报告题目Title：基于密度的量子力学-分子力学计算方法 Density-Based Adaptive QM/MM Methods
报 告 人Speaker：Mark Waller （Shanghai University ）
报告时间Time：2016年7月13日(周三)10:00
报告地点Venue：校本部E106会议室，上海大学量子与分子结构国际中心SHU ICQMS
报告摘要：
QM/MM modeling has become one of the methods of choice for modeling macromolecular systems. This is evidenced by the awarding on the 2013 Nobel Prize in Chemistry "for the development of multiscale models for complex chemical systems".1 However, one of the limitations of QM/MM modeling is the traditional rigid partitioning of a given system into a QM and MM region. For instance, this becomes problematic during QM/MM-MD simulations, as the initial partitioning on the system eventually becomes invalid. There has been much work spanning more than almost two decades on an adaptive variant, i.e. where the partitioning occurs during the simulation. We recently wrote a clear and easy to follow review2 on the practical aspects of carrying
out adaptive QM/MM calculations. Adaptive QM/MM methods use two types of partitioning criteria. Firstly, there are distance-based3 approaches, which are empirical in nature because the cut-offs must be fitted. Secondly, a number based approach4, which enables a pre-determined integer number of molecules to surround the QM
core region. Our approach5 is to develop a method whereby no fitted parameters are needed to partition the system, instead the system is analyzed and partitioned based on physical arguments.
This neatly circumvents empiricism, and makes the adaptive-QM/MM method more generally applicable. Our new adaptive-QM/MM method is based on employing an auxiliary atom-centered spherical density, which is analyzed to detect non-covalent interactions between the QM-core and the rest of the system. If non-covalent interactions are detected between a fragment and any QMcore atom, then the fragment is placed into the QM region. Based on this definition, all noninteracting fragments are placed into the MM region.
References
1. http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2013/press.html
2. Zheng, M.; Waller, M. P., Adaptive QM/MM methods, WIRES Comput. Sci. 2016, DOI.10.1002/wcms.1255
3. Kerdcharoen, T.; Liedl, K. R.; Rode, B. M. Chem. Phys., 211, 313–323, 1996.
4. Takenaka, N.; Kitamura, Y.; Koyano, Y.; Nagaoka, M. Chem. Phys. Lett., 524, 56–61, 2012.
5.Waller, M. P.; Kumbhar, S; Yang, J., ChemPhysChem., 2014, 15, 3218–3225
