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首页> 外文期刊>Journal of chemical theory and computation: JCTC >Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design
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Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design

机译:基于绝对局部分子轨道的能量分解分析,用于药物设计中的大规模密度泛函理论计算

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摘要

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 87538765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.
机译:我们报告在ONETEP线性缩放电子结构包中的能量分解分析(EDA)方案的开发和实施。我们的方法是混合的,因为它结合了局部分子轨道EDA(Su,P .; Li,HJ Chem。Phys。,2009,131,014102)和绝对局部分子轨道EDA(Khaliullin,RZ;等.J。Phys Chem.A,2007,111,87538765)将分子间相互作用能划分为化学上不同的组分(静电,交换,相关,保利斥力,极化和电荷转移)。讨论了EDA方法中存在的局限性,例如极化和电荷转移中的基集相关性问题,并提出了利用ONETEP轨道严格局部化的特性对此问题的补救措施。我们的方法在一系列与药物设计相关的配合物上得到了验证。我们展示了我们的方法对凝血酶与抑制剂(最多包含4975个原子)的复合物的大规模计算能力。鉴于ONETEP具有进行大规模计算(例如对整个蛋白质)的能力,我们希望我们的EDA方案可以应用于各种生物分子问题,尤其是在药物设计的背景下。

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