ConoServer: updated content, knowledge, and discovery tools in the conopeptide database

Abstract

ConoServer (http://www.conoserver.org) is a database specializing in the sequences and structures of conopeptides, which are toxins expressed by marine cone snails. Cone snails are carnivorous gastropods, which hunt their prey using a cocktail of toxins that potently subvert nervous system function. The ability of these toxins to specifically target receptors, channels and transporters of the nervous system has attracted considerable interest for their use in physiological research and as drug leads. Since the founding publication on ConoServer in 2008, the number of entries in the database has nearly doubled, the interface has been redesigned and new annotations have been added, including a more detailed description of cone snail species, biological activity measurements and information regarding the identification of each sequence. Automatically updated statistics on classification schemes, three-dimensional structures, conopeptide-bearing species and endoplasmic reticulum signal sequence conservation trends, provide a convenient overview of current knowledge on conopeptides. Transcriptomics and proteomics have began generating massive numbers of new conopeptide sequences, and two dedicated tools have been recently implemented in ConoServer to standardize the analysis of conopeptide precursor sequences and to help in the identification by mass spectrometry of toxins whose sequences were predicted at the nucleic acid level.

Optimized deep-targeted proteotranscriptomic profiling reveals unexplored Conus toxin diversity and novel cysteine frameworks

“…As described in Table 1, 37 conotoxin cysteine patterns have been reported to date (8 of which have known disulfide bond connectivity) (15). Although cysteine bridges always improve toxin stability and provide resistance to enzymatic degradation, some cysteine frameworks combined to particular loop lengths are more pharmacologically relevant.…”

“…As a result of speciation, a high rate of hypermutations, and a remarkable number of posttranslational modifications, little overlap of conopeptides between Conus species has been observed (11,12), which has led to an estimation of >70,000 pharmacologically active conopeptides although fewer than 1% have been characterized to date (13). The precursor form of conotoxins is composed of three distinct regions: a highly conserved N-terminal endoplasmic reticulum (ER) signal region (used to classify the toxins into gene superfamilies), a central proregion, and a hypervariable mature region, typically between 10 and 35 amino acids long, characterized by conserved cysteine patterns and connectivities (14)(15)(16). Mature conotoxins are able to selectively modulate specific subtypes of voltage-or ligand-gated transporters, receptors, and ion channels, expressed in organisms…”

An efficient transcriptome analysis pipeline to accelerate venom peptide discovery and characterisation

“…Extracted sequences are then searched against a training dataset comprised of sequences from the Conoserver (Kaas et al, 2008;Kaas et al, 2011) database using Regular Expressions first to sort the sequences. ConoSorter also calculates class and superfamily scores ranging from 0-3 based on the similarity of the predicted signal-, pro-and mature regions of the sequences to known toxin classes and superfamilies with a score of 3 indicating matches for each region and 0 indicating no matches.…”

“…only sequences representing clusters with n>1 are considered for further analysis. The signal, pro-and mature regions of the sequences are then generated using ConoPrec available on the conoserver (Kaas et al, 2011) and sequences with cysteine frameworks typical of a particular superfamily, and signal sequences that are more than 53.3% similar to it are designated as new members of the superfamily. Those sequences with less than 53.3% similarity despite displaying the archetypal conotoxin architecture are designated as M A N U S C R I P T…”

“…Sequences without readily identified known conotoxin characteristics were discarded to reduce false positives although they may represent highly divergent toxin families. All sequences are finally verified manually using the ConoPrec program (Kaas et al, 2011).…”