the growth of protein structures in the protein data bank ( pdb ) and expansion of our understanding of protein physical properties are constantly enhancing our ability to predict structural and functional features .
we have contributed three such methods : wesa for predicting the solvent accessibility of amino acids from a protein sequence ( 1 ) , cons - ppisp for predicting interface residues from the structure of a protein which binds a second protein ( 2,3 ) , and displar for predicting interface residues from the structure of a protein which binds dna ( 4 ) .
both wesa and displar were found to have higher prediction accuracy than competing methods ( 1,4 ) .
cons - ppisp was shown to be able to complement experimental techniques such as nmr chemical shift perturbation in mapping protein  protein interfaces ( 3 ) .
the methods have found uses in protein structure prediction ( 5 ) and in docking of protein complexes ( 6 ) . for wide access to them ,
here we describe the functionality of the web servers and illustrate their utility by a structural model , built from predictions of the web servers , for a multicomponent protein  dna complex .
the web servers are components of pipe , the protein interface / interior prediction engine , located at http://pipe.scs.fsu.edu .
together , they serve as a pipeline from protein sequences to tertiary structures , then onto quaternary structures of binary complexes , and finally onto superstructures of functioning , multicomponent complexes .
the input in each case consists of data for a list of residues . in wesa ,
sequential neighbors on the left and on the right . in both cons - ppisp and displar ,
the input data in wesa are sequential profiles , as given by the position - specific scoring matrix produced by psi - blast ( 7 ) . in cons - ppisp and displar , solvent accessibilities ( defined as percentages of exposed surface areas of residues )
the dataset of wesa was comprised of 2148 proteins chains with sequence identity < 25% . for cons - ppisp ,
the dataset was comprised of 1256 protein chains that form either heterodimers ( involving 458 chains ) or homodimers ( accounting for the remaining 798 chains of the dataset ) .
for displar , the dataset was comprised of 264 protein multimers that form complexes with dna in their pdb entries .
the three protein lists can be downloaded at http://pipe.scs.fsu.edu . to illustrate why the prediction methods work , in figure 1 we show the distributions of the 20 types of amino acids in interior and surface regions of folded proteins , and in interface and non - interface portions of protein surfaces that bind proteins or dna .
expectedly non - polar amino acids show preference for the interior whereas polar and charged residues for the surface .
non - polar amino acids similarly ( albeit less prominently ) prefer interfaces of protein  protein complexes . on the other hand , protein  dna interfaces appear to be more dictated by electrostatic complementarity ( instead of hydrophobicity ) , with positively charged arginine and lysine significantly enriched while negatively charged aspartate and glutamate significantly depleted in the interfaces . 

figure 1.percentages of the 20 types of amino acids in ( a ) interior and surface regions of folded proteins , ( b ) interface and non - interface portions of protein surfaces in protein  protein complexes , and ( c ) interface and non - interface portions of protein surfaces in protein  dna complexes . in each plot , the amino acids are ordered according to the difference between the two contrasting groups . interior ( or surface )
residues were those with < ( or > ) 20% solvent accessibilities ; interface residues were those with a heavy atom that is < 5   from a heavy atom across a protein  protein or protein  dna interface .
percentages of the 20 types of amino acids in ( a ) interior and surface regions of folded proteins , ( b ) interface and non - interface portions of protein surfaces in protein  protein complexes , and ( c ) interface and non - interface portions of protein surfaces in protein  dna complexes . in each plot , the amino acids are ordered according to the difference between the two contrasting groups . interior ( or surface )
residues were those with < ( or > ) 20% solvent accessibilities ; interface residues were those with a heavy atom that is < 5   from a heavy atom across a protein  protein or protein  dna interface .
another feature , captured by sequence profiles , that distinguishes interior from surface and interface from non - interface is sequence conservation . for structural and functional reasons , interior and interface positions
such a trend is indeed shown through a comparison in conservation scores between interior and surface positions and between interface and non - interface positions ( supplementary figure 1 ) .
in addition to sequence profiles , cons - ppisp and displar also use solvent accessibilities as part of the input . in protein  protein complexes , interface positions consistently have higher solvent accessibilities than non - interface positions . on the other hand , in protein 
dna complexes , positively charged arginine and lysine have higher solvent accessibilities in interface positions than in non - interface positions , but negatively charged aspartate and glutamate show the opposite tendency ( supplementary figure 2 ) . both cons - ppisp and displar
wesa is a metamethod , based on a weighted ensemble of five separate methods , one of which is neural network training .
further details on the implementations of the methods can be found in the original papers ( 14 ) .
wesa has consistently shown a two - state ( interior / surface ) prediction accuracy 80% .
once there , the user is asked to provide the sequence , in fasta format , of the protein on which solvent accessibility is predicted .
in addition , the user is asked to type in a unique identifier , at the user 's choice , for referencing the particular wesa submission , and an e - mail address , for receiving the prediction .
a link ( http://pipe.scs.fsu.edu/output_wesa.txt ) also provides a sample output ( obtained from submitting the sequence of pdb entry 1who ) , with explanations for the columns of numbers for each residue . in short , for each residue in the sequence , the results predicted by five separate methods and the wesa metamethod are given as 1 for exposed or 0 for buried , along with the prediction confidence ( ranging from 0.00 for no confidence at all to 1.00 for full confidence ) .
two figures displaying the actual and wesa - predicted buried residues of 1who are found at the web server .
the direct web link for the cons - ppisp web server is http://pipe.scs.fsu.edu/ppisp.html . the protein structure , on which an interface prediction is to be made ,
in addition , the user must specify the chain(s ) in the structure to be used for prediction .
( 1 ) the pdb file does not have chain i d ;  _  is to be entered .
( 2 ) the pdb file has a single chain i d ( say  a  ) , or , it has multiple chains but only a single chain is to be used for prediction ;  a  must be entered . (
3 ) multiple chains ( e.g. a , b and c ) in a pdb file are to be treated as a single structure and used together for interface prediction ; the user must enter 
input and output formats are very similar to cons - ppisp predictions . for convenience of using the web servers ,
the scripts allow the user to submit multiple jobs by a unix command from his / her terminal , as if the prediction programs are installed on the local computer .
in reality the scripts upload the sequences or pdb files to the pipe web servers .
the predictions are run at the servers , and results are sent back to the local computer and saved in files specified by the scripts .
we now present interface residues predicted by the cons - ppisp and displar web servers to illustrate their utility .
first , results are given for three proteins that competitively bind proteins and dna and have unbound structures in the pdb .
next , predictions for a protein that simultaneously binds dna and another protein are given , and the results are used to build structures for the protein 
full lists of predicted interface residues for the proteins are given in supplementary table s1 .
figure 2a displays the cons - ppisp predictions for the ribonuclease barnase , in reference to the structure of the complex with its inhibitor , barstar ( pdb entry 1brs ) .
as shown in figure 2b , the 27 predicted interface residues are concentrated around the binding site for a tetradeoxynucleotide , d(cgac ) ( as defined in 1brn ) .
six residues ( i55-s57 , r59 , y97 and y103 ) are common in the two sets of predictions .
it is of interest to note that cons - ppisp predicted two clusters on the unbound structure of barstar ( 1bta ) , one is in the actual interface with barnase ( shown in figure 2a ) and the other defines an unknown binding site .
displar did not make any positive predictions on 1bta , which is not expected to bind dna . 

figure 2.predictions of residues in ( a ) barnase  barstar and ( b ) barnase  dna interfaces by cons - ppisp and displar , respectively , shown on the x - ray structures of the complexes ( 1brs and 1brn ) .
predictions were made on unbound structures ( 1a2p for barnase and 1bta for barstar ) .
barnase is shown in surface , with predicted interface residues in blue and the rest of the surface in yellow .
barstar and d(cgac ) are shown as red sticks ; side chains of barstar residues predicted in the interface with barnase are shown as green sticks .
predictions of residues in ( a ) barnase  barstar and ( b ) barnase  dna interfaces by cons - ppisp and displar , respectively , shown on the x - ray structures of the complexes ( 1brs and 1brn ) .
predictions were made on unbound structures ( 1a2p for barnase and 1bta for barstar ) .
barnase is shown in surface , with predicted interface residues in blue and the rest of the surface in yellow .
barstar and d(cgac ) are shown as red sticks ; side chains of barstar residues predicted in the interface with barnase are shown as green sticks .
we applied cons - ppisp to the tumor repressor p53 core domain ( 2fej ) . in figure 3a
, the predictions are displayed on the structure of p53 in complex with either 53bp1 or 53bp2 ( 1gzh or 1ycs ) .
the five predicted residues ( n239-m243 ) lie in the interfaces with the p53-binding proteins .
a second cluster of 22 residues ( listed in supplementary table 1 ) was also predicted ; many of these residues are found in the dimer 
dimer interface of a tetramer of the p53 core domain bound to dna ( 8) . some of these residues are also implicated in the binding with the e6/e6-ap complex ( 9 ) .
these also lie in the interface with dna ( as found in 1tsr ) ( figure 3b ) .
cons - ppisp predicted residues are close to some of the displar predicted residues , but no residue was predicted by both methods . 

figure 3.protein-contacting and dna - contacting residues predicted by cons - ppisp and displar , respectively , on the p53 core domain .
predictions were made on the unbound structure of p53 ( 2fej ) but are displayed on the bound ( a ) protein  protein and ( b ) protein  dna ( 1tsr ) complexes .
p53 is shown as surface , with predicted residues in blue and the rest of the surface in yellow . in ( a ) the structures of the complexes of p53 with 53bp1 ( 1gzh ) and 53bp2 ( 1ycs ) , after superimposing p53 , are shown , with 53bp1 and 53bp2 as purple and red sticks , respectively .
protein - contacting and dna - contacting residues predicted by cons - ppisp and displar , respectively , on the p53 core domain .
predictions were made on the unbound structure of p53 ( 2fej ) but are displayed on the bound ( a ) protein  protein and ( b ) protein  dna ( 1tsr ) complexes .
p53 is shown as surface , with predicted residues in blue and the rest of the surface in yellow . in ( a ) the structures of the complexes of p53 with 53bp1 ( 1gzh ) and 53bp2 ( 1ycs ) , after superimposing p53 , are shown , with 53bp1 and 53bp2 as purple and red sticks , respectively .
the two - component transcriptional activator phob regulates its dna - binding activity through transiently forming a domain  domain complex , thereby blocking the dna - binding site .
we used cons - ppisp to predict interface residues on the unbound structures of both the effector and receiver domains ( 1qqi and 1b00 ) .
the structure for full - length phob is not available , but we found the structure ( 1ys6 ) for a close homolog , prra , in the pdb . the root - mean - square deviations ( rmsd ) of 1qqi and 1b00 from the corresponding domains in 1ys6 are 2.4 and 2.1   , with sequence identities over aligned positions at 35 and 41% , respectively .
when 1qqi and 1b00 are aligned onto 1ys6 , the 23 and 21 predicted residues on the two respective domains indeed mostly line the interface as modeled on 1ys6 ( figure 4a ) .
displar predicted 25 residues on 1qqi , which are located in the actual interface between the effector domain and dna ( as found in 1gxp ) ( figure 4b ) .
the binding sites for the receiver domain and dna on the effector domain ( 1qqi ) overlap , and eight residues ( r68 , t69 , d71 , h73 and v93-t96 ) were predicted by both cons - ppisp and displar .
no dna - contacting residues were predicted by displar on the receiver domain ( 1b00 ) , which is not known to binding dna . 

figure 4.(a ) predicted protein - contacting residues on the effector and receiver domains of phob .
the two domains are shown as yellow and green ribbons , respectively ; side chains of predicted residues are shown as ball - and - stick .
the two unbound structures ( 1qqi and 1b00 ) are superimposed to the respective domains in prra ( 1ys6 ) .
( b ) dna - contacting residues predicted on the unbound structure of the phob effector domain ( 1qqi ) and displayed on the complex with dna ( 1gxp ) .
( a ) predicted protein - contacting residues on the effector and receiver domains of phob .
the two domains are shown as yellow and green ribbons , respectively ; side chains of predicted residues are shown as ball - and - stick .
the two unbound structures ( 1qqi and 1b00 ) are superimposed to the respective domains in prra ( 1ys6 ) .
( b ) dna - contacting residues predicted on the unbound structure of the phob effector domain ( 1qqi ) and displayed on the complex with dna ( 1gxp ) .
core binding factors ( cbf ) form a heterodimer between the  and  subunits , which in turn forms a ternary complex with dna . using the unbound structures of cbf and cbf ( 1eaq and 1ilf , respectively ) , we predicted interface residues between these two proteins by cons - ppisp .
examined on the dimer structure of cbf and cbf ( 1e50 ) , the 20 and 23 predicted residues on the two subunits indeed line the actual interface ( figure 5a ) .
previously we have used cons - ppisp predictions to drive the docking of unbound structures ( 6 ) .
here we use the predictions to score docked structures , obtained by running zdock 2.3 ( 10 ) with 15 sampling .
the best 200 zdock structures ( out of a total of 2000 ) were re - ranked according to the number of cons - ppisp predicted residues among the interfacial residues ( defined as having 10- contacts across the interface ) . a structure with an rmsd of 2.2   was ranked second according to cons - ppisp predictions ( improved from zdock 's ranking of 49th ) .
figure 5.(a ) protein - contacting residues on cbf and cbf ( as yellow and green ribbons , respectively ) , predicted on the unbound structures ( 1eaq and 1ilf ) and displayed on the dimeric complex ( 1e50 ) as ball - and - stick .
( b ) structure for the complex obtained by docking 1eaq and 1ilf and re - ranking according to predicted interface residues .
( a ) protein - contacting residues on cbf and cbf ( as yellow and green ribbons , respectively ) , predicted on the unbound structures ( 1eaq and 1ilf ) and displayed on the dimeric complex ( 1e50 ) as ball - and - stick .
( b ) structure for the complex obtained by docking 1eaq and 1ilf and re - ranking according to predicted interface residues .
the dimer structure of cbf and cbf , 1e50 , was used to predict dna - contacting residues by displar .
as shown in figure 6a , cbf is indeed the subunit that contacts dna in the ternary complex ( 1h9d ) , and the predicted cbf residues line the dna - binding site .
we docked the dimer structure with a b - dna decamer built in insightii ( accelrys software inc . ,
parameters for dna nucleotides required for running zdock were taken from fanelli and ferrari ( 11 ) . a docked structure for the ternary complex , ranked 113th in zdock but improved to 11th by displar predictions , was found to have an rmsd of just 1.2   from 1h9d and is shown in figure 6b . 

figure 6.(a ) dna - contacting residues predicted on the dimeric complex of cbf and cbf ( 1e50 ) , and displayed on the ternary complex ( 1h9d ) .
side chains of predicted residues , exclusively located on cbf , are shown as blue ball - and - stick .
( b ) structure for the ternary complex obtained by docking 1e50 and a modeled b - dna decamer and re - ranking according to predicted interface residues .
( a ) dna - contacting residues predicted on the dimeric complex of cbf and cbf ( 1e50 ) , and displayed on the ternary complex ( 1h9d ) .
side chains of predicted residues , exclusively located on cbf , are shown as blue ball - and - stick .
( b ) structure for the ternary complex obtained by docking 1e50 and a modeled b - dna decamer and re - ranking according to predicted interface residues .
the continuous growth of the sequence database ( ftp://ftp.ncbi.nlm.nih.gov/blast/db/ ) and the pdb ( http://www.rcsb.org ) will further improve the accuracy of the three prediction methods .
we plan to periodically upload the ncbi the non - redundant ( nr ) onto pipe ( http://pipe.scs.fsu.edu ) .
in addition , we plan to expand the datasets for the three predictors by including new entries from the pdb ; re - training will be done .
the high accuracy of wesa predictions suggests that solvent accessibility is now a matured field .
future methodological developments will thus focus on protein  protein and protein  dna interface predictions .
a strategy that contributed to the success of wesa is the combination of complementary methods .
we plan to combine cons - ppisp and displar with approaches based on phylogenetic tree ( 12,13 ) , surface patch characteristics ( 14 ) , secondary structure ( 15 ) , empirical scoring function ( 16 ) , support vector machine ( 1720 ) and bayesian network ( 21,22 ) . ultimately proteins need to be studied within their functioning units , which often are multicomponent protein complexes .
 the side chains of the 20 types of amino acids , owing to a large extent to their different physical properties , have characteristic distributions in interior / surface regions of individual proteins and in interface / non - interface portions of protein surfaces that bind proteins or nucleic acids . 
 these distributions have important structural and functional implications . 
 we have developed accurate methods for predicting the solvent accessibility of amino acids from a protein sequence and for predicting interface residues from the structure of a protein - binding or dna - binding protein . 
 the methods are called wesa , cons - ppisp and displar , respectively . 
 the web servers of these methods are now available at http://pipe.scs.fsu.edu . to illustrate the utility of these web servers , cons - ppisp and displar predictions are used to construct a structural model for a multicomponent protein  
 dna complex . 
INTRODUCTION
METHODS
FUNCTIONALITY OF THE WEB SERVERS
ILLUSTRATIVE APPLICATIONS
FUTURE DEVELOPMENTS
SUPPLEMENTARY DATA