Bioinformatics Advance Access originally published online on December 6, 2007
Bioinformatics 2008 24(3):445-446; doi:10.1093/bioinformatics/btm596
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ConoServer, a database for conopeptide sequences and structures
Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
*To whom correspondence should be addressed.
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ABSTRACT |
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 TOP ABSTRACT 1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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Summary: ConoServer is a new database dedicated to conopeptides, a large family of peptides found in the venom of marine snails of the genus Conus. These peptides have an exceptional diversity of sequences and chemical modifications and their ability to block ion channels makes them important as drug leads and tools for physiological studies. ConoServer uses standardized names and a genetic and structural classification scheme to present data retrieved from SwissProt, GenBank, the Protein DataBank and the literature. The ConoServer web site incorporates specialized features like the graphic display of post-translational modifications that are extensively present in conopeptides. Currently, ConoServer manages 1214 nucleic sequences (from 54 Conus species), 2258 proteic sequences (from 66 Conus species) and 99 3D structures.
Availability: http://research1t.imb.uq.edu.au/conoserver/
Contact: d.craik{at}imb.uq.edu.au
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1 INTRODUCTION |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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Predatory marine cone snails of the Conus genus produce a concoction of venom peptides, referred to as conopeptides, which they use to capture prey (Gray et al., 1988; Terlau and Olivera, 2004). With >700 Conus species, each with their own repertoire of peptide toxins, conopeptides form a huge library of bioactive peptides (Olivera, 1997; Olivera and Cruz, 2001). They are typically 10–40 amino acids long and contain up to five disulfide bonds (Craik et al., 2007). Due to their high specificity for ion channel isoforms and their high potency, conopeptides are of great interest as neuropharmacological tools and as drug leads (Adams et al., 1999). PrialtTM, a synthetic version of a conopeptide from Conus magus, is an approved drug for the treatment of chronic pain. Several other conopeptides are in clinical or pre-clinical trials.
Conopeptides are synthesized as prepro-peptides, which are proteolytically cleaved to yield the mature peptide. The signal sequence is well conserved, but the mature toxin sequence, at the C-terminus of the prepro-peptide, is highly divergent. The mature peptides have a high frequency of post-translational modifications. Conopeptides are classified into disulfide-rich and -poor, into superfamilies (signal sequence similarity), into cysteine framework categories and into pharmacological families, as explained in Figure 1. With interest in conotoxin growing, a database is needed to systematize the increasing number of discovered sequences and structures.
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2 DATA RETRIEVAL AND ANNOTATIONS |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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The sequences and structures of conopeptides were extracted from public databases, GenBank (Benson et al., 2007), SwissProt (Boeckmann et al., 2003) and the Protein DataBank (Berman et al., 2000), and by an extensive survey of the literature. The sequences of mature peptides were also extracted from prepro-peptide sequences.
Manual curation of each entry contributes to a high level of standardization that is necessary for efficient searches and comparisons. Wherever applicable a standard naming scheme (Gray et al., 1988) was used: one or two letters indicating the Conus species, a Roman numeral indicating the disulfide framework category and an upper case letter denoting the order of discovery. A list of alternative names found in the literature was also built. The conotoxin superfamilies were assigned based on the analysis of the signal sequence.
ConoServer currently manages 1214 nucleic sequences (from 54 Conus species), 2258 proteic sequences (from 66 species) and 99 3D structures. The proteic sequences are split into 450 mature peptides, 615 prepro-peptides, 34 synthetic peptides and 1159 sequences from patents. The 427 mature conotoxins are split into superfamilies as follows: 133 O, 104 A, 58 M, 51 T, 31 I, 7 L, 6 P, 6 J, 6 P, 3 D, 2 S and 1 G superfamily peptides. The superfamilies of the remaining 19 conotoxins have not yet been published.
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3 INTERFACE AND VISUALIZATION |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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3.1 Search
ConoServer allows searches of nucleic acids, proteins and 3D structures of conopeptides based on their name, patent ID, sub-sequence, FASTA alignment, mass range, peptide mass fragments (fingerprints), classification (Fig. 1), type (mature peptide, prepro-peptide, synthetic peptide or patent) and species. The name search simultaneously uses standard names and related names (historical names, non-standard names, trade names).
3.2 Results
The results are displayed as a table whose column fields are customizable: standard names, target families, superfamilies, protein types, species, sequences, masses, curation notes, literature references and external links. A list of more than 400 references (linked to the corresponding PubMed abstract) is stored in the database and can be displayed.
3.3 Cards
Each element of the result list is linked to an entry card presenting four parts: (i) general information with name, classification, sequence, mass, isoelectric point and extinction coefficient (ii) literature references with links to PubMed, (iii) cross references between ConoServer cards and with external databases and (iv) tools to predict the digestion of proteic sequences and to visualize the 3D structures with the Jmol applet (http://www.jmol.org/). The visualization of sequences in cards and lists highlights the precursors in nucleic acids sequences, the signal sequence and the mature peptide in prepro-sequences, and the cysteine framework and the post-translational modifications in mature peptide sequences.
3.4 Sequence comparison
ConoServer allows comparison of sequences of entries selected from a result list. The sequences can be aligned with CLUSTALW (Thompson et al., 1994) and the alignment analysed with an amino acid based colour scheme or with a LOGO representation (Schneider and Stephens, 1990) or with a distance tree computed with protdist and dnadist from the PHYLIP package (Felsenstein, 1989).
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4 IMPLEMENTATION |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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ConoServer uses MySQL (http://www.mysql.com) and its web interface is implemented in PHP (http://www.php.net). A single XML file for proteins, nucleic acids and structures allows a common definition of the search, list and card pages. A web-based annotation interface allows efficient entry or change of data. ConoServer is freely available at http://research1t.imb.uq.edu.au/conoserver/.
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5 CONCLUSIONS |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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ConoServer is a new database that provides standardized annotations of conopeptides. The web interface allows searching of the database using a combination of criteria that include the conopeptide sequence, classification and names. The unique display features and cross links between nucleic acid, proteic and structural data and the high quality of the annotations will hopefully make ConoServer a useful resource for researchers working on conopeptides and more broadly on bioactive peptides.
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ACKNOWLEDGEMENT |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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Work in our laboratory on conotoxins is supported by the Australian Research Council.
Conflict of Interest: none declared.
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FOOTNOTES |
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Associate Editor: Alex Bateman
Received on October 15, 2007; revised on November 26, 2007; accepted on November 27, 2007
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REFERENCES |
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TOPABSTRACT1 INTRODUCTION2 DATA RETRIEVAL AND...3 INTERFACE AND VISUALIZATION4 IMPLEMENTATION5 CONCLUSIONSACKNOWLEDGEMENTREFERENCES |
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Adams DJ, et al. Conotoxins and their potential pharmaceutical applications. Drug Dev. Res (1999) 46:219–234.[CrossRef][Web of Science]
Benson DA, et al. GenBank. Nucleic Acids Res (2007) 35:D21–D25.
Berman HM, et al. The Protein Data Bank. Nucleic Acids Res (2000) 28:235–242.
Boeckmann B, et al. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res (2003) 31:365–370.
Craik DJ, Adams DJ. Chemical modification of conotoxins to improve stability and activity. ACS Chem. Biol (2007) 2:457–468.[CrossRef][Medline]
Felsenstein J. PHYLIP - Phylogeny Inference Package (Version 3.2). Cladistics (1989) 5:164–166.
Gray WR, et al. Peptide toxins from venomous Conus snails. Annu. Rev. Biochem (1988) 57:665–700.[CrossRef][Web of Science][Medline]
Olivera BM. E.E. Just Lecture, 1996. Conus venom peptides, receptor and ion channel targets, and drug design: 50 million years of neuropharmacology. Mol. Biol. Cell (1997) 8:2101–2109.
Olivera BM, Cruz LJ. Conotoxins, in retrospect. Toxicon (2001) 39:7–14.[Medline]
Schneider TD, Stephens RM. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res (1990) 18:6097–6100.
Terlau H, Olivera BM. Conus venoms: a rich source of novel ion channel-targeted peptides. Physiol. Rev (2004) 84:41–68.
Thompson JD, et al. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res (1994) 22:4673–4680.
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