ArticleJournal of molecular modeling2019
Enhanced GROMACS: toward a better numerical simulation framework.
Article in Journal of molecular modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
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- Exploring the Molecular Mechanism of Niuxi-Mugua Formula in Treating Coronavirus Disease 2019Current computer-aided drug design · 2024Article
- Sertraline Alleviates Chronic Prostatitis by Regulating the TRPV1 Channel.Journal of inflammation research · 2024Article
- Advancements in small molecule drug design: A structural perspective.Drug discovery today · 2023Review
- Diagnostic and treatment value ofJournal of thoracic disease · 2023Article
- Clec12a inhibits MSU-induced immune activation through lipid raft expulsion.Life science alliance · 2023Article
- Network Pharmacology, Molecular Docking and Molecular Dynamics to Explore the Potential Immunomodulatory Mechanisms of Deer Antler.International journal of molecular sciences · 2023Article
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The GROMACS software package represented a promising direction toward the molecular dynamic simulation and there is ongoing interest to extend it. In this study, we introduce a new component into the conventional package with the goal being to facilitate the process of finding the native structure of proteins with minimal free-energy value. We achieved this through incorporating a wide range of metaheuristic optimization algorithms and force fields, leading up to the EGROMACS molecular simulation toolkit. Compared with other programs, the EGROMACS supports all standard force fields as well as new minimization algorithms and Hybrid MPI/OpenMP parallelization. We applied the proposed EGROMACS framework to minimize the structure of several target sequences. The obtained results showed comparative performance of the introduced framework to current well-known molecular simulation algorithms. This extension to the GROMACS, however, uses metaheuristic algorithms to address the problem.
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Registered trials
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