Web-based computational tools for the prediction and analysis of post-translational modifications of proteins.
TL;DR: The paper presents a set of computational protocols describing how to work with the Internet resources when dealing withPTMSs, intended for querying in PTMSs related data bases, search of the PT MSs in the protein sequences and structures, and calculating the pI and molecular mass of the PTM isoforms.
Abstract: The increase in the number of Web-based resources on posttranslational modification sites (PTMSs) in proteins is accelerating. This chapter presents a set of computational protocols describing how to work with the Internet resources when dealing with PTMSs. The protocols are intended for querying in PTMS-related databases, search of the PTMSs in the protein sequences and structures, and calculating the pI and molecular mass of the PTM isoforms. Thus, the modern bioinformatics prediction tools make it feasible to express protein modification in broader quantitative terms.
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TL;DR: High-resolution profiling of PTM networks will advance disease understanding and precision medicine, which can accelerate the discovery of biomarkers and drug targets and allow systems level insights into their network architecture.
Abstract: The biological complexity cannot be captured by genes or proteins alone. The protein posttranslational modifications (PTMs) impart functional diversity to the proteome and regulate protein structure, activity, localization and interactions. Their dynamics drive cellular signaling, growth and development while their dysregulation causes many diseases. Mass spectrometry based quantitative profiling of PTMs and bioinformatics analysis tools allow systems level insights into their network architecture. High-resolution profiling of PTM networks will advance disease understanding and precision medicine. It can accelerate the discovery of biomarkers and drug targets. This requires better tools for unbiased, high-throughput and accurate PTM identification, site localization and automated annotation on a systems level.
10 citations
TL;DR: In this paper, a review of post-translational modifications (PTMs) or protein interaction network and delineating if PTMs or their changes and cross-talks are involved during infection, disease initiation or as a result of disease progression is presented.
5 citations
01 Jan 2008
1 citations
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TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Abstract: The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
34,239 citations
TL;DR: An artificial neural network method is presented that predicts phosphorylation sites in independent sequences with a sensitivity in the range from 69 % to 96 % and predicts novel phosphorylated sites in the p300/CBP protein that may regulate interaction with transcription factors and histone acetyltransferase activity.
2,984 citations
2,583 citations
TL;DR: A full understanding of the pathogenesis of the protein-folding diseases will require greater knowledge of how misfolded proteins are recognized and selectively degraded.
Abstract: The ultimate mechanism that cells use to ensure the quality of intracellular proteins is the selective destruction of misfolded or damaged polypeptides. In eukaryotic cells, the large ATP-dependent proteolytic machine, the 26S proteasome, prevents the accumulation of non-functional, potentially toxic proteins. This process is of particular importance in protecting cells against harsh conditions (for example, heat shock or oxidative stress) and in a variety of diseases (for example, cystic fibrosis and the major neurodegenerative diseases). A full understanding of the pathogenesis of the protein-folding diseases will require greater knowledge of how misfolded proteins are recognized and selectively degraded.
2,004 citations
TL;DR: A new method for kinase‐specific prediction of phosphorylation sites, NetPhosK, is presented, which extends the earlier and more general tool, netPhos, and the issues of underestimation, over‐prediction and strategies for improving prediction specificity are discussed.
Abstract: Post-translational modifications (PTMs) occur on almost all proteins analyzed to date. The function of a modified protein is often strongly affected by these modifications and therefore increased knowledge about the potential PTMs of a target protein may increase our understanding of the molecular processes in which it takes part. High-throughput methods for the identification of PTMs are being developed, in particular within the fields of proteomics and mass spectrometry. However, these methods are still in their early stages, and it is indeed advantageous to cut down on the number of experimental steps by integrating computational approaches into the validation procedures. Many advanced methods for the prediction of PTMs exist and many are made publicly available. We describe our experiences with the development of prediction methods for phosphorylation and glycosylation sites and the development of PTM-specific databases. In addition, we discuss novel ideas for PTM visualization (exemplified by kinase landscapes) and improvements for prediction specificity (by using ESS--evolutionary stable sites). As an example, we present a new method for kinase-specific prediction of phosphorylation sites, NetPhosK, which extends our earlier and more general tool, NetPhos. The new server, NetPhosK, is made publicly available at the URL http://www.cbs.dtu.dk/services/NetPhosK/. The issues of underestimation, over-prediction and strategies for improving prediction specificity are also discussed.
1,838 citations