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HOMCOS: a server to predict interacting protein pairs and interacting sites by homology modeling of complex structures
As protein–protein interactions are crucial in most biological processes, it is valuable to understand how and where protein pairs interact. We developed a web server HOMCOS (Homology Modeling of Complex Structure, http://biunit.naist.jp/homcos) to predict interacting protein pairs and interacting s...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447736/ https://www.ncbi.nlm.nih.gov/pubmed/18442990 http://dx.doi.org/10.1093/nar/gkn218 |
Sumario: | As protein–protein interactions are crucial in most biological processes, it is valuable to understand how and where protein pairs interact. We developed a web server HOMCOS (Homology Modeling of Complex Structure, http://biunit.naist.jp/homcos) to predict interacting protein pairs and interacting sites by homology modeling of complex structures. Our server is capable of three services. The first is modeling heterodimers from two query amino acid sequences posted by users. The server performs BLAST searches to identify homologous templates in the latest representative dataset of heterodimer structures generated from the PQS database. Structure validity is evaluated by the combination of sequence similarity and knowledge-based contact potential energy as previously described. The server generates a sequence-replaced model PDB file and a MODELLER script to build full atomic models of complex structures. The second service is modeling homodimers from one query sequence. The third service is identification of potentially interacting proteins for one query sequence. The server searches the dataset of heterodimer structures for a homologous template, outputs the candidate interacting sequences in the Uniprot database homologous for the interacting partner template proteins. These features are useful for wide range of researchers to predict putative interaction sites and interacting proteins. |
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