The DOI matches its Crossref record.
Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites
Open accessAbstract
MOTIVATION: Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster. RESULTS: There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. AVAILABILITY: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder
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
Cited by
Role of computer-aided drug design in modern drug discovery
Macalino, S. J. Y., Gosu, V., Hong, S., & Choi, S. (2015) · Archives of Pharmacal Research · doi:10.1007/s12272-015-0640-5 · Cited by 762
Brenke, R., Kozakov, D., Chuang, G.-Y., Beglov, D., Hall, D., Landon, M. R., Mattos, C., & Vajda, S. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp036 · Cited by 455
Structural Biology and Drug Discovery of Difficult Targets: The Limits of Ligandability
Surade, S., & Blundell, T. L. (2012) · Chemistry & Biology · doi:10.1016/j.chembiol.2011.12.013 · Cited by 230
Pharmacological chaperones stabilize retromer to limit APP processing
Mecozzi, V. J., Berman, D. E., Simoes, S., Vetanovetz, C., Awal, M. R., Patel, V. M., Schneider, R. T., Petsko, G. A., Ringe, D., & Small, S. A. (2014) · Nature Chemical Biology · doi:10.1038/nchembio.1508 · Cited by 216
2P2Idb: a structural database dedicated to orthosteric modulation of protein–protein interactions
Basse, M. J., Betzi, S., Bourgeas, R., Bouzidi, S., Chetrit, B., Hamon, V., Morelli, X., & Roche, P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1002 · Cited by 148
Metadata
- Authors
- Laurie, A. T. R., & Jackson, R. M.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-02-08
- Volume
- 21
- Issue
- 9
- Pages
- 1908-1916
- ISSN
- 0266-7061 (ISSN-L)
- 1367-4803
- 1460-2059
- OpenAlex
- W2128402268
- Cited by
- 1,047
- References
- 0
- FWCI
- 30.12
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. https://app.cochat.ai/papers/10.1093/bioinformatics/bti315
- The paper
- Laurie, A. T. R., & Jackson, R. M. (2005). Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics. https://doi.org/10.1093/bioinformatics/bti315
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.