ArticleJournal of computational chemistry2021
On the use of multiple-time-step algorithms to save computing effort in molecular dynamics simulations of proteins.
Article in Journal of computational chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy.Frontiers in cellular and infection microbiology · 2024Review
- Article
- On the use of multiple-time-step algorithms to save computing effort in molecular dynamics simulations of proteins.Journal of computational chemistry · 2021Article
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3 authors.
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Abstract
Computer simulation of proteins in aqueous solution at the atomic level of resolution is still limited in time span and system size due to limited computing power available and thus employs a variety of time-saving techniques that trade some accuracy against computational effort. Examples of such time-saving techniques are the application of constraints to particular degrees of freedom or the use of a multiple-time-step (MTS) algorithm distinguishing between particular forces when integrating Newton's equations of motion. The application of two types of MTS algorithms to bond-stretching forces versus the remaining forces in molecular dynamics (MD) simulations of a protein in aqueous solution or of liquid water is investigated and the results in terms of total energy conservation and the influence on various other properties are compared to those of MD simulations of the same systems using bond-length, and for water bond-angle, constraints. At comparable computational effort, the use of bond-length constraints in proteins leads to better energy conservation and less distorted properties than the two MTS algorithms investigated.
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