SPONGE: A GPU-Accelerated Molecular Dynamics Package with Enhanced Sampling and AI-Driven Algorithms
Huang YP5,6,7; Xia YJ5,6,7; Yang LJ4,5,6,7; Wei JC(韦佳辰)1,2,3; Yang YI1; Gao YQ1,4,5,6,7
刊名CHINESE JOURNAL OF CHEMISTRY
2022
卷号40期号:1页码:160-168
关键词Molecular dynamics Molecular modeling Enhanced sampling Machine learning Computational chemistry
ISSN号1001-604X
DOI10.1002/cjoc.202100456
通讯作者Gao, Yi Qin(gaoyq@pku.edu.cn)
英文摘要Comprehensive Summary SPONGE (Simulation Package tOward Next GEneration molecular modeling) is a software package for molecular dynamics (MD) simulation of solution and surface molecular systems. In this version of SPONGE, the all- atom potential energy functions used in AMBER MD packages are used by default and other all-atom/coarse- grained potential energy functions are also supported. SPONGE is designed to extend the timescale being approached in MD simulations by utilizing the latest CUDA- enabled graphical processing units (GPU) and adopting highly efficient enhanced sampling algorithms, such as integrated tempering, selective integrated tempering and enhanced sampling of reactive trajectories. It is highly modular and new algorithms and functions can be incorporated con veniently. Particularly, a specialized Python plugin can be easily used to perform the machine learning MD simulation with MindSpore, TensorFlow, PyTorch or other popular machine learning frameworks. Furthermore, a plugin of Finite-Element Method (FEM) is also available to handle metallic surface systems. All these advanced features increase the power of SPONGE for modeling and simulation of complex chemical and biological systems. What is the most favorite and original chemistry developed in your research group? Our research centers at developing methods and theories to unravel molecular mechanisms of chemical and biological systems. By establishing theoretical models, developing enhanced sampling methods combined with machine learning techniques, we are able to conduct comprehensive thermodynamic and dynamic analyses for these complex systems. How do you get into this specific field? Could you please share some experiences with our readers? I got into theoretical chemistry as a PhD student. My PhD adviser Prof. Rudolph A. Marcus led me into this field and inspired me by his love of science. Enjoy life, always learn new things and be independent in thinking are something I learnt from my advisers (Professors Dalin Yang, Qihe Zhu, Rudy Marcus, and Martin Karplus) and would love to pass to my students. How do you supervise your students? We learn from each other. What is the most important personality for scientific research? Curiosity, passion, and persistence have been of great value to my career. What are your hobbies? What's your favorite book(s)? Reading, Ping-Pong, and jogging. I always enjoy reading history. Who influences you mostly in your life? Too many, family, academic advisors, friends, students, and colleagues.
分类号二类
资助项目National Key R&D Program of China[2017YFA0204702] ; National Natural Science Foundation of China[21821004] ; National Natural Science Foundation of China[21873007] ; National Natural Science Foundation of China[21927901] ; CAAI-Huawei MindSpore Open Fund
WOS关键词SIMULATION ; ENERGY ; EFFICIENT ; KINETICS ; PROTEIN
WOS研究方向Chemistry
语种英语
WOS记录号WOS:000722929900001
资助机构National Key R&D Program of China ; National Natural Science Foundation of China ; CAAI-Huawei MindSpore Open Fund
其他责任者Gao, Yi Qin
内容类型期刊论文
源URL[http://dspace.imech.ac.cn/handle/311007/88043]  
专题力学研究所_非线性力学国家重点实验室
作者单位1.Gaoke Innovat Ctr, Shenzhen Bay Lab, Guangqiao Rd, Shenzhen 518132, Guangdong, Peoples R China
2.Chinese Acad Sci, Inst Mech, Beijing Key Lab Engn Construct & Mechanobiol, Beijing 100190, Peoples R China;
3.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China;
4.Peking Univ, Beijing Adv Innovat Ctr Genom, Beijing 100871, Peoples R China;
5.Peking Univ, Biomed Pioneering Innovat Ctr, Beijing 100871, Peoples R China;
6.Peking Univ, Beijing Natl Lab Mol Sci, Beijing 100871, Peoples R China;
7.Peking Univ, Coll Chem & Mol Engn, Beijing 100871, Peoples R China;
推荐引用方式
GB/T 7714
Huang YP,Xia YJ,Yang LJ,et al. SPONGE: A GPU-Accelerated Molecular Dynamics Package with Enhanced Sampling and AI-Driven Algorithms[J]. CHINESE JOURNAL OF CHEMISTRY,2022,40(1):160-168.
APA Huang YP,Xia YJ,Yang LJ,韦佳辰,Yang YI,&Gao YQ.(2022).SPONGE: A GPU-Accelerated Molecular Dynamics Package with Enhanced Sampling and AI-Driven Algorithms.CHINESE JOURNAL OF CHEMISTRY,40(1),160-168.
MLA Huang YP,et al."SPONGE: A GPU-Accelerated Molecular Dynamics Package with Enhanced Sampling and AI-Driven Algorithms".CHINESE JOURNAL OF CHEMISTRY 40.1(2022):160-168.
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