The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Evaluating conformational free energies: The colony energy and its application to the problem of loop prediction
Open accessAbstract
In this paper, we introduce a method to account for the shape of the potential energy curve in the evaluation of conformational free energies. The method is based on a procedure that generates a set of conformations, each with its own force-field energy, but adds a term to this energy that favors conformations that are close in structure (have a low rmsd) to other conformations. The sum of the force-field energy and rmsd-dependent term is defined here as the “colony energy” of a given conformation, because each conformation that is generated is viewed as representing a colony of points. The use of the colony energy tends to select conformations that are located in broad energy basins. The approach is applied to the ab initio prediction of the conformations of all of the loops in a dataset of 135 nonredundant proteins. By using an rmsd from a native criterion based on the superposition of loop stems, the average rmsd of 5-, 6-, 7-, and 8-residue long loops is 0.85, 0.92, 1.23, and 1.45 Å, respectively. For 8-residue loops, 60 of 61 predictions have an rmsd of less than 3.0 Å. The use of the colony energy is found to improve significantly the results obtained from the potential function alone. (The loop prediction program, “Loopy,” can be downloaded at http://trantor.bioc.columbia.edu .)
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
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
Comparison of systematic search and database methods for constructing segments of protein structure
Fidelis, K., Stern, P. S., Bacon, D., & Moult, J. (1994) · "Protein Engineering, Design and Selection" · doi:10.1093/protein/7.8.953 · Cited by 126
Cited by
Macromolecular modeling and design in Rosetta: recent methods and frameworks
Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0848-2 · Cited by 888
Comparative protein structure modeling using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Protein Science · doi:10.1002/cpps.20 · Cited by 730
“The accuracy of loop predictions can be further improved by clustering the sampled loop conformations and partially accounting for the entropic contribution to the free energy (Xiang et al., 2002).”
BackgroundHemagglutinin-stem nanoparticles generate heterosubtypic influenza protection
Yassine, H. M., Boyington, J. C., McTamney, P. M., Wei, C.-J., Kanekiyo, M., Kong, W.-P., Gallagher, J. R., Wang, L., Zhang, Y., Joyce, M. G., et al. (2015) · Nature Medicine · doi:10.1038/nm.3927 · Cited by 699
Al-Lazikani, B., Jung, J., Xiang, Z., & Honig, B. (2001) · Current Opinion in Chemical Biology · doi:10.1016/s1367-5931(00)00164-2 · Cited by 316
Self-citationFREAD revisited: accurate loop structure prediction using a database search algorithm
Choi, Y., & Deane, C. M. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22658 · Cited by 161
Metadata
- Authors
- Xiang, Z., Soto, C. S., & Honig, B.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2002-05-14
- Volume
- 99
- Issue
- 11
- Pages
- 7432-7437
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2047163848
- Cited by
- 367
- References
- 2
- FWCI
- 6.59
- Type
- journal article
- Language
- en
- Open access
- green
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: Evaluating conformational free energies: The colony energy and its application to the problem of loop prediction. https://app.cochat.ai/papers/10.1073/pnas.102179699
- The paper
- Xiang, Z., Soto, C. S., & Honig, B. (2002). Evaluating conformational free energies: The colony energy and its application to the problem of loop prediction. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.102179699
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.