※ Computational Resources for Kinase and Phosphatase:

    <1>. Protein Kinase Resources.

        (1) Protein kinase databases.

        (2) Phosphorylation Sites Database.

        (3) Prediction of kinase-specific phosphorylation sites.

        (4) Prediction of non-specific or organism-specific phosphorylation sites.

        (5) Protein kinases associated with diseases.

    <2>. Protein phosphatase Resources.

==================================================================================

<1>. Protein Kinase Resources.


1. Protein kinase databases.

(1) PKR: a Protein Kinase Resource database that includes expanded table set and features comprehensive coverage of all kinase-related data and derived information, including genomic sequences, detailed organism and tissue cataloging, multiple sequence alignments, clustering into families, literature citations and structural data.

(2) Kinomer v. 1.0: is a protein kinase enzyme database utilize a highly sensitive and accurate hidden Markov model-based method for automatic detection and classification of protein kinases in 43 eukaryotic genomes, including fungi (16 species), plants (6), diatoms (1), amoebas (2), protists (1) and animals (17) (Martin, et al., 2009).

(3) KinG: is a comprehensive collection of serine/threonine/tyrosine-specific kinases and their homologues identified in various completed genomes using various sensitive sequence and profile search methods including PSI-BLAST, HMMER-2 and RPS-BLAST. The database allows user to search for kinases with a specific combination of domains and a specific subfamily (Krupa, et al., 2004).

(4) Kinase.com: is a resource including genomics, functions and evolution of protein kinases. Kinase.com also provide a accrute kinase database, KinBase which contains information on over 3000 kinase genes found in a variety of species from unicellular, plant, invertebrate and vertebrate.

(5) PlantsP: is a curated database that combines information derived from sequences with experimental functional genomics information. PlantsP provides framework for proteins involved in phosphory-lation, i.e. protein kinases, protein phosphatases and their substrates in plants. PlantsP also provides a a curated view of each protein that includes a comprehensive annotation of related sequence motifs, sequence family definitions and so on (Gribskov, et al., 2001).

2. Phosphorylation Sites Database.

(1) PhosphoSitePlus: (PSP) is a comprehensive, manually curated and interactive resource on post-translational modifications (PTM). PSP contains encompasses 130000 non-redundant modification sites, manily on phosphorylation, ubiquitinylation and acetylation (Hornbeck, et al., 2004).

(2) Phospho.ELM 8.3: is a database of serine/threonine/tyrosine phosphorylation sites, the data in the database are derived from scientific literature and phosphoproteomic analyses. The database contains more than 42574 serine, threonine and tyrosine non-redundant sites (Diella, et al., 2004; Diella, et al., 2008).

(3) PhosphoNET: presently holds data on over 650,000 known and putative phosphorylation sites in over 23,000 human proteins. The data have been collected from the scientific literature and other reputable websites and about 14% sites have been experimentally validated.

(4) SysPTM: provides a systematic and sophisticated platform for proteomic PTM research. SysPTM contains data detailing 117,349 experimentally determined PTM sites on 33,421 proteins involving nearly 50 PTM types. The data derived from five database, four web serves and more than one hundred peer-reviewed mass spectrometry papers. (Li, et al., 2009)

(5) PHOSIDA: provide posttranslational modification sites of various species ranging from bacteria to human. The data are derived from high-resolution mass spectrometric data using the same stringent quality criteria. Over 80000 phosphorylated, N-glycosylated or acetylated sites have been collecte in the database (Gnad, et al., 2007; Gnad, et al., 2009).

(6) PhospoPep 2.0: support systems biology signaling research by providing interactive interrogation of MS-derived phosphorylation data from 4 different organisms, including fly, human, worm and yeast (Bodenmiller, et al., 2008.).

(7) LymPHOS: is a web-oriented database containing peptidic and protein sequences and spectrometric information on the PhosphoProteome of human T-Lymphocytes (Ovelleiro, et al., 2009).

(8) PhosphoGRID: is a database containing phosphorylation sites curated from the S.cerevisiae primary literature. More than 5000 specific phosphorylated residues on 1495 gene products have been collected in the database and nearly 900 sites are reproted from detailed studies of individual proteins (Stark, et al., 2004).

(9) PhosPhoAT 3.0: information on Arabidopsis phosphorylation sites which were identified by mass spectrometry in large scale experiments by different research groups. The database also provides specific information about peptide properties, annotated biological function and experimental and analytical context (Heazlewood, et al., 2008; Durek, et al., 2010).

(10) ProMEX: is a mass spectral reference database and consists of tryptic peptide fragmentation mass spectra derived from plants (Hummel, et al., 2009).

(11) dbPTM v2.0: is a database that compiles information on protein post-translational modifications (PTMs), including the catalytic sites, solvent accessibility of amino acid residues, protein secondary and tertiary structures, protein domains and protein variations (Lee, et al., 2006).

(12) PhosphoPOINT: is a comprehensive human kinase interactome and phospho-protein database, containing the interactions among kinases, substrates and their interacting phospho-proteins via integrating 4195 phosphoproteins, 518 serine/threonin/tyrosine kinases and PPI datasets (Yang, et al., 2008).

(13) Phospho3D: is a database of three-dimensional structures of phosphorylation sites derived from Phospho.ELM database. The database also contains the results of a large-scale structural comparison procedure procedure providing clues for the identification of new putative phosphorylation sites (Zanzoni, et al., 2007).

3. Prediction of kinase-specific phosphorylation sites.

(1) GPS 2.1: A Group-based Prediction System could predict kinase-specific phosphorylation sites for 408 human Protein Kinases in hierarchy (Xue, et al., 2008).

(2) ScanSite 2.0: could identifies short protein sequence motifs recognized by modular signaling domains, phosphorylated by ser/thr/tyr kinase or mediate specific interactions with protein or phospholipid ligands using position-specific scoring matrix (PSSM) (Obenauer, et al., 2003).

(3) PPSP 1.0: is a kinase-specific phosphorylation sites predictor with Baysian Decision Theory (BDT) (Xue, et al., 2006).

(4) KinasePhos 1.0: use Profile Hidden Markov Model (HMM) to predict phosphorylation sites within given protein sequences. The HMM profiles are derived from learning each groups sequences surrounding to the phosphorylation residues (Huang, et al., 2005).

(5) NetPhosK 1.0: is a prediction application of kinase specific eukaryotic protein phosphorylation sites. NetPhosK covers a variety of protein kinases, including PKA, PKC, PKG, CKII, Cdc2, CaM-II, ATM, DNA PK, Cdk5, p38 MAPK, GSK3, CKI, PKB, RSK, INSR, EGFR and Src (Blom, et al., 2004).

(6) pkaPS: is a Protein Kinase A specific phosphorylation sites predictor. pkaPS uses simplified kinase binding model and can predicte the S/T residues phosphorylated by PKA (Neuberger, et al., 2007).

(7) PhoScan: is a probability-based method for phosphorylation site prediction using MS2/MS3 pair information (Li, et al., 2007).

(8) Netphorest: is a non-redundant collection of 125 sequence-based classifiers for linear motifs in phosphorylation-dependent signaling. The collection contains both family-based and gene-specific classifiers (Miller, et al., 2008).

(9) PredPhospho 1.0: is a SVM algorithm based kinase-specific phosphorylation sites predictor for 4 kinase groups and 4 kinase families. (Kim, et al., 2004).

(10) PredPhospho 2.0: is an enhance version SVM algorithm based kinase-specific phosphorylation sites predictor for 7 kinase groups and 18 kinase families. (Ryu, et al., 2009).

(11) CRPhos 0.8: can predict kinase-specific phosphorylation sites using conditional random fields. (Dang, et al., 2008).

(12) PostMod: combines physicochemical information, motif information, and evolutionary information by simply comaparing sequence similarities, and could predict phosphorylation sites for 48 different kinases. (Jung, et al., 2010).

4. Prediction of non-specific or organism-specific phosphorylation sites.

(1) NetPhos 2.0: could produces neural network predictions for serine, threonine and tyrosine phosphorylation sites in eukaryotic proteins (Blom, et al., 1999).

(2) CRP: Cleaved Radioactivity of Phosphopeptide, performs an in silico proteolytic cleavage of the sequence and reports the predicted Edman cycles in which radioactivity would be observed if a given serine, threonine or tyrosine were phosphorylated (Mackey, et al., 2003).

(3) PHOSIDA: a predictor based on more than 5,000 high confidence phosphosites, with the Support vector machines (SVMs) algorithm (Gnad, et al., 2007).

(5) DISPHOS 1.3: a S/T/Y phosphorylation sites predictor, is trained on over 2000 non-redundant expreimentally confirmed protein phosphorylation sites and use disorder information to improve the discrimination between phosphorylation and non-phosphorylation sites (Iakoucheva, et al., 2004).

(6) NetPhosYeast 1.0: could predicts serine and threonine phosphorylation sites in yeast proteins. (Ingrell, et al., 2007).

(7) NetPhosBac 1.0: could predicts serine and threonine phosphorylation sites in yeast proteins (Miller et al., 2009).

(8) PhosPhAt 3.0: a plant specific phosphorylation site predictor trained on the experimental dataset for Serine, threonine and tyrosine phosphorylation (pSer, pThr, pTyr). Protein sequences or Arabidopsis AGI gene identifier can be submitted to the predictor (Heazlewood, et al., 2008; Durek, et al., 2010).

5. Protein kinases associated with diseases.

(1) KinMutBase: is a comprehensive database of disease-causing mutations in protein kinase domains. This new release of the database contains 582 mutations in 20 tyrosine kinase domains and 13 serine/threonine kinase domains. The database refers 1790 cases from 1322 families. (Ortutay C, et al., 2005).

(2) MoKCa: (Mutations of Kinases in Cancer) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer (Richardson CJ, et al., 2009).

<2>. Protein Phosphatase Resources.


(1) Protein Tyrosine Phosphatases: is a Web-Accessible Resource of Information on Protein Tyrosine Phosphatases. This website provied a peer-reviewed compendium on Protein Tyrosine Phosphatases (PTPs) and intergrates PTP related information, such as sequence, structure, cellular and biological function. This website allows reader to explore the diversity of the PTP family and download files containing distint PTP information, including multiple sequence alignments, phylogenetic trees, structure, molecular graphics files, chromosomal mapping data an so on. In addtion, phylogenetic classification based on sequence similarity is available by using the Blast search.

(2) PhosphaBase: is a Protein Phosphatase Information Resource. This database contains protein phosphatase and information about their protein sequences. The data resource is from Swiss-Prot and TrEMBL database and classificated phosphatase into five superfamily, including PTP, DUSP, PTEN/MTM, Ser/Thr and Histidine. This database also provide three phosphatase analysis tools: PhosphaScan, PhosphaBase3D and PhosphaClass, for analysis of sequence, structure and classification respectively (Wolstencroft, et al., 2005).

(3) PlantsP: is a curated database that combines information derived from sequences with experimental functional genomics information. PlantsP provides framework for proteins involved in phosphory-lation, i.e. protein kinases, protein phosphatases and their substrates in plants. PlantsP also provides a a curated view of each protein that includes a comprehensive annotation of related sequence motifs, sequence family definitions and so on. (Gribskov, et al., 2001)

(4) TAIR (The Arabidopsis Information Resource): is a database containing genetic and molecular biology data for the model higher plant Arabidopsis thaliana. TAIR provides information about Arabidopsis thaliana including gene structure, gene product, metabolism, gene expression, genome maps etc. Protein phosphatase information is also provided in the database.

(5) Kinase Phosphatase Database: is a kinase and phosphatase database organized with their substrates. Users are allowed to search by kinases, phosphatases or by substrates.

(6) PROKARYOTIC PROTEIN PHOSPHATASE DATABASE: is a database provides information of prokaryotic phosphatase derived form scientific literature. Diverse search methods are provided, including search by species, name, reference, classification, and dephosphorylation sites. Crosslinks with UniProt, GenBank and PubMed are also available.