In this section, we introduce GraBCas, a tool written in Java to predict granzyme B and caspase cleavage sites. Caspases are enzymes orchestrating the cellular pathways that lead to apoptosis and inflammatory signals. Besides these functions they are supposed to
be involved in other cellular processes, such as development, cell cycle, cell proliferation, cell migration and receptor internalization [83, 84]. Caspases are cysteine proteases with specificity for an aspartic acid residue at positionP1 of the substrate. This primary speci- ficity is shared by the serine protease granzyme B, which induces cytotoxic T lymphocyte- mediated target cell DNA fragmentation and apoptosis [85, 86]. Granzyme B-mediated cleavage also plays a role in the induction of autoimmunity [87].
A more comprehensive knowledge of caspase and granzyme B substrates is essential to understand the biological roles of these enzymes in more detail. The relatively high variability in their recognition sequence often complicates the identification of cleavage sites. At the time of publication in 2005, GraBCas was the first tool that allowed identifi- cation of caspase and/or granzyme cleavage sites differing from the consensus sequence. Other available tools at that time were the PeptidCutter program provided by the ExPasy Server8 that considers only the preferred peptide substrate sites and ’PEPS’, a tool of Lohm ¨uller et al. [88], that is restricted to caspase 3 and cathepsin B and -L substrates. In the meantime, more recent applications make use of SVMs to predict the cleavage sites of caspases [89, 90] or combine sequence and structure information to predict substrates of endoproteases [91]. In the work of Wee and coworkers [92], GraBCas has been integrated to reduce efficiently the number of false positives when predicting caspase cleavage sites. In the following, we briefly summarize the score-based prediction of potential cleavage sites integrated in GraBCas for the caspases 1-9 and granzyme B as presented in our NAR Web Server Issue publication [43].
2.3.1 Design of cleavage site scoring matrices
We developed position specific scoring matrices (PSSMs) for the endopeptidases granzyme B and caspase 1-9 based on experimentally determined substrate specificities for the cleavage site positionsP4,P3, andP2 of these proteases [93]. Thornbery et al. [93] deter- mined the substrate specificities using positional scanning synthetic combinatorial libraries. Cleavage was fluorimetrically determined with maximum value annotated with 100 for the best cleavage site and the values for the remaining cleavage sites given as percentage of the observed maximum rate. These experimental values provided the basis for creating our PSSMs.
The values for each amino acid at positionPi are shown in Table D.1 in Appendix D. For
8
a better readability we decided to set the maximum values to 1000 instead of 100 and adjusted the other values accordingly. For each endopeptidase the scores of the amino acids were entered in a 3 x 20 matrix. The rows of such a matrix correspond to positions
P4, P3 or P2 of a possible cleavage site. Each column represents one amino acid and contains the relative frequencies of the amino acid measured in the study of Thornbery et al. [93]. We are working with PSSM that can be interpreted as probability matrices. Since probabilities of value 0 should be avoided in such probability-based position scores, all entries of experimental relative frequencies with value 0 were set to 1. The amino acids cysteine and methionine were not part of the study of Thornbery et al. [93]. The entries for these amino acids were also set to 1 in Table D.1.
2.3.2 Computing the scores of endopeptidase cleavage sites
For computing the score, the GraBCas program screens for tetrapeptides with Asp (D) at their last position (P1) in a given amino acid sequence. Given the tetrapeptideA4A3A2D (≈ P4P3P2P1) of a potential cleavage site, its score for a given endopeptidase is computed by the formula in Equation 2.5. The corresponding matrix entries ofA2 at positionP2,A3 at positionP3, and A4 at positionP4 are multiplied. The product is divided by the value of the product of the consensus recognition motif for normalization and multiplied by 100, yielding a total score between 0 and 100.
Score(A4A3A2D) = 100 ·
ScoreP4(A4) · ScoreP3(A3) · ScoreP2(A2)
10003 (2.5)
2.3.3 Sensitivity-specificity plot for granzyme B
For determining the specificity and sensitivity of the GraBCas predictions and an optimal cutoff for the PSSM scores, we used the known cleavage sites of granzyme B [86, 87, 93– 97] and the known non-substrates of granzyme B [87]. The x-axis of the plot in Figure 2.14 represents the cutoff values (with respect to the PSSM scores), while the y-axis rep- resents the percentage of the specificity or sensitivity of the predictions made by GraBCas, respectively.
The specificity is computed as follows:
Specificity= Number of true negatives
0,00 0,10 0,20 0,30 0,40 0,50 0,60 0,70 0,80 0,90 1,00 scores Sensitivity Specificity Sensitivity 1,00 0,80 0,80 0,80 0,80 0,80 0,80 0,80 0,80 0,77 0,73 0,70 0,63 0,60 0,57 0,53 0,50 0,47 0,43 0,37 0,33 0,30 0,27 0,17 0,13 Specificity 0,00 0,12 0,18 0,53 0,71 0,76 0,76 0,82 0,82 0,88 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 0,94 1,00 0,0 0,1 0,2 0,3 0,5 0,8 1,0 1,2 1,4 1,5 1,6 2,5 2,7 3,2 4,2 4,8 5,4 7,5 8,0 9,9 11,5 17,2 18,6 23,9 28,8
Figure 2.14: Sensitivity-specificity plot for granzyme B cleavage sites according to GraBCas. x- axis: scores by the GraBCas program; y-axis: percentage of specificity or sensitivity.
The true negatives are the known non-substrates, where the maximal PSSM score of all tetrapeptides ending with a D is smaller than the chosen cutoff value. Analogously, the false positives correspond to the non-substrates that are falsely classified as substrates given the chosen cutoff value. A specificity of 1 means that all known non-substrates were below the cutoff, i.e. all known non-substrates were correctly classified as negatives. The sensitivity is defined as:
Sensitivity= Number of true positives
Number of true positives+Number of false negatives
where true positives are the known cleavage sites with a score larger than the chosen cutoff value. Analogously, the false negatives correspond to the substrates that are falsely classified as non-substrates given the chosen cutoff value. A sensitivity of 1 means that all cleavage sites of our test set have a score higher than the chosen cutoff and that they have been correctly classified as positives.
In total, we collected 29 substrates with 30 cleavage sites for granzyme B and additionally 17 sequences which are non-substrates of this endopeptidase. We computed the scores of all putative cleavage sites in these sequences and extracted the best hit by GraBCas
for each of these (non-)substrates. The sensitivity-specificity plot for granzyme B in Figure 2.14 shows that we obtain a sensitivity of 80% and a specificity of 82% when using a cutoff value of 1.2 in the GraBCas program. The cutoff value can be adjusted if a higher specificity or sensitivity is needed for the cleavage site prediction.
Given these findings for granzyme B, we integrated the GraBCas prediction for granzyme B in GeneTrail using a cutoff of 1.2.