Efficient double hybrid density functional theory algorithms for conformational a

构象α的高效双杂化密度泛函理论算法

• 批准号: 8714619
• 负责人: Yihan Shao
• 金额: $ 48.02万
• 依托单位: Q-CHEM, INC.
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8714619
• 关键词: Active Sites; Address; Affinity; Algorithms; Amino Acids; Attenuated; Benchmarking; Binding; Binding Proteins; Biochemical; Biochemical Reaction; Biological; Biology; Biomedical Research; Biopolymers; Chemicals; Chemistry; Code; Complex; Computer Assisted; Computer software; DNA; Data Set; Development; Discipline; Drug Design; Electrostatics; Enzymes; Free Energy; Goals; Hybrids; Hydrocarbons; Hydrogen Bonding; Inherited; Lead; Ligands; Marketing; Mechanics; Metals; Methods; Modeling; Molecular; Molecular Models; Nucleic Acids; Peptides; Phase; Positioning Attribute; Process; Proteins; Quantum Mechanics; RNA; Research; Running; Science; Scientist; Simulate; Structure; System; Testing; Time; Tweens; Work; base; biological systems; carbohydrate receptor; computer studies; computerized tools; cost; density; improved; meetings; molecular mechanics; molecular modeling; molecular recognition; programs; protein folding; public health relevance; quantum; quantum chemistry; receptor; simulation; success; theories; tool; wasting

DESCRIPTION (provided by applicant): Q-Chem is a state-of-the-art commercial computational quantum chemistry program that has aided tens of thousands users in their modeling of molecular processes in a wide range of disciplines, including biology, chemistry, and materials science. In quantum chemistry, density functional theory (DFT) and second order Moller-Plesset theory (MP2) are already heavily used in the development of molecular mechanics force fields and in the hybrid quantum mechanical molecular mechanical simulations of protein-ligand binding affinities and enzymatic reaction free energies, despite their accuracy and computational cost limitations. To address these limitations, we seek to advance double hybrid density functionals (DHDFs) for computing conformational and binding energies. Specifically, we aim to: (1) Further enhance the computational efficiency of the short range MP2 (SR-MP2) method, which was developed in our Phase I research and demonstrated to yield unprecedented accuracy and efficiency; (2) Build new double hybrid density functionals on top of our SR-MP2 in order to further extend its applicability; and (3) Demonstrate the use of both SR-MP2 and associated new DHDFs in chemical and biological problems. The new tools coming out of this Phase II research will outperform existing DFT and MP2 methods, and yield improved accuracy with reduced computational cost, opening new applications as well as improving existing ones in chemical, biochemical and biomedical research. This work will further strengthen Q-Chem's position as a global leader in the molecular modeling software market, making our program the most efficient and reliable computational quantum chemistry package for simulating large, complex chemical/biological systems.

描述（由申请人提供）：Q-Chem是一个最先进的商业计算量子化学程序，它已经帮助成千上万的用户在广泛的学科中建模分子过程，包括生物学，化学和材料科学。在量子化学中，密度泛函理论（DFT）和二阶Moller-Plesset理论（MP2）已经大量用于分子力学力场的发展，以及蛋白质-配体结合亲和和酶反应自由能的混合量子力学分子力学模拟，尽管它们的准确性和计算成本有限。为了解决这些限制，我们寻求推进双杂化密度泛函（dhdf）计算构象和结合能。具体而言，我们的目标是：(1)进一步提高短程MP2 （SR-MP2）方法的计算效率，该方法在我们的I期研究中开发出来，并被证明具有前所未有的准确性和效率；(2)在SR-MP2的基础上构建新的双混合密度泛函，进一步扩展SR-MP2的适用性；(3)演示SR-MP2和相关的新dhdf在化学和生物问题中的应用。第二阶段研究中出现的新工具将超越现有的DFT和MP2方法，在降低计算成本的同时提高准确性，在化学、生物化学和生物医学研究中开辟新的应用，并改进现有的应用。这项工作将进一步加强Q-Chem作为分子建模软件市场的全球领导者的地位，使我们的程序成为模拟大型，复杂的化学/生物系统的最有效和可靠的计算量子化学软件包。