The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
HotPoint: hot spot prediction server for protein interfaces
Open accessAbstract
The energy distribution along the protein-protein interface is not homogenous; certain residues contribute more to the binding free energy, called 'hot spots'. Here, we present a web server, HotPoint, which predicts hot spots in protein interfaces using an empirical model. The empirical model incorporates a few simple rules consisting of occlusion from solvent and total knowledge-based pair potentials of residues. The prediction model is computationally efficient and achieves high accuracy of 70%. The input to the HotPoint server is a protein complex and two chain identifiers that form an interface. The server provides the hot spot prediction results, a table of residue properties and an interactive 3D visualization of the complex with hot spots highlighted. Results are also downloadable as text files. This web server can be used for analysis of any protein-protein interface which can be utilized by researchers working on binding sites characterization and rational design of small molecules for protein interactions. HotPoint is accessible at http://prism.ccbb.ku.edu.tr/hotpoint.
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Cites
Anatomy of hot spots in protein interfaces
Bogan, A. A., & Thorn, K. S. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1843 · Cited by 1,988
Guerois, R., Nielsen, J. E., & Serrano, L. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00442-4 · Cited by 1,728
Principles of Protein−Protein Interactions: What are the Preferred Ways For Proteins To Interact?
Keskin, O., Gursoy, A., Ma, B., & Nussinov, R. (2008) · Chemical Reviews · doi:10.1021/cr040409x · Cited by 697
Lise, S., Archambeau, C., Pontil, M., & Jones, D. T. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-365 · Cited by 107
Cited by
Chan, C.-H., Morrow, J. K., Li, C.-F., Gao, Y., Jin, G., Moten, A., Stagg, L. J., Ladbury, J. E., Cai, Z., Xu, D., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.048 · Cited by 391
Predicting Protein–Protein Interactions from the Molecular to the Proteome Level
Keskin, O., Tuncbag, N., & Gursoy, A. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00683 · Cited by 369
BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations
Dehouck, Y., Kwasigroch, J. M., Rooman, M., & Gilis, D. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt450 · Cited by 338
Tuncbag, N., Gursoy, A., Nussinov, R., & Keskin, O. (2011) · Nature Protocols · doi:10.1038/nprot.2011.367 · Cited by 263
Self-citationGTP-Dependent K-Ras Dimerization
Muratcioglu, S., Chavan, T. S., Freed, B. C., Jang, H., Khavrutskii, L., Freed, R. N., Dyba, M. A., Stefanisko, K., Tarasov, S. G., Gursoy, A., et al. (2015) · Structure · doi:10.1016/j.str.2015.04.019 · Cited by 202
Metadata
- Authors
- Tuncbag, N., Keskin, O., & Gursoy, A.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-05-05
- Volume
- 38
- Issue
- Web Server
- Pages
- W402-W406
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2103860090
- Cited by
- 207
- References
- 4
- FWCI
- 6.50
- Type
- journal article
- Language
- en
- Open access
- gold
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