Link to eLAB journal Karin and Ydwine: 20200131_AJ_Peptide selection ORF1 and ORF2 - https://elabjournal.rug.nl/members/experiments/browser/#view=experiment&nodeID=218610
Assay design targeted proteomics for ORF2p and ORF1p - Selection of the suitable quantotypic peptides
The general workflow for the assay development has been described step-by-step in the following bookchapter, illustrated with examples of the assays developed for a set of mitochondrial targets See: Wolters JC, Permentier HP, Bakker BM, Bischoff R. (2019) Targeted Proteomics to Study Mitochondrial Biology. Adv Exp Med Biol. 2019;1158:101-117. doi: 10.1007/978-981-13-8367-0_7. (PMID: 31452138)
The main steps are
1. Selection of peptides to detect the target proteins
2. Develop and validate the targeted proteomics assay
3. Application of the assay for bio(medical) research questions
The selection of the peptides was done taking the following levels of information into account
1.1 Uniqueness
- checked if peptide is not present in other proteins in the human proteome (Human SwissProt database)
1.2 Detectability for LC-MS applications
- length between 8-25 AA preferably
- checked with bio-informatics tool ConSequence for prediction (SVM and ANN-> the closer the score is to 1 to more likely the peptide can be detected in LC-MS. The binary count is in how many of the four datasets the peptide was previously observed).
- additionally a column is added to see if the peptide is present in the NIST library and if is was detected in the measurements done by Johns’ group previously (annotated as NY)
1.3 Risk for modifications
- excluding N and C-terminal peptides
- checked for the presence of methionines, NG sites and in a lesser extend for cysteines (as cysteines can be dealt with reduction and alkylation). Other modifications like phosphorylations etc were checked manually on the UniProt entry after selection of the optimal peptides based on the other described properties
1.4 Risk for missed cleavages
- checked with bio-informatics too MCPred (scores closer to 1 is more likely to suffer from missed cleavages
- also visualized in the presence of double tryptic sides and presence of acidic amino acids near the cleavage site).
All information is gathered in the supplemented excelsheet and further details for the selection criteria can be found in the book chapter For ORF2p also genetic variation was taken into account. A list of 75 versions of the proteins was provided by John and peptides from the UniProt sequence had to be present in at least 65 of the 75 versions in order to be taken into account. To provide maximal opportunity both optimal and sub-optimal peptides were taken into account in the initial screening with cheap synthetic peptides
For ORF1p this yielded the following 4 peptides with predicted optimal properties
L1ORF1p_QANVQIQEIQR
L1ORF1p_LENTLQDIIQENFPNLAR
L1ORF1p_LSFISEGEIK
L1ORF1p_NLEECITR
For ORF2p this yielded the following 11 peptides with predicted optimal (6) and sub-optimal (5) properties
Optimal peptides
ORF2p_GSIQQEELTILNIYAPNTGAPR, 71/75 versions
ORF2p_QGCPLSPLLFNIVLEVLAR, 69/75 versions
ORF2p_STEYTFFSAPHHTYSK, 71/75 versions
ORF2p_TLEENLGITIQDIGVGK, 68/75 versions
ORF2p_TAWYWYQNR, 70/75 versions
ORF2p_DTTYQNLWDAFK, 67/75 versions
Suboptimal peptides
ORF2p_IFATYSSDK, 73/75 versions
ORF2p_EGILPNSFYEASIILIPKPGR, 65/75 versions
ORF2p_QVLSDLQR, 71/75 versions
ORF2p_QEQTHSK, 75/75 versions
ORF2p_GDITTDPTEIQTTIR, 71/75 versions
The 15 peptides were ordered as Pepotec (heavy) peptides, which will be used for assay development and to establish which peptides are optimal for accurate quantification.