Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS.

Müllender L, Hess B, Lindahl E

DOI: 10.1021/acs.jctc.6c00808
Published: 2026 Sep 8
Container: Journal of chemical theory and computation
Publisher: Not recorded
Open access: yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1021/acs.jctc.6c00808,
  title = {Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS.},
  author = {Müllender L and Hess B and Lindahl E},
  year = {2026},
  journal = {Journal of chemical theory and computation},
  doi = {10.1021/acs.jctc.6c00808},
  url = {https://doi.org/10.1021/acs.jctc.6c00808}
}

RIS

TY  - JOUR
TI  - Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS.
AU  - Müllender L
AU  - Hess B
AU  - Lindahl E
PY  - 2026
JO  - Journal of chemical theory and computation
DO  - 10.1021/acs.jctc.6c00808
UR  - https://doi.org/10.1021/acs.jctc.6c00808
ER  -

APA

L, M., B, H., & E, L. (2026). Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS.. Journal of chemical theory and computation. https://doi.org/10.1021/acs.jctc.6c00808

Source records

pubmed · retrieved 2026-09-25T15:43:23.912Z