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Open AcceDatabasePASS2: an automated database of protein alignments organised as structural superfamiliesAnirban Bhaduri, Ganesan Pugalenthi and Ramanathan Sowdhamini*

Address: National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India

Email: Anirban Bhaduri - anirban@ncbs.res.in; Ganesan Pugalenthi - pugal@ncbs.res.in; Ramanathan Sowdhamini* - mini@ncbs.res.in

* Corresponding author

AbstractBackground: The functional selection and three-dimensional structural constraints of proteins innature often relates to the retention of significant sequence similarity between proteins of similarfold and function despite poor sequence identity. Organization of structure-based sequencealignments for distantly related proteins, provides a map of the conserved and critical regions ofthe protein universe that is useful for the analysis of folding principles, for the evolutionaryunification of protein families and for maximizing the information return from experimentalstructure determination. The Protein Alignment organised as Structural Superfamily (PASS2)database represents continuously updated, structural alignments for evolutionary related,sequentially distant proteins.

Description: An automated and updated version of PASS2 is, in direct correspondence withSCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domainshave been grouped into 628 multi-member superfamilies and 566 single member superfamilies.Structure-based sequence alignments for the superfamilies have been obtained using COMPARER,while initial equivalencies have been derived from a preliminary superposition using LSQMAN orSTAMP 4.0. The final sequence alignments have been annotated for structural features usingJOY4.0. The database is supplemented with sequence relatives belonging to different genomes,conserved spatially interacting and structural motifs, probabilistic hidden markov models ofsuperfamilies based on the alignments and useful links to other databases. Probabilistic models andsensitive position specific profiles obtained from reliable superfamily alignments aid annotation ofremote homologues and are useful tools in structural and functional genomics. PASS2 presents thephylogeny of its members both based on sequence and structural dissimilarities. Clustering ofmembers allows us to understand diversification of the family members. The search engine hasbeen improved for simpler browsing of the database.

Conclusions: The database resolves alignments among the structural domains consisting ofevolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantlyrelated proteins despite poor sequence identity and single-member superfamilies permit bettersampling of structures in libraries for fold recognition of new sequences and for the understandingof protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

Published: 02 April 2004

BMC Bioinformatics 2004, 5:35

Received: 28 November 2003Accepted: 02 April 2004

This article is available from: http://www.biomedcentral.com/1471-2105/5/35

© 2004 Bhaduri et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.

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BackgroundClassification of proteins into families is performed onthe basis of the similarity of sequences to the family mem-bers [1,2]. Importantly, however, detectable globalsequence similarity in a protein family is not required forretention of the three-dimensional fold and only a verysmall number of conserved functional residues arerequired for biochemical activity amongst proteinsbelonging to a superfamily [3]. Establishing evolutionaryrelationships between superfamily members having simi-lar structure and function but sequentially diverged ischallenging. Over 49,000 domains deposited in the Pro-tein Data Bank (PDB) [4] are organized in different data-bases by hierarchical classification schemes or in terms ofstructural neighbourhood distances [5-7]. SCOP (1.63release) records 49,497 protein domains, grouped intomerely 765 folds, suggesting a strong structural conver-gence of proteins. Homologous families can be easilygrouped by simple sequence searches whereas super-family members, adopting the same fold and performingsimilar biological roles [8-13] can often be identified bysensitive fold prediction algorithms followed by a carefulalignment of sequences.

Availability of reliable sequence alignments for distantlyrelated proteins despite poor sequence identity permitsbetter sampling of structures in libraries for fold recogni-tion of new sequences and for the understanding of pro-tein structure-function relationships of individualsuperfamilies. In addition, the construction of three-dimensional models using homology modelling tech-niques are usually reliable where the sequence identitybetween query and the structural homologues (templates)are 30% or above. Analyses of structural and sequence dif-ferences amongst known superfamily members can hope-fully provide useful guidelines for modelling distantlyrelated proteins. PASS2 database [14,15] presents align-ments of sequentially distant proteins related at the super-family level. We report an automated, updated version ofthe superfamily alignment database that is in direct corre-spondence with SCOP (1.63) database.

Construction and contentThe present version of PASS2 consider domains asassigned in SCOP 1.63 [6]. Domains within a super-family, no more than 40% identical with each other, havebeen considered for curating the database. The choice of40% cut-off in percentage sequence identity, as comparedto the previous version of PASS2 that works at 25% iden-tity level, was to reduce the number of single-membersuperfamilies. The 4,001 protein domains were assigned1,194 superfamilies spanning the seven classes of proteinsand were thus chosen for structure based sequencealignments.

Curation of alignmentsStructural domains, obtained consulting SCOP [6] defini-tions, have been grouped at the superfamily level andsuperposed by rigid-body superposition (Figure 1). Aninitial superposition for all the structural domains belong-ing to each non-redundant superfamily was performedusing LSQMAN [16] or STAMP 4.0 [17]. LSQMAN [16]was used for superposing two member superfamilieswhile STAMP 4.0 [17] was utilised in multi-membersuperfamilies. From the coarse alignment, equivalentregions were identified using JOY [18]. COMPARER [19]was employed to derive a refined alignment and superpo-sition for the structures. Superposition was achieved bythe choice of 'initial equivalencies' that served as seeds forpairwise rigid-body superposition using PMNFC, a modi-fied form of MNYFIT [20] (Figure 2). The final alignmentwas presented using the three-dimensional structural fea-tures of JOY [18] (Figure 3).

Utility and discussionAssigning new structural entries to pre-existing superfamiliesImproved methods of protein engineering, crystallogra-phy and NMR spectroscopy have led to a surge of newthree-dimensional protein structures deposited in the Pro-tein Data Bank. PASS2 allows classification of three-dimensional domains into respective superfamilies basedon sequential and structural properties. Sequence of theuploaded structure is compared to the hidden markovmodels of PASS2 and assigned to superfamilies on thebasis of liberal expectation values (E = 1.0). Representa-tive structures of the putative superfamilies have beensuperposed with the query using LSQMAN [16], thusassociating the query to a particular superfamily. Alterna-tively, the user can superpose an uploaded structure tospecific superfamilies.

Predicting superfamilies and alignment for sequencesLinks have been provided to popular sequence searchmethods like PSI-BLAST [21] and PHI-BLAST [22], whichmay be employed to associate unannotated sequences toPASS2 superfamilies. A sequence to probabilistic profilematch method Hmmpfam [23] can also be used for simi-lar assignment. Sequence alignments for a query sequencecan be obtained with superfamily members usingMALIGN [24]. 3-dimensional features can also be attrib-uted to the sequence alignment using JOY [18].

Hidden markov models for PASS2During search for sequence homologues and sequenceassignment, profile-based methods perform better com-pared to those that use pairwise comparisons [25]. Familyprofiles based on hidden markov models are popularprobabilistic models applied for sequence annotationsand searches [26,27]. Structure-based sequence alignment

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of respective superfamilies in PASS2 provides a reliablebasis for building hidden markov models. We provideHMMs, built using HMM suite [23], for superfamily align-ments corresponding to the latest version of PASS2. Theperformances of these HMMs have been compared withmodels built using their structural homologues present inthe PDB [28]. Search for homologues have been per-formed on the non-redundant sequence database usingboth sets of models. Higher coverage has been obtained(Table 1) for superfamilies using PASS2 HMMs suggestingtheir value in sensitive sequence searches. Hidden markovmodels for both the structure-based sequence alignmentsand the sequence enriched superfamily alignments can bedownloaded from the World Wide Web.

Superfamily members in the genome databasePASS2 has several new features to associate the structure-based sequences to their homologues in various genomedatabases. Sequence homologues of the superfamilieshave been searched in the non-redundant sequence data-base using PSI-BLAST [21] and Hmmsearch [23]. For thePSI-BLAST searches, individual member for each super-family was queried against the non-redundant sequencedatabase. The expectation value was set to 0.001 with 20iterations. Hidden Markov Models for every superfamilywas built using structural alignments (as explainedabove). These models were searched against the non-redundant database to enrich the sequence membersusing the Hmmsearch program belonging to the HMMsuite applying an E-value threshold of 0.1. A thirdapproach has been to employ interacting motifs,

Flowchart representation of the steps involved in the curation of PASS2 databaseFigure 1Flowchart representation of the steps involved in the curation of PASS2 database. Listed are useful tools and additional derived information that may be obtained from PASS2.

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identified for superfamilies, as constraints in PHI-BLASTagainst searches in the non-redundant database using anE-value 1.0 as explained elsewhere [29]. Hits obtained bythe three approaches belonging to the genomes werealigned using CLUSTALW [30] and presented along withtheir structural representatives of the superfamilies. Thetop 10 hits displayed in the web are aligned with PASS2members. The entire set of hits corresponding to genomescan also be downloaded.

Information about superfamily membersA structure-based sequence alignment for the query withthe appropriate superfamily can be obtained. Superposedcoordinates for the query with the best ranking super-

family (based on the RMSD value) is also provided.Motifs represent invariant regions of the superfamily andare helpful in protein design, engineering and foldingstudies. Spatially conserved interacting motifs are identi-fied as described elsewhere [29] for each superfamily andare listed in the current version of the database along withpsuedoenergies for their spatial interactions (Bhaduri etal., in press). Corresponding links to the structural motifsof superfamily (SMoS) database [31] can also be accessed.

Phylogenetic analysis aids in the understanding of thediversity among the members. Diversification of struc-tural members may be studied in terms of the dissimilar-ity of structure or divergence of the sequences. Thedatabase has been linked to other useful protein databasesas in the previous version of PASS2 [15].

PASS2 and its applicationsPASS2 is a compendium of structure-based sequencealignments of distantly related proteins grouped at thesuperfamily level in direct correspondence with SCOPdefinitions. Furthermore, PASS2 acts as a 'junction' pointto obtain links of representative superfamily members togenome, sequence and structural databases. Phylogeniesof superfamily members provide a crude but quantitativeestimate of evolutionary relationships among the mem-bers. Motifs explain the invariant regions of proteins act-ing as descriptors for the superfamily. HMM models canbe useful in identifying more members. Availability ofsuch alignment databases over the World Wide Web facil-itates the study and design of experiments on specificsuperfamilies. They also enable systematic survey andanalysis of various structural properties for performingfold predictions. The database may be accessed and down-loaded across the World Wide Web.

ConclusionsAssociating different proteins with structurally similar andevolutionarily related proteins enhance our functionalunderstanding of protein superfamily. The multiple align-ments of distantly related representatives are particularlyinformative and often reveal a signature of invariantlyconserved residues. Access to sequence alignments of dis-tantly related proteins over the World Wide Web offers thepossibility to study and design experiments on specificsuperfamilies. They also permit systematic survey andanalysis of various structural properties and to performfold predictions.

Availability of PASS2 databasePASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

Superposed structures of the cytochrome superfamily repre-sentatives: The cytochrome superfamily has six representa-tive members in PASS2 (1a7va-, 1bbha-, 1cpq--, 1e85a-, 256ba-, 2ccya-) which have been superposed as explained (see Curation of Alignments section)Figure 2Superposed structures of the cytochrome superfamily repre-sentatives: The cytochrome superfamily has six representa-tive members in PASS2 (1a7va-, 1bbha-, 1cpq--, 1e85a-, 256ba-, 2ccya-) which have been superposed as explained (see Curation of Alignments section). The figure has been created using MOLSCRIPT [32].

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Representative structure-based sequence alignment for the cytochrome superfamilyFigure 3Representative structure-based sequence alignment for the cytochrome superfamily. The six members have been aligned and represented incorporating the three-dimensional features of JOY [18].

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Authors' contributionsAB and GP have contributed equally to the curation of thedatabase. RS has supervised the study and provided inputboth in the design of the study and drafting of the finalmanuscript.

AcknowledgementsR.S. is a Senior Research Fellow funded by the Wellcome Trust, U.K. GP is supported by the Wellcome Trust. Financial and infrastructural support from NCBS (TIFR) is also acknowledged.

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Table 1: Comparision of the number of hits obtained in HMMSearch using models derived from regular multiple sequence alignments and structure based sequence alignments.

Superfamily name SCOP code Hits obtained from PASS2 HMMs

Hits obtained from superfamily HMMs

Superoxide dismutase 46609 152 137Anticodon-binding domain of class I

aminoacyl-tRNA synthetases47323 220 182

Cyclophilin (peptidylprolyl isomerase) 50891 112 98Hemopexin-like domain 50923 103 73

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