ArticleJournal of chemical information and modeling2023
Analysis of Protein Folding Simulation with Moving Root Mean Square Deviation.
Article in Journal of chemical information and modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed.
- Article
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- In silico analysis of PERK interactions with engineered alpha lactalbumin peptides using molecular dynamics simulations.Scientific reports · 2026Article
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- Illuminating the pleiotropic effects of bixin-loaded nanoemulsion on glioblastoma cell behavior through an integrated approach.Molecular biology reports · 2026Article
- Deep learning-driven QSAR and micro-scale MD simulation-guided strategy reveals non-toxic human HGFR inhibitors.Molecular diversity · 2026Article
- Discovery of novel natural compounds as PKCθ inhibitors: structure-based virtual screening and in vitro evaluation.Journal of computer-aided molecular design · 2026Article
- The Role of the Electronic Structure during Protein Folding through Electron Density-Based Quantum Chemical Descriptors.ACS omega · 2026Article
- Spectrochemical, medicinal, and toxicological studies of moxifloxacin and its novel analogs: a quantum chemistry and drug discovery approach.RSC advances · 2026Article
- Integrated machine learning, molecular dynamics, and density functional theory approaches for identifying potential inhibitor targeting TEM 𝛽-lactamase inFrontiers in bioinformatics · 2026Article
- Theta-Defensin Proteins: Conformational Variability and Environmental Effects.Computational and structural biotechnology journal · 2026Article
7 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We apply moving root-mean-square deviation (mRMSD), which does not require a reference structure, as a method for analyzing protein dynamics. This method can be used to calculate the root-mean-square deviation (RMSD) of structure between two specified time points and to analyze protein dynamics behavior through time series analysis. We applied this method to the Trp-cage trajectory calculated by the Anton supercomputer and found that it shows regions of stable states as well as the conventional RMSD. In addition, we extracted a characteristic structure in which the side chains of Asp1 and Arg16 form hydrogen bonds near the most stable structure of the Trp-cage. We also determined that ≥20 ns is an appropriate time interval to investigate protein dynamics using mRMSD. Applying this method to NuG2 protein, we found that mRMSD can be used to detect regions of metastable states in addition to the stable state. This method can be applied to molecular dynamics simulations of proteins whose stable structures are unknown.
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