The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Detection of common three‐dimensional substructures in proteins
Abstract
We present a fully automatic algorithm for three‐dimensional alignment of protein structures and for the detection of common substructures and structural repeats. Given two proteins, the algorithm first identifies all pairs of structurally similar fragments and subsequently clusters into larger units pairs of fragments that are compatible in three dimensions. The detection of similar substructures is independent of insertion/deletion penalties and can be chosen to be independent of the topology of loop connections and to allow for reversal of chain direction. Using distance geometry filters and other approximations, the algorithm, implemented in the WHAT IF program, is so fast that structural comparison of a single protein with the entire database of known protein structures can be performed routinely on a workstation. The method reproduces known non‐trivial superpositions such as plastocyanin on azurin. In addition, we report surprising structural similarity between ubiquitin and a (2Fe‐2S) ferredoxin.
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
Self-citation
Cited by
Combining evolutionary information and neural networks to predict protein secondary structure
Rost, B., & Sander, C. (1994) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340190108 · Cited by 1,452
Self-citationSurprising similarities in structure comparison
Gibrat, J.-F., Madej, T., & Bryant, S. H. (1996) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(96)80058-3 · Cited by 1,049
Selection of representative protein data sets
Hobohm, U., Scharf, M., Schneider, R., & Sander, C. (1992) · Protein Science · doi:10.1002/pro.5560010313 · Cited by 819
Self-citationBork, P., Sander, C., & Valencia, A. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.16.7290 · Cited by 811
Self-citationA New Method to Detect Related Function Among Proteins Independent of Sequence and Fold Homology
Schmitt, S., Kuhn, D., & Klebe, G. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00811-2 · Cited by 423
Metadata
- Authors
- Vriend, G., & Sander, C.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 1991-09
- Volume
- 11
- Issue
- 1
- Pages
- 52-58
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2000468790
- Cited by
- 194
- References
- 1
- FWCI
- 5.07
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.
