How to cite COSMO¶
If COSMO contributed to work you are publishing, please cite it. Citing the software lets others find the exact model and version you used, and credits the people who developed the underlying force fields.
Tip
The repository ships a CITATION.cff file, so on
GitHub you can click “Cite this repository” to export formatted APA and
BibTeX automatically. Keep that file and this page in step whenever the
citation details change.
Primary citation¶
Cite the paper that introduces this coarse-grained toolkit:
Vu, Q. V.; Sitarik, I.; Li, M. S.; O’Brien, E. P. Noncovalent Lasso Entanglements are Common in Experimentally Derived Intrinsically Disordered Protein Ensembles and Strongly Influenced by Protein Length and Charge. J. Phys. Chem. B 129, 4682–4691 (2025). https://doi.org/10.1021/acs.jpcb.5c01260
@article{cosmo,
author = {Vu, Quyen V. and Sitarik, Ian and Li, Mai Suan and O'Brien, Edward P.},
title = {Noncovalent Lasso Entanglements are Common in Experimentally Derived
Intrinsically Disordered Protein Ensembles and Strongly Influenced by
Protein Length and Charge},
journal = {The Journal of Physical Chemistry B},
year = {2025},
volume = {129},
pages = {4682--4691},
doi = {10.1021/acs.jpcb.5c01260}
}
The software itself is archived on Zenodo. Cite the concept DOI (always the latest release) alongside the paper:
Vu, Q. (2026). COSMO: COarse-grained Simulation of intrinsically disordered prOteins with OpenMM (Version 2026.1) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21361272
To pin the exact version you ran, use the version-specific DOI for 2026.1 instead
(https://doi.org/10.5281/zenodo.21361273), and record the version
(import cosmo; print(cosmo.__version__) or pyproject.toml) and commit
(git rev-parse --short HEAD) — different versions can produce different numbers.
The force fields COSMO implements¶
COSMO runs sequence-based, one-bead-per-residue intrinsically-disordered-protein
force fields. Cite the model(s) you actually run (set by the model key).
HPS hydropathy-scale family (hps_urry / hps_kr / hps_ss)¶
Dignon, G. L.; Zheng, W.; Kim, Y. C.; Best, R. B.; Mittal, J. Sequence Determinants of Protein Phase Behavior from a Coarse-Grained Model. PLoS Comput. Biol. 14 (1), e1005941 (2018). https://doi.org/10.1371/journal.pcbi.1005941
Regy, R. M.; Thompson, J.; Kim, Y. C.; Mittal, J. Improved Coarse-Grained Model for Studying Sequence-Dependent Phase Separation of Disordered Proteins. Protein Sci. 30 (7), 1371–1379 (2021). https://doi.org/10.1002/pro.4094
Rizuan, A.; Jovic, N.; Phan, T. M.; Kim, Y. C.; Mittal, J. Developing Bonded Potentials for a Coarse-Grained Model of Intrinsically Disordered Proteins. J. Chem. Inf. Model. 62 (18), 4474–4485 (2022). https://doi.org/10.1021/acs.jcim.2c00450
Mpipi model (mpipi)¶
Joseph, J. A.; Reinhardt, A.; Aguirre, A.; Chew, P. Y.; Russell, K. O.; Espinosa, J. R.; Garaizar, A.; Collepardo-Guevara, R. Physics-Driven Coarse-Grained Model for Biomolecular Phase Separation with Near-Quantitative Accuracy. Nat. Comput. Sci. 1 (11), 732–743 (2021). https://doi.org/10.1038/s43588-021-00155-3
Co-translational synthesis (CSP)¶
If you use the cosmo-csp / cosmo-cylinder runners, also cite the O’Brien-lab
per-codon, three-stage continuous-synthesis protocol they reproduce:
Jiang, Y. et al. How synonymous mutations alter enzyme structure and function over long timescales. Nat. Chem. 15, 308–318 (2023). https://doi.org/10.1038/s41557-022-01091-z
Codon dwell-time datasets. When you run synthesis with a species dwell-time table (see Codon dwell-time tables (per-codon timing)), cite the source dataset:
E. coli — Fluitt, A.; Pienaar, E.; Viljoen, H. Comput. Biol. Chem. 31, 335–346 (2007). https://doi.org/10.1016/j.compbiolchem.2007.07.003
Yeast — Gardin, J. et al. eLife 3, e03735 (2014). https://doi.org/10.7554/eLife.03735
Human — Gobet, C. et al. PNAS 117 (17), 9630–9641 (2020). https://doi.org/10.1073/pnas.1918145117
N. crassa — Yang, Q. et al. Nucleic Acids Res. 47 (17), 9243–9258 (2019). https://doi.org/10.1093/nar/gkz710
MD engine (always)¶
All dynamics run on OpenMM:
Eastman, P. et al. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLoS Comput. Biol. 13 (7), e1005659 (2017). https://doi.org/10.1371/journal.pcbi.1005659
Questions¶
For anything not covered here — collaboration, a preprint DOI, or how to cite a specific analysis — open an issue on the GitHub repository.