Scuola Normale Superiore di Pisa , Piazza dei Cavalieri 7 I-56126, Pisa, Italy.
Dipartimento di Scienze Fisiche e Chimiche, Universitá di L'Aquila , Via Vetoio s.n.c.67100, L'Aquila, Italy.
J Chem Theory Comput. 2017 Nov 14;13(11):5506-5514. doi: 10.1021/acs.jctc.7b00341. Epub 2017 Oct 6.
The Perturbed Matrix Method (PMM) approach to be used in combination with Molecular Dynamics (MD) trajectories (MD-PMM) has been recoded from scratch, improved in several aspects, and implemented in the Gaussian suite of programs for allowing a user-friendly and yet flexible tool to estimate quantum chemistry observables in complex systems in condensed phases. Particular attention has been devoted to a description of rigid and flexible quantum centers together with powerful essential dynamics and clustering approaches. The default implementation is fully black-box and does not require any external action concerning both MD and PMM sections. At the same time, fine-tuning of different parameters and use of external data are allowed in all the steps of the procedure. Two specific systems (Tyrosine and Uridine) have been reinvestigated with the new version of the code in order to validate the implementation, check the performances, and illustrate some new features.
已从头开始重新编写、在几个方面进行了改进,并将用于与分子动力学 (MD) 轨迹(MD-PMM)结合使用的受扰矩阵方法 (PMM) 编码到 Gaussian 程序套件中,以便为在凝聚相的复杂系统中估算量子化学可观测量提供用户友好且灵活的工具。特别关注了与强大的基本动力学和聚类方法一起描述刚性和柔性量子中心。默认实现是完全黑盒的,不需要在 MD 和 PMM 部分都涉及任何外部操作。同时,允许在程序的所有步骤中微调不同的参数和使用外部数据。为了验证实现、检查性能并说明一些新功能,我们使用新版本的代码重新研究了两个特定系统(酪氨酸和尿嘧啶)。