Cargando…

Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach

Systematic identification of binding partners for modular domains such as Src homology 2 (SH2) is important for understanding the biological function of the corresponding SH2 proteins. We have developed a worldwide web-accessible computer program dubbed SMALI for scoring matrix-assisted ligand ident...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Lei, Wu, Chenggang, Huang, Haiming, Zhang, Kaizhong, Gan, Jacob, Li, Shawn S.-C.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2425477/
https://www.ncbi.nlm.nih.gov/pubmed/18424801
http://dx.doi.org/10.1093/nar/gkn161
_version_ 1782156264090894336
author Li, Lei
Wu, Chenggang
Huang, Haiming
Zhang, Kaizhong
Gan, Jacob
Li, Shawn S.-C.
author_facet Li, Lei
Wu, Chenggang
Huang, Haiming
Zhang, Kaizhong
Gan, Jacob
Li, Shawn S.-C.
author_sort Li, Lei
collection PubMed
description Systematic identification of binding partners for modular domains such as Src homology 2 (SH2) is important for understanding the biological function of the corresponding SH2 proteins. We have developed a worldwide web-accessible computer program dubbed SMALI for scoring matrix-assisted ligand identification for SH2 domains and other signaling modules. The current version of SMALI harbors 76 unique scoring matrices for SH2 domains derived from screening oriented peptide array libraries. These scoring matrices are used to search a protein database for short peptides preferred by an SH2 domain. An experimentally determined cut-off value is used to normalize an SMALI score, therefore allowing for direct comparison in peptide-binding potential for different SH2 domains. SMALI employs distinct scoring matrices from Scansite, a popular motif-scanning program. Moreover, SMALI contains built-in filters for phosphoproteins, Gene Ontology (GO) correlation and colocalization of subject and query proteins. Compared to Scansite, SMALI exhibited improved accuracy in identifying binding peptides for SH2 domains. Applying SMALI to a group of SH2 domains identified hundreds of interactions that overlap significantly with known networks mediated by the corresponding SH2 proteins, suggesting SMALI is a useful tool for facile identification of signaling networks mediated by modular domains that recognize short linear peptide motifs.
format Text
id pubmed-2425477
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-24254772008-06-12 Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach Li, Lei Wu, Chenggang Huang, Haiming Zhang, Kaizhong Gan, Jacob Li, Shawn S.-C. Nucleic Acids Res Computational Biology Systematic identification of binding partners for modular domains such as Src homology 2 (SH2) is important for understanding the biological function of the corresponding SH2 proteins. We have developed a worldwide web-accessible computer program dubbed SMALI for scoring matrix-assisted ligand identification for SH2 domains and other signaling modules. The current version of SMALI harbors 76 unique scoring matrices for SH2 domains derived from screening oriented peptide array libraries. These scoring matrices are used to search a protein database for short peptides preferred by an SH2 domain. An experimentally determined cut-off value is used to normalize an SMALI score, therefore allowing for direct comparison in peptide-binding potential for different SH2 domains. SMALI employs distinct scoring matrices from Scansite, a popular motif-scanning program. Moreover, SMALI contains built-in filters for phosphoproteins, Gene Ontology (GO) correlation and colocalization of subject and query proteins. Compared to Scansite, SMALI exhibited improved accuracy in identifying binding peptides for SH2 domains. Applying SMALI to a group of SH2 domains identified hundreds of interactions that overlap significantly with known networks mediated by the corresponding SH2 proteins, suggesting SMALI is a useful tool for facile identification of signaling networks mediated by modular domains that recognize short linear peptide motifs. Oxford University Press 2008-06 2008-04-19 /pmc/articles/PMC2425477/ /pubmed/18424801 http://dx.doi.org/10.1093/nar/gkn161 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Li, Lei
Wu, Chenggang
Huang, Haiming
Zhang, Kaizhong
Gan, Jacob
Li, Shawn S.-C.
Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title_full Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title_fullStr Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title_full_unstemmed Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title_short Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
title_sort prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2425477/
https://www.ncbi.nlm.nih.gov/pubmed/18424801
http://dx.doi.org/10.1093/nar/gkn161
work_keys_str_mv AT lilei predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach
AT wuchenggang predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach
AT huanghaiming predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach
AT zhangkaizhong predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach
AT ganjacob predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach
AT lishawnsc predictionofphosphotyrosinesignalingnetworksusingascoringmatrixassistedligandidentificationapproach