Protein Fold recognition

1. Protein Fold recognition Morten Nielsen, CBS, BioCentrum, DTU

2. Objectives • Understand the basic concepts of fold recognition • Learn why even sequences with very low sequence similarity can be modeled • Understand why is %id such a terrible measure for reliability • See the beauty of sequence profiles • Position specific scoring matrices (PSSMs)

3. Protein Homology modeling? • Identify template(s) – initial alignment • Can give you protein function • Improve alignment • Can give you active site • Backbone generation • Loop modeling • Most difficult part • Side chains • Refinement • Validation

4. Identify fold (template) for modeling Find the structure in the PDB database that resembles your new protein the most Can be used to predict function And maybe active sites Align protein sequence to template Simple alignment methods Sequence profiles Threading methods Pseudo force fields Model side chains and loops How to do it?

5. Homology modeling and the human genome

6. Identification of fold • If sequence similarity is high proteins share structure (Safe zone) • If sequence similarity is low proteins may share structure (Twilight zone) • Most proteins do not have a high sequence homologous partner Rajesh Nair & Burkhard Rost Protein Science, 2002, 11, 2836-47

7. Example. A post doc in our group did her PhD obtaining the structure of the sequence below >1K7C.A TTVYLAGDSTMAKNGGGSGTNGWGEYLASYLSATVVNDAVAGRSARSYTREGRFENIADV VTAGDYVIVEFGHNDGGSLSTDNGRTDCSGTGAEVCYSVYDGVNETILTFPAYLENAAKL FTAKGAKVILSSQTPNNPWETGTFVNSPTRFVEYAELAAEVAGVEYVDHWSYVDSIYETL GNATVNSYFPIDHTHTSPAGAEVVAEAFLKAVVCTGTSLKSVLTTTSFEGTCL • What is the function • Where is the active site?

8. What would you do? • Function • Run Blast against PDB • No significant hits • Run Blast against NR (Sequence database) • Function is Acetylesterase? • Where is the active site?

9. Example. Where is the active site? 1G66 Acetylxylan esterase 1USW Hydrolase 1WAB Acetylhydrolase

10. Example. Where is the active site? • Align sequence against structures of known acetylesterase, like • 1WAB, 1FXW, … • Cannot be aligned. Too low sequence similarity 1K7C.A 1WAB._ RMSD 11.2397 QAL 1K7C.A 71 GHNDGGSLSTDNGRTDCSGTGAEVCYSVYDGVNETILTF DAL 1WAB._ 160 GHPRAHFLDADPGFVHSDGTISH--HDMYDYLHLSRLGY

11. Is it really impossible? Protein homology modeling is only possible if %id greater than 30-50% WRONG!!!!!!!

12. Why %id is so bad!! 1200 models sharing 25-95% sequence identity with the submitted sequences (www.expasy.ch/swissmod)

13. Identification of correct fold • % ID is a poor measure • Many evolutionary related proteins share low sequence homology • A short alignment of 5 amino acids can share 100% id, what does this mean? • Alignment score even worse • Many sequences will score high against every thing (hydrophobic stretches) • P-value or E-value more reliable

14. Score 150 10 hits with higher score (E=10) 10000 hits in database => P=10/10000 = 0.001 P(Score) Score What are P and E values? • E-value • Number of expected hits in database with score higher than match • Depends on database size • P-value • Probability that a random hit will have score higher than match • Database size independent

15. What goes wrong when Blast fails? • Conventional sequence alignment uses a (Blosum) scoring matrix to identify amino acids matches in the two protein sequences

16. Blosum scoring matrix A R N D C Q E G H I L K M F P S T W Y V A 4 -1 -2 -2 0 -1 -1 0 -2 -1 -1 -1 -1 -2 -1 1 0 -3 -2 0 R -1 5 0 -2 -3 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1 -3 -2 -3 N -2 0 6 1 -3 0 0 0 1 -3 -3 0 -2 -3 -2 1 0 -4 -2 -3 D -2 -2 1 6 -3 0 2 -1 -1 -3 -4 -1 -3 -3 -1 0 -1 -4 -3 -3 C 0 -3 -3 -3 9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1 -2 -2 -1 Q -1 1 0 0 -3 5 2 -2 0 -3 -2 1 0 -3 -1 0 -1 -2 -1 -2 E -1 0 0 2 -4 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1 -3 -2 -2 G 0 -2 0 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -2 -3 -3 H -2 0 1 -1 -3 0 0 -2 8 -3 -3 -1 -2 -1 -2 -1 -2 -2 2 -3 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1 -3 -1 3 L -1 -2 -3 -4 -1 -2 -3 -4 -3 2 4 -2 2 0 -3 -2 -1 -2 -1 1 K -1 2 0 -1 -3 1 1 -2 -1 -3 -2 5 -1 -3 -1 0 -1 -3 -2 -2 M -1 -1 -2 -3 -1 0 -2 -3 -2 1 2 -1 5 0 -2 -1 -1 -1 -1 1 F -2 -3 -3 -3 -2 -3 -3 -3 -1 0 0 -3 0 6 -4 -2 -2 1 3 -1 P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4 7 -1 -1 -4 -3 -2 S 1 -1 1 0 -1 0 0 0 -1 -2 -2 0 -1 -2 -1 4 1 -3 -2 -2 T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5 -2 -2 0 W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1 1 -4 -3 -2 11 2 -3 Y -2 -2 -2 -3 -2 -1 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7 -1 V 0 -3 -3 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -2 0 -3 -1 4

17. What goes wrong when Blast fails? • Conventional sequence alignment uses a (Blosum) scoring matrix to identify amino acids matches in the two protein sequences • This scoring matrix is identical at all positions in the protein sequence! EVVFIGDSLVQLMHQC X X X X X X AGDS.GGGDS

18. Alignment accuracy. Scoring functions • Blosum62 score matrix. Fg=1. Ng=0? • Score =2+6+6+4-1=17 • Alignment LAGDS I-GDS

19. When Blast works! 1PLC._ 1PLB._

20. When Blast fails! 1PLC._ 1PMY._

21. When Blast fails, use sequence profiles!

22. When Blast fails, use sequence profiles! 1PLC._ 1PMY._

23. Sequence profiles • In reality not all positions in a protein are equally likely to mutate • Some amino acids (active cites) are highly conserved, and the score for mismatch must be very high • Other amino acids can mutate almost for free, and the score for mismatch should be lower than the BLOSUM score • Sequence profiles can capture these differences

24. Protein superfamily Protein world New Fold Protein family Protein fold Protein structure classification

25. All a: Hemoglobin (1bab)

26. All b: Immunoglobulin (8fab)

27. a/b:Triose phosphate isomerase (1hti)

28. a+b: Lysozyme (1jsf)

29. Non-conserved Conserved Sequence profiles ADDGSLAFVPSEF--SISPGEKIVFKNNAGFPHNIVFDEDSIPSGVDASKISMSEEDLLN TVNGAI--PGPLIAERLKEGQNVRVTNTLDEDTSIHWHGLLVPFGMDGVPGVSFPG---I -TSMAPAFGVQEFYRTVKQGDEVTVTIT-----NIDQIED-VSHGFVVVNHGVSME---I IE--KMKYLTPEVFYTIKAGETVYWVNGEVMPHNVAFKKGIV--GEDAFRGEMMTKD--- -TSVAPSFSQPSF-LTVKEGDEVTVIVTNLDE------IDDLTHGFTMGNHGVAME---V ASAETMVFEPDFLVLEIGPGDRVRFVPTHK-SHNAATIDGMVPEGVEGFKSRINDE---- TVNGQ--FPGPRLAGVAREGDQVLVKVVNHVAENITIHWHGVQLGTGWADGPAYVTQCPI TVNGQ--FPGPRLAGVAREGDQVLVKVVNHVAENITIHWHGVQLGTGWADGPAYVTQCPI TKAVVLTFNTSVEICLVMQGTSIV----AAESHPLHLHGFNFPSNFNLVDPMERNTAGVP Matching any thing but G => large negative score Any thing can match

30. How to make sequence profiles • Align (BLAST) sequence against large sequence database (Swiss-Prot) • Select significant alignments and make profile (weight matrix) using techniques for sequence weighting and pseudo counts • Use weight matrix to align against sequence database to find new significant hits • Repeat 2 and 3 (normally 3 times!)

31. Example. (SGNH active site)

32. Example. Where is the active site? • Sequence profiles might show you where to look! • The active site could be around • S9, G42, N74, and H195

33. Profile-profile scoring matrix 1K7C.A 1WAB._

34. Example. Where is the active site? Align using sequence profiles ALN 1K7C.A 1WAB._RMSD = 5.29522. 14% ID 1K7C.A TVYLAGDSTMAKNGGGSGTNGWGEYLASYLSATVVNDAVAGRSARSYTREGRFENIADVVTAGDYVIVEFGHNDGGSLSTDN SGN 1WAB._ EVVFIGDSLVQLMHQCE---IWRELFS---PLHALNFGIGGDSTQHVLW--RLENGELEHIRPKIVVVWVGTNNHG------ 1K7C.A GRTDCSGTGAEVCYSVYDGVNETILTFPAYLENAAKLFTAK--GAKVILSSQTPNNPWETGTFVNSPTRFVEYAEL-AAEVA 1WAB._ ---------------------HTAEQVTGGIKAIVQLVNERQPQARVVVLGLLPRGQ-HPNPLREKNRRVNELVRAALAGHP 1K7C.A GVEYVDHWSYVDSIYETLGNATVNSYFPIDHTHTSPAGAEVVAEAFLKAVVCTGTSL H 1WAB._ RAHFLDADPG---FVHSDG--TISHHDMYDYLHLSRLGYTPVCRALHSLLLRL---L

35. Where was the active site? Rhamnogalacturonan acetylesterase (1k7c)

36. How good are we?

37. Alignment accuracy

38. AUC performance measure Query Templ Score Hit/nonhit 1CJ0.A 1B78.A 0.170963 0 1CJ0.A 1B8A.A -0.040029 0 1CJ0.A 1B8B.A -0.012789 0 1CJ0.A 1B8G.A 12.342823 1 1CJ0.A 1B9H.A 13.394361 1 1CJ0.A 1BAR.A -1.281068 0 1CJ0.A 1BAV.C -1.091305 0 AUC (area under the ROC curve) Query Templ Score Hit/nonhit 1CJ0.A 1B8G.A 12.342823 1 1CJ0.A 1DTY.A 11.867786 1 1CJ0.A 1DGD._ 11.271914 1 1CJ0.A 1GTX.A 11.010288 1 1CJ0.A 2GSA.A 10.958170 1 1CJ0.A 1BW9.A 2.651775 0 1CJ0.A 1AUP._ 2.507336 1 1CJ0.A 1GTM.A 2.444512 0

39. Fold recognition performance

40. Outlook • Include position dependent gap penalties • The conventional alignment methods use equal gap penalties through out the scoring matrix • In real proteins placement of insertions and deletions is highly structure dependent • No gaps in secondary structure elements • Gaps most frequent in loops • Distance dependency

41. Take home message • Identifying the correct fold is only a small step towards successful homology modeling • Do not trust % ID or alignment score to identify the fold. Use P-values • You can do reliable fold recognition AND homology modeling when for low sequence homology • Use sequence profiles and local protein structure to align sequences

42. What are (some of) the different available methods? • Simple sequence based methods • Align (BLAST) sequence against sequence of proteins with known structure (PDB database) • Sequence profile based methods • Align sequence profile (Psi-BLAST) against sequence of proteins with known structure (PDB, FUGUE) • Align sequence profile against profile of proteins with known structure (FFAS) • Sequence and structure based methods • Align profile and predicted secondary structure against proteins with known structure (3D-PSSM, Phyre) • Sequence profiles and structure based methods • HHpred