Bioactive Peptides in Octopus Skin Mucus

For the study of bioactive peptides encoded in the common octopus skin mucus proteome, the MS-Digest software (https://prospector.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msdigest, accessed on 23 May 2024), which is included in the ProteinProspector v.6.5.0 website, was used (https://prospector.ucsf.edu/prospector/mshome.htm, accessed on 23 May 2024). In-silico protein hydrolysates using pepsin and trypsin enzymes were analyzed and all peptides were ranked using the PeptideRanker software (https://prospector.ucsf.edu/prospector/mshome.htm, accessed on 23 May 2024) using the N-to-1 neural network probability to predict the potential bioactivity of peptides [31 (link)]. Selected peptides with a score of >0.9 in PeptideRanker were compared with the BIOPEP-UWM database (http://www.uwm.edu.pl/biochemia/index.php/pl/biopep/, accessed on 25 May 2024) [58 (link)] and CAMP database (http://www.bicnirrh.res.in/antimicrobial/, accessed on 25 April 2024) [59 (link)] applying the DAC score (Discriminate Analysis Classifier score) to predict all potential bioactive peptides.

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Pérez-Polo S., Mena A.R., Barros L., Borrajo P., Pazos M., Carrera M, & Gestal C. (2024). Decoding Octopus Skin Mucus: Impact of Aquarium-Maintenance and Senescence on the Proteome Profile of the Common Octopus (Octopus vulgaris). International Journal of Molecular Sciences, 25(18), 9953.

Publication 2024

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Variable analysis

independent variables

Use of pepsin and trypsin enzymes for in-silico protein hydrolysis

dependent variables

Ranking of peptides using PeptideRanker software
Comparison of selected peptides with BIOPEP-UWM and CAMP databases to predict potential bioactivity

control variables

Use of the MS-Digest software from the ProteinProspector v.6.5.0 website
Use of the N-to-1 neural network probability in PeptideRanker to predict potential bioactivity of peptides
Use of the DAC score (Discriminate Analysis Classifier score) to predict potential bioactive peptides

positive controls

None specified

negative controls

None specified

Annotations

Based on most similar protocols

Use MS-Digest software included in ProteinProspector v.6.5.0 website to perform in-silico protein hydrolysis with pepsin and trypsin enzymes (Input protocol, Protocol 1, Protocol 2).

Rank all potential peptides using PeptideRanker software with N-to-1 neural network probability to predict their potential bioactivity (Input protocol, Protocol 1, Protocol 2).

Compare selected peptides (score >0.9 in PeptideRanker) with BIOPEP-UWM and CAMP databases to predict potential bioactive peptides (Input protocol).

For jumbo squid skin proteome, use ProteinProspector v.5.24.0 website to perform in-silico protein hydrolysis (Protocol 1).

For O. vulgaris ink proteins, use ProteinProspector v.6.4.0 website to perform in-silico protein hydrolysis (Protocol 2).

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