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

使用 QM/MM 预测和解释蛋白质 pKa

• 批准号: 0209941
• 负责人: Jan Jensen
• 金额: $ 33.3万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-15 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0209941&HistoricalAwards=false
• 关键词: Prediction; Interpretation; Protein; pKa; Using

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.

本项目的目的是建立一个QM/MM方法的预测和解释蛋白质的pKa的，有不寻常的价值和/或难以建模与目前的方法。 该方法将被应用于三种蛋白质（火鸡卵类粘蛋白的第三个结构域，泛素，木聚糖酶）的影响pKa的因素进行了详细的实验研究。 一个三层计算（QM/MM/LPBE）的蛋白质pKa预测方法将被开发。 可电离残基及其周围环境将用从头计算电子结构（QM）方法（包括能量最小化和简谐振动分析）处理。 蛋白质的其余部分将用可极化的基于多极的静电模型（MM）处理，该模型通过单独的从头计算针对每种蛋白质专门推导。 本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。 将这种新方法与现有方法相结合，将大大有助于设计具有更高稳定性或新功能的蛋白质的实验。这项研究是分子物理学、量子化学和结构生物学的交叉研究，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密切合作，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中的大分子建模。 此外，所有算法开发将在量子化学程序GAMESS中实施，该程序免费分发给科学界。 这项工作由化学部的理论和计算化学计划以及分子和细胞生物科学部的分子生物物理计划共同资助。