García-Argote Williams, Ruiz Lina, Inostroza Diego, Cardenas Carlos, Yañez Osvaldo, Tiznado William
Centro de Química Teórica & Computacional (CQT&C), Departamento de Ciencias Químicas, Facultad de Ciencias Exactas, Universidad Andrés Bello, Avenida República 275, 8370146, Santiago de Chile, Chile.
Doctorado en Fisicoquímica Molecular, Facultad de Ciencias Exactas, Universidad Andres Bello, República 275, Santiago, Chile.
J Mol Model. 2024 Oct 8;30(11):369. doi: 10.1007/s00894-024-06155-0.
Exploring potential energy surfaces (PES) is fundamental in computational chemistry, as it provides insights into the relationship between molecular energy, geometry, and chemical reactivity. We introduce Kick-MEP, a hybrid method for exploring the PES of atomic and molecular clusters, particularly those dominated by non-covalent interactions. Kick-MEP computes the Coulomb integral between the maximum and minimum electrostatic potential values on a 0.001 a.u. electron density isosurface for two interacting fragments. This approach efficiently estimates interaction energies and selects low-energy configurations at reduced computational cost. Kick-MEP was evaluated on silicon-lithium clusters, water clusters, and thymol encapsulated within Cucurbit[7]uril, consistently identifying the lowest energy structures, including global minima and relevant local minima.
Kick-MEP generates an initial population of molecular structures using the stochastic Kick algorithm, which combines two molecular fragments (A and B). The molecular electrostatic potential (MEP) values on a 0.001 a.u. electron density isosurface for each fragment are used to compute the Coulomb integral between them. Structures with the lowest Coulomb integral are selected and refined through gradient-based optimization and DFT calculations at the PBE0-D3/Def2-TZVP level. Molecular docking simulations for the thymol-Cucurbit[7]uril complex using AutoDock Vina were performed for benchmarking. Kick-MEP was validated across different molecular systems, demonstrating its effectiveness in identifying the lowest energy structures, including global minima and relevant local minima, while maintaining a low computational cost.
探索势能面(PES)是计算化学的基础,因为它能深入了解分子能量、几何结构和化学反应性之间的关系。我们引入了Kick-MEP,一种用于探索原子和分子团簇势能面的混合方法,特别是那些由非共价相互作用主导的团簇。Kick-MEP计算两个相互作用片段在0.001 a.u.电子密度等值面上的最大和最小静电势值之间的库仑积分。这种方法能以降低的计算成本有效地估计相互作用能并选择低能量构型。Kick-MEP在硅锂团簇、水团簇以及包封在葫芦[7]脲中的百里酚上进行了评估,始终能识别出最低能量结构,包括全局最小值和相关局部最小值。
Kick-MEP使用随机Kick算法生成分子结构的初始种群,该算法将两个分子片段(A和B)组合在一起。每个片段在0.001 a.u.电子密度等值面上的分子静电势(MEP)值用于计算它们之间的库仑积分。选择库仑积分最低的结构,并通过基于梯度的优化和PBE0-D3/Def2-TZVP水平的DFT计算进行优化。使用AutoDock Vina对百里酚 - 葫芦[7]脲复合物进行分子对接模拟以作基准测试。Kick-MEP在不同分子系统中得到了验证,证明了其在识别最低能量结构(包括全局最小值和相关局部最小值)方面的有效性,同时保持了较低的计算成本。