Conotoxins, the disulfide rich conopeptides, are classified according to three schemes: the similarities between the ER signal sequence of the conotoxin precursors (gene superfamilies), the cysteine patterns of conotoxin mature peptide regions (cysteine frameworks), and the specificities to pharmacological targets (pharmacological families). This page provides a brief introduction to the gene superfamilies and a list of the gene superfamilies used in ConoServer. The two other classification schemes are detailed in separate pages accessible from the menu on the left. A more comprehensive discussion of the conopeptide classification schemes can be found in Kaas et al. Toxicon 2010 .
Conopeptides are expressed as precursor proteins, which are processed into mature peptide toxins in the endoplasmic reticulum (ER) and in the Golgi apparatus. The classical organisation of a conopeptide precursor is shown in Figure 1. During the maturation process, the ER signal sequence and then the N- and C-terminal pro-regions are cleaved and some amino acids can be post-translationally modified (see amino acid post-translational modifications).
The sequence regions of the conopeptide precursors (Figure 1) have been shown to evolve at different rate . The sequence of the mature peptide region is highly diverse, in keeping with the high variety of conopeptides, while the ER signal sequence is more conserved. The comparison of conopeptide ER signal sequences allowed to define several groups, the gene superfamilies, that share higher sequence similarity. Figure 2 shows a clustering analysis of the ER signal sequences in ConoServer together with the identification of the superfamilies. This analysis shows that by using a cut-off of 35% sequence identity, most of the superfamilies are well defined. The only exception is the unique member of the Y-superfamily which shares around 40% identity with some members of the M-superfamily.
Table 1 provides the definition of the 27 published gene superfamilies that are used in ConoServer. The relationship between the gene superfamilies and the other classification schemes, the cysteine frameworks and the pharmacological families, are complex. Up-to-date statistics on those relationships can be found in the ConoServer statistics pages and in Kaas et al. Toxicon 2010 . Recently the gene superfamily classification was extended to the disulfide poor conopeptides , and the gene superfamilies B and C have been introduced in ConoServer.
|Gene superfamily||Cysteine frameworks||# protein precursors||Reference|
|A||I, II, IV, VI/VII, XIV, XXII||288||Santos,A.D. et al. (2004) J. Biol. Chem. 279:17596-17606|
|B1||18||Puillandre,N. et al. (2012) J. Mol. Evol. 74:297-309|
|B2||VIII||2||Dutertre,S. et al. (2013) Mol. Cell Proteomics 12:312-329|
|B3||XXIV||1||Luo,S. et al. (2013) PLoS ONE 8|
|C||4||Puillandre,N. et al. (2012) J. Mol. Evol. 74:297-309|
|D||XX||29||Loughnan,M.L. et al. (2009) Biochemistry 48:3717-3729|
|E||XXII||1||Dutertre,S. et al. (2013) Mol. Cell Proteomics 12:312-329|
|F||2||Dutertre,S. et al. (2013) Mol. Cell Proteomics 12:312-329|
|G||XIII||1||Aguilar,M.B. et al. (2013) Peptides [ahead of print]|
|H||VI/VII||10||Dutertre,S. et al. (2013) Mol. Cell Proteomics 12:312-329|
|I1||VI/VII, XI||26||Jimenez,E.C. et al. (2003) J. Neurochem. 85:610-621|
|I2||XI, XII, XIV||63||Buczek,O. et al. (2005) FEBS J. 272:4178-4188|
|I3||VI/VII, XI||9||Yuan,D.D. et al. (2009) Peptides 30:861-865|
|J||XIV||30||Imperial,J.S. et al. (2006) Biochemistry 45:8331-8340|
|K||XXIII||4||Ye,M. et al. (2012) J Biol Chem 287:14973-14983|
|L||XIV, XXIV||15||Peng,C. et al. (2006) Peptides 27:2174-2181|
|M||I, II, III, IV, VI/VII, IX, XIV, XVI||444||Corpuz,G.P. et al. (2005) Biochemistry 44:8176-8186|
|N||XV||3||Dutertre,S. et al. (2013) Mol. Cell Proteomics 12:312-329|
|O1||I, VI/VII, IX, XII, XIV, XVI||598||McIntosh,J.M. et al. (1995) J. Biol. Chem. 270:16796-16802|
|O2||VI/VII, XIV, XV||137||Zhangsun et al. (2006) Chem Biol Drug Des. 68:256-265|
|O3||VI/VII||43||Zhangsun et al. (2006) Chem Biol Drug Des. 68:256-265|
|P||IX, XIV||12||Lirazan,M.B. et al. (2000) Biochemistry 39:1583-1588|
|Q||VI/VII, XVI||22||Lu,A. et al. (2014) Mol. Cell Proteomics 13:105-118|
|S||VIII||21||Liu,L. et al. (2008) Toxicon 51:1331-1337|
|T||I, V, X, XVI||238||Walker,C.S. et al. (1999) J. Biol. Chem. 274:30664-30671|
|V||XV||2||Peng,C. et al. (2008) Peptides 29:985-991|
|Y||XVII||1||Yuan,D.D. et al. (2008) Peptides 29:1521-1525|
Phylogenetic analyses have classified cone snails into different groups, or clades, according to the homology of their 16S RNA sequence . One clade, named "Early", is highly divergent from the others. In a recent study , a number of conopeptide precusors have been sequenced from Conus californicus, a member of the Early clade, and those conopeptides do not correspond to any previously identified superfamilies. Table 2 provides the 'temporary names' that have been introduced in ConoServer to designate those superfamilies. The clustering analysis shown in Figure 2 clearly demonstrates that those new superfamilies are distinct. The names of those superfamilies are only temporary and are likely to be changed in the future when a definitive nomenclature will be published in a peer-reviewed journal.
|Gene superfamily||Cysteine frameworks||# protein precursors|
|Divergent M---L-LTVA||VI/VII, IX, XIV||9|
|Divergent MRFYIGLMAA||I, V||3|
|Divergent MSTLGMTLL-||IX, XIX, XXII||6|
|||Kaas,Q. et al. (2010) Toxicon 55:1491-1509|
|||Woodward,S.R. et al. (1990) EMBO J. 9:1015-1020|
|||Puillandre,N. et al. (2012) J. Mol. Evol. 74:297-309|
|||Espiritu,D.J. et al. (2001) Toxicon 39:1899-1916|
|||Biggs,J.S. et al. (2010) Mol. Phylogenet. Evol. 56:1-12|
ConoServer is managed at the Institute of Molecular Bioscience IMB, Brisbane, Australia.
The database and computational tools found on this website may be used for academic research only, provided that it is referred to ConoServer, the database of conotoxins (http://www.conoserver.org) and the above reference is cited. For any other use please contact David Craik (email@example.com).
Last updated: Sunday 23 October 2016