PSI-BLAST-ISS: an intermediate sequence search tool for estimation of the position-specific alignment reliability.

Abstract

Protein sequence alignments have become indispensable for virtually any evolutionary, structural or functional study involving proteins. Modern sequence search and comparison methods combined with rapidly increasing sequence data often can reliably match even distantly related proteins that share little sequence similarity. However, even highly significant matches generally may have incorrectly aligned regions. Therefore when exact residue correspondence is used to transfer biological information from one aligned sequence to another, it is critical to know which alignment regions are reliable and which may contain alignment errors.
PSI-BLAST-ISS is a standalone Unix-based tool designed to delineate reliable regions of sequence alignments as well as to suggest potential variants in unreliable regions. The region-specific reliability is assessed by producing multiple sequence alignments in different sequence contexts followed by the analysis of the consistency of alignment variants. The PSI-BLAST-ISS output enables the user to simultaneously analyze alignment reliability between query and multiple homologous sequences. In addition, PSI-BLAST-ISS can be used to detect distantly related homologous proteins. The software is freely available at: http://www.ibt.lt/bioinformatics/iss.
PSI-BLAST-ISS is an effective reliability assessment tool that can be useful in applications such as comparative modelling or analysis of individual sequence regions. It favorably compares with the existing similar software both in the performance and functional features.

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BioMed Central
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BMC Bioinformatics
Open Access
Software
PSI-BLAST-ISS: an intermediate sequence search tool for
estimation of the position-specific alignment reliability
Mindaugas Margelevičius and Жeslovas Venclovas*
Address: Institute of Biotechnology, Graičiūno 8, LT-02241 Vilnius, Lithuania
Email: Mindaugas Margelevičius - minmar@ibt.lt; Жeslovas Venclovas* - venclovas@ibt.lt
* Corresponding author
Abstract
Background: Protein sequence alignments have become indispensable for virtually any
evolutionary, structural or functional study involving proteins. Modern sequence search and
comparison methods combined with rapidly increasing sequence data often can reliably match even
distantly related proteins that share little sequence similarity. However, even highly significant
matches generally may have incorrectly aligned regions. Therefore when exact residue
correspondence is used to transfer biological information from one aligned sequence to another,
it is critical to know which alignment regions are reliable and which may contain alignment errors.
Results: PSI-BLAST-ISS is a standalone Unix-based tool designed to delineate reliable regions of
sequence alignments as well as to suggest potential variants in unreliable regions. The region-
specific reliability is assessed by producing multiple sequence alignments in different sequence
contexts followed by the analysis of the consistency of alignment variants. The PSI-BLAST-ISS
output enables the user to simultaneously analyze alignment reliability between query and multiple
homologous sequences. In addition, PSI-BLAST-ISS can be used to detect distantly related
homologous proteins. The software is freely available at: http://www.ibt.lt/bioinformatics/iss.
Conclusion: PSI-BLAST-ISS is an effective reliability assessment tool that can be useful in
applications such as comparative modelling or analysis of individual sequence regions. It favorably
compares with the existing similar software both in the performance and functional features.
Background
Protein sequence alignments are at the heart of many bio-
logical applications such as sequence database searches,
annotation of new sequences, inference of functional
regions, comparative protein modeling. Modern sequence
comparison methods (e.g. PSI-BLAST [1]) often can relia-
bly establish an evolutionary link between two proteins
and align them even if they share little sequence similar-
ity. However, the resulting significant match between
these protein sequences may well include incorrectly
aligned regions that are impossible to identify by straight-
forward inspection. Usually, the lower is the sequence
similarity the more challenging is to distinguish align-
ment regions that can be trusted from those that may have
errors. Yet, such a distinction is very important if the exact
correspondence of residue positions in sequence align-
ments is used to extrapolate the biological information
from one protein to another. Modeling protein structure
by comparison (comparative modeling), identification of
active site residues, selection of sites for point mutations
are just a few examples where the reliability of aligned
positions is critical.
Published: 21 July 2005
BMC Bioinformatics 2005, 6:185doi:10.1186/1471-2105-6-185
Received: 17 March 2005
Accepted: 21 July 2005
This article is available from: http://www.biomedcentral.com/1471-2105/6/185
© 2005 Margelevičius and Venclovas; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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The importance of delineating reliable alignment regions
has been recognized more than a decade ago, however,
earlier studies focused on pairwise alignments [2-5]. Cur-
rently, due to abundant sequence data, most protein
sequence comparisons are performed within the context
of multiple homologs, and the importance of pairwise
alignments has diminished. By including multiple
homologous sequences, methods such as PSI-BLAST are
able to reliably detect more distant evolutionary links and
also produce more accurate alignments. Unfortunately,
even most advanced sequence alignment methods do
make mistakes and the identification of reliable align-
ment regions remains an important problem. Estimation
of position-specific alignment reliability is being
addressed in some recent multiple sequence alignment
methods [e.g. [6,7]]. However, in the multiple alignment
case the position-specific reliability index estimates the
overall proportion of correct pairwise matches in each
alignment column without specifying the contribution of
individual sequences. Yet in applications such as compar-
ative modeling usually it is more important to know the
position-specific alignment reliability for a given
sequence pair than for the whole set of aligned sequences.
Recently, a growing understanding of the importance of
the problem led to several studies aiming at identification
of reliable alignment regions for a pair of sequences
within the context of multiple homologs. For example,
one of these studies found that a substantial number of
misaligned positions could be removed using the near-
optimal alignment information [8]. Two other recent
methods have been developed that predict reliable align-
ment regions either directly from a generated sequence
profile [9,10] or using a consensus result of several align-
ment algorithms [11,12]. Both latter methods are imple-
mented as web-based servers, which makes them easily
accessible and simple to use, but not without certain lim-
itations. For example, both servers require that one of the
two sequences in the alignment would have a correspond-
ing PDB structure, which in turn would have to be present
in local databases used by these servers.
Here, we present the PSI-BLAST Intermediate Sequence
Search tool (PSI-BLAST-ISS) that is primarily designed to
help identify reliable regions of the alignment as well as
suggest potential alignment variants in unreliable regions.
In comparative modeling PSI-BLAST-ISS can also help
identify best matching structural templates. In addition,
PSI-BLAST-ISS can be used to detect remote homologs
that cannot be identified by a straightforward single PSI-
BLAST search. However, it should be noted that the detec-
tion of remote homologs, unlike in the original and sub-
sequent implementations of the Intermediate Sequence
Search (ISS) strategy [13-17], is not the main purpose of
our tool.
Since PSI-BLAST-ISS might be most useful in comparative
modeling we are going to refer to the sequence pair of
interest as the target (query) and the template (reference)
sequences throughout the article. However, it should be
emphasized that the tool can be applied for any protein
sequences that could be linked through common
homologs, independently whether the three-dimensional
structure for any of them is available or not.
The main idea of PSI-BLAST-ISS is to obtain a number of
alignment variants for the sequence pair of interest (target
and template) and analyze their consistency. This idea has
stemmed from previous manual analysis of multiple PSI-
BLAST alignment variants suggesting that regions where
variants do agree are likely to be aligned correctly and dis-
play close structural similarity [18].
Implementation
The whole PSI-BLAST-ISS procedure may be described as
the following steps: (1) identification of multiple
sequences related both to the target and template
sequences, (2) formation of a representative set from
these sequences by filtering out close homologs, (3) gen-
eration of sequence profiles for each sequence from this
representative set by searching a sequence database with
PSI-BLAST, (4) using each of the generated profiles to
search a second sequence database that includes
sequences of both the target and the template, (5) reten-
tion of all the instances of significant matches between the
target and the template, (6) merging all significant target-
template alignments by taking the target sequence as a
frame of reference and (7) reducing the multiple variants
of aligned template into the consensus sequence. The lat-
ter option enables contrasting of the region-specific relia-
bility for multiple target-template
simultaneously. All the seven main steps are illustrated in
a sketch of the data flow (Fig. 1) and are described in more
detail below.
alignments
As an input, PSI-BLAST-ISS takes the target sequence in
FASTA format and a file containing a number of parame-
ters that enable a user both to specify sequence databases
and to control the execution of the whole ISS procedure at
every step. The target sequence is initially searched against
a sequence database to collect intermediate sequences
(step 1). By default, the target is searched against the non-
redundant sequence database. Intermediate sequences are
collected from the user-specified PSI-BLAST iteration in
the resulting output file using the expectation value (E-
value) threshold provided as a parameter. The reduced
representative sequence set is constructed by filtering the
initial set to a user-defined percentage of sequence simi-
larity with CD-HIT (Li et al., 2001), the sequence clusteri-
zation program (step 2). Optionally, a user may introduce
a strict limit to the number of sequences to be included in

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Main steps in the PSI-BLAST-ISS execution
Figure 1
Main steps in the PSI-BLAST-ISS execution. PSI-BLAST-ISS comprises seven main steps to produce consensus sequence
alignment starting with the target sequence. The position-specific alignment reliability can be estimated either from individual
target-template multiple alignments obtained in step 6 or from the combined alignment of consensus template sequences (step
7). For example, in this figure (step 7) only two template sequences are estimated to be reliably aligned with the last helix of
the target, other templates lack consensus in this region.

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the representative set or even supply independently pre-
selected set of sequences. A PSI-BLAST-ISS user can also
choose whether to collect intermediate sequences as com-
plete protein sequences or just as sequence fragments
matching the target sequence. In the case when the target
sequence represents a domain that is also found in multi-
domain proteins the ability to select only homologous
fragments of matching sequences may help to keep the ISS
procedure from straying into the realm of unrelated
sequences. Each of the intermediate sequences is used to
generate a sequence profile in the form of the PSI-BLAST
checkpoint file by running a user-defined number of PSI-
BLAST iterations (step 3). The resulting checkpoint files
are then used to restart PSI-BLAST searches in a second
sequence database specified by the user (step 4). This
database is expected to include sequences of both proteins
of interest (target and template). In a common situation,
when the template represents a structural template
intended for use in comparative modeling, such a data-
base may be derived by simply appending the target
sequence to the PDB sequence database. In this case there
is no need to define template(s) in advance since they are
identified automatically. Searches against the second
database generate corresponding multiple sequence align-
ments that contain a number of target-template alignment
variants. The significance of the target-template alignment
is then determined by counting the number of alignment
variants that satisfy the expectation value threshold (step
5). Both parameters can be specified by the user. The sig-
nificant target-template alignment variants are extracted
and merged into a single multiple sequence alignment,
where the target sequence is aligned with multiple
instances of the template sequence according to different
alignment variants (step 6). Such an alignment immedi-
ately reveals the regions where most (or all) alignment
variants are identical and thus might be considered relia-
ble as well as those regions where there is little agreement
between alignment variants and therefore unreliable.
Often it is useful to analyze position-specific reliability for
target alignments with multiple templates. However, it
may be inconvenient to contrast/compare at once many
multiple sequence alignments obtained by PSI-BLAST-ISS.
To make this task easier we introduced a step (step 7) that
reduces template alignment variants into a consensus
template sequence for each of the target-template align-
ments. The consensus sequence is generated by analyzing
each column of the alignment. A residue is considered
conserved in the consensus template sequence if its repe-
tition count in the corresponding position exceeds the
user-defined conservation threshold.
PSI-BLAST-ISS currently is implemented as a standalone
UNIX-based tool meant to be installed and run locally. It
consists of fairly independent modules linked together
using Perl. Some of the sequence data processing tasks in
PSI-BLAST-ISS are handled by a few modified SEALS
scripts [19].
Results and Discussion
PSI-BLAST-ISS output
PSI-BLAST-ISS produces several types of results. Perhaps
the most informative output file is the FASTA-formatted
sequence alignment between the target and automatically
detected multiple template sequences, each represented as
a consensus sequence derived from multiple alignment
variants. The definition line for each consensus template
sequence indicates the strength of the consensus in the
interval from 0 to 1 (0 – no consensus, 1 – complete agree-
ment) and the number of significant target-template
alignment variants that were used to produce the consen-
sus. This output provides a possibility to simultaneously
assess the alignment reliability between the target and
multiple templates in a region-specific manner. In addi-
tion, the consensus strength and the number of significant
target-template alignments may help in selecting tem-
plates that are structurally most consistent with the target.
PSI-BLAST-ISS also produces individual FASTA-formatted
multiple sequence alignment files for each target-template
pair, where the target is aligned with multiple copies of
the same template according to obtained multiple align-
ment variants. These alignment files provide a visual
assessment of the region-specific alignment reliability as
well as candidate alignment variants if further analysis of
unreliably aligned stretches is needed. Finally, all the tem-
plate sequences represented in the consensus alignment
are collected together in a separate output file.
Performance of PSI-BLAST-ISS in the assessment of
alignment reliability
Like for any method it is important to know how PSI-
BLAST-ISS performs relative to other available methods.
At the time of this study we have been aware of only two
publicly available servers that estimate the position-spe-
cific reliability of sequence alignment using information
from multiple sequences: the Consensus server [12] and
SQUARE [9]. Of those, the performance of PSI-BLAST-ISS
could be directly compared only with the Consensus
server since SQUARE estimates reliability only for the sup-
plied alignment and does not address the problem of
alignment itself.
To compare PSI-BLAST-ISS and Consensus we chose pro-
tein sequences provided as prediction targets in the last
round [20] of the community-wide protein structure pre-
diction experiment known as CASP http://prediction
center.org/casp6/. These proteins represent a variety of
different structural folds and different degree of similarity
to known structures. We ran PSI-BLAST-ISS for all the tar-
get sequences assessed in CASP6, but only those, for
which PSI-BLAST-ISS with default parameters generated at

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Table 1: Comparison of PSI-BLAST-ISS and the Consensus server performance
Target TemplateAlign
length
Rmsd,
Å
Seq id,
%
Consensus serverPSI-BLAST-ISS (consensus, 0.8)
PSI-BLAST-
ISS (consensus, 0.9)
discrepanciesdiscrepancies d-len/cons-lendiscrepancies d-len/cons-len d-len/cons-len
T01961jny 801.63368–77 10/
62
1/45
5/146
1/173
5/102
0/13
0/177
1/96
68–74, 77 8/
56
0/58
2/186
2/17
1/90
0/65
3/238
7/143
69–72 4/
50
0/50
0/144
0/14
0/85
0/55
0/107
7/116
T0200
T0202
T0204
T0208
T0211
T0216
T0222
1ush
1u0r
1gup
1i60
1eut
1vpb
1rzm
210
245
280
254
126
417
239
2.7
2.0
2.0
3.1
1.7
2.5
2.7
16
26
25
11
22
25
14
71--
-
-
-
-
-
59–62, 94
164
258–262
-
-
154
59, 108
139, 141
292
-
38–39, 71
154, 246, 281–
285
113–119, 121–
124, 128–132
170–172, 174–
181
82–83, 120–127
-
5–6, 40, 42–43,
66, 158
136, 245, 325–
327
11, 13–14, 16
207–208, 443,
478–479
10–11, 20–22,
24–26, 28–30,
65–66
231–234
-
76, 162, 305
154, 246,
281–285
113–116T02231vfr1232.5 11-0/2216/39 4/24
T0228 1qpn145 3.111-0/21 11/57-0/39
T0229
T0231
T0232
1ml8
1v6f
11gs
125
136
199
1.9
1.4
2.1
35
79
19
120–127
-
-
8/61
0/133
0/32
10/114
0/130
7/114
120–127
-
6, 40, 42–43,
66, 158
136, 245
8/84
0/125
6/97
T02331kgz3191.836136, 325–326 3/276 5/3062/279
T0234
T0235
1g76
1nb8
118
276
2.8
2.4
14
26
161/59
3/44
4/67
5/104
11, 13–14, 16
207–208, 443
4/58
3/93442–443, 478
T02401lr070 2.51725,332/3913/51 20–22, 24–266/43
T0244
T0246
T0247
1iim
1cnz
1pj5
242
353
338
2.6
1.4
2.1
24
57
25
206, 229–234
-
76, 115–126,
128–129, 162–
165, 261, 302
60
-
60–65, 77
80–83
121, 153–154
89–92, 95, 119–
120
43,102–103
26–30, 41–45
92–94
-
7/157
0/315
21/227
4/153
0/313
3/227
-
-
0/115
0/276
1/150 76
T0264
T0265
T0266
T0267
T0268
T0269
1vhv
1sfx
1dbu
1tiq
1m6y
1qmv
244
87
145
165
277
182
2.1
3.0
1.8
2.1
1.6
2.1
34
25
25
16
49
35
1/120
0/50
7/91
4/77
3/216
7/125
17–19
-
28, 77
68, 80–81
44, 126, 249
119–120
3/92
0/50
2/132
3/102
3/258
2/128
17–19
-
-
68, 80–81
126
-
3/81
0/42
0/95
3/91
1/216
0/99
T0274
T0275
T0276
T0279
1i0r
1mjh
1sbq
1jr2
144
125
153
240
1.7
2.0
1.7
5.9
24
30
26
16
3/86
10/75
3/56
0/31
8, 43, 73
26–30, 41–42
18, 39, 150–151
144–145, 202–
204, 258
119
41–42, 208–210
3/107
7/107
431/87
3/92
0/84
0/6
29–30, 41
-
-
4/122
6/68
T0280
T0282
1o5o
1gq6
144
275
3.0
2.4
19
21
170–175
245
6/55
1/129
1/51
5/202
- 0/46
1/13842
Total:
113/3311
3.5/103.5
Total:
140/3947
4.4/123.3
Total:
57/3081
1.8/96.3
Average per
target:
Fraction
Average per target:Average per
target:
Fraction
3.4%
Fraction
3.5% 1.9%
Target-template structure-based alignments that were used as reference are characterized by the number of superimposed residues (column Align
length), root-mean-square deviation of their Cα atoms (Rmsd), and the sequence identity (Seq id). Differences between each structure-based
alignment and alignments obtained either by the Consensus server or PSI-BLAST-ISS are reported in corresponding discrepancies columns. The
discrepancies are reported as segments, and their begin-end positions are given with respect to the target sequence. Only consensus segments of at
least 3 residues were considered. Columns d-len/cons-len provide ratios between the length of discrepancies (d-len) and the total length of the
alignment considered to be reliable (cons-len) by the corresponding method.