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高效处理有机晶体晶格能最小化中的分子柔性。

Efficient Handling of Molecular Flexibility in Lattice Energy Minimization of Organic Crystals.

机构信息

Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.

出版信息

J Chem Theory Comput. 2011 Jun 14;7(6):1998-2016. doi: 10.1021/ct100597e. Epub 2011 May 9.

DOI:10.1021/ct100597e
PMID:26596459
Abstract

This paper presents a novel algorithm, CrystalOptimizer, for the minimization of the lattice energy of crystals formed by flexible molecules. The algorithm employs isolated-molecule quantum mechanical (QM) calculations of the intramolecular energy and conformation-dependent atomic multipoles in the course of the lattice energy minimization. The algorithm eliminates the need to perform QM calculations at each iteration of the minimization by using Local Approximate Models (LAMs), with a minimal impact on accuracy. Additional computational efficiencies are achieved by storing QM-derived components of the lattice energy model in a database and reusing them in subsequent calculations whenever possible. This makes the approach particularly well suited to applications that involve a sequence of lattice energy evaluations, such as crystal structure prediction. The algorithm is capable of handling efficiently complex systems with considerable conformational flexibility. The paper presents examples of the algorithm's application ranging from single-component crystals to cocrystals and salts of flexible molecules with tens of intramolecular degrees of freedom whose optimal values are determined by the interplay of conformational strain and packing forces. For any given molecule, the degree of flexibility to be considered can vary from a few torsional angles to relaxation of the entire set of torsion angles, bond angles, and bond lengths present in the molecule.

摘要

本文提出了一种新的算法 CrystalOptimizer,用于最小化由柔性分子形成的晶体的晶格能。该算法在晶格能最小化过程中采用孤立分子量子力学(QM)计算来计算分子内能量和构象相关的原子多极矩。该算法通过使用局部近似模型(LAMs)消除了在最小化的每次迭代中都进行 QM 计算的需要,同时对准确性的影响最小。通过将 QM 衍生的晶格能模型组件存储在数据库中,并在可能的情况下在后续计算中重复使用它们,可以实现额外的计算效率。这使得该方法特别适合涉及一系列晶格能评估的应用,例如晶体结构预测。该算法能够有效地处理具有相当构象灵活性的复杂系统。本文介绍了该算法的应用示例,范围从单组分晶体到复杂分子的共晶和盐,这些分子具有数十个分子内自由度,其最佳值是由构象应变和堆积力的相互作用决定的。对于给定的分子,可以考虑的灵活性程度可以从几个扭转角到整个扭转角、键角和键长的弛豫变化。

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