Multi-factor model for prediction of the caspase degradome Lawrence Wee

1. Multi-factor model for prediction of the caspase degradome Lawrence Wee

2. What are Caspases? The Biochemistry of Caspases1 Caspases are cysteine proteases. Recognize tetrapeptide sequence on substrates (P4-P3-P2-P1). P4 P3 P2 P1 P1’ P2’ - D– E – V – D --- T – Y Cleave after canonical Asp (D) residue at the P1 position. • 1. Fuentes-Prior et al. Biochem J. 2004 Dec 1;384(Pt 2):201-32. • 2. Thornberry et al. J Biol Chem. 1997 Jul 18;272(29):17907-11.

3. What are Caspases? Caspases in Apoptosis1 Extrinsic Intrinsic As the final effectors of apoptosis, caspases cleave many protein substrates. 1. Hengartner MO. The biochemistry of apoptosis.Nature. 2000 Oct 12;407(6805):770-6.

4. The Caspase Degradome The State of the Caspase Degradome1 1. Categories are assigned according to Fischer et al (2003).

5. What is the Degradome? The Degradome Degradome: The protease-substrate repertoire in a cell, tissue or organism1 Degradome Genome Transcriptome Proteome Proteases Substrates Genomics Transcriptomics Proteomics Degradomics The Caspase Degradome: The repertoire of proteins cleaved by caspases . 1. Lopez-Otin C and Overall CM. Protease degradomics: a new challenge for proteomics. Nat Rev Mol Cell Biol. 2002 Jul;3(7):509-19.

6. Question What proteins are cleaved by caspases?

7. Question What proteins are cleaved by caspases? Strategy How about predicting the caspase degradome?

8. Algorithms and servers Existing algorithms and servers • 1. Accuracy as reported in papers using the authors’ datasets. • 2. GraBCas accuracy when tested on our dataset.

9. Server for SVM-based prediction CASVM Web Server1,2 CASVM web server predicts caspase cleavage sites using our SVM algorithm www.casbase.org/casvm 1. Wee et al.CASVM: web server for SVM-based prediction of caspase substrates cleavage sites. Bioinformatics. 2007 Dec 1;23(23):3241-3. 2. Wee et al. SVM-based prediction of caspase substrate cleavage sites.BMC Bioinformatics. 2006 Dec 18;7 Suppl 5:S14

10. Question What proteins are cleaved by caspases? Strategy How about predicting the caspase degradome? Problem Predicting caspase cleavage sites is not good enough

11. Predicting the Caspase Degradome Limitations of Caspase Cleavage Sites Prediction • Not all bona fide cleavage site motifs are cleaved in vivo1: • 80% of true substrates contain at least one other identical caspase cleavage site sequence which is not reported as a true cleavage site in literature. • - Tpr (DDED-2117) • - p28BAP31 (AAVD-163) • - golgin 160 (SEVD-311) • - Topo I (PEDD-123) • - heterogeneous nuclear ribonucleoparticle C1/C2 (GEDD-305) 1. Analysis on our caspase substrates dataset.

12. Problem Predicting caspase cleavage sites is not good enough Solution How about incorporating other structural factors?

13. Problem Predicting caspase cleavage sites is not good enough Solution How about incorporating other structural factors? Secondary structures? Solvent exposure?

14. Analysis of caspase cleavage sites Caspase cleavage sites are analyzed for: Propensity for secondary structures Dataset of caspase cleavage sites & non-cleavage sites SABLE1 Propensity for solvent exposure 1. http://sable.cchmc.org/

15. Analysis of caspase cleavage sites Cleavage sites tend to locate in unstructured regions Figure 1 Figure 2 Cleavage sites prefer unstructured regions

16. Analysis of caspase cleavage sites Cleavage sites tend to locate in solvent exposed regions Figure 3 Figure 4 Cleavage sites prefer solvent exposed regions

17. Analysis of caspase cleavage sites Cleavage sites tend to locate in unstructured and solvent exposed regions Figure 5 Cleavage sites prefer highly unstructured regions with high solvent exposure

18. Analysis of caspase cleavage sites Cleavage sites tend to locate in unstructured and solvent exposed regions Figure 6 Non-cleavage sites prefer regions with secondary structures and less solvent exposure

19. Multi-factor model Current algorithms Better algorithm? Cleavage site prediction Cleavage site prediction Secondary structures Solvent exposure

20. Multi-factor model prediction Schematic diagram of the multi-factor algorithm Step 1 - Caspase cleavage site prediction (using an existing algorithm) ......MIREYRQMVETELKLICCDILDVLDKHLIPAANTGESKVF..... Step 2 – Selection of structurally favorable candidates VETELKLICCDILDVLDKHLIPAA ELKLICCDILDVLDKHLIPAANTG LAKAAFDDAIAELDTLSEESYKDS Cp, Sp and P-score are calculated for all subsequences Cleavage sites in subsequences with P-score above cut-off are selected ELKLICCDILDVLDKHLIPAANTG

21. Algorithms and servers Existing algorithms and servers • 1. Accuracy as reported in papers using the authors’ datasets. • 2. GraBCas accuracy when tested on our dataset.

22. Multi-factor model prediction Validating the multi-factor model Analysis Dataset of caspase cleavage sites & non-cleavage sites Test Multi-factor model prediction

23. Multi-factor model prediction Validating the multi-factor model Figure 7 Using CASVM

24. Multi-factor model prediction Validating the multi-factor model Figure 8 Using GraBCas

25. Multi-factor model prediction Validating the multi-factor model Figure 9 CASVM GraBCas

26. RTK cleavage prediction Prediction of potential caspase cleavage among RTKs • Receptor Tyrosine Kinases (RTKs) • Belong to the tyrosine kinase superfamily • Plasma membrane bound • Involved in cell survival, proliferation, differentiation Image taken from http://www.pvrireview.org/viewimage.asp?img=PVRIReview_2009_1_2_124_50732_u1.jpg

27. Questions Which RTKs are cleaved by caspases? What are the consequences of cleavage?

28. RTK cleavage prediction Prediction of RTK cleavage using the multi-factor model 52 RTKs from Uniprot Step 1 Caspase cleavage sites predicted with CASVM Step 2 Cleavage sites scored for Cp, Sp and P-score Selection of structurally favorable cleavage sites

29. RTK cleavage prediction Prediction of potential caspase cleavage among RTKs

30. RTK cleavage prediction Prediction of potential caspase cleavage among RTKs Results and conclusion • Cleavage sites are found throughout the length of receptor • 92% of all RTKs contain intracellular cleavage sites • 98% contain extracellular cleavage sites • 21% contain juxtamembrane domain cleavage sites (in cytoplasmic portion) • 80% contain cleavage sites within the tyrosine kinase domain (in cytoplasmic portion)

31. Conclusion Conclusion • Multi-factor model can be applicable to other protease-substrate prediction problem. • Two step approach may be better than a single step • Other factors can be incorporated into separate steps (exosites prediction, protein-protein interactions). But correlations must be low.

32. The End