it is well known that genes can be silenced by antisense rna oligonucleotides called small interfering rna ( sirna ) ( 1,2 ) . in order to design an efficient sirna sequence , empirical rules based on the features of the sirna sequence
have been discovered , including , for example , low g / c content , lack of self - structure , preference of a at position 3 , absence of g or c at position 19 and asymmetry in the stability of the terminal base pairs ( 310 ) .
the self - structure of the target and oligonucleotide is also an important consideration for the effective binding ( 1115 ) .
it is desirable to select an oligonucleotide having high accessibility to the target - binding site and low duplex stability . here
, the oligowalk server , which predicts efficient sirna sequences using an accessibility calculation with a convenient web interface , is described .
overall , the positive predictive value of the server is 0.786 , meaning that 78.6% of the sirnas selected by the server will be efficient at silencing ( 16 ) .
the positive predictive value was determined by testing against a database of sirna experiments conducted under diverse experimental conditions ( 17 ) . in the calculation of the oligowalk server ,
unimolecular and bimolecular self - structures for the sirna are considered along with unimolecular self - structure in the target at the oligonucleotide binding region ( 16 ) .
oligowalk predicts the free energy changes ( g ) involved in these equilibrium states ( 18 ) .
the predicted thermodynamics ( g ) , plus the oligonucleotide sequence features ( 19 ) , are then utilized to predict sirna efficacy for candidate sirna sequences ( 16 ) , which are generally 19 nucleotide duplexes with 3 dinucleotide dangling ends ( 7 ) .
a support vector machine ( svm ) program ( 20 ) is embedded in the server to take the thermodynamic and sequence features as input .
the svm classification model used in the server has been proven to be able to predict efficient sirna ( greater than 70% inhibition of the target mrna expression ) with high accuracy ( 16 ) .
the svm was trained on a sirna database that contains 2431 experimental results conducted in human cells at 37c ( 10 ) .
the output of the oligowalk server is a table of sirna candidates , showing the sirna sequences and the probabilities of being efficient ( having silencing efficacy larger than 70% ) .
each of the free energy change terms for each candidate is also listed in a separate table .
the oligowalk server uses the cgi ( common gateway interface ) module of perl for taking user input and submitting calculations from the homepage .
the input of oligowalk server is the rna sequence of the target gene . only a , u , t , g and c are the acceptable types of nucleotides in the sequence ( the server will replace the nucleotide t with u for calculations ) , and the maximum sequence length is 10 000 nucleotides .
an email address is required because the server sends an email to the user when the calculation is completed .
submit query , the server generates a list of efficient sirna candidates for the target gene .
jobs are submitted by the server to a cluster of seven nodes with 3.2 or 3.4 ghz pentium 4 processors running fedora linux ( http://fedoraproject.org/ ) , managed by sun grid engine ( http://gridengine.sunsource.net/ ) .
when the calculation is complete , an html ( hypertext markup language ) page is generated with links to tables containing predicted sirna efficacy data and thermodynamic binding data . in the sirna efficacy table ( figure 1 ) , the sequences of sirna candidates are ranked in the output list by their probabilities of being efficient sirna .
the probabilities are predicted by a svm embedded in the web server for selecting efficient sirna .
the classification model ( 16 ) used in the svm was trained with a publically available database ( 10 ) , using thermodynamic and sequence features of sirna candidates . the position number of each sirna candidate is also listed in the table as the index of the 5 most base in the target - binding region . 

the sequences of sirna are ranked from top to end by their probabilities of being efficient ( antisense efficacy larger than 70% ) . a table of sirna candidates generated by oligowalk server .
the sequences of sirna are ranked from top to end by their probabilities of being efficient ( antisense efficacy larger than 70% ) .
in addition , the predicted equilibrium thermodynamics table is generated as a reference for advanced users . in the table
 overall ( in kcal / mol ) is the overall free energy change of oligonucleotide - target binding ,   when all contributions are considered , including breaking target and oligonucleotide self - structures ( 18 ) .
 duplex ( in kcal / mol ) is the free energy change of hybridized duplex between oligonucleotide and target ( antisense  sense duplex ) , .
the value is independent of oligonucleotide concentration because it is a standard free energy change . 
tm - dup ( in c ) is the melting temperature in degrees for the duplex formation of oligonucleotide and target . 
break - targ. ( in kcal / mol ) is the free energy cost to open the intramolecular target base pairs for oligonucleotide binding , .
a more negative number indicates higher free energy cost , which is unfavorable for oligonucleotide - target binding . 
intraoligo ( in kcal / mol ) is the free energy change of intramolecular oligonucleotide structure , .
it usually has a negative value or , if there is no favor - able intramolecular structure , it is zero . 
interoligo ( in kcal / mol ) is the free energy change of intermolecular oligonucleotide structure , .
antisense bimolecular structure , which decreases the oligonucleotide - target ( antisense  sense ) binding affinity .  end_diff. ( in kcal / mol ) is the free energy difference between the 5 and 3 end of the antisense strand of sirna , with windows of two base pairs .
functional sirna prefer to have an unstable 5 end ( 3 ) , which means a positive end_diff .
 prefilter_score is the score calculated with a method based on the empirical rules by reynolds et al . ( 7 ) .
( 7 ) , except for the melting temperature of intramolecular oligonucleotide self - structure because the free energy ( 21 ) and enthalpy parameters ( 22 ) used by oligowalk are more recent .
when calculating the prefilter score , 57c is used as the cutoff of the intramolecular oligonucleotide melting temperature , as suggested in another study ( 23 ) . as an example
, the prediction of the webserver is compared with experimental results in figure 2 . in the experiment ( 3 ) , sirna were tested for efficacy against the target mrna , human cyclophilin ( genbank i d : m60857 ) , at 37c .
the inhibition efficacy of each sirna is defined as 100% minus the percentage of mrna level after sirna application as compared to matched control .
the prediction result is the probability of being efficient ( having inhibition efficacy larger than 70% ) , which is calculated with the server . in figure 2 , most of the sirna with high inhibition efficacy are predicted to have high probability of being efficient . 

figure 2.a comparison between the prediction and experimental result . in blue is the experimental result ( inhibition efficacy ) for an mrna target , human cyclophilin ( genbank i d : m60857 ) , at 37c ( 3 ) .
the inhibition efficacy is defined as 100% minus the percent level of mrna expression after sirna application as compared to a control . in red
is the probability ( ranging from 01 ) of being efficient ( having inhibition efficacy larger than 70% ) , as predicted by oligowalk .
a comparison between the prediction and experimental result . in blue is the experimental result ( inhibition efficacy ) for an mrna target , human cyclophilin ( genbank i d : m60857 ) , at 37c ( 3 ) .
the inhibition efficacy is defined as 100% minus the percent level of mrna expression after sirna application as compared to a control . in red
is the probability ( ranging from 01 ) of being efficient ( having inhibition efficacy larger than 70% ) , as predicted by oligowalk .
advanced options ( figure 3 ) are available for users who understand the underlying calculations and would like to test novel hypotheses . the option form is written in html , embedded with javascript controlling the options so that they are context - aware .
the oligonucleotide concentration does not affect the result of sirna sequence design , because the inputs to the svm are standard free energy changes , g . concentration changes do , however , alter the overall free energy change ( ) , which is provided to the user with the thermodynamic details table .
the sense  antisense duplex free energy changes are calculated without considering the self - structures of the target . this mode is not recommended for an accurate sirna prediction .
it is more rigorous to consider the accessibility of the target and oligonucleotide self - structures because binding affinity is lost to open existing base pairs in the target and oligonucleotide .
the second mode is to break local structure . in this case , the structure of target is fixed and only the base pairs on the binding site will be broken without refolding the global structure of target . the final and most rigorous mode is to refold the target rna . in this mode ,
the rna target is folded before oligonucleotide binding and refolded afterwards for each possible oligonucleotide to consider complete equilibration .
the default setting of sirna design is shown in the figure . if the target rna secondary structure is considered , three different prediction methods are available to calculate the free energy change of target self - structure .
the first method is optimal structure prediction , where only the optimal structure ( lowest free energy structure ) of the target is considered to calculate the free energy cost of opening the base pairs of binding region .
the second method considers a set of suboptimal structures to determine the free energy cost .
each structure 's free energy cost is weighted according to the free energy change of the structure to arrive at the ensemble cost .
for this option , at most 1000 suboptimal structures ( within 10% free energy difference from the optimal structure ) are generated with a heuristic method ( 24 ) .
the number of suboptimal structures will be listed in the output table if the target is folded with suboptimal structure prediction method .
constrained target structure is the refolded structure where the binding region is forced to be single - stranded , so that the oligonucleotide can bind to it .
this is the most rigorous method because it considers every possible secondary structure in the folding ensemble , with boltzmann weight .
the structure prediction only folds a certain total number ( folding size ) of nucleotides centered at the binding region .
the user can define this number , but the largest folding size is 1000 nucleotides for the webserver in order to save compute time .
users can define longer folding sizes by downloading and installing the oligowalk program to a local machine .
( 7 ) can be used to rule out nonefficient sirna candidates before folding the target sequence , i.e. the sirna sequences having score less than six points will not be considered for the folding step .
it is suggested to turn on the prefilter option to save considerable computation time ( table 1 ) .
furthermore , the scan region can be redefined if the user is interested only in a specific region of the target . 

table 1.calculation size and time of oligowalk server for different target sequencestarget mrna ( genbank id)sequence length ( nucleotide)time ( h : min : sec)memory ( mb)nm_0205487300:57:1793m608578513:55:53110nm_00287012116:09:25112nm_00246721896:36:42113aj27221234606:53:05117the benchmarks were performed with the default options : the oligonucleotide was a 19 base rna ; the folding size of the target was 800 nucleotides centering on the binding site ( full length if the whole target has less than 800 nt ) ; the partition function calculation was conducted ; the entire mrna was scanned ; and the prefilter was on . the time cost changes little for long sequence because the prefilter ( 7 ) is on and number of candidates being folded is limited to about the same number for each sequence.the calculations were submitted and benchmarked on the oligowalk web server ( http://rna.urmc.rochester.edu/servers/oligowalk ) .
each node has a 3.2 or 3.4 ghz pentium 4 processor running fedora linux.the calculation for sequences less than 800 nucleotides is relatively fast because the dynamic programming arrays are reused for calculations of short sequences ( 16 ) .
calculation size and time of oligowalk server for different target sequences the benchmarks were performed with the default options : the oligonucleotide was a 19 base rna ; the folding size of the target was 800 nucleotides centering on the binding site ( full length if the whole target has less than 800 nt ) ; the partition function calculation was conducted ; the entire mrna was scanned ; and the prefilter was on .
the time cost changes little for long sequence because the prefilter ( 7 ) is on and number of candidates being folded is limited to about the same number for each sequence .
the calculation for sequences less than 800 nucleotides is relatively fast because the dynamic programming arrays are reused for calculations of short sequences ( 16 ) .
the oligowalk web server predicts the hybridization thermodynamics of an oligonucleotide binding to a complementary target rna using the most recent rna folding parameters ( 21 , 22 ) .
it predicts efficient sirna with high accuracy using a transparent implementation of an svm ( 16 ) , which considers both sequence and thermodynamic features .
the calculation time and memory size of oligowalk are shown in table 1 for a sample of mrna sequences .
the prefilter ( 7 ) that uses local sequence information to narrow down the list of sirna candidates before calculating the equilibrium affinity is used by default .
for example , the server takes 3 h and 43 min for a complete scan of all possible sirnas on an mrna having 730 nucleotides using the partition function calculation . for the same sequence ,
the algorithm time scales o(mn ) and the memory use scales o(n ) ( table 1 ) , m is the number of candidates and n is the value of folding size .
the time and memory costs change little with sequence because the same folding size ( e.g. 800 nucleotides ) is used and the prefilter ( 7 ) is turned on , which limits the number of candidates to be folded in a way that is apparently independent of target length .
there is currently significant interest in using sirna for both basic science and medical research .
the fact that not all sirna duplexes will function in silencing means that there is a significant cost in trial and error for sirna design .
 given an mrna sequence as input , the oligowalk web server generates a list of small interfering rna ( sirna ) candidate sequences , ranked by the probability of being efficient sirna ( silencing efficacy greater than 70% ) . 
 to accomplish this , the server predicts the free energy changes of the hybridization of an sirna to a target mrna , considering both sirna and mrna self - structure . 
 the free energy changes of the structures are rigorously calculated using a partition function calculation . by changing advanced options , the free energy changes 
 can also be calculated using less rigorous lowest free energy structure or suboptimal structure prediction methods for the purpose of comparison . 
 considering the predicted free energy changes and local sirna sequence features , the server selects efficient sirna with high accuracy using a support vector machine . 
 on average , the fraction of efficient sirnas selected by the server that will be efficient at silencing is 78.6% . 
 the oligowalk web server is freely accessible through internet at http://rna.urmc.rochester.edu/servers/oligowalk . 
INTRODUCTION
OLIGOWALK SERVER INPUT
OLIGOWALK SERVER OUTPUT
ADVANCED OPTIONS
CONCLUSIONS