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protein phosphorylation is an important and dynamic type of protein modification , orchestrating a variety of cellular signaling processes . about 2% of the human and mouse proteomes encode protein kinases ( pks ) with 518 and 540 distinct pks determined in human ( 1 ) and mouse ( 2 ) , respectively . in vivo or in vitro identification of phosphorylation sites
is labor - intensive , time - consuming and often limited by the availability and optimization of enzymatic reactions .
recently , several large - scale phosphoproteomic data using the mass spectrometry ( ms ) approach have been published for yeast ( 3 ) , mouse ( 4 ) and human ( 5 ) .
but in these cases , it is still difficult to distinguish the kinase - specific sites on the substrates
. the in silico prediction of phosphorylation sites with their specific pks plays an important role in this field .
most of the existing systems adopt the putative rule that protein substrates are phosphorylated at the specific sites with flanking consensus sequences / motifs / functional patterns ( 6 ) .
application of 3d structure conservation / similarity can significantly improve the prediction specificity ( 7,8 ) , but the 3d structure information of proteins is very limited compared with the huge number of protein primary sequences available in the public databases .
thus , it would be more feasible and convenient to predict the phosphorylation sites with the specific pks solely from the protein primary sequences .
for example , disphos distinguishes the potential phosphorylation sites with position - specific amino acid frequencies and disorder information ( 9 ) .
another system netphos outperforms the consensus sequence - based methods by training the artificial neural networks with the known data set ( 10 ) .
however , the above two systems provide little information about the corresponding pks for the predicted phosphorylation sites .
the enhanced version of netphos , netphosk , incorporates the functionality of providing pks ' information for 17 pks ( 11 ) .
scansite ( 12 ) constructs the profiles of known phosphorylation sites of 20 eukaryotic pks for prediction . in this work ,
we present a comprehensive pk - specific prediction server gps ( group - based phosphorylation scoring ) , which can predict kinase - specific phosphorylation sites in the substrate sequence for 71 pk groups , including many newly considered pks , such as aurora - a , aurora - b and nima ( nima - like protein kinases ) , etc .
we evaluate the sensitivity and specificity of different cut - off scores for each pk group by  leave - one - out validation .
the default cut - off scores are chosen for the balanced pair of sensitivity and specificity .
we also use the rat spinophilin ( o35274 ) as an example to illustrate the usage of the gps server . compared with the two separate in vivo or in vitro experiments ( 14,15 ) and the two in silico phosphorylation sites prediction tools scansite 2.0 and netphosk 1.0
thus , we propose that gps server will be more useful and helpful in further research in the field of protein phosphorylation .
first of all , we obtained the data set of phosphorylation sites with their pks from phospho.elm ( 16 ) , which also included the data of phosphobase ( 17 ) . after removing the phosphorylation sites with ambiguous information of pks ,
we retrieved the sequences for the pks of the data sets from swiss - prot and performed homology search in human proteome for each pk .
next , we checked the blast results and protein annotations manually to validate the pk subfamily information .
after clustering some homology pks with too few known phosphorylation sites into groups , we obtained 71 pk groups with 216 unique pks .
the gps www server is implemented in php + mysql and the prediction page is shown in figure 1 .
the detailed information for each pk group can be visited by clicking on the pk group 's name .
several pairs of sensitivity and specificity at different cut - off values for each pk group by the  leave - one - out validation are also listed for each pk group .
users can choose their required cut - off or select zero for the full list of the scores of the s / t or y sites .
here , we present the rat spinophilin protein ( swiss - prot accession no : o35274 ) as an example to demonstrate the simplicity and precision in the usage of gps web server .
rat spinophilin ( also called neural tissue - specific f - actin binding protein ii or neurabin - ii ) is an 817 amino acid , actin- and protein phosphotase-1 ( pp1)-binding protein that is ubiquitously expressed but enriched in dendritic spines of rat brain and adherents junction of rat liver ( 14,15,1822 ) .
spinophilin binds to and bundles f - actin in vivo , involving in the regulation of dendritic spine morphogenesis ( 14,19 ) .
spinophilin also modulates excitatory synaptic transmission by binding pp1 , redirecting it to postsynaptic densities , and regulating its dephosphorylation activity toward glutamate receptors ( 18,20,21 ) .
moreover , spinophilin knock - out mice show impaired synaptic transmission and long - term depression .
in addition , young spinophilin - deficient mice exhibit a significant increase in spine density and enhanced filopodial formation ( 21 ) .
the n - terminal 221 residues of spinophilin ( actin - binding domain ) can be phosphorylated by at least four pks , including pka ( 14 ) , ca / calmodulin - dependent pk ii ( camkii / cam - ii ) ( 22 ) , cyclin - dependent pk5 ( cdk5 ) and erk2 ( mapk1 ) ( 15 ) .
phosphorylation of spinophilin by pka and cam - ii disrupts its association with the f - actin ( 14,22 ) .
it is proposed that erk2 phosphorylates the actin - binding domain of spinophilin to reduce its interaction with actin filaments ( 15 ) .
the phosphorylation sites on spinophilin were experimentally identified by tryptic phosphopeptide mapping , site - directed mutagenesis , microsequencing analysis and phosphospecific antibodies ( 14,15,22 ) .
we scanned our training data set and found that the cam - ii sites have been used in the current gps server .
the sites for the other three pks are not included in our training data set .
therefore , we choose to predict the phosphorylation sites on spinophilin for kinases pka , erk2 and cdk5 .
the gps server clusters all cdk pks , except p34cdc2 ( cdk1 ) as the pk group  cdks , and all map kinases as the pk group 
mapk. we obtained the primary sequence of rat spinophilin ( o35274 ) from the swiss - prot database and pasted it into the  prediction section of the gps server ( figure 1 ) .
the prediction result of pka ( default cut - off value : 2.4 ; sensitivity : 88.9% ; and specificity : 90.6% ) is shown in figure 2a , and the prediction results of cdks ( default cut - off value : 2.5 ; sensitivity : 94.4% ; and specificity : 91.7% ) and mapk ( default cut - off value : 2.5 ; sensitivity : 83.0% ; and specificity : 91.9% ) are shown in figure 2b . for comparison ,
the prediction results from scansite 2.0 and netphosk 1.0 are also listed in table 1 . both scansite 2.0 and netphosk 1.0
do not provide prediction for mapk1 , so we choose p38mapk ( mapk5 ) since the substrate specificity is very similar among the mapk family .
we followed the low stringency for scansite 2.0 and default threshold 0.5 for netphosk 1.0 .
pka phosphorylates spinophilin at three major sites , s94 , s100 and s177 ( 14 ) .
since only the n - terminal sequence ( 1221 amino acids ) was used in the experimental identification , it is possible that pka may have additional phosphorylation sites in rest of the spinophilin sequence with unknown functions . for the n - terminal sequence of spinophilin ,
scansite predicts five sites as positive hits ( s17 , s59 , s94 , s100 and s177 ) while gps claims eight potential sites ( s17 , s87 , s94 , s99 , s100 , s122 , s126 and s177 ) . in the other region ,
scansite and netphosk predict two ( s694 and s756 ) and three sites ( s694 , s756 and s814 ) , respectively , while gps claims three potential sites ( s356 , t777 and s814 ) .
since gps has no entries for cdk5 and erk2 ( mapk1 ) , we choose their pks group cdks and mapk instead .
hence , we choose p38mapk ( mapk5 ) as a homolog pk to predict its sites on spinophilin , based on the hypothesis that pks in one subfamily exhibit very similar substrate specificity .
cdk5 and erk2 can phosphorylate spinophilin at s17 , and s15 and s205 , respectively .
scansite and netphosk could accurately predict s17 properly , while gps predicted three sites ( s17 , s131 and s205 ) . for p38mapk / mapk
, only gps could correctly predict one site s205 . since we used pk groups of cdks and mapk to predict the spinophilin
, the prediction result suggests that spinophilin may also be phosphorylated by other cdks and mapk kinases .
the example used here shows that gps could be a good complementary tool for the experimental work and for other in silico prediction tools , e.g. scansite and netphosk .
the prediction page of gps www server . the detailed information for each pk can be viewed by clicking on the pk names .
there are 13 predicted hits ( s17 , s87 , s94 , s99 , s100 , s122 , s126 , s177 , s356 , s694 , s756 , t777 and s814 ) .
there are seven predicted hits ( s17 , s131 , s205 , t337 , s339 , s635 and s658 ) for cdks and five predicted hits ( s17 , s205 , s339 , s635 and s658 ) for mapk .
protein phosphorylation plays a fundamental role in most of the cellular regulatory pathways 
 . experimental identification of protein kinases ' ( pks ) substrates with their phosphorylation sites is labor - intensive and often limited by the availability and optimization of enzymatic reactions . 
 recently , large - scale analysis of the phosphoproteome by the mass spectrometry ( ms ) has become a popular approach . but experimentally , it is still difficult to distinguish the kinase - specific sites on the substrates . in this regard , 
 the in silico prediction of phosphorylation sites with their specific kinases using protein 's primary sequences may provide guidelines for further experimental consideration and interpretation of ms phosphoproteomic data . 
 a variety of such tools exists over the internet and provides the predictions for at most 30 pk subfamilies . 
 we downloaded the verified phosphorylation sites from the public databases and curated the literature extensively for recently found phosphorylation sites . with the hypothesis that pks in the same subfamily share similar consensus sequences / motifs / functional patterns on substrates , we clustered the 216 unique pks in 71 pk groups , according to the blast results and protein annotations . then , we applied the group - based phosphorylation scoring ( gps ) method on the data set ; here , we present a comprehensive pk - specific prediction server gps , which could predict kinase - specific phosphorylation sites from protein primary sequences for 71 different pk groups . 
 gps has been implemented in php and is available on a www server at .