the quality of multiple sequence alignments directly affects their applications in similarity searches , structure modeling , functional prediction and phylogenetic analysis . preparing accurate multiple alignments for distantly related proteins ( e.g. sequence identity below 20% ) remains a difficult task .
aligning all sequences together by dynamic programming is not feasible for large numbers of sequences ( 1 ) .
progressive alignment methods reduce the problem of aligning multiple sequences to making a limited number of pairwise alignments .
although progressive methods can be fast , errors made at early stages are not corrected .
classic progressive methods such as clustalw ( 2 ) can give reasonable results for similar sequences , but fail to produce accurate alignments for divergent sequences ( 3 ) .
in recent years , extensive research has been conducted to improve alignment quality for progressive methods .
refinement after progressive steps is an effective way of correcting alignment errors ( 4,5 ) .
consistency - based alignment strategy ( 6 ) derives a better scoring function before the progressive alignment steps .
probcons ( 7 ) introduced and mummals ( 8) implemented a probabilistic treatment of consistency derived from pairwise alignment hidden markov models . additional information from protein structures and database homologs can lead to further improvement of alignment quality ( 5,911 ) .
we developed promals ( 12 ) , a progressive method that combines recent advanced techniques to improve multiple alignment quality , especially for distantly related proteins .
promals integrates additional information from database searches and secondary structure predictions into a new hidden markov model that aligns profiles .
the alignment scoring function of promals is based on probabilistic consistency among profile  profile comparisons .
promals has shown improved results as compared to other leading methods , such as spem ( 13 ) , mummals , probcons and mafft ( 12 ) . here , we describe the promals web server for multiple protein sequence alignments .
in addition to alignment construction , this server outputs useful information about predicted secondary structures , sequence grouping and positional conservation for target sequences .
being a progressive method , promals sets the order of pairwise alignments according to a tree built by a k - mer counting method ( 4 ) . to improve alignment speed , promals has two alignment stages for easy and difficult cases , as first implemented in our program pcma ( 14 ) . in the first stage ,
highly similar sequences are progressively aligned in a fast way with a weighted sum - of - pairs measure of blosum62 ( 15 ) scores .
this procedure results in a set of pre - aligned groups that are relatively divergent from each other . in the second alignment stage ,
for each representative sequence , psi - blast ( 16 ) is used to identify homologs from the sequence database uniref90 ( 17 ) , and the psi - blast profile ( checkpoint file ) is used to predict secondary structures by psipred ( 18 ) . for each pair of representatives ,
profiles are derived from the psi - blast alignments and psipred secondary structure prediction , and a matrix of posterior probabilities of matches between positions are obtained by a profile  profile hidden markov model ( 12 ) .
these matrices are used to calculate the probabilistic consistency scoring function , which is used to progressively align the representative sequences .
then the pre - aligned groups obtained in the first stage are merged to the alignment of the representatives . finally , gap placements in highly gapped regions are refined to make the gap patterns more realistic .
the alignment accuracy results of promals and several other methods on sabmark ( 19 ) and prefab 4.0 ( 4 ) benchmarks are shown in table 1 . 

table 1.evaluation of alignment methods on sabmark and prefab benchmarksmethodsabmark- twi(209/7.7)sabmark- sup(425/8.3)prefab ( 1682/45.2)promals0.3910.6650.790spem0.3260.6280.774mummals0.1960.5220.731probcons0.1660.4850.716mafft - linsi0.1840.5100.722muscle0.1360.4330.680clustalw0.1270.3900.617average q - scores of two sabmark data sets ( 
q - score is the number of correctly aligned residue pairs in the test alignment divided by the total number of aligned residue pairs in the reference alignment . for each data
set , the two numbers in the parentheses separated by a slash are the number of alignments tested and the average number of sequences per alignment , respectively . for each data
set , promals yields statistically higher accuracy ( bold numbers ) than any other method ( p - value  < 
promals and spem use secondary structure prediction and database homologs in alignment process , while the other five methods only utilize the input sequences .
evaluation of alignment methods on sabmark and prefab benchmarks average q - scores of two sabmark data sets ( 
q - score is the number of correctly aligned residue pairs in the test alignment divided by the total number of aligned residue pairs in the reference alignment . for each data
set , the two numbers in the parentheses separated by a slash are the number of alignments tested and the average number of sequences per alignment , respectively . for each data
set , promals yields statistically higher accuracy ( bold numbers ) than any other method ( p - value  < 
promals and spem use secondary structure prediction and database homologs in alignment process , while the other five methods only utilize the input sequences .
the main section allows the user to paste or upload sequences and enter an email address for the results .
options to modify alignment parameters , psi - blast searches and output format are provided .
a brief description of each option is available by clicking on the option 's name .
the main section allows the user to paste or upload sequences and enter an email address for the results .
options to modify alignment parameters , psi - blast searches and output format are provided .
a brief description of each option is available by clicking on the option 's name .
if such an alignment is provided , it is split into individual sequences and these sequences will be re - aligned by promals .
it is also recommended that the user provide an email address to receive alignment results , as promals can take a considerable amount of time to finish for a large number of divergent sequences , due to the time - consuming steps of running psi - blast searches and profile consistency measure . on a data set of 1785 scop ( 20,21 ) domain pairs with up to
48 homologs added ( the average number of sequences is 41.6 per alignment ) , the average cpu time of promals is about half an hour under default settings ( 12 ) . the actual time to finish an alignment job
depends on factors such as the number of sequences and their lengths , the diversity among the sequences , the numbers of homologs found in database searches and the server load .
it can take several hours for the server to finish aligning a sequence set with a large number of distantly related sequences ( > 50 ) .
one important parameter is the identity threshold that determines the partition of fast alignment stage and slow alignment stage , and thus balances alignment quality and speed .
lowering this threshold can cause more sequences to be aligned in a fast and less accurate way , resulting in fewer representative groups subject to the time and memory - consuming steps of psi - blast searches and profile consistency measure .
if the number of pre - aligned groups is large ( e.g. > 100 ) , promals could run out of memory during the consistency measure step and generate an error message with the report of the number of pre - aligned groups in the second alignment stage . in this case
, the user can lower the identity threshold ( default 0.6 ) so that the number of sequence groups subject to consistency measure can be reduced .
we also provide options for changing weights of amino acid scoring and predicted secondary structure scoring .
the default values were determined by a large scale testing on divergent scop superfamily domains ( 20,21 ) .
several parameters for running psi - blast and processing psi - blast alignments ( used for generating amino acid profiles ) are also provided , such as e - value cutoff , the number of psi - blast iterations , identity cutoff to remove divergent hits , and the number of homologs kept for profile calculation .
in addition , the server provides a colored alignment with information about sequence grouping , secondary structure predictions and positional conservation ( figure 2 ) .
. sequences with black names immediately under a representative sequence belong to the same pre - aligned group as the representative sequence .
q1tav7_9myco_205_370 belong to the same pre - aligned group , and they are aligned in the fast alignment stage . predicted secondary structures are shown for representative sequences ( residues with red and blue fonts are predicted to be -helices and -strands , respectively ) . above each alignment block ,
conserved positions are marked by their conservation indices ( integer values from 0 to 9 ) calculated using our program al2co ( 22 ) .
the line beneath each alignment block shows consensus secondary structure predictions derived from predictions of individual representative sequences (  h : -helix ;  e : -strand ) .
such a coloring and labeling scheme provides additional information about the promals alignment , and is helpful for further sequence and structural analysis of the target sequences .
in addition to the alignments , the server also provides links to the original input sequences and intermediate results of psi - blast alignments and psi - pred secondary structure predictions . 

these sequences are adenylate / guanylate cyclase catalytic domains selected from the pfam database ( accession number : pf00211 ) ( 23 ) .
the first line in each alignment block begins with  conservation: and shows conservation index numbers for conserved positions .
the last line in each block begins with  consensus_ss: and shows the consensus secondary structure predictions (  h : -helix ;  e : -strand ) .
each representative sequence has a magenta name and is colored according to psipred secondary structure predictions ( red : -helix , blue : -strand ) . a representative sequence and the immediate sequences below it with black names , if there are any , form a closely related group ( determined by the option 
the groups are aligned using profile consistency with enhanced information from database searches and secondary structure predictions .
these sequences are adenylate / guanylate cyclase catalytic domains selected from the pfam database ( accession number : pf00211 ) ( 23 ) .
the first line in each alignment block begins with  conservation: and shows conservation index numbers for conserved positions .
the last line in each block begins with  consensus_ss: and shows the consensus secondary structure predictions (  h : -helix ;  e : -strand ) .
each representative sequence has a magenta name and is colored according to psipred secondary structure predictions ( red : -helix , blue : -strand ) . a representative sequence and the immediate sequences below it with black names , if there are any , form a closely related group ( determined by the option  identity threshold ) .
the groups are aligned using profile consistency with enhanced information from database searches and secondary structure predictions .
if such an alignment is provided , it is split into individual sequences and these sequences will be re - aligned by promals .
it is also recommended that the user provide an email address to receive alignment results , as promals can take a considerable amount of time to finish for a large number of divergent sequences , due to the time - consuming steps of running psi - blast searches and profile consistency measure . on a data set of 1785 scop ( 20,21 )
domain pairs with up to 48 homologs added ( the average number of sequences is 41.6 per alignment ) , the average cpu time of promals is about half an hour under default settings ( 12 ) . the actual time to finish an alignment job
depends on factors such as the number of sequences and their lengths , the diversity among the sequences , the numbers of homologs found in database searches and the server load .
it can take several hours for the server to finish aligning a sequence set with a large number of distantly related sequences ( > 50 ) .
one important parameter is the identity threshold that determines the partition of fast alignment stage and slow alignment stage , and thus balances alignment quality and speed .
lowering this threshold can cause more sequences to be aligned in a fast and less accurate way , resulting in fewer representative groups subject to the time and memory - consuming steps of psi - blast searches and profile consistency measure .
if the number of pre - aligned groups is large ( e.g. > 100 ) , promals could run out of memory during the consistency measure step and generate an error message with the report of the number of pre - aligned groups in the second alignment stage . in this case
, the user can lower the identity threshold ( default 0.6 ) so that the number of sequence groups subject to consistency measure can be reduced .
we also provide options for changing weights of amino acid scoring and predicted secondary structure scoring .
the default values were determined by a large scale testing on divergent scop superfamily domains ( 20,21 ) .
several parameters for running psi - blast and processing psi - blast alignments ( used for generating amino acid profiles ) are also provided , such as e - value cutoff , the number of psi - blast iterations , identity cutoff to remove divergent hits , and the number of homologs kept for profile calculation .
in addition , the server provides a colored alignment with information about sequence grouping , secondary structure predictions and positional conservation ( figure 2 ) .
sequences with black names immediately under a representative sequence belong to the same pre - aligned group as the representative sequence . for example , in figure 2 , 
q1tav7_9myco_205_370 belong to the same pre - aligned group , and they are aligned in the fast alignment stage . predicted secondary structures are shown for representative sequences ( residues with red and blue fonts are predicted to be -helices and -strands , respectively ) . above each alignment block ,
conserved positions are marked by their conservation indices ( integer values from 0 to 9 ) calculated using our program al2co ( 22 ) .
the line beneath each alignment block shows consensus secondary structure predictions derived from predictions of individual representative sequences (  h : -helix ;  e : -strand ) .
such a coloring and labeling scheme provides additional information about the promals alignment , and is helpful for further sequence and structural analysis of the target sequences . in addition to the alignments , the server also provides links to the original input sequences and intermediate results of psi - blast alignments and psi - pred secondary structure predictions . 

these sequences are adenylate / guanylate cyclase catalytic domains selected from the pfam database ( accession number : pf00211 ) ( 23 ) .
the first line in each alignment block begins with  conservation: and shows conservation index numbers for conserved positions .
the last line in each block begins with  consensus_ss: and shows the consensus secondary structure predictions (  h : -helix ;  e : -strand ) .
each representative sequence has a magenta name and is colored according to psipred secondary structure predictions ( red : -helix , blue : -strand ) . a representative sequence and the immediate sequences below it with black names , if there are any , form a closely related group ( determined by the option  identity threshold ) .
the groups are aligned using profile consistency with enhanced information from database searches and secondary structure predictions .
these sequences are adenylate / guanylate cyclase catalytic domains selected from the pfam database ( accession number : pf00211 ) ( 23 ) .
the first line in each alignment block begins with  conservation: and shows conservation index numbers for conserved positions .
the last line in each block begins with  consensus_ss: and shows the consensus secondary structure predictions (  h : -helix ;  e : -strand ) .
each representative sequence has a magenta name and is colored according to psipred secondary structure predictions ( red : -helix , blue : -strand ) . a representative sequence and the immediate sequences below it with black names , if there are any , form a closely related group ( determined by the option  identity threshold ) .
the groups are aligned using profile consistency with enhanced information from database searches and secondary structure predictions .
 multiple sequence alignments are essential in homology inference , structure modeling , functional prediction and phylogenetic analysis . 
 we developed a web server that constructs multiple protein sequence alignments using promals , a progressive method that improves alignment quality by using additional homologs from psi - blast searches and secondary structure predictions from psipred . 
 promals shows higher alignment accuracy than other advanced methods , such as mummals , probcons , mafft and spem . 
 the promals web server takes fasta format protein sequences as input . 
 the output includes a colored alignment augmented with information about sequence grouping , predicted secondary structures and positional conservation . 
 the promals web server is available at : http://prodata.swmed.edu/promals/ 
INTRODUCTION
PROMALS MULTIPLE ALIGNMENT PROCEDURE
PROMALS WEB SERVER
Input
Alignment options
Output of PROMALS results