GraBCas: a bioinformatics tool for score-based prediction of Caspase- and Granzyme B-cleavage sites in protein sequences

Abstract

Caspases and granzyme B are proteases that share the primary specificity to cleave at the carboxyl terminal of aspartate residues in their substrates. Both, caspases and granzyme B are enzymes that are involved in fundamental cellular processes and play a central role in apoptotic cell death. Although various targets are described, many substrates still await identification and many cleavage sites of known substrates are not identified or experimentally verified. 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 cleavage site recognition sequence often complicates the identification of cleavage sites. As of yet there is no software available that allows identification of caspase and/or granzyme with cleavage sites differing from the consensus sequence. Here, we present a bioinformatics tool ‘GraBCas’ that provides score-based prediction of potential cleavage sites for the caspases 1–9 and granzyme B including an estimation of the fragment size. We tested GraBCas on already known substrates and showed its usefulness for protein sequence analysis. GraBCas is available at http://wwwalt.med-rz.uniklinik-saarland.de/med_fak/humangenetik/software/index.html.

INTRODUCTION

Caspases are enzymes orchestrating the cellular pathways leading 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 (1,2). Caspases are cysteine proteases with specificity for an aspartic acid residue at position P1 of the substrate. This primary specificity is shared by the serine protease granzyme B, which induces cytotoxic T lymphocyte-mediated target cell DNA fragmentation and apoptosis (3,4). Granzyme B-mediated cleavage also plays a role in induction of autoimmunity (5).

To date, at least 14 mammalian caspases can be grouped into three classes based on their substrate specificities. Group I consisting of caspases -1, -4, -5 (-14 and murine -11 and -12) cleaves the substrate sequence (W/L)EHD, group II (caspases -2, -3, -7) cleaves the DEXD motif and group III (caspase -6, -8, -9, -10) preferentially cleaves the (L/V)E(T/H)D sequence (6,7). Caspases of group I play an important role in the generation of inflammatory signals and in the immune regulation. Caspases -8, -9 and -10 are so-called initiator caspases mainly cleaving and activating procaspases, whereas caspases -3, -6 and -7 as effector caspases cleave numerous cellular proteins. The serine protease granzyme B prefers substrates with sequence IEXD, and is released by cytotoxic lymphocytes to kill virus-infected or tumor cells.

Although more than 280 caspase targets are described [for comprehensive review see (8)] many substrates still await identification and many cleavage sites of known substrates are not identified or experimentally verified. Likewise, the identification of granzyme B substrates is still at its infancy. Intracellular substrates of granzyme B include other caspases, mainly caspase 3 (9), ADPRT (ADP-ribosyltransferase 1, PARP) (10), BID (BH3 interacting domain death agonist) (11) and ICAD (DNA fragmentation factor) (12). Notably, the majority of autoantigens in systemic autoimmune diseases are efficiently cleaved by granzyme B (5).

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 cleavage site recognition sequence often complicates the identification of cleavage sites. As of yet there is no software available that allows identification of caspase and/or granzyme cleavage sites differing from the consensus sequence. The PeptidCutter program provided by the ExPasy Server (http://www.expasy.org/tools/peptidecutter) considers only the preferred peptide substrate sites. A recent tool of Lohmüller et al. (13) is restricted to caspase 3 and cathepsin B and -L substrates. Here, we present a bioinformatics tool GraBCas that provides score-based prediction of potential cleavage sites for the caspases 1–9 and granzyme B including an estimation of the fragment size. We validated our tool by scoring known substrates and demonstrated its usefulness for protein sequence analysis.

MATERIALS AND METHODS

Design of cleavage site scoring matrices

We developed position specific scoring matrices (PSSM) for the endopeptidases granzyme B and caspase 1–9 based on experimentally determined substrate specificities (6). Thornbery et al. (6) determined the substrate specificities using positional scanning synthetic combinatorial libraries. Cleavage was fluorimetrically determined with maximum value annotated with 100 and the values for the remaining amino acids given as percentage of the observed maximum rate. These experimental values provided the basis for creating our PSSM.

The values for each amino acid at position Pi are shown in Table 1. For 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 × 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. (6). 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. (6). The entries for these amino acids were also set to 1 in Table 1.

Table 1.

Scoring matrices for granzyme B and caspases 1–9

	Position Pi	AA of consensus recognition motif	C	S	T	P	A	G	N	D	E	Q	H	R	K	M	I	L	V	F	Y	W
Granzyme B	4	I	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1000	52	500	12	1	1
	3	E	1	297	54	1	153	477	1	198	1000	81	9	1	1	1	1	1	1	1	1	9
	2	P	1	752	544	1000	576	16	624	144	288	576	544	1	1	1	16	96	304	144	16	16
Caspase 1	4	W	1	48	48	48	48	16	16	80	96	16	128	1	1	1	96	288	80	496	576	1000
	3	E	1	357	442	1	442	425	119	374	1000	646	187	51	34	1	221	323	442	272	187	85
	2	H	1	144	396	144	180	18	72	36	72	108	1000	54	72	1	198	54	108	126	144	126
Caspase 2	4	D	1	1	50	10	1	1	10	1000	200	1	1	1	1	1	180	400	80	40	40	1
	3	E	1	425	884	1	680	119	119	102	1000	680	153	408	221	1	119	187	646	255	187	153
	2	H	1	624	528	352	336	48	96	1	1	16	1000	320	304	1	144	16	80	16	16	80
Caspase 3	4	D	1	40	50	1	10	1	20	1000	40	1	10	1	1	1	10	1	20	10	1	1
	3	E	1	306	357	1	357	85	153	255	1000	408	187	17	17	1	153	153	306	272	255	119
	2	V	1	14	378	406	182	1	14	1	0	14	196	42	0	1	714	224	1000	182	154	84
Caspase 4	4	W	1	80	208	144	96	48	80	288	256	96	48	1	1	1	304	848	224	384	352	1000
	3	E	1	187	119	34	119	17	85	221	1000	306	85	1	17	1	51	85	204	187	85	17
	2	H	1	102	119	119	425	17	102	221	357	153	1000	51	1	1	595	17	119	85	102	51
Caspase 5	4	W	1	14	56	1	56	126	42	98	98	84	56	1	1	1	280	1000	154	504	406	1000
	3	E	1	24	12	1	12	1	1	124	1000	12	12	1	1	1	12	12	12	12	12	1
	2	H	1	340	425	323	323	1	85	119	323	85	1000	17	34	1	272	17	272	153	204	102
Caspase 6	4	V	1	144	880	64	96	16	64	224	256	48	48	1	1	1	656	304	1000	80	48	48
	3	E	1	48	48	16	80	16	16	176	1000	144	48	1	1	1	16	16	48	48	16	48
	2	H	1	54	576	18	72	18	108	18	18	36	1000	54	36	1	648	486	918	288	216	558
Caspase 7	4	D	1	117	78	1	39	26	26	1000	104	26	39	1	1	1	13	1	13	13	13	1
	3	E	1	221	357	1	323	51	153	255	1000	425	187	85	102	1	306	221	697	204	204	102
	2	V	1	16	448	448	128	16	48	1	1	16	208	80	16	1	704	176	1000	160	128	48
Caspase 8	4	L	1	208	304	480	448	96	304	704	448	96	144	1	1	1	576	1000	720	224	256	144
	3	E	1	45	75	0	45	15	15	180	1000	150	45	1	1	1	45	15	105	45	45	15
	2	T	1	180	1000	216	324	18	126	72	198	108	306	72	72	1	720	108	792	180	198	306
Caspase 9	4	L	1	198	216	594	576	144	108	414	468	180	126	36	18	1	576	1000	684	252	216	144
	3	E	1	85	136	51	85	17	17	272	1000	187	119	1	17	1	102	119	204	102	85	51
	2	H	1	85	136	102	85	17	17	51	34	17	1000	34	1	1	187	17	153	51	34	51

Amino acid preference distribution for each position Pi was extracted from Thornberry et al. (6) giving the most common amino acid a value of 1000.

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 tetrapeptide A4A3A2D (≈P4P3P2P1) of a potential cleavage site, its score for a given endopeptidase is computed by multiplying the corresponding matrix entries of A2 at position P2, A3 at position P3 and A4 at position P4. The product is divided by the value (1000³) of the product of the consensus recognition motif for normalization and multiplied by 100, yielding a total score between 0 and 100.

$$\begin{array}{c}\text{Score}\left(\text{A}4\text{A}3\text{A}2\text{D}\right)\\ =100\times \frac{{\text{Score}}_{\text{P4}}\left(\text{A4}\right)\times {\text{Score}}_{\text{P3}}\left(\text{A3}\right)\times {\text{Score}}_{\text{P2}}\left(\text{A2}\right)}{{1000}^3}.\end{array}$$

Using additional filter options for granzyme B and caspase 3

To improve the power of the prediction we analyzed the amino acid distribution of known granzyme B and caspase 3 cleavage sites at positions P6–P2′ taken from the literature (see also Supplementary Material 1 and 2).

For granzyme B we found a preference for V (15×) and I (11×) at position P4, for E (9×) at position P3 and for P (11×) at position P2 in accordance with the results of Thornberry et al. (6). We detected S at position P1′ and G at position P2′, respectively in 9 out of 30 cleavage sites. The result list of the PSSM-based cleavage sites can optionally be filtered with two ‘stringency’ filters that take the occurrence of amino acids at position P2′ into account. We installed a ‘low stringency’ filter that excludes hits with the amino acids C, Q, I, M, V all of which are medium sized or large amino acids. A second ‘high stringency’ filter selects hits with a G at position P2′.

The analysis of the 59 cleavage sites of caspase 3 substrate confirmed the preferences for D at P4 (31×), E at P3 (17×) and V at P2 (16×). For P1′ we found an abundance of G (18×) and S (17×) and in lower amount A (5×) and N (4×). As for the granzyme B prediction, two additional ‘stringency’ filters for the prediction of caspase 3 cleavage sites are available. The ‘high stringency’ filter screens the predicted hits for occurrences of G, S, A or N at position P1′, and the ‘low stringency’ filter screens for absence of R, E, H, K, Q, I, L, M, F, W and Y at this position.

GraBCas software tool

The GraBCas program was written in Java™ and is available as an application or as an applet. Both are available at http://wwwalt.med-rz.uniklinik-saarland.de/med_fak/humangenetik/software/index.html. If your browser does not support Java™ you need to install the Java Runtime Environment (JRE) 1.4.x, which can be downloaded at http://java.sun.com.

The graphical user interface is easy to use. There are several register cards for each endopeptidase and one register card presenting the input form, where the amino acid sequence can be pasted and a cutoff for the PSSM scores can be chosen. After pressing the OK-button in the input form, the program calculates the scores of potential cleavage sites for all endopeptidases and presents them in the corresponding register card sorted with the highest scoring sites on top. The user can open an additional window for viewing the positions of the predicted cleavage sites within the amino acid sequence. The window also shows the fragment length and size in kDa (0.11 kDa per amino acid) of the predicted fragments.

As described above, for caspase 3 and granzyme B additional filter options are available in their register cards. The two filter types for these enzymes, a ‘high-stringency’ and a ‘low-stringency’ filter, are based on the extended substrate specificity. For granzyme B the amino acids at position P2′ were taken into account in addition to the positions P4–P1. For caspase 3, amino acids at position P1′ are evaluated.

Sensitivity–specificity plots

For determining the specificity and sensitivity of the GraBCas predictions we used the known cleavage sites of granzyme B (4–6,9–12) summarized in Table 2 and the known non-substrates of granzyme B (5) presented in Table 4. Due to the lack of information on known non-substrates for caspase 3 the sensitivity–specificity plot could only be calculated for granzyme B (Figure 1).

Table 2.

Analysis of cleavage sites of known granzyme B substrates with GraBCas

Granzyme B substrate	Acc_number	Known cleavage site	Score by GraBCas	P6–P2′ of cleavage site
AARS: alanyl-tRNA synthetase	NP_001596	VADP (632)	7,65	SLVAPDRL
ADPRT: ADP-ribosyltransferase (NAD+; poly (ADP-ribose) polymerase)	NP_001609	VDPD (536)	9,9	AAVDPDSG
BID: BH3 interacting domain death agonist	NP_001187	IEAD (75)	57,6	GRIEADSE
CASP3: caspase 3, apoptosis-related cysteine protease	NP_004337	IETD (175)	54,4	CGIETDSG
CASP7: caspase 7, apoptosis-related cysteine protease	NP_001218	IQAD (198)	4,6656	DGIQADSG
CENPB: centromere protein B, 80 kDa	NP_001801	VDSD (457)	7,4448	GDVDSDEE
CHD4: chromodomain helicase DNA binding protein 4	NP_001264	VDPD (1312)	9,9	ESVDPDYW
DFFA: DNA fragmentation factor, 45 kDa, alpha polypeptide	NP_004392	DETD (117)	0,0544	MEVTGDAG
DFFA: DNA fragmentation factor, 45 kDa, alpha polypeptide	NP_004392	VTGD (6)	0,0432	DVDETDSG
FBL: fibrillarin	NP_001427	VGPD (184)	23,85	DIVGPDGL
FLNA: filamin A, alpha (actin binding protein 280)	NP_001447	?	11,4048	TEIDQDKY
G22P1: thyroid autoantigen 70 kDa (Ku antigen)	NP_001460	ISSD (79)	22,3344	KIISSDRD
GRIA3: glutamate receptor, ionotrophic, AMPA 3	NP_000819	ISND (416)	18,5328	QQISNDSA
HARS: histidyl-tRNA synthetase	NP_002100	LGPD (48)	2,4804	AQLGPDES
IARS: isoleucine-tRNA synthetase	NP_002152	VTPD (983)	2,7	LDVTPDQS
L4 100K [Human adenovirus C]	AAQ19301	IEQD (48)	57,6	VIIEQDPG
MKI67: antigen identified by monoclonal antibody Ki-67	NP_002408	VCTD (1481)	0,0272	TPVCTDKP
NUMA1: nuclear mitotic apparatus protein 1	NP_006176	VATD (1705)	4,1616	FQVATDAL
PMS1: PMS1 postmeiotic segregation increased 1	NP_000525	ISAD (496)	17,1072	SEISADEW
PMS2: PMS2 postmeiotic segregation increased 2	NP_000526	VEKD (493)	0,05	AEVEKDSG
PMSCL2: polymyositis/scleroderma autoantigen 2, 100 kDa	NP_002676	VEQD (252)	28,8	QQVEQDMF
POLR1A: polymerase (RNA) I polypeptide A, 194 kDa	NP_056240	ICPD (448)	0,1	SVICPDMY
POLR2A: polymerase (RNA) II (DNA directed) polypeptide A, 220 kDa	NP_000928	ITPD (370)	5,4	TVITPDPN
PRKDC: protein kinase, DNA-activated, catalytic polypeptide	NP_008835	VGPD (2698)	23,85	KSVGPDFG
SNRP70: small nuclear ribonucleoprotein 70 kDa polypeptide (RNP antigen)	NP_003080	LGND (409)	1,5477696	EGLGNDSR
SRP72: signal recognition particle 72 kDa	NP_008878	VTPD (573)	2,7	PKVTPDPE
SSB: Sjogren syndrome antigen B (autoantigen La)	NP_003133	LEED (220)	1,4976	QKLEEDAE
TOP1: topoisomerase (DNA) I	NP_003277	IEAD (15)	57,6	SQIEADFR
UBE4B: ubiquitination factor E4B (UFD2 homolog, yeast)	NP_006039	VDVD (123)	3,0096	SQVDVDSG
UBTF: upstream binding transcription factor, RNA polymerase I	NP_055048	VRPD (220)	0,05	LKVRPDAT

The bold printed amino acids in the extended cleavage site indicate hits with a G residue at position P2′ detected by the high stringency filter. Numbers in brackets indicate cleavage site position in the amino acid sequence.

Table 4.

Analysis of cleavage sites of known non-substrates of granzyme B with GraBCas

Granzyme B non-substrate	Acc_number	Best hit	Score by GraBCas
TRIM21: 52 kD Ro/SSA autoantigen	NP_003132	LDPD (294)	1,0296
SSA2: 60 kD Ro/SSA autoantigen	NP_004591	VTTD (427)	1,4688
XRCC5: ATP-dependent DNA helicase II Ku80	NP_066964	FGTD (62)	0,3113856
VCL: vinculin isoform VCL	NP_003364	LQSD (98)	0,3167424
VCL: vinculin isoform meta-VCL	NP_054706	LQSD (98)	0,3167424
TUBB2: tubulin, beta 2	NP_001060	VISD (26)	0,0376
CRP: C-reactive protein, pentraxin-related	NP_000558	LSPD (187)	1,5444
SERPINA1: serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1	NP_000286	LAED (26)	0,2291328
SERPINA1: serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1	NP_001002235	LAED (26)	0,2291328
SERPINA1: serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1	NP_001002236	LAED (26)	0,2291328
GSTA1: glutathione S-transferase A1	NP_665683	VEID (61)	0,8
PYGB: brain glycogen phosphorylase	NP_002853	IEED (129)	28,8
TF: transferring	NP_001054	VTLD (82)	0,2592
LTF: lactotransferrin	NP_002334	VTLD (79)	0,2592
LYZ: lysozyme precursor	NP_000230	RSTD (71)	0,0161568
ORM1: orosomucoid 1 precursor	NP_000598	LAFD (133)	0,1145664
F2: coagulation factor II precursor (Thrombin B-chain)	NP_000497	LDED (306)	0,2965248

Numbers in brackets indicate cleavage site position in the amino acid sequence.

Figure 1.

Sensitivity–specificity plot for granzyme B. x-axis: scores by the GraBCas program; y-axis: percentage of specificity or sensitivity.

The x-axis of the plots represents the cutoff values (with respect to the PSSM scores), while the y-axis represents the percentage of the specificity or sensitivity of the predictions made by GraBCas, respectively. The specificity is computed as follows:

$$\frac{\text{Number of true negatives}}{\text{Number of false positives}+\text{Number of true negatives}}.$$

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. 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:

$$\frac{\text{Number of true positives}}{\text{Number of true positives}+\text{Number of false negatives}},$$

where true positives are the known cleavage sites with a score larger than the chosen cutoff value. A sensitivity of 1 means that all cleavage sites of our test set (Table 2) have a score higher than the chosen cutoff and that they have been correctly classified as positives.

RESULTS AND DISCUSSION

We analyzed the cleavage sites of known substrates of granzyme B and caspase 3 to compare the experimentally identified peptide specificity with the cleavage site predicted by the program GraBCas.

In total, we collected 29 substrates with 30 cleavage sites for granzyme B (Table 2) and 47 substrates with 59 cleavage sites for caspase 3 (Table 3) and computed the GraBCas scores of the cleavage sites. For granzyme B we collected additionally 17 sequences which are non-substrates of this endopeptidase (Table 4), computed the scores of all putative cleavage sites in these sequences and extracted the best hit by GraBCas for each of these non-substrates.

Table 3.

Analysis of cleavage sites of known caspase 3 substrates with GraBCas

Caspase 3 substrate	Acc_number	Known cleavage site	Score by GraBCas	P6–P2′ of cleavage site
ADD1: adducing 1 (alpha)	NP_001110	DDSD (633)	0,357	TGDDSDAA
APAF1: apoptotic protease activating factor	NP_001151	SVTD (271)	0,462672	DKSVTDSV
ARHGDIB: Rho GDP dissociation inhibitor (GDI) beta	NP_001166	DELD (19)	22,4	DDDELDSK
ATP2B4: ATPase, Ca++ transporting, plasma membrane 4	NP_001675	DEID (1080)	71,4	GLDEIDHA
BAD: BCL2-antagonist of cell death	NP_004313	EQED (14)	0,001632	PSEQEDSS
BAX: BCL2-associated X protein	NP_004315	FIQD (33)	0,002142	QGFIQDRA
BCL2: B-cell CLL/lymphoma 2	NP_000624	DAGD (34)	0,0357	EWDAGDVG
BCL2L1: BCL2-like 1	NP_001182	HLAD (61)	0,027846	SWHLADSP
BCL2L1: BCL2-like 2	NP_001182	SSLD (76)	0,274176	HSSSLDAR
BIRC2: baculoviral IAP repeat-containing 2	NP_001157	ENAD (372)	0,111384	GEENADPP
BLM: Bloom syndrome	NP_000048	TEVD (415)	5	LLTEVDFN
BRCA1: breast cancer 1, early onset	NP_009225	DLLD (1154)	3,4272	PDDLLDDG
CAMK4: calcium/calmodulin-dependent protein kinase IV	NP_001735	YWID (31)	0,0084966	PDYWIDGS
CAMK4: calcium/calmodulin-dependent protein kinase IV	NP_001735	PAPD (176)	0,0144942	ATPAPDAP
CDC2L1: cell division cycle 2-like 1 (PITSLRE proteins)	NP_001778	YVPD (391)	0,0124236	GDYVPDSP
CDC6: CDC6 cell division cycle 6 homolog (Saccharomyces cerevisiae)	NP_001245	SEVD (442)	4	VISEVDGN
CDC6: CDC6 cell division cycle 6 homolog (S.cerevisiae)	NP_001245	LVRD (99)	0,0055692	RRLVFDNQ
CDKN1A: cyclin-dependent kinase inhibitor 1A (p21, Cip1)	NP_000380	DHVD (112)	18,7	EEDHVDLS
CSEN: calsenilin, presenilin binding protein, EF hand transcription factor	NP_038462	DSSD (64)	0,4284	GSDSSDSE
CTNNB1: catenin (cadherin-associated protein), beta 1, 88 kDa	NP_001895	DLMD (764)	0,0153	AQDLMDGL
CTNNB1: catenin (cadherin-associated protein), beta 1, 88 kDa	NP_001895	YPVD (751)	10	ADYPVDGL
CTNNB1: catenin (cadherin-associated protein), beta 1, 88 kDa	NP_001895	ADID (83)	0,18207	QVADIDGQ
CTNNB1: catenin (cadherin-associated protein), beta 1, 88 kDa	NP_001895	TQFD (115)	0,37128	PSTQFDAA
CTNNB1: catenin (cadherin-associated protein), beta 1, 88 kDa	NP_001895	SYLD (32)	0,22848	QQSYLDSG
DFFA: DNA fragmentation factor, 45 kDa, alpha polypeptide	NP_004392	DAVD (224)	35,7	EVDAVDTG
DFFA: DNA fragmentation factor, 45 kDa, alpha polypeptide	NP_004392	DETD (117)	37,8	DVDETDSG
DRPLA: dentatorubral-pallidoluysian atrophy (atrophin-1)	NP_001931	DSLD (109)	6,8544	DLDSLDGR
EIF2S1: eukaryotic translation initiation factor 2, subunit 1 alpha, 35 kDa	NP_004085	AEVD (301)	1	ENAEVDGD
EIF2S1: eukaryotic translation initiation factor 2, subunit 1 alpha, 35 kDa	NP_004085	DGDD (304)	0,0085	EVDGDDDA
FNTA: farnesyltransferase, CAAX box, alpha	NP_002018	VSLD (59)	0,137088	GFVSLDSP
GCLC: glutamate-cysteine ligase, catalytic subunit	NP_001489	AVVD (499)	0,306	GNAVVDGC
GSN: gelsolin (amyloidosis, Finnish type)	NP_000168	DQTD (403)	15,4224	DPDQTDGL
HD: huntingtin (Huntington disease)	NP_002102	DSVD (513)	30,6	WEAQRDSH
HNRPU: heterogeneous nuclear ribonucleoprotein U (scaffold attachment factor A)	NP_004492	SALD (100)	0,319872	GISALDGD
IL16: interleukin 16 (lymphocyte chemoattractant factor)	NP_004504	SSTD (510)	0,462672	LNSSTDSA
IL18: interleukin 18 (interferon-gamma-inducing factor)	NP_001553	LESD (36)	0,0014	ENLESDYF
KRT18: keratin 18	NP_000215	VEVD (238)	2	LTVEVDAP
MAPT: microtubule-associated protein tau	NP_005901	DMVD (421)	0,1	SIDMVDSP
MDM2: Mdm2, transformed 3T3 cell double minute 2, p53 binding protein (mouse)	NP_002383	DVPD (361)	12,4236	GFDVPDCK
NFKBIA: nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha	NP_065390	DRHD (32)	0,3332	LDDRHDSG
NUMA1: nuclear mitotic apparatus protein 1	NP_006176	DSLD (1712)	6,8544	SIDSLDLS
PAK2: p21 (CDKN1A)-activated kinase 2	NP_002568	SHVD (212)	0,748	GDSHVDGA
POLE: polymerase (DNA directed), epsilon	NP_006222	DQLD (189)	9,1392	IADQLDNI
POLE: polymerase (DNA directed), epsilon	NP_006222	DMED (1185)	10	APDMEDFG
PPP2R1A: protein phosphatase 2 (formerly 2A), regulatory subunit A (PR 65), alpha isoform	NP_055040	DEQD (218)	1,4	ASDEQDSV
PRKCD: protein kinase C, delta	NP_006245	DMQD (329)	0,0014	GEDMQDNS
PRKCM: protein kinase C, mu	NP_002733	CQND (378)	5,712	AECQNDSG
PRKCQ: protein kinase C, theta	NP_006248	DEVD (354)	100	PLDEVDKM
PRKCZ: protein kinase C, zeta	NP_002735	DGVD (239)	0,0085	VIDGMDGI
PRKCZ: protein kinase C, zeta	NP_002735	EETD (210)	1,512	PSEETDGI
PRKDC: protein kinase, DNA-activated, catalytic polypeptide	NP_008835	DEVD (2713)	100	PGDEVDNK
PSEN2: presenilin 2 (Alzheimer disease 4)	NP_000438	DSYD (329)	4,7124	EEDSYDSF
RB1: retinoblastoma 1 (including osteosarcoma)	NP_000312	DEAD (886)	18,2	GSDEADGS
RFC1: replication factor C (activator 1) 1, 145 kDa	NP_002904	DEVD (722)	100	IMDEVDGM
ROCK1: Rho-associated, coiled-coil containing protein kinase 1	NP_005397	DETD (1113)	37,8	SADETDGN
SNRP70: small nuclear ribonucleoprotein 70 kDa polypeptide (RNP antigen)	NP_003080	DGPD (341)	3,451	GPDGPDGP
SPTBN1: spectrin, beta, non-erythrocytic 1	NP_003119	DEVD (1457)	100	STDEVDSK
SPTBN1: spectrin, beta, non-erythrocytic 2	NP_003119	ETVD (2146)	1,428	MAETVDTS
VIM: vimentin	NP_003371	DSVD (85)	30,6	KGDEVDGV

The bold printed amino acids in the extended clevage site indicate hits detected by the high stringency filter. Numbers in brackets indicate clevage site position in the amino acid sequence.

The sensitivity–specificity plot for granzyme B is shown in Figure 1. When using a cutoff value of 1.2 in the GraBCas program, we obtain a sensitivity of ∼80% and a specificity of ∼82%. The cutoff value can be adjusted if a higher specificity or sensitivity is needed for the cleavage site prediction.

A closer look at the sensitivity–specificity plot shows that the best score (28.8 for IEED in glycogen phosphorylase) of the alleged non-substrates is extremely high. The top value of the best hit IEED is due to the fact that this tetrapeptide has three identical positions with the granzyme B consensus recognition motif IEPD. Furthermore, the amino acid E on P2 has a middle-sized value and the tetrapeptides LEED, IEAD and IETD are known substrates of granzyme B. We assume that glycogen phosphorylase is probably a substrate of granzyme B. This warrants further experimental analysis.

We also studied the occurrences of amino acids at position P1′ and P2′ of the known cleavage sites of granzyme B and caspase 3. Additional filtering options have been added to GraBCas that are based on these statistics. For granzyme B, we detected G at position P2′ in 9/30 cleavage sites. This confirms the results of Harris et al. (14), who found for recombinant rat granzyme B a specificity for G at P2′. We did not, however, confirm the proposed total absence of charged amino acids at P1′, in that we found E three times, R two times and K and D one time, each.

For caspase 3, we found in total 44/59 (75%) cleavage sites with G, S, A or N at position P1′. These results are in good accordance with the results of Stennicke et al. (15). Absent amino acids included the charged residues R, E, H, K and the large residues Q, I, L, M, F, W and Y.

With GraBCas we provide a position specific scoring scheme for the prediction of cleavage sites for granzyme B and caspases 1–9. GraBCas offers an easy to use, concise user interface in register card format. The design of GraBCas specifically acknowledged the high variability of cleavage site recognition sequences. We validated our tool by scoring known substrates and demonstrated its usefulness for protein sequence analysis. GraBCas may contribute to a more comprehensive knowledge of caspase and granzyme B substrates and a better understanding of the biological roles of these enzymes.

SUPPLEMENTARY MATERIAL

Supplementary Material is available at NAR Online.