The DOI matches its Crossref record; 162 of the 162 references it cites were found in a registry or an index.
Molecular Dynamics Simulation for All
Open accessAbstract
The impact of molecular dynamics (MD) simulations in molecular biology and drug discovery has expanded dramatically in recent years. These simulations capture the behavior of proteins and other biomolecules in full atomic detail and at very fine temporal resolution. Major improvements in simulation speed, accuracy, and accessibility, together with the proliferation of experimental structural data, have increased the appeal of biomolecular simulation to experimentalists—a trend particularly noticeable in , though certainly not limited to, neuroscience. Simulations have proven valuable in deciphering functional mechanisms of proteins and other biomolecules, in uncovering the structural basis for disease, and in the design and optimization of small molecules, peptides, and proteins. Here we describe in practical terms the types of information MD simulations can provide and the ways in which they typically motivate further experimental work.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015) · SoftwareX · doi:10.1016/j.softx.2015.06.001 · Cited by 27,190
Scalable molecular dynamics with NAMD
Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20289 · Cited by 16,914
CHARMM‐GUI: A web‐based graphical user interface for CHARMM
Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008) · Journal of Computational Chemistry · doi:10.1002/jcc.20945 · Cited by 9,284
CHARMM: The biomolecular simulation program
Brooks, B. R., Brooks, C. L., Mackerell, A. D., Nilsson, L., Petrella, R. J., Roux, B., Won, Y., Archontis, G., Bartels, C., Boresch, S., et al. (2009) · Journal of Computational Chemistry · doi:10.1002/jcc.21287 · Cited by 8,939
PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data
Roe, D. R., & Cheatham, T. E. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct400341p · Cited by 7,382
CHARMM36m: an improved force field for folded and intrinsically disordered proteins
Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., & MacKerell, A. D. (2017) · Nature Methods · doi:10.1038/nmeth.4067 · Cited by 7,285
Madhavi Sastry, G., Adzhigirey, M., Day, T., Annabhimoju, R., & Sherman, W. (2013) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-013-9644-8 · Cited by 6,006
Towards automated crystallographic structure refinement with phenix.refine
Afonine, P. V., Grosse-Kunstleve, R. W., Echols, N., Headd, J. J., Moriarty, N. W., Mustyakimov, M., Terwilliger, T. C., Urzhumtsev, A., Zwart, P. H., & Adams, P. D. (2012) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444912001308 · Cited by 5,511
Replica-exchange molecular dynamics method for protein folding
Sugita, Y., & Okamoto, Y. (1999) · Chemical Physics Letters · doi:10.1016/s0009-2614(99)01123-9 · Cited by 4,514
Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types
Klauda, J. B., Venable, R. M., Freites, J. A., O’Connor, J. W., Tobias, D. J., Mondragon-Ramirez, C., Vorobyov, I., MacKerell, A. D., & Pastor, R. W. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp101759q · Cited by 4,501
Cited by
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Salo-Ahen, O. M. H., Alanko, I., Bhadane, R., Bonvin, A. M. J. J., Honorato, R. V., Hossain, S., Juffer, A. H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A. S., et al. (2020) · Processes · doi:10.3390/pr9010071 · Cited by 659
The Art and Science of Molecular Docking
Paggi, J. M., Pandit, A., & Dror, R. O. (2024) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-030222-120000 · Cited by 459
Self-citationRecent advances in green synthesized nanoparticles: from production to application
kazemi, S., Hosseingholian, A., Gohari, S. D., Feirahi, F., Moammeri, F., Mesbahian, G., Moghaddam, Z. S., & Ren, Q. (2023) · Materials Today Sustainability · doi:10.1016/j.mtsust.2023.100500 · Cited by 341
Two decades of Martini: Better beads, broader scope
Marrink, S. J., Monticelli, L., Melo, M. N., Alessandri, R., Tieleman, D. P., & Souza, P. C. T. (2023) · WIREs Computational Molecular Science · doi:10.1002/wcms.1620 · Cited by 255
Deep Learning in Protein Structural Modeling and Design
Gao, W., Mahajan, S. P., Sulam, J., & Gray, J. J. (2020) · Patterns · doi:10.1016/j.patter.2020.100142 · Cited by 227
Metadata
- Authors
- Hollingsworth, S. A., & Dror, R. O.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 99
- Issue
- 6
- Pages
- 1129-1143
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2892113269
- Cited by
- 3,257
- References
- 162
- FWCI
- 31.39
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Molecular Dynamics Simulation for All. https://app.cochat.ai/papers/10.1016/j.neuron.2018.08.011
- The paper
- Hollingsworth, S. A., & Dror, R. O. (2018). Molecular Dynamics Simulation for All. Neuron. https://doi.org/10.1016/j.neuron.2018.08.011
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
