Accurate and efficient density functional theory calculations of intermolecular interactions and conformational energies
准确高效的分子间相互作用和构象能量的密度泛函理论计算
基本信息
- 批准号:9410007
- 负责人:
- 金额:$ 14.19万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-19 至 2018-07-31
- 项目状态:已结题
- 来源:
- 关键词:AlgebraAlgorithmic SoftwareAlgorithmsAmino AcidsAreaBackBenchmarkingBindingBiologicalBiophysicsCatalysisComputer SimulationComputer softwareComputersData SetDevelopmentDrug Binding SiteEnzymesLigand BindingMechanicsMelatoninMethodsModelingModificationMolecular ConformationPathway interactionsPharmaceutical PreparationsPhaseProceduresProductionProtocols documentationQuantum MechanicsResearchRunningSpeedSystemWorkbasebiophysical chemistrybiophysical modelbiophysical propertiescombinatorialcostdensitydesignimprovedinnovationintermolecular interactionmolecular recognitionpolypeptideprototypequantumtheoriestoolvirtual
项目摘要
Project summary
Key biophysical properties such as drug binding sites and enzyme catalysis arise can be
computer-modeled using quantum mechanics, but limitations in the accuracy of practical
quantum methods have held back progress. Over the past five years, this situation has changed
with exciting, (and ongoing) improvements in the accuracy of density functional theory (DFT).
New and better density functionals open new opportunities for applications in conformational
searching, molecular recognition, ligand binding, and all the areas where ab initio calculations
are employed in biophysical chemistry. However, these functionals require very large and
computationally demanding basis sets to attain their high accuracy. Use of smaller basis sets
leads to unconverged results with often unacceptable errors. There is an unmet need to
significantly reduce the computational cost of achieving large basis set accuracy.
The central innovation of this proposal is to use minimal adaptive basis functions (MAB)
for this purpose, in place of traditional large basis sets. The MAB is a small (minimal) set of
functions, adaptively formed from a traditional large basis via an atom-blocked, sparse
transformation. The DFT calculation is performed in the adaptive basis, followed by a dual basis
correction. This potentially permits very large computational speedups, while yielding accuracy
virtually indistinguishable from a computationally costly calculation performed conventionally
in the large target basis.
The Phase I research has three principal objectives. First, the research will establish the
accuracy of the MAB protocol for a range of biophysically relevant energy differences. Second,
the research will lead to a carefully justified estimate of the speed-up that is attainable with the
MAB approach, and will produce a new software implementation of several of the algorithmic
steps that must be optimized. Third, modifications and improvements of the MAB approach will
be sought as possible and needed. The results will lay the groundwork for basis set limit DFT
calculations at greatly reduced computational cost, thereby potentially greatly expanding their
usefulness for biophysical modeling.
项目摘要
关键的生物物理特性,如药物结合位点和酶催化作用,
计算机模拟使用量子力学,但限制在实际的准确性,
量子方法阻碍了进展。五年来,这种情况有所改变
随着密度泛函理论(DFT)的精确性的令人兴奋的(和持续的)改进。
新的和更好的密度泛函为构象的应用开辟了新的机会
搜索,分子识别,配体结合,以及从头计算的所有领域
被用于生物物理化学。然而,这些泛函需要非常大的和
计算要求高的基集,以达到其高精度。使用较小的基组
导致不收敛的结果,通常具有不可接受的误差。有一个未得到满足的需要,
显著降低实现大基组精度的计算成本。
该方案的核心创新点是使用最小自适应基函数(MAB)
为了这个目的,代替传统的大基组。MAB是一个小(最小)集合,
函数,自适应地从传统的大基通过原子阻塞,稀疏
转型DFT计算在自适应基中执行,然后是对偶基
纠正一下这可能允许非常大的计算加速,同时产生精度
实际上与常规执行的计算成本高的计算没有区别
在大目标的基础上。
第一阶段的研究有三个主要目标。首先,研究将建立
MAB方案对于一系列生物药理学相关能量差异的准确性。第二、
这项研究将导致一个仔细合理的估计速度是可以达到的
MAB的方法,并将产生一个新的软件实现的几个算法
必须优化的步骤。第三,人与生物圈计划方法的修改和改进将
尽可能地寻求和需要。所得结果为基集限DFT的研究奠定了基础
以大大降低的计算成本进行计算,从而潜在地大大扩展其
生物物理建模的有用性。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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