GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line.     

Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection

Meta-predictors make predictions by organizing and processing the predictions produced by several other predictors in a defined problem domain. A proficient meta-predictor not only offers better predicting performance than the individual predictors from which it is constructed, but it also relieves experimentally researchers from making difficult judgments when faced with conflicting results made by multiple prediction programs. As increasing numbers of predicting programs are being developed in a large number of fields of life sciences, there is an urgent need for effective meta-prediction strategies to be investigated. We compiled four unbiased phosphorylation site datasets, each for one of the four major serine/threonine (S/T) protein kinase families-CDK, CK2, PKA and PKC. Using these datasets, we examined several meta-predicting strategies with 15 phosphorylation site predictors from six predicting programs: GPS, KinasePhos, NetPhosK, PPSP, PredPhospho and Scansite. Meta-predictors constructed with a generalized weighted voting meta-predicting strategy with parameters determined by restricted grid search possess the best performance, exceeding that of all individual predictors in predicting phosphorylation sites of all four kinase families. Our results demonstrate a useful decision-making tool for analysing the predictions of the various S/T phosphorylation site predictors. An implementation of these meta-predictors is available on the web at: http://MetaPred.umn.edu/MetaPredPS/.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary sequences can help predict phosphorylation sites catalyzed by different protein kinase and most computational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are considered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic detection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were obtained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and convenience.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary se-quences can help predict phosphorylation sites catalyzed by different protein kinase and most com-putational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are consid-ered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic de-tection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were ob-tained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and con-venience.     

Aurora B phosphorylates multiple sites on mitotic centromere-associated kinesin to spatially and temporally regulate its function

Chromosome congression and segregation require the proper attachment of microtubules to the two sister kinetochores. Disruption of either Aurora B kinase or the Kinesin-13 mitotic centromere-associated kinesin (MCAK) increases chromosome misalignment and missegregation due to improper kinetochore-microtubule attachments. MCAK localization and activity are regulated by Aurora B, but how Aurora B phosphorylation of MCAK affects spindle assembly is unclear. Here, we show that the binding of MCAK to chromosome arms is also regulated by Aurora B and that Aurora B-dependent chromosome arm and centromere localization is regulated by distinct two-site phosphoregulatory mechanisms. MCAK association with chromosome arms is promoted by phosphorylation of T95 on MCAK, whereas phosphorylation of S196 on MCAK promotes dissociation from the arms. Although targeting of MCAK to centromeres requires phosphorylation of S110 on MCAK, dephosphorylation of T95 on MCAK increases the binding of MCAK to centromeres. Our study reveals a new role for Aurora B, which is to prevent excess MCAK binding to chromatin to facilitate chromatin-nucleated spindle assembly. Our study also shows that the interplay between multiple phosphorylation sites of MCAK may be critical to temporally and spatially control MCAK function.     

Proteome-wide prediction of PKA phosphorylation sites in eukaryotic kingdom

Protein phosphorylation is one of the most essential post-translational modifications (PTMs), and orchestrates a variety of cellular functions and processes. Besides experimental studies, numerous computational predictors implemented in various algorithms have been developed for phosphorylation sites prediction. However, large-scale predictions of kinase-specific phosphorylation sites have not been successfully pursued and remained to be a great challenge. In this work, we raised a “kiss farewell” model and conducted a high-throughput prediction of cAMP-dependent kinase (PKA) phosphorylation sites. Since a protein kinase (PK) should at least “kiss” its substrates and then run away, we proposed a PKA-binding protein to be a potential PKA substrate if at least one PKA site was predicted. To improve the prediction specificity, we reduced false positive rate (FPR) less than 1% when the cut-off value was set as 4. Successfully, we predicted 1387, 630, 568 and 912 potential PKA sites from 410, 217, 173 and 260 PKA-interacting proteins in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens, respectively. Most of these potential phosphorylation sites remained to be experimentally verified. In addition, we detected two sites in one of PKA regulatory subunits to be conserved in eukaryotes as potentially ancient regulatory signals. Our prediction results provide an excellent resource for delineating PKA-mediated signaling pathways and their system integration underlying cellular dynamics and plasticity.     

Prediction of phosphorylation sites using SVMs

MOTIVATION: Phosphorylation is involved in diverse signal transduction pathways. By predicting phosphorylation sites and their kinases from primary protein sequences, we can obtain much valuable information that can form the basis for further research. Using support vector machines, we attempted to predict phosphorylation sites and the type of kinase that acts at each site. RESULTS: Our prediction system was limited to phosphorylation sites catalyzed by four protein kinase families and four protein kinase groups. The accuracy of the predictions ranged from 83 to 95% at the kinase family level, and 76-91% at the kinase group level. The prediction system used-PredPhospho-can be applied to the functional study of proteins, and can help predict the changes in phosphorylation sites caused by amino acid variations at intra- and interspecies levels.     

Aurora B regulates MCAK at the mitotic centromere

Chromosome orientation and alignment within the mitotic spindle requires the Aurora B protein kinase and the mitotic centromere-associated kinesin (MCAK). Here, we report the regulation of MCAK by Aurora B. Aurora B inhibited MCAK's microtubule depolymerizing activity in vitro, and phospho-mimic (S/E) mutants of MCAK inhibited depolymerization in vivo. Expression of either MCAK (S/E) or MCAK (S/A) mutants increased the frequency of syntelic microtubule-kinetochore attachments and mono-oriented chromosomes. MCAK phosphorylation also regulates MCAK localization: the MCAK (S/E) mutant frequently localized to the inner centromere while the (S/A) mutant concentrated at kinetochores. We also detected two different binding sites for MCAK using FRAP analysis of the different MCAK mutants. Moreover, disruption of Aurora B function by expression of a kinase-dead mutant or RNAi prevented centromeric targeting of MCAK. These results link Aurora B activity to MCAK function, with Aurora B regulating MCAK's activity and its localization at the centromere and kinetochore.     

Identifying human kinase-specific protein phosphorylation sites by integrating heterogeneous information from various sources

Phosphorylation is an important type of protein post-translational modification. Identification of possible phosphorylation sites of a protein is important for understanding its functions. Unbiased screening for phosphorylation sites by in vitro or in vivo experiments is time consuming and expensive; in silico prediction can provide functional candidates and help narrow down the experimental efforts. Most of the existing prediction algorithms take only the polypeptide sequence around the phosphorylation sites into consideration. However, protein phosphorylation is a very complex biological process in vivo. The polypeptide sequences around the potential sites are not sufficient to determine the phosphorylation status of those residues. In the current work, we integrated various data sources such as protein functional domains, protein subcellular location and protein-protein interactions, along with the polypeptide sequences to predict protein phosphorylation sites. The heterogeneous information significantly boosted the prediction accuracy for some kinase families. To demonstrate potential application of our method, we scanned a set of human proteins and predicted putative phosphorylation sites for Cyclin-dependent kinases, Casein kinase 2, Glycogen synthase kinase 3, Mitogen-activated protein kinases, protein kinase A, and protein kinase C families (available at http://cmbi.bjmu.edu.cn/huphospho). The predicted phosphorylation sites can serve as candidates for further experimental validation. Our strategy may also be applicable for the in silico identification of other post-translational modification substrates.     

In silico studies of potential phosphoresidues in the human nucleophosmin/B23: its kinases and related biological processes

Human nucleophosmin/B23 is a phosphoprotein involved in ribosome biogenesis, centrosome duplication, cancer, and apoptosis. Its function, localization, and mobility within cells, are highly regulated by phosphorylation events. Up to 21 phosphosites of B23 have been experimentally verified even though the corresponding kinase is known only for seven of them. In this work, we predict the phosphorylation sites in human B23 using six kinase-specific servers (KinasePhos 2.0, PredPhospho, NetPhosK 1.0, PKC Scan, pkaPS, and MetaPredPS) plus DISPHOS 1.3, which is not kinase specific. The results were integrated with information regarding 3D structure and residue conservation of B23, as well as cellular localizations, cellular processes, signaling pathways and protein-protein interaction networks involving both B23 and each predicted kinase. Thus, all 40 potential phosphosites of B23 were predicted with significant score (>0.50) as substrates of at least one of 38 kinases. Thirteen of these residues are newly proposed showing high susceptibility of phosphorylation considering their solvent accessibility. Our results also suggest that the enzymes CDKs, PKC, CK2, PLK1, and PKA could phosphorylate B23 at higher number of sites than those previously reported. Furthermore, PDK, GSK3, ATM, MAPK, PKB, and CHK1 could mediate multisite phosphorylation of B23, although they have not been verified as kinases for this protein. Finally, we suggest that B23 phosphorylation is related to cellular processes such as apoptosis, cell survival, cell proliferation, and response to DNA damage stimulus, in which these kinases are involved. These predictions could contribute to a better understanding, as well as addressing further experimental studies, of B23 phosphorylation.     

PLK1 phosphorylates mitotic centromere-associated kinesin and promotes its depolymerase activity

During cell division, interaction between kinetochores and dynamic spindle microtubules governs chromosome movements. The microtubule depolymerase mitotic centromere-associated kinesin (MCAK) is a key regulator of mitotic spindle assembly and dynamics. However, the regulatory mechanisms underlying its depolymerase activity during the cell cycle remain elusive. Here, we showed that PLK1 is a novel regulator of MCAK in mammalian cells. MCAK interacts with PLK1 in vitro and in vivo. The neck and motor domain of MCAK associates with the kinase domain of PLK1. MCAK is a novel substrate of PLK1, and the phosphorylation stimulates its microtubule depolymerization activity of MCAK in vivo. Overexpression of a polo-like kinase 1 phosphomimetic mutant MCAK causes a dramatic increase in misaligned chromosomes and in multipolar spindles in mitotic cells, whereas overexpression of a nonphosphorylatable MCAK mutant results in aberrant anaphase with sister chromatid bridges, suggesting that precise regulation of the MCAK activity by PLK1 phosphorylation is critical for proper microtubule dynamics and essential for the faithful chromosome segregation. We reasoned that dynamic regulation of MCAK phosphorylation by PLK1 is required to orchestrate faithful cell division, whereas the high levels of PLK1 and MCAK activities seen in cancer cells may account for a mechanism underlying the pathogenesis of genomic instability.     

A Grammar Inference Approach for Predicting Kinase Specific Phosphorylation Sites

Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.     

Aurora B phosphorylates centromeric MCAK and regulates its localization and microtubule depolymerization activity

BACKGROUND: Sister kinetochores must bind microtubules in a bipolar fashion to equally segregate chromosomes during mitosis. The molecular mechanisms underlying this process remain unclear. Aurora B likely promotes chromosome biorientation by regulating kinetochore-microtubule attachments. MCAK (mitotic centromere-associated kinesin) is a Kin I kinesin that can depolymerize microtubules. These two proteins both localize to mitotic centromeres and have overlapping mitotic functions, including regulation of microtubule dynamics, proper chromosome congression, and correction of improper kinetochore-microtubule attachments. RESULTS: We show that Aurora B phosphorylates and regulates MCAK both in vitro and in vivo. Specifically, we mapped six Aurora B phosphorylation sites on MCAK in both the centromere-targeting domain and the neck region. Aurora B activity was required to localize MCAK to centromeres, but not to spindle poles. Aurora B phosphorylation of serine 196 in the neck region of MCAK inhibited its microtubule depolymerization activity. We found that this key site was phosphorylated at centromeres and anaphase spindle midzones in vivo. However, within the inner centromere there were pockets of both phosphorylated and unphosphorylated MCAK protein, suggesting that phosphate turnover is crucial in the regulation of MCAK activity. Addition of alpha-p-S196 antibodies to Xenopus egg extracts or injection of alpha-p-S196 antibodies into cells caused defects in chromosome positioning and/or segregation. CONCLUSIONS: We have established a direct link between the microtubule depolymerase MCAK and Aurora B kinase. Our data suggest that Aurora B both positively and negatively regulates MCAK during mitosis. We propose that Aurora B biorients chromosomes by directing MCAK to depolymerize incorrectly oriented kinetochore microtubules.     

Signaling-dependent Phosphorylation of Mitotic Centromere-associated Kinesin Regulates Microtubule Depolymerization and Its Centrosomal Localization

Although p21-activated kinase 1 (PAK1) and microtubule (MT) dynamics regulate numerous fundamental processes including cytoskeleton remodeling, directional motility, and mitotic functions, the significance of PAK1 signaling in regulating the functions of MT-destabilizing protein mitotic centromere-associated kinesin (MCAK) remains unknown. Here we found that MCAK is a cognate substrate of PAK1 wherein PAK1 phosphorylates MCAK on serines 192 and 111 both in vivo and in vitro. Furthermore, we found that PAK1 phosphorylation of MCAK on serines 192 and 111 preferentially regulates its microtubule depolymerization activity and localization to centrosomes, respectively, in the mammalian cells.     

Cloning and expression of two human p70 S6 kinase polypeptides differing only at their amino termini.

Two classes of human cDNA encoding the insulin/mitogen-activated p70 S6 kinase have been isolated; the two classes differ only in the 5' region, such that the longer polypeptide (p70 S6 kinase alpha I; calculated Mr 58,946) consists of 525 amino acids, of which the last 502 residues are identical in sequence to the entire polypeptides encoded by the second cDNA (p70 S6 kinase alpha II; calculated Mr 56,153). Both p70 S6 kinase polypeptides predicted by these cDNAs are present in p70 S6 kinase purified from rat liver, and each is thus expressed in vivo. Moreover, both polypeptides are expressed from a single mRNA transcribed from the (longer) p70 S6 kinase alpha I cDNA through the utilization of different translational start sites. Although the two p70 S6 kinase polypeptides differ by only 23 amino acid residues, the slightly longer alpha I polypeptide exhibits anomalously slow mobility on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), migrating at an apparent Mr of 90,000 probably because of the presence of six consecutive Arg residues immediately following the initiator methionine. Transient expression of p70 alpha I and alpha II S6 kinase cDNA in COS cells results in a 2.5- to 4-fold increase in overall S6 kinase activity. Upon immunoblotting, the recombinant p70 polypeptides appear as a closely spaced ladder of four to five bands between 65 and 70 kDa (alpha II) and 85 and 90 kDa (alpha I). Transfection with the alpha II cDNA yields only the smaller set of bands, while transfection with the alpha I cDNA generates both sets of bands. Mutation of Met-24 in the alpha I cDNA to Leu or Thr suppresses synthesis of the alpha II polypeptides. Only the p70 alpha I and alpha II polypeptides of slowest mobility on SDS-PAGE comigrate with the 70- and 90-kDa proteins observed in purified rat liver S6 kinase. Moreover, it is the recombinant p70 polypeptides of slowest mobility that coelute with S6 kinase activity on anion-exchange chromatography. The slower mobility and higher enzymatic activity of these p70 proteins is due to Ser/Thr phosphorylation, inasmuch as treatment with phosphatase 2A inactivates kinase activity and increases the mobility of the bands on SDS-PAGE in an okadaic acid-sensitive manner. Thus, the recombinant p70 S6 kinase undergoes multiple phosphorylation and partial activation in COS cells. Acquisition of S6 protein kinase catalytic function, however, is apparently restricted to the most extensively phosphorylated recombinant polypeptides.     

Xenopus laevis occludin. Identification of in vitro phosphorylation sites by protein kinase CK2 and association with cingulin.

Occludin is a protein component of the membrane domain of tight junctions, and has been shown to be phosphorylated in vivo in cultured cells and Xenopus laevis embryos. However, nothing is known about the identity of specific occludin kinase(s) and occludin phosphorylation site(s). Furthermore, nothing is known about the interaction of occludin with cingulin, a cytoplasmic plaque component of tight junctions. Here we report the isolation and sequencing of a complete X. laevis occludin cDNA, and experiments aimed at mapping X. laevis occludin in vitro phosphorylation site(s) and characterizing occludin interaction with cingulin. The sequence of Xenopus occludin is homologous to that of occludins from other species, with identities ranging from 41% to 58%. Bacterially expressed domain E of Xenopus occludin (amino acids 247-493) was a good substrate for protein kinase CK2 (stoichiometry 10.8%, Km 8.4 microM) but not for CK1 kinase, protein kinase A, cdc2 kinase, MAP kinase or syk kinase. Residues Thr375 and Ser379 were identified as potential CK2 phosphorylation sites in this region based on sequence analysis. Mutation of Ser379 to aspartic acid or alanine reduced phosphorylation by CK2 by approximately 50%, and double mutation of Ser379 into aspartic acid and Thr375 into aspartic acid essentially abolished phosphorylation. Glutathione S-transferase (GST) pull-down experiments using extracts of Xenopus A6 epithelial cells showed that constructs of GST fused to wild-type and mutant forms of the C-terminal region of X. laevis occludin associate with several polypeptides, and immunoblot analysis showed that one of these polypeptides is cingulin. GST pull-down experiments using in vitro translated, full-length Xenopus cingulin indicated that cingulin interacts directly with the C-terminal region of occludin.     

Aurora A phosphorylates MCAK to control ran-dependent spindle bipolarity

During mitosis, mitotic centromere-associated kinesin (MCAK) localizes to chromatin/kinetochores, a cytoplasmic pool, and spindle poles. Its localization and activity in the chromatin region are regulated by Aurora B kinase; however, how the cytoplasmic- and pole-localized MCAK are regulated is currently not clear. In this study, we used Xenopus egg extracts to form spindles in the absence of chromatin and centrosomes and found that MCAK localization and activity are tightly regulated by Aurora A. This regulation is important to focus microtubules at aster centers and to facilitate the transition from asters to bipolar spindles. In particular, we found that MCAK colocalized with NuMA and XMAP215 at the center of Ran asters where its activity is regulated by Aurora A-dependent phosphorylation of S196, which contributes to proper pole focusing. In addition, we found that MCAK localization at spindle poles was regulated through another Aurora A phosphorylation site (S719), which positively enhances bipolar spindle formation. This is the first study that clearly defines a role for MCAK at the spindle poles as well as identifies another key Aurora A substrate that contributes to spindle bipolarity.     

Prediction of cyclin-dependent kinase phosphorylation substrates

Protein phosphorylation, mediated by a family of enzymes called cyclin-dependent kinases (Cdks), plays a central role in the cell-division cycle of eukaryotes. Phosphorylation by Cdks directs the cell cycle by modifying the function of regulators of key processes such as DNA replication and mitotic progression. Here, we present a novel computational procedure to predict substrates of the cyclin-dependent kinase Cdc28 (Cdk1) in the Saccharomyces cerevisiae. Currently, most computational phosphorylation site prediction procedures focus solely on local sequence characteristics. In the present procedure, we model Cdk substrates based on both local and global characteristics of the substrates. Thus, we define the local sequence motifs that represent the Cdc28 phosphorylation sites and subsequently model clustering of these motifs within the protein sequences. This restraint reflects the observation that many known Cdk substrates contain multiple clustered phosphorylation sites. The present strategy defines a subset of the proteome that is highly enriched for Cdk substrates, as validated by comparing it to a set of bona fide, published, experimentally characterized Cdk substrates which was to our knowledge, comprehensive at the time of writing. To corroborate our model, we compared its predictions with three experimentally independent Cdk proteomic datasets and found significant overlap. Finally, we directly detected in vivo phosphorylation at Cdk motifs for selected putative substrates using mass spectrometry.     

GPS 5.0: An Update on the Prediction of Kinase-specific Phosphorylation Sites in Proteins

In eukaryotes, protein phosphorylation is specifically catalyzed by numerous protein kinases(PKs), faithfully orchestrates various biological processes, and reversibly determines cellular dynamics and plasticity. Here we report an updated algorithm of Group-based Prediction System(GPS) 5.0 to improve the performance for predicting kinase-specific phosphorylation sites(p-sites). Two novel methods, position weight determination(PWD) and scoring matrix optimization(SMO), were developed. Compared with other existing tools, GPS 5.0 exhibits a highly competitive accuracy. Besides serine/threonine or tyrosine kinases, GPS 5.0 also supports the prediction of dual-specificity kinase-specific p-sites. In the classical module of GPS 5.0, 617 individual predictors were constructed for predicting p-sites of 479 human PKs. To extend the application of GPS5.0, a species-specific module was implemented to predict kinase-specific p-sites for 44,795 PKs in161 eukaryotes. The online service and local packages of GPS 5.0 are freely available for academic research at http://gps.biocuckoo.cn.     

Molecular dissection of the microtubule depolymerizing activity of mitotic centromere-associated kinesin

Mitotic centromere-associated kinesin (MCAK) is a microtubule depolymerizer that is consistent with its role in promoting chromosome segregation during mitosis. Here we show that the conserved motor domain of MCAK is necessary but not sufficient for microtubule depolymerization in cells or in vitro. The addition of only 30 amino acids N-terminal to the motor restores depolymerization activity. Furthermore, dimerization studies revealed that the smallest functional MCAK deletion constructs are monomers. These results define a highly conserved domain within MCAK and related (KIN I) kinesins that is critical for depolymerization activity and show that this depolymerization is not dependent on MCAK dimerization.