The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
GalaxyRefine: protein structure refinement driven by side-chain repacking
Open accessAbstract
The quality of model structures generated by contemporary protein structure prediction methods strongly depends on the degree of similarity between the target and available template structures. Therefore, the importance of improving template-based model structures beyond the accuracy available from template information has been emphasized in the structure prediction community. The GalaxyRefine web server, freely available at http://galaxy.seoklab.org/refine, is based on a refinement method that has been successfully tested in CASP10. The method first rebuilds side chains and performs side-chain repacking and subsequent overall structure relaxation by molecular dynamics simulation. According to the CASP10 assessment, this method showed the best performance in improving the local structure quality. The method can improve both global and local structure quality on average, when used for refining the models generated by state-of-the-art protein structure prediction servers.
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
All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins
MacKerell, A. D., Bashford, D., Bellott, M., Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., et al. (1998) · The Journal of Physical Chemistry B · doi:10.1021/jp973084f · Cited by 14,311
MolProbity : all-atom structure validation for macromolecular crystallography
Chen, V. B., Arendall, W. B., Headd, J. J., Keedy, D. A., Immormino, R. M., Kapral, G. J., Murray, L. W., Richardson, J. S., & Richardson, D. C. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909042073 · Cited by 14,115
I-TASSER: a unified platform for automated protein structure and function prediction
Roy, A., Kucukural, A., & Zhang, Y. (2010) · Nature Protocols · doi:10.1038/nprot.2010.5 · Cited by 6,170
Comparative Protein Structure Modeling of Genes and Genomes
Martí-Renom, M. A., Stuart, A. C., Fiser, A., Sánchez, R., Melo, F., & Šali, A. (2000) · Annual Review of Biophysics and Biomolecular Structure · doi:10.1146/annurev.biophys.29.1.291 · Cited by 3,169
Scoring function for automated assessment of protein structure template quality
Zhang, Y., & Skolnick, J. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20264 · Cited by 2,392
Leaver-Fay (2011) · doi:10.1016/b978-0-12-381270-4.00019-6 · Cited by 1,904
LGA: a method for finding 3D similarities in protein structures
Zemla, A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg571 · Cited by 1,069
GalaxyWEB server for protein structure prediction and refinement
Ko, J., Park, H., Heo, L., & Seok, C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks493 · Cited by 1,007
Self-citationA graph‐theory algorithm for rapid protein side‐chain prediction
Canutescu, A. A., Shelenkov, A. A., & Dunbrack, R. L. (2003) · Protein Science · doi:10.1110/ps.03154503 · Cited by 997
Rotamer Libraries in the 21st Century
Dunbrack, R. L. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00344-5 · Cited by 644
Cited by
An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study
Yang, Z., Bogdan, P., & Nazarian, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-81749-9 · Cited by 271
Artificial Intelligence Technologies for COVID-19 De Novo Drug Design
Floresta, G., Zagni, C., Gentile, D., Patamia, V., & Rescifina, A. (2022) · doi:10.20944/preprints202203.0032.v1 · Cited by 67
Barh, D., Tiwari, S., Rodrigues Gomes, L. G., Ramalho Pinto, C. H., Andrade, B. S., Ahmad, S., Aljabali, A. A. A., Alzahrani, K. J., Banjer, H. J., Hassan, S. S., et al. (2023) · Inflammation · doi:10.1007/s10753-022-01734-w · Cited by 50
Recent Advances in Studying Toll-like Receptors with the Use of Computational Methods
Bzówka, M., Bagrowska, W., & Góra, A. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00419 · Cited by 34
Benchmarking protein language models for protein crystallization
Mall, R., Kaushik, R., Martinez, Z. A., Thomson, M. W., & Castiglione, F. (2025) · Scientific Reports · doi:10.1038/s41598-025-86519-5 · Cited by 20
Metadata
- Authors
- Heo, L., Park, H., & Seok, C.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-05-21
- Volume
- 41
- Issue
- W1
- Pages
- W384-W388
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W1998917415
- Cited by
- 1,363
- References
- 31
- FWCI
- 5.51
- Type
- journal article
- Language
- en
- Open access
- gold
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: GalaxyRefine: protein structure refinement driven by side-chain repacking. https://app.cochat.ai/papers/10.1093/nar/gkt458
- The paper
- Heo, L., Park, H., & Seok, C. (2013). GalaxyRefine: protein structure refinement driven by side-chain repacking. Nucleic Acids Research. https://doi.org/10.1093/nar/gkt458
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.