Consider including conopeptide prediction in the pipeline

[taylorreiter]

Description of feature

This paper has a section on RiPPs in animals. The only thing included was conopeptides:

Marine snails, such as cone snails, are known to produce a variety of ribosomally synthesized and post-translationally modified peptide venoms. Those venomes are produced by predatory cone snails, injected into the prey, and lead to paralysis. The best characterized marine snail peptides are conopeptides, also known as conotoxins. It was estimated that more than 500 species of predatory marine Conus snails are capable of producing conotoxins [51,52]. Those Conus species can produce as many as 70,000 structurally diverse conotoxins [53,54]. Many conotoxins act by targeting ion channels, thus have been widely used as basic research tools in neuroscience. A number of conotoxins showed therapeutic potential due to their unparalleled potency and selectivity against a wide range of receptors and ion channels [55]. For example, Ziconotide, a calcium channel agonist isolated from Conus magus, was approved by the United States Food and Drug Administration (US FDA) in 2004 for the treatment of chronic pain. A detailed review of conopeptides discovery and biosynthesis was made in 2013, and more structures of conopeptides have been characterized since then [1,56,57,58].

The precursor peptide sequences of conotoxins were studied by analyzing the transcriptomes of cone snails. Those studies revealed that conotoxin precursor transcript sequences consist of three regions: An ER signal peptide, a mature peptide region, and pre-/postpropeptide regions [59,60]. The ER signal peptide sequence is highly conserved, whereas the mature peptide region is highly diverse [60]. Types of conotoxin post-translational modifications include disulfide-bond formation, proline hydroxylation, O-glycosylation on serine or threonine residues, and glutamate γ-carboxylation [61,62]. A web-based ConoServer database (conoserver.org) was established to record known structures of conopeptides, classifications, post-translational modifications, and their general statistics. Due to that conopeptide biosynthetic genes are not organized in clusters, biosynthetic studies of animal RiPPs are extremely challenging. The details of conotoxin biosynthetic pathways and the mechanism and molecular basis for their post-translational modifications still remain largely unexplored [55].

It could be interesting to include conopeptide prediction in this pipeline.

Some tools that could accomplish this:

• conodictor: https://github.com/koualab/conodictor; https://pypi.org/project/conodictor/; https://academic.oup.com/bioinformaticsadvances/article/1/1/vbab011/6323232

[taylorreiter]

update: I tried conodictor and encountered this issue https://github.com/koualab/conodictor/issues/18

[taylorreiter]

With an update to conodictor, I was able to get it to run. However, reading the paper, the authors suggest that it is written to be very sensitive and specific to conopeptides, and not peptides from other venomous species. Given this, I think this tools is not worth including in the pipeline.

(it was also fairly buggy which would make it difficult to support)

[taylorreiter]

After discussing with Adair, we both agree it doesn't make sense to include this tool at this time.