The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists.

Ferraro, E., Via, A., Ausiello, G., HELMER CITTERICH, M. (2005). A neural strategy for the inference of SH3 domain-peptide interaction specificity. BMC BIOINFORMATICS, 6 Suppl 4(6), S13 [10.1186/1471-2105-6-S4-S13].

A neural strategy for the inference of SH3 domain-peptide interaction specificity

AUSIELLO, GABRIELE;HELMER CITTERICH, MANUELA
2005-12-01

Abstract

The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists.
1-dic-2005
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore BIO/11 - BIOLOGIA MOLECOLARE
English
Con Impact Factor ISI
Sensitivity and Specificity; Saccharomyces cerevisiae; Computational Biology; Protein Structure, Tertiary; Peptides; src Homology Domains; Saccharomyces cerevisiae Proteins; Amino Acid Motifs; Protein Conformation; Neural Networks (Computer); Binding Sites; Models, Molecular; Peptide Library; Proteins; Sequence Alignment; Amino Acid Sequence; Ligands; Protein Binding
http://www.biomedcentral.com/1471-2105/6/S4/S13
Ferraro, E., Via, A., Ausiello, G., HELMER CITTERICH, M. (2005). A neural strategy for the inference of SH3 domain-peptide interaction specificity. BMC BIOINFORMATICS, 6 Suppl 4(6), S13 [10.1186/1471-2105-6-S4-S13].
Ferraro, E; Via, A; Ausiello, G; HELMER CITTERICH, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/15262
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