Nucleic Acids Research 2006 34(Web Server issue):W143-W146; doi:10.1093/nar/gkl157
© The Author 2006. Published by Oxford University Press. All rights reserved
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Cascade PSI-BLAST web server: a remote homology search tool for relating protein domains
R. Bhadra1,
S. Sandhya1,2,
K. R. Abhinandan1,
S. Chakrabarti2,
R. Sowdhamini2 and
N. Srinivasan1,*
1 Molecular Biophysics Unit, Indian Institute of Science 560 012, Bangalore, India
2 National Center for Biological Sciences, Tata Institute of Fundamental Research GKVK Campus, Bellary Road, Bangalore 560 065, India
*To whom correspondence should be addressed. Tel: +91 80 2293 2837; Fax: +91 80 2360 0535; Email: ns{at}mbu.iisc.ernet.in
Received February 3, 2006. Revised February 22, 2006. Accepted March 20, 2006.
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ABSTRACT
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Owing to high evolutionary divergence, it is not always possible
to identify distantly related protein domains by sequence search
techniques. Intermediate sequences possess sequence features
of more than one protein and facilitate detection of remotely
related proteins. We have demonstrated recently the employment
of Cascade PSI-BLAST where we perform PSI-BLAST for many ‘generations’,
initiating searches from new homologues as well. Such a rigorous
propagation through generations of PSI-BLAST employs effectively
the role of intermediates in detecting distant similarities
between proteins. This approach has been tested on a large number
of folds and its performance in detecting superfamily level
relationships is
35% better than simple PSI-BLAST searches.
We present a web server for this search method that permits
users to perform Cascade PSI-BLAST searches against the Pfam,
SCOP and SwissProt databases. The URL for this server is
http://crick.mbu.iisc.ernet.in/~CASCADE/CascadeBlast.html.
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INTRODUCTION
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Remote homology sequence search tools are powerful methods for
detecting distant and non-obvious similarities among proteins.
Such methods are often challenged with detecting relationships
in proteins that are usually restricted to the realm of structural
comparisons. The detection of such similarities that are often
exemplified by poor sequence similarities remains the Holy Grail
of most sequence search methods. Databases such as SCOP (
1)
and CATH (
2) perform a hierarchical clustering of protein structures
and help define evolutionary relationships. The SCOP database
clusters proteins that show high similarities in sequence, structure
and function into families such that an evolutionary relationship
between family members is expected. It also defines superfamily
as a collection of protein families that show similarities in
structure and function but poor sequence identity.
Several interesting approaches have employed in different ways, profiles (3,4), templates (5), HMMs (6) and intermediate sequences (7–9) to detect such relationships. We have developed recently a remote homology search approach (10) that establishes such relationships by cascading an entirely sequence analysis based method. The principle behind this approach is a rigorous implementation of an intermediate sequence based search procedure through an extensive application of PSI-BLAST (3,10). In such procedures, intermediate sequences serve as ‘links’ and bridge the sequence gap between proteins. Earlier applications of such search methods (8,9) overcome the intensity of the search by restricting the propagation of searches through a few representative hits. Programs that perform such searches are available in the public domain for download. This is the first implementation of an online server which performs cascade propagation of PSI-BLAST searches through all hits identified for a query. Since the searches are rigorous and time-intensive depending on the query and database selected, results are intimated to the users through e-mail response at the end of every generation.
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CASCADE PSI-BLAST APPROACH
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Briefly, in the cascade PSI-BLAST search method (
10), we propagate
PSI-BLAST searches through hits identified at the end of each
search until no new hits are detectable through further searches.
The rigorous propagation through each hit can help overcome
the query-dependence and asymmetry of traditional use of PSI-BLAST
(
11). The search is initiated against a database with a single
query and we term this ‘a first generation’ search.
All hits identified at the end of this search serve as queries
in what we term as ‘second generation’ to possibly
detect hits not identified in the earlier search. New hits,
if detected are then used to propagate further generations of
the search. Such a cascade propagation of PSI-BLAST searches
continues until a convergence is reached and no new hits are
detectable. An intense propagation of PSI-BLAST through such
cascaded searches for a single query results in, on an average,
500–1000 individual PSI-BLAST searches through all detected
hits over many generations.
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CASCADE PSI-BLAST WEB SERVER
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The web-server implementation of our Cascade PSI-BLAST search
protocol (
Figure 1) accepts a protein sequence as an input.
It is best if the query corresponds potentially to a protein
domain. The databases available for querying the sequence are
the SwissProt-Release
48.9 (
12), SCOP-Release 1.69 (
1) and PFAM-Release
19.0 (
13) databases. Since this is a very time-intensive process
and each hit is given a chance to scan protein sequence space,
we have chosen databases that contain experimentally verified
sequences and larger databases, that may compromise on speed
and time taken to perform the searches, such as the NR are not
included. The homologues are identified in cascaded searches
within the database selected by the user. Default
E- and
H-values
of 0.001 and 0.0001 are employed. However, the user can change
the values if desired. Also, to avoid false positives being
detected in the searches, a length alignment filter of 75% is
employed in the searches. This filter may also be relaxed or
made more stringent by the user. In addition, the user can choose
low complexity filter options for the searches. The web server
is interactive and allows selection of those hits through which
further generations of the search are propagated. At the end
of each generation, an Email, with a link to the hits, is sent
to the user. The result pages are descriptive with annotations
for each hit and indicate the domain boundaries of the hits
identified in the PSI-BLAST searches. The detailed PSI-BLAST
output files that contain alignments are made available to the
user as a gzipped tar file at the end of every generation. All
hits identified at the end of each generation of the search
are made available for download in FASTA format for subsequent
analysis. In order to overcome limitations on computing time
involving multiple server requests, the next generation of the
search can be seeded through a maximum of 30 sequences at a
time. If the user wishes to seed the searches in a generation
with >30 sequences, such hits may be selected as queries
subsequent to the completion of the previous runs. A maximum
of up to four generations of the search is permitted although
our earlier assessments indicate that up to three generations
of the search can effectively detect most of the remote hits
for a query. As can be seen in
Figure 1, hits identified at
each generation of the search are stored in a MYSQL database
and these are queried through a PERL-CGI interface. Programs
that employ Perl DBD modules are used to process the searches
and results. Links to results are notified to the user through
Email since searches can be computationally intensive and time
consuming. Results are presented in two formats as clickable
links in the Email sent to the user at the end of every generation.
Link 1 lists the annotated sequence details of the hits with
E-values at which detection is made. These sequences correspond
to the alignment region reported in the search and not to the
full length of the protein and may be used to generate sequence
libraries or multiple alignments of all remote homologues identified
by the search since the sequences may be downloaded. Link 2
presents the results in tabular format. This representation
allows a quick assessment of those hits in each generation that
have served as the actual ‘intermediate links’ in
propagating the searches and elucidating the evolutionary relationships.
In searches in Pfam (
13), the protein family name of the hits
associated with the query is provided. Protein annotations are
also made available as links in searches involving the SwissProt
database. The scop code of the hits is provided in searches
in the SCOP database (
1). This is a very useful feature since
the examination of these defined codes allows the user to quickly
ascertain whether the hits appearing in each generation of the
search belong to the same family, superfamily or fold of the
query. Such an analysis allows evaluation of the evolutionary
significance of the relationships detected. We had demonstrated
such relationships in the superfamilies of the TIM and Globin
folds (
10). In our earlier analysis, we have shown an improvement
in coverage of family members of
15% and detect
35% more superfamily
level relationships than typical PSI-BLAST searches (
10).
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CONCLUSIONS
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Proteins may evolve to the extent that they have little similarity
in sequence and yet preserve their inherent relationships through
similarities in structure and function. When sequences mutate
so extensively, it is difficult to ascertain whether they may
be true relatives through pure sequence analysis. Structural
comparisons are often successful in detecting such remote similarities
as seen in SCOP and CATH databases (
1,
2). Park
et al. and others
(
7,
10) have shown that intermediate sequences can serve as missing
links and bridge protein sequence space. With the escalation
in genome sequence initiatives, there is an excellent and exciting
opportunity to employ these sequences in a rigorous manner to
scan protein space further and detect more meaningful hits.
Large sequence dispersions within protein families and superfamilies are often the cause for difficulties in detecting evolutionary relationships. While search methods such as PSI-BLAST are powerful in detecting most family relationships, we have shown an improved coverage at the level of both family and superfamily since more than one generation of the search is effective in detecting related members of a protein query (10). Large sequence dispersions may also result in sub-clustering of family members. Thus, ‘profile traps’, caused due to over-representation of some of the sub-clusters often become a bottleneck in detecting other members. Since every hit can propagate the search in a non-uniform direction, we attempt to overcome the inherent asymmetry of other approaches (10). Our search method has exciting implications in fold recognition and in detecting distant similarities through an entirely sequence analysis based approach.
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ACKNOWLEDGEMENTS
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R.S. thanks NCBS (TIFR) for financial and infrastructural support.
N.S. thanks the Department of Biotechnology, New Delhi for support
through the computational genomics project. This work is supported
by the award of Senior Research Fellowships in Biomedical Sciences
by the Wellcome Trust, London to R.S. and N.S. R.B. is supported
by Department of Biotechnology, New Delhi. S.S. and K.R.A. were
also supported by the Wellcome Trust, London. S.S. is a Senior
Research Fellow of the Council of Scientific and Industrial
Research, India. The Open Access publication charges for this
article were waived by Oxford University Press.
Conflict of interest statement. None declared.
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Footnotes
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Present addresses: K. R. Abhinandan, Department of Biochemistry
and Molecular Biology, University College, London, Gower Street,
London WC1E 6BT, England
S. Chakrabarti, Computational Biology Branch, National Center for Biotechnology, Information (NCBI), National Library of Medicine (NLM), NIH, 8600, Rockville Pike, Bethesda, MD 20894, USA
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ABSTRACT
INTRODUCTION