响pKa的因素进行了详细的实验研究。将开发一种用于蛋白质pKa预测的三层计算（QM/MM/LPBE）方法。可电离残留物及其直接环境将采用从头算电子结构（QM）方法（包括能量最小化和谐波振动分析）进行处理。蛋白质的其余部分将用一个极化的、多极的静电模型（MM）处理，该模型是通过单独的从头计算专门为每种蛋白质导出的。体溶剂将通过线性化泊松-玻尔兹曼方程（LPBE）的非常精确的解来处理。这种新方法与现有方法的结合使用将对具有更大稳定性或新功能的蛋白质的实验设计做出重大贡献。这项研究是分子物理学、量子化学和结构生物学的交叉，因此将为博士后、研究生和本科生提供重要的跨学科培训。通过与实验研究小组的紧密合作，他们的培训得到进一步加强。由此产生的科学家将精通量子化学的数学基础和实践方面（包括算法开发和并行化），以及跨学科研究环境下的大分子建模。此外，所有的算法开发都将在量子化学程序GAMESS中实现，该程序将免费分发给科学界。本研究由化学学部的理论与计算化学项目和分子与细胞生物科学部的分子生物物理项目共同资助。

The objective of this project is to establish a QM/MM methodology for the prediction and interpretation of protein pKa's that have unusual values and/or are difficult to model with current methodologies. The methodology will be applied to three proteins (turkey ovomucoid third domain, ubiquitin, and xylanase) for which detailed experimental studies of the factors that influence pKa's have been performed. A three-layered computational (QM/MM/LPBE) methodology for protein pKa prediction will be developed. The ionizable residue and its immediate environment will be treated by ab initio electronic structure (QM) methods (including energy minimization and harmonic vibrational analysis). The rest of the protein will be treated with a polarizable, multipole-based electrostatic model (MM) derived specifically for each protein by separate ab initio calculations. The bulk solvent will be treated by a very accurate solution of the linearized Poisson-Boltzmann equation (LPBE). The combined use of this new method with current methods will contribute significantly to the experimental design of proteins with greater stability or new functions.This research is at the intersection of molecular physics, quantum chemistry, and structural biology, and will therefore offer important cross-disciplinary training to the postdoctoral associate, graduate student, and undergraduate students involved. Their training is further enhanced by tight collaboration with experimental research groups. The resulting scientists will be well versed in both the mathematical foundations and practical aspects of quantum chemistry (including algorithm development and parallelization) and macromolecular modeling within the context of an interdisciplinary research environment. Furthermore, all algorithmic developments will be implemented in the quantum chemistry program GAMESS, which is distributed free of charge to the scientific community. This work is funded jointly by the Theoretical and Computational Chemistry Program in the Chemistry Division and the Molecular Biophysics Program in the Division of Molecular and Cellular Biosciences.