Venomics-Accelerated Cone Snail Venom Peptide Discovery
AbstractCone snail venoms are considered a treasure trove of bioactive peptides. Despite over 800 species of cone snails being known, each producing over 1000 venom peptides, only about 150 unique venom peptides are structurally and functionally characterized. To overcome the limitations of the traditional low-throughput bio-discovery approaches, multi-omics systems approaches have been introduced to accelerate venom peptide discovery and characterisation. This “venomic” approach is starting to unravel the full complexity of cone snail venoms and to provide new insights into their biology and evolution. The main challenge for venomics is the effective integration of transcriptomics, proteomics, and pharmacological data and the efficient analysis of big datasets. Novel database search tools and visualisation techniques are now being introduced that facilitate data exploration, with ongoing advances in related omics fields being expected to further enhance venomics studies. Despite these challenges and future opportunities, cone snail venomics has already exponentially expanded the number of novel venom peptide sequences identified from the species investigated, although most novel conotoxins remain to be pharmacologically characterised. Therefore, efficient high-throughput peptide production systems and/or banks of miniaturized discovery assays are required to overcome this bottleneck and thus enhance cone snail venom bioprospecting and accelerate the identification of novel drug leads. View Full-Text
Share & Cite This Article
Himaya, S.W.A.; Lewis, R.J. Venomics-Accelerated Cone Snail Venom Peptide Discovery. Int. J. Mol. Sci. 2018, 19, 788.
Himaya SWA, Lewis RJ. Venomics-Accelerated Cone Snail Venom Peptide Discovery. International Journal of Molecular Sciences. 2018; 19(3):788.Chicago/Turabian Style
Himaya, S. W.A.; Lewis, Richard J. 2018. "Venomics-Accelerated Cone Snail Venom Peptide Discovery." Int. J. Mol. Sci. 19, no. 3: 788.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.