loop prediction is generally one of the most challenging tasks in protein structure determination and modeling ( 117 ) .
the preferred conformation of loops often remains unclear even when the rest of the protein is resolved at high resolution .
this is due to the high flexibility of loops that is often related to their function ( 18 ) .
medically highly relevant interactions , such as the coupling of receptors to g proteins are mediated by membrane protein loops ( 19 ) .
therefore , the knowledge of the conformation or the conformational space of a loop is essentially important to understand the mechanisms to activate or deactivate membrane receptors and transporters , or more broadly to model protein  protein or protein  ligand interactions . for loop modeling ,
two different methods , ab initio ( 1,3,5,8,1517 ) and comparative modeling ( 6,9,14 ) are applied .
ab initio methods calculate possible loop conformations with the help of various energy functions and minimizations .
these methods do not depend on large template libraries , but are generally time consuming , and are therefore less appropriate for interactive searches .
comparative modeling approaches allow quick searches , but the quality of prediction largely depends on the availability of a suitable template loop structure .
thus , the potential of comparative modeling methods grows , as the diversity of available templates enlarges ( 14 ) .
it is estimated that , at the moment , the conformation of any loop up to the length of 14 residues is already represented very well by protein fragments in the rcsb protein data bank ( pdb ) ( 12,20 ) .
therefore , the performance of knowledge - based methods to find the native loop conformation particularly depends on the size of the loop databank and on the scoring function .
we have developed a scoring function for knowledge - based loop predictions that performs very well compared with other methods ( 14 ) . based on this scoring function , we now setup superlooper , a web application that provides a very simple , quick , user - friendly and reliable way to fill in a missing loop .
no extra software has to be installed and no databank has to be downloaded to get the program started . for user guidance
, the candidate loops can be visualized by a jmol ( http://www.jmol.org/ ) plug - in .
moreover , the web server provides information on sequence identities or proline and glycine exchanges between the template and the target , as well as close distances between a selected loop and the remainder of the protein .
finally , the membrane planes are automatically detected and visualized using the tmdet algorithm ( 21 ) .
thus , the specificities of membrane protein loops arising from the positioning at the membrane  water interface can be respected , too ( 22 ) .
to allow the searches to be performed in real time , we have improved the scoring procedure that is the most time consuming process of our method ( 14 ) .
the search for the appropriate loop is now performed in a three - step process , described below .
this hierarchical principle causes that the most cpu intensive calculations are performed on relatively small datasets . 

up to 100 000 candidates with the required loop length are preselected from the two databases lip ( loops in proteins , 500 000 000 protein segments ) and limp ( loops in membrane proteins , 180 000 loops ) .
the stem atoms ( two main chain atoms preceding and following the loop , respectively ) of candidate loops must fit the stem atoms of the target structure with a maximum deviation of 0.75  for each atom pair.the best 500 candidates are chosen by a specific 
goodness value that allows a quick estimation of the steric fit of loop candidates to a target protein , described in detail in our previous analysis ( 14).finally , the loop candidates are ranked by a score that includes the sequence similarity between loop candidate and target sequence , as well as the root mean square deviation ( rmsd ) of the stem atoms . to assure that the 50 top listed loops cover a maximum of the plausible conformational space , candidates with identical sequences and similar backbone conformations ( rmsd < 1.0  ) are further excluded from the list . for the benchmarks described in the following , only the top - ranked loop was considered in each case . 
 
up to 100 000 candidates with the required loop length are preselected from the two databases lip ( loops in proteins , 500 000 000 protein segments ) and limp ( loops in membrane proteins , 180 000 loops ) .
the stem atoms ( two main chain atoms preceding and following the loop , respectively ) of candidate loops must fit the stem atoms of the target structure with a maximum deviation of 0.75  for each atom pair .
goodness value that allows a quick estimation of the steric fit of loop candidates to a target protein , described in detail in our previous analysis ( 14 ) .
finally , the loop candidates are ranked by a score that includes the sequence similarity between loop candidate and target sequence , as well as the root mean square deviation ( rmsd ) of the stem atoms . to assure that the 50 top listed loops cover a maximum of the plausible conformational space , candidates with identical sequences and similar backbone conformations ( rmsd < 1.0  ) are further excluded from the list . for the benchmarks described in the following ,
using the test dataset of the sali lab ( 15 ) , we have shown previously that the accuracy of the method underlying superlooper performs better than other methods in particular for longer loops ( 14 ) .
the performance of superlooper was now benchmarked applying a new test dataset that was recently published to benchmark four commercially available programs for loop sampling prime ( schrdinger , llc ) , modeler ( accelrys software , inc . ) , icm ( molsoft , llc ) and sybyl ( tripos , inc . )
the outcome of that study is that prime , an ab initio method performs best especially with increasing loop lengths . to compare our results with this study , protein structures with the same pdb entry as in the test datasets
different versions of the same protein or slightly mutated variants. this criterion is assessed by a sliding window technique as described previously ( 14 ) . as a result ,
top - ranked loops show a global rmsd ( main chain atoms ) to the original loops of < 1.3  for loops up to six residues or < 3.0  for loops shorter than 10 residues .
best results are obtained , when loops with nearly identical sequences or close homologs are available .
this , however , is presently not always the case for longer loops . to compare the performance of superlooper with that of the above mentioned tools , the analysis was repeated for loops with 11- and 12-residues length using a sequence identity limit of 90% . as a result , the average performance of superlooper at loop lengths 11 and 12 ( rmsd = 2.6 and 4.0 , respectively ) is comparable with that of prime ( rmsd = 3.7 and 3.5 , respectively ) . at loop length
11 homologous templates with sequence identities ranging from 32% to 82% are detected by superlooper for 9 of 14 tested loops .
the average global rmsd of the modeled to the native loops is 0.7 . for the remaining five template loops ( with no homologous template available ) the rmsd is 5.9 . at loop length 12 homologous templates with sequence identities ranging from 58% to 95%
the average global rmsd of the modeled to the native loops is 0.6 . for the remaining six template loops , the rmsd = 6.3 .
thus , superlooper clearly outperforms prime at these critical loop lengths if a homologous template is available .
if no homologue is found , the ab initio method prime performs usually better . in conclusion ,
the performance of knowledge based methods such as superlooper clearly depends on the size and actuality of the data base in use .
more detailed data on actual benchmarks of superlooper are available from http://bioinformatics.charite.de / superlooper/. better results can always be obtained when not only the top ranked loop is considered .
thus , the user is encouraged to visually inspect the loops to determine , which is most reasonable .
superlooper was , therefore , implemented with a user - friendly interface to visualize and select the proper loop structure from a list of proposed conformations .
superlooper is implemented as an easy to use web application combining an interactive query of the loop database with a 3d visualization of the results . at the query site ,
the stem amino acids of the uploaded pdb file have to be provided together with the destined amino acid sequence .
the result site provides all information necessary for the user to select the appropriate loop from a list of candidates ranked from the limp and lip data bases ( figure 1 ) .
loop candidates can be selected from both data bases provided . due to the extensive size ,
the quality of loop predictions taken from the lip data base generally ranges above that of predictions with the limp data base .
nevertheless , considering the specific amino acid composition of transmembrane helix caps and loops ( 22 ) candidates taken from the limp data base should always be checked first , when a membrane loop is to be modeled . 

figure 1.alternative conformations ( red ) for loop 2 of the human 2-adrenergic receptor ( 2rh1.pdb ) can be selected from the list calculated by superlooper considering the predicted membrane planes ( yellow ) .
alternative conformations ( red ) for loop 2 of the human 2-adrenergic receptor ( 2rh1.pdb ) can be selected from the list calculated by superlooper considering the predicted membrane planes ( yellow ) .
if no appropriate loop is found , the search may be expanded easily in n- or c - terminal direction up to a final loop length of 35 amino acids . to generally avoid unfavorable loop conformations and steric hindrance ,
the positions of proline and glycine exchanges in the selected loop are highlighted as well as distances < 2.4  to the rest of the protein .
the percentage sequence identity of a template loop is always noted to inform the user about the probability that the native loop conformation is actually matched .
a membrane protein loop should be selected with respect to its relative orientation to the lipid bilayer indicated by the protein viewer .
the expansions of the lipid bilayer are predicted applying the tmdet algorithm ( 21,23 ) .
membrane planes are calculated on a remote server ( tmdet ) connected via web service ( 21 ) .
the web site uses jmol ( http://jmol.sf.net ) for visualization , and therefore needs a java jre , freely available from http://java.net .
the web application uses the pdb - file format as the default input and output format , and is designed to be used with internet explorer 7 and firefox 2.03.0 .
the web application is also compatible with ie 6 , but tends to be unstable on some computers regarding some combinations of jre and ie 6 .
using the test dataset of the sali lab ( 15 ) , we have shown previously that the accuracy of the method underlying superlooper performs better than other methods in particular for longer loops ( 14 ) .
the performance of superlooper was now benchmarked applying a new test dataset that was recently published to benchmark four commercially available programs for loop sampling prime ( schrdinger , llc ) , modeler ( accelrys software , inc . ) , icm ( molsoft , llc ) and sybyl ( tripos , inc . )
the outcome of that study is that prime , an ab initio method performs best especially with increasing loop lengths . to compare our results with this study , protein structures with the same pdb entry as in the test datasets
different versions of the same protein or slightly mutated variants. this criterion is assessed by a sliding window technique as described previously ( 14 ) . as a result ,
top - ranked loops show a global rmsd ( main chain atoms ) to the original loops of < 1.3  for loops up to six residues or < 3.0  for loops shorter than 10 residues .
best results are obtained , when loops with nearly identical sequences or close homologs are available .
this , however , is presently not always the case for longer loops . to compare the performance of superlooper with that of the above mentioned tools , the analysis was repeated for loops with 11- and 12-residues length using a sequence identity limit of 90% . as a result , the average performance of superlooper at loop lengths 11 and 12 ( rmsd = 2.6 and 4.0 , respectively ) is comparable with that of prime ( rmsd = 3.7 and 3.5 , respectively ) . at loop length
11 homologous templates with sequence identities ranging from 32% to 82% are detected by superlooper for 9 of 14 tested loops .
the average global rmsd of the modeled to the native loops is 0.7 . for the remaining five template loops ( with no homologous template available ) the rmsd is 5.9 . at loop length 12 homologous templates with sequence identities ranging from 58% to 95%
the average global rmsd of the modeled to the native loops is 0.6 . for the remaining six template loops , the rmsd = 6.3 .
thus , superlooper clearly outperforms prime at these critical loop lengths if a homologous template is available .
if no homologue is found , the ab initio method prime performs usually better . in conclusion ,
the performance of knowledge based methods such as superlooper clearly depends on the size and actuality of the data base in use .
more detailed data on actual benchmarks of superlooper are available from http://bioinformatics.charite.de / superlooper/. better results can always be obtained when not only the top ranked loop is considered .
thus , the user is encouraged to visually inspect the loops to determine , which is most reasonable .
superlooper was , therefore , implemented with a user - friendly interface to visualize and select the proper loop structure from a list of proposed conformations .
superlooper is implemented as an easy to use web application combining an interactive query of the loop database with a 3d visualization of the results . at the query site ,
the stem amino acids of the uploaded pdb file have to be provided together with the destined amino acid sequence .
the result site provides all information necessary for the user to select the appropriate loop from a list of candidates ranked from the limp and lip data bases ( figure 1 ) .
loop candidates can be selected from both data bases provided . due to the extensive size , the quality of loop predictions taken from the lip data base generally ranges above that of predictions with the limp data base . nevertheless , considering the specific amino acid composition of transmembrane helix caps and loops ( 22 ) candidates taken from the limp data base should always be checked first , when a membrane loop is to be modeled . 

figure 1.alternative conformations ( red ) for loop 2 of the human 2-adrenergic receptor ( 2rh1.pdb ) can be selected from the list calculated by superlooper considering the predicted membrane planes ( yellow ) .
alternative conformations ( red ) for loop 2 of the human 2-adrenergic receptor ( 2rh1.pdb ) can be selected from the list calculated by superlooper considering the predicted membrane planes ( yellow ) .
if no appropriate loop is found , the search may be expanded easily in n- or c - terminal direction up to a final loop length of 35 amino acids . to generally avoid unfavorable loop conformations and steric hindrance ,
the positions of proline and glycine exchanges in the selected loop are highlighted as well as distances < 2.4  to the rest of the protein .
the percentage sequence identity of a template loop is always noted to inform the user about the probability that the native loop conformation is actually matched .
a membrane protein loop should be selected with respect to its relative orientation to the lipid bilayer indicated by the protein viewer .
the expansions of the lipid bilayer are predicted applying the tmdet algorithm ( 21,23 ) .
membrane planes are calculated on a remote server ( tmdet ) connected via web service ( 21 ) .
the web site uses jmol ( http://jmol.sf.net ) for visualization , and therefore needs a java jre , freely available from http://java.net .
the web application uses the pdb - file format as the default input and output format , and is designed to be used with internet explorer 7 and firefox 2.03.0 .
the web application is also compatible with ie 6 , but tends to be unstable on some computers regarding some combinations of jre and ie 6 .
european union ( profit ) ; deutsche forschungsgemeinschaft ( sfb449 , sfb740 , dfg grk1360 ) . funding for open access charge : sfb449 .
 superlooper provides the first online interface for the automatic , quick and interactive search and placement of loops in proteins ( lip ) . 
 a database containing half a billion segments of water - soluble proteins with lengths up to 35 residues can be screened for candidate loops . a specified database containing 180 000 membrane loops in proteins ( limp ) can be searched , alternatively . 
 loop candidates are scored based on sequence criteria and the root mean square deviation ( rmsd ) of the stem atoms . 
 searching lip , the average global rmsd of the respective top - ranked loops to the original loops is benchmarked to be < 2  , for loops up to six residues or <3  for loops shorter than 10 residues . 
 other suitable conformations may be selected and directly visualized on the web server from a top-50 list . for user guidance , 
 the sequence homology between the template and the original sequence , proline or glycine exchanges or close contacts between a loop candidate and the remainder of the protein are denoted . for membrane proteins , 
 the expansions of the lipid bilayer are automatically modeled using the tmdet algorithm . 
 this allows the user to select the optimal membrane protein loop concerning its relative orientation to the lipid bilayer . 
 the server is online since october 2007 and can be freely accessed at url : http://bioinformatics.charite.de/superlooper/ 
INTRODUCTION
METHODS
RESULTS
Performance
Server implementation
Technical notes
FUNDING