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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.14070 |
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| _version_ | 1866909295821455360 |
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| author | Fan, Jiahao Wang, Yanze Wang, Dongdong Zhang, Linfeng |
| author_facet | Fan, Jiahao Wang, Yanze Wang, Dongdong Zhang, Linfeng |
| contents | Developing an efficient method to accelerate the speed of molecular dynamics is a central theme in the field of molecular simulation. One category among the methods are collective-variable-based methods, which rely on predefined collective variables (CVs). The difficulty of selecting a few important CVs hinders the methods to be applied to large systems easily. Here we present a CV-based enhanced sampling method RiD-kit, which could handle a large number of CVs and perform efficient sampling. The method could be applied to various kinds of systems, including biomolecules, chemical reactions and materials. In this protocol, we guide the users through all phases of the RiD-kit workflow, from preparing the input files, setting the simulation parameters and analyzing the results. The RiD-kit workflow provides an efficient and user-friendly command line tool which could submit jobs to various kinds of platforms including the high-performance computers (HPC), cloud server and local machines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_14070 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RiD-kit: Software package designed to do enhanced sampling using reinforced dynamics Fan, Jiahao Wang, Yanze Wang, Dongdong Zhang, Linfeng Chemical Physics Disordered Systems and Neural Networks Biological Physics Computational Physics Developing an efficient method to accelerate the speed of molecular dynamics is a central theme in the field of molecular simulation. One category among the methods are collective-variable-based methods, which rely on predefined collective variables (CVs). The difficulty of selecting a few important CVs hinders the methods to be applied to large systems easily. Here we present a CV-based enhanced sampling method RiD-kit, which could handle a large number of CVs and perform efficient sampling. The method could be applied to various kinds of systems, including biomolecules, chemical reactions and materials. In this protocol, we guide the users through all phases of the RiD-kit workflow, from preparing the input files, setting the simulation parameters and analyzing the results. The RiD-kit workflow provides an efficient and user-friendly command line tool which could submit jobs to various kinds of platforms including the high-performance computers (HPC), cloud server and local machines. |
| title | RiD-kit: Software package designed to do enhanced sampling using reinforced dynamics |
| topic | Chemical Physics Disordered Systems and Neural Networks Biological Physics Computational Physics |
| url | https://arxiv.org/abs/2408.14070 |