The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Predicted protein–protein interaction sites from local sequence information
Abstract
Protein–protein interactions are facilitated by a myriad of residue–residue contacts on the interacting proteins. Identifying the site of interaction in the protein is a key for deciphering its functional mechanisms, and is crucial for drug development. Many studies indicate that the compositions of contacting residues are unique. Here, we describe a neural network that identifies protein–protein interfaces from sequence. For the most strongly predicted sites (in 34 of 333 proteins), 94% of the predictions were confirmed experimentally. When 70% of our predictions were right, we correctly predicted at least one interaction site in 20% of the complexes (66/333). These results indicate that the prediction of some interaction sites from sequence alone is possible. Incorporating evolutionary and predicted structural information may improve our method. However, even at this early stage, our tool might already assist wet‐lab biology.
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Cites
Principles of protein-protein interactions
Jones, S., & Thornton, J. M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.13 · Cited by 2,684
Detecting Protein Function and Protein-Protein Interactions from Genome Sequences
Marcotte, E. M., Pellegrini, M., Ng, H.-L., Rice, D. W., Yeates, T. O., & Eisenberg, D. (1999) · Science · doi:10.1126/science.285.5428.751 · Cited by 1,670
Karp, P. D., Paley, S., & Romero, P. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s225 · Cited by 661
Cited by
Rost, B., Yachdav, G., & Liu, J. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh377 · Cited by 1,453
Self-citationKeskin, O., Ma, B., & Nussinov, R. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.10.077 · Cited by 519
Zeng, M., Zhang, F., Wu, F.-X., Li, Y., Wang, J., & Li, M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz699 · Cited by 281
Deep Learning in Protein Structural Modeling and Design
Gao, W., Mahajan, S. P., Sulam, J., & Gray, J. J. (2020) · Patterns · doi:10.1016/j.patter.2020.100142 · Cited by 227
Protein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination
Mukherjee, S., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.04.006 · Cited by 174
Metadata
- Authors
- Ofran, Y., & Rost, B.
- Venue
- FEBS Letters
- Publisher
- Wiley
- Published
- 2003-05-14
- Volume
- 544
- Issue
- 1-3
- Pages
- 236-239
- ISSN
- 0014-5793 (ISSN-L)
- 1873-3468
- OpenAlex
- W2000093524
- Cited by
- 255
- References
- 3
- FWCI
- 5.58
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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