Dataset Information

Proteome-wide detection of Abl1 SH3-binding peptides by integrating computational prediction and peptide microarray.

ABSTRACT: Protein-protein interactions are essential for regulating almost all aspects of cellular functions. Many of these interactions are mediated by weak and transient protein domain-peptide binding, but they are often under-represented in high throughput screening of protein-protein interactions using techniques such as yeast two-hybrid and mass spectrometry. On the other hand, computational predictions and in vitro binding assays are valuable in providing clues of in vivo interactions. We present here a systematic approach that integrates computer modeling and a peptide microarray technology to identify binding peptides of the SH3 domain of the tyrosine kinase Abl1 in the human proteome. Our study provides a comprehensive list of candidate interacting partners for the Abl1 protein, among which the presence of numerous methyltransferases and RNA splicing proteins may suggest a novel function of Abl1 in chromatin remodeling and RNA processing. This study illustrates a powerful approach for integrating computational and experimental methods to detect protein interactions mediated by domain-peptide recognition.

SUBMITTER: Xu Z

PROVIDER: S-EPMC3270110 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Proteome-wide detection of Abl1 SH3-binding peptides by integrating computational prediction and peptide microarray.

Xu Zheng Z Hou Tingjun T Li Nan N Xu Yang Y Wang Wei W

Molecular & cellular proteomics : MCP 20111024 1

Protein-protein interactions are essential for regulating almost all aspects of cellular functions. Many of these interactions are mediated by weak and transient protein domain-peptide binding, but they are often under-represented in high throughput screening of protein-protein interactions using techniques such as yeast two-hybrid and mass spectrometry. On the other hand, computational predictions and in vitro binding assays are valuable in providing clues of in vivo interactions. We present he ...[more]

PMID: 22023807

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Project description:BACKGROUND: Metal-containing proteins comprise a diverse and sizable category within the proteomes of organisms, ranging from proteins that use metals to catalyze reactions to proteins in which metals play key structural roles. Unfortunately, reliably predicting that a protein will contain a specific metal from its amino acid sequence is not currently possible. We recently developed a generally-applicable experimental technique for finding metalloproteins on a genome-wide scale. Applying this metal-directed protein purification approach (ICP-MS and MS/MS based) to the prototypical microbe Pyrococcus furiosus conclusively demonstrated the extent and diversity of the uncharacterized portion of microbial metalloproteomes since a majority of the observed metal peaks could not be assigned to known or predicted metalloproteins. However, even using this technique, it is not technically feasible to purify to homogeneity all metalloproteins in an organism. In order to address these limitations and complement the metal-directed protein purification, we developed a computational infrastructure and statistical methodology to aid in the pursuit and identification of novel metalloproteins. RESULTS: We demonstrate that our methodology enables predictions of metal-protein interactions using an experimental data set derived from a chromatography fractionation experiment in which 870 proteins and 10 metals were measured over 2,589 fractions. For each of the 10 metals, cobalt, iron, manganese, molybdenum, nickel, lead, tungsten, uranium, vanadium, and zinc, clusters of proteins frequently occurring in metal peaks (of a specific metal) within the fractionation space were defined. This resulted in predictions that there are from 5 undiscovered vanadium- to 13 undiscovered cobalt-containing proteins in Pyrococcus furiosus. Molybdenum and nickel were chosen for additional assessment producing lists of genes predicted to encode metalloproteins or metalloprotein subunits, 22 for nickel including seven from known nickel-proteins, and 20 for molybdenum including two from known molybdo-proteins. The uncharacterized proteins are prime candidates for metal-based purification or recombinant approaches to validate these predictions. CONCLUSIONS: We conclude that the largely uncharacterized extent of native metalloproteomes can be revealed through analysis of the co-occurrence of metals and proteins across a fractionation space. This can significantly impact our understanding of metallobiochemistry, disease mechanisms, and metal toxicity, with implications for bioremediation, medicine and other fields.

Dataset Information

Proteome-wide detection of Abl1 SH3-binding peptides by integrating computational prediction and peptide microarray.

Publications

Proteome-wide detection of Abl1 SH3-binding peptides by integrating computational prediction and peptide microarray.

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