The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
MULTIPROSPECTOR: An algorithm for the prediction of protein–protein interactions by multimeric threading
Open accessAbstract
In this postgenomic era, the ability to identify protein–protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein–protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z‐score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI‐BLAST using a (less) permissive E‐value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein–protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI‐BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false‐negative rate for yeast‐predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein–protein interactions on a genomic scale has been developed. Proteins 2002;49:350–364. © 2002 Wiley‐Liss, Inc.
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Cites
A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae
Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., et al. (2000) · Nature · doi:10.1038/35001009 · Cited by 4,706
A comprehensive two-hybrid analysis to explore the yeast protein interactome
Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., & Sakaki, Y. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.061034498 · Cited by 3,566
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
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221
Topology fingerprint approach to the inverse protein folding problem
Godzik, A., Kolinski, A., & Skolnick, J. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)90693-e · Cited by 339
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021) · Molecular Diversity · doi:10.1007/s11030-021-10217-3 · Cited by 1,473
“In this method, proteins with known template structures are rethreaded, and their interaction with other proteins, their interfacial energy, and Z-score are established [154].”
MethodProtein-Protein Interaction Detection: Methods and Analysis
Rao, V. S., Srinivas, K., Sujini, G. N., & Kumar, G. N. S. (2014) · International Journal of Proteomics · doi:10.1155/2014/147648 · Cited by 811
Structure-based prediction of protein–protein interactions on a genome-wide scale
Zhang, Q. C., Petrey, D., Deng, L., Qiang, L., Shi, Y., Thu, C. A., Bisikirska, B., Lefebvre, C., Accili, D., Hunter, T., et al. (2012) · Nature · doi:10.1038/nature11503 · Cited by 723
Vreven, T., Moal, I. H., Vangone, A., Pierce, B. G., Kastritis, P. L., Torchala, M., Chaleil, R., Jiménez-García, B., Bates, P. A., Fernandez-Recio, J., et al. (2015) · Journal of Molecular Biology · doi:10.1016/j.jmb.2015.07.016 · Cited by 424
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
Metadata
- Authors
- Lu, L., Lu, H., & Skolnick, J.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2002-09-19
- Volume
- 49
- Issue
- 3
- Pages
- 350-364
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2160223331
- Cited by
- 240
- References
- 6
- FWCI
- 4.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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