3.7 Potential
Bioactive Peptides
1. Analyze all the potential peptides using previous databases that
included known bioactive peptides, such as CAMP (http://
www.bicnirrh.res.in/antimicrobial/) for antimicrobial peptides applying the DAC score (Discriminate Analysis Classifier
score) and the BIOPEP-UWM (http://www.uwm.edu.pl/
biochemia/index.php/pl/biopep/) and BioPD (http://
biopd.bjmu.edu.cn/) databases (see Note 5).
Using this workflow, bioactive collagen peptides, antihypertensive, antimicrobial, and antitumor peptides were predicted as potential valuable bioactive peptides from seafood
and marine by-products [11, 15] (see Note 6).
4 Notes
1. Different food samples and different lysis buffer need to be
optimized.
2. DTT (DL-dithiothreitol) is used to stabilize proteins, to reduce
disulfide bonds and to maintain monothiols in a reduced state.
This can be substituted by TCEP (Tris(2-carboxyethyl)
phosphine hydrochloride). IAA (iodoacetamide) is a
sulfhydryl-reactive alkylating reagent used to bind covalently
with the thiol group of cysteines in order to avoid disulfide
bond formation for protein characterization and peptide
mapping.
3. Different LC–MS instruments from different commercial
brands may require specific parameters for peptide ionization
and fragmentation.
4. In silico proteolytic digestion can be performed using different
online programs such as MS-Digest (http://prospector.ucsf.
edu/prospector/cgi-bin/msform.cgi?form¼msdigest)
and
PeptideCutter
(https://web.expasy.org/peptide_cutter/
) [35].
5. Different bioactive peptide databases can be evaluated such as
APD3 [24], ACEpepDB [25], BIOPEP-UWM [26], BioPD
[27], BioPepDB [28], CAMP [29], FeptideDB [30], PPIP
[31], SpirPep [13], StraPep [32], and starPepDB [33].
6. All these potential bioactive peptides need to be validated by
further bioassays and using synthetic versions of the peptides.
However, compared with the classical approaches, the computational methods are faster and lower-cost alternatives that
predict and reduce the number of potential targets to be investigated. In addition, bioinformatics-driven tools provide useful
insights not achievable in human or animal model studies.
Shotgun Proteomics and Protein-ased Bioinformatics. . .
221
Bioactive Peptides
1. Analyze all the potential peptides using previous databases that
included known bioactive peptides, such as CAMP (http://
www.bicnirrh.res.in/antimicrobial/) for antimicrobial peptides applying the DAC score (Discriminate Analysis Classifier
score) and the BIOPEP-UWM (http://www.uwm.edu.pl/
biochemia/index.php/pl/biopep/) and BioPD (http://
biopd.bjmu.edu.cn/) databases (see Note 5).
Using this workflow, bioactive collagen peptides, antihypertensive, antimicrobial, and antitumor peptides were predicted as potential valuable bioactive peptides from seafood
and marine by-products [11, 15] (see Note 6).
4 Notes
1. Different food samples and different lysis buffer need to be
optimized.
2. DTT (DL-dithiothreitol) is used to stabilize proteins, to reduce
disulfide bonds and to maintain monothiols in a reduced state.
This can be substituted by TCEP (Tris(2-carboxyethyl)
phosphine hydrochloride). IAA (iodoacetamide) is a
sulfhydryl-reactive alkylating reagent used to bind covalently
with the thiol group of cysteines in order to avoid disulfide
bond formation for protein characterization and peptide
mapping.
3. Different LC–MS instruments from different commercial
brands may require specific parameters for peptide ionization
and fragmentation.
4. In silico proteolytic digestion can be performed using different
online programs such as MS-Digest (http://prospector.ucsf.
edu/prospector/cgi-bin/msform.cgi?form¼msdigest)
and
PeptideCutter
(https://web.expasy.org/peptide_cutter/
) [35].
5. Different bioactive peptide databases can be evaluated such as
APD3 [24], ACEpepDB [25], BIOPEP-UWM [26], BioPD
[27], BioPepDB [28], CAMP [29], FeptideDB [30], PPIP
[31], SpirPep [13], StraPep [32], and starPepDB [33].
6. All these potential bioactive peptides need to be validated by
further bioassays and using synthetic versions of the peptides.
However, compared with the classical approaches, the computational methods are faster and lower-cost alternatives that
predict and reduce the number of potential targets to be investigated. In addition, bioinformatics-driven tools provide useful
insights not achievable in human or animal model studies.
Shotgun Proteomics and Protein-ased Bioinformatics. . .
221