1. Sequence similarity search Glance to the protein world

2. WHATS TODAY? BLASTing Proteins -Similarity scores for protein sequences -Searching for remote homologies

3. How can we decide if two sequences are homologs  Rule of thumb: Proteins are homologous if 25%-35% identical (length >100) DNA sequences are homologous if 70% identical Homolog = come from a common origin => have the same function

4. Alignment between the unknown protein and human arrestin VERY SIGNIFICANT, NOT HIGH IDENTITY

5. Assessing whether proteins are functional homologous RBP4 and PAEP: E value= 0.49; identity=24% Are they functionally homologous ??? RBP4= carrier of vitamin A in the blood

6. retinol-binding protein odorant-binding protein apolipoprotein D PAEP Lipocalin family RBP4

7. Is identity the right way to score?

8. Protein Pairwise Sequence Alignment Main difference: instead of scoring match (+2) and mismatch (-1) we have similarity scores: Score s(i,j) > 0 if amino acids i and j have similar properties Score s(i,j) is  0 otherwise How should we score s(i,j)?

9. The 20 Amino Acids

10. Chemical Similarities Between Amino Acids Acids & AmidesDENQ (Asp, Glu, Asn, Gln) Basic HKR (His, Lys, Arg) AromaticFYW (Phe, Tyr, Trp) Hydrophilic ACGPST (Ala, Cys, Gly, Pro, Ser, Thr) HydrophobicILMV (Ile, Leu, Met, Val)

11. Sequence Alignment based on AA similarity TQSPSSLSASVGDTVTITCRASQSISTYLNWYQQKP----GKAPKLLIYAASSSQSGVPS || + |||| +|| ||| | +| | | | | TQGKKVVLGKKGDTVELTCTASQKKSIQFHWKNSNQIKILGNQGSFLTKGPSKLNDRADS RFSGSGSGTDFTLTINSLQPEDFATYYCQ---------------QSYSTPHFSQGTKLEI | | | +| | | +|+ || || |+ + | | || | + RRSLWDQG-NFPLIIKNLKIEDSDTYICEVEDQKEEVQLLVFGLTANSDTHLLQGQSLTL ---KRTVAAPSVFIFPPSDEQLKSGTASVVCLLN---------NFYPREAKVQWKVD ++||| | + ++ | | | + ||++|+| TLESPPGSSPSVQCRSPRGKNIQGGKTLSVSQLELQDSGTWTCTVLQNQKKVEFKID | = identity 45/178=25% + = similarity 63/178=35%

12. Scoring Matrices Scoring Matrix -match/mismatch score –Not bad for similar sequences –Does not show distantly related sequences

13. Given an alignment of closely related sequences we can score the relation between amino acids based on how frequently they substitute each other In this column E & D are found 7/8 M G Y D E M G Y E E M G Y D E M G Y Q E M G Y D E M G Y E E Substitution Matrix

14. CH +H3N+H3N COO - HCH C O-O- O CH +H3N+H3N C COO - HCH O-O- O Aspartate (Asp, D) Glutamate (Glu, E) D / E

15. PAM - Point Accepted Mutations Developed by Margaret Dayhoff, 1978. Analyzed very similar protein sequences “Accepted” mutations – do not negatively affect a protein’s fitness Used global alignment. Counted the number of substitutions (i,j) per amino acid pair: Many i j substitutions => high score s(i,j) Margaret Dayhoff 1925-1983

16. Basic matrix normalized probabilities multiplied by 10000 Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val A R N D C Q E G H I L K M F P S T W Y V A 9867 2 9 10 3 8 17 21 2 6 4 2 6 2 22 35 32 0 2 18 R 1 9913 1 0 1 10 0 0 10 3 1 19 4 1 4 6 1 8 0 1 N 4 1 9822 36 0 4 6 6 21 3 1 13 0 1 2 20 9 1 4 1 D 6 0 42 9859 0 6 53 6 4 1 0 3 0 0 1 5 3 0 0 1 C 1 1 0 0 9973 0 0 0 1 1 0 0 0 0 1 5 1 0 3 2 Q 3 9 4 5 0 9876 27 1 23 1 3 6 4 0 6 2 2 0 0 1 E 10 0 7 56 0 35 9865 4 2 3 1 4 1 0 3 4 2 0 1 2 G 21 1 12 11 1 3 7 9935 1 0 1 2 1 1 3 21 3 0 0 5 H 1 8 18 3 1 20 1 0 9912 0 1 1 0 2 3 1 1 1 4 1 I 2 2 3 1 2 1 2 0 0 9872 9 2 12 7 0 1 7 0 1 33 L 3 1 3 0 0 6 1 1 4 22 9947 2 45 13 3 1 3 4 2 15 K 2 37 25 6 0 12 7 2 2 4 1 9926 20 0 3 8 11 0 1 1 M 1 1 0 0 0 2 0 0 0 5 8 4 9874 1 0 1 2 0 0 4 F 1 1 1 0 0 0 0 1 2 8 6 0 4 9946 0 2 1 3 28 0 P 13 5 2 1 1 8 3 2 5 1 2 2 1 1 9926 12 4 0 0 2 S 28 11 34 7 11 4 6 16 2 2 1 7 4 3 17 9840 38 5 2 2 T 22 2 13 4 1 3 2 2 1 11 2 8 6 1 5 32 9871 0 2 9 W 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 9976 1 0 Y 1 0 3 0 3 0 1 0 4 1 1 0 0 21 0 1 1 2 9945 1 V 13 2 1 1 3 2 2 3 3 57 11 1 17 1 3 2 10 0 2 9901

17. Log Odds Matrices PAM matrices converted to log-odds matrix –Calculate odds ratio for each substitution Taking scores in previous matrix Divide by frequency of amino acid –Convert ratio to log10 and multiply by 10 –Take average of log odds ratio for converting A to B and converting B to A –Result: Symmetric matrix

18. PAM250 Log odds matrix Entry (i,i) is greater than any entry (i,j), j  i. Entry (i,j): the score of aligning amino acid i against amino acid j. Simliar aa have high score

19. Selecting a PAM Matrix There are different PAM matrices (PAM 1- PAM250). The matrices are derived from each other by multiplying the PAM1 matrices N times Low PAM numbers: short sequences, strong local similarities. High PAM numbers: long sequences, weak similarities. –PAM120 recommended for general use (40% identity) –PAM60 for close relations (60% identity) –PAM250 for distant relations (20% identity) If uncertain, try several different matrices –PAM40, PAM120, PAM250 recommended

20. BLOSUM Blocks Substitution Matrix –Steven and Jorga G. Henikoff (1992) Based on BLOCKS database ( www.blocks.fhcrc.org) –Families of proteins with identical function –Highly conserved protein domains Ungapped local alignment to identify motifs –Each motif is a block of local alignment –Counts amino acids observed in same column –Symmetrical model of substitution AABCDA… BBCDA DABCDA. A.BBCBB BBBCDABA.BCCAA AAACDAC.DCBCDB CCBADAB.DBBDCC AAACAA… BBCCC

21. BLOSUM Matrices Different BLOSUMn matrices are calculated independently from BLOCKS BLOSUMn is based on blocks that are at most n percent identical.

22. Selecting a BLOSUM Matrix For BLOSUMn, higher n suitable for sequences which are more similar –BLOSUM62 recommended for general use –BLOSUM80 for close relations –BLOSUM45 for distant relations

23. Summary: BLOSUM matrices are based on the replacement patterns found in more highly conserved regions of the sequences without gaps =Loacl alignment PAM matrices based on mutations observed throughout a global alignment, includes both highly conserved and highly mutable regions BLAST uses BLOSUM62 as a default REMEMBER !!!! you can always change it

24. Remote homologues Sometimes BLAST isn’t enough. Large protein family, and BLAST only gives close members. We want more distant members PSI-BLAST

25. [1] Select a query and search it against a protein database [2] PSI-BLAST constructs a multiple sequence alignment then creates a “profile” or specialized position-specific scoring matrix (PSSM) Page 138

26. R,I,KCD,E,TK,R,TN,L,Y,G

27. A R N D C Q E G H I L K M F P S T W Y V 1 M -1 -2 -2 -3 -2 -1 -2 -3 -2 1 2 -2 6 0 -3 -2 -1 -2 -1 1 2 K -1 1 0 1 -4 2 4 -2 0 -3 -3 3 -2 -4 -1 0 -1 -3 -2 -3 3 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 4 V 0 -3 -3 -4 -1 -3 -3 -4 -4 3 1 -3 1 -1 -3 -2 0 -3 -1 4 5 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 6 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 7 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 8 L -1 -3 -3 -4 -1 -3 -3 -4 -3 2 2 -3 1 3 -3 -2 -1 -2 0 3 9 L -1 -3 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 2 10 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 11 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 12 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 13 W -2 -3 -4 -4 -2 -2 -3 -4 -3 1 4 -3 2 1 -3 -3 -2 7 0 0 14 A 3 -2 -1 -2 -1 -1 -2 4 -2 -2 -2 -1 -2 -3 -1 1 -1 -3 -3 -1 15 A 2 -1 0 -1 -2 2 0 2 -1 -3 -3 0 -2 -3 -1 3 0 -3 -2 -2 16 A 4 -2 -1 -2 -1 -1 -1 3 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 -1... 37 S 2 -1 0 -1 -1 0 0 0 -1 -2 -3 0 -2 -3 -1 4 1 -3 -2 -2 38 G 0 -3 -1 -2 -3 -2 -2 6 -2 -4 -4 -2 -3 -4 -2 0 -2 -3 -3 -4 39 T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5 -3 -2 0 40 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 41 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -2 -1 -2 -1 3 -3 -2 -2 2 7 -1 42 A 4 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0

28. A R N D C Q E G H I L K M F P S T W Y V 1 M -1 -2 -2 -3 -2 -1 -2 -3 -2 1 2 -2 6 0 -3 -2 -1 -2 -1 1 2 K -1 1 0 1 -4 2 4 -2 0 -3 -3 3 -2 -4 -1 0 -1 -3 -2 -3 3 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 4 V 0 -3 -3 -4 -1 -3 -3 -4 -4 3 1 -3 1 -1 -3 -2 0 -3 -1 4 5 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 6 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 7 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 8 L -1 -3 -3 -4 -1 -3 -3 -4 -3 2 2 -3 1 3 -3 -2 -1 -2 0 3 9 L -1 -3 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 2 10 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 11 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 12 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 13 W -2 -3 -4 -4 -2 -2 -3 -4 -3 1 4 -3 2 1 -3 -3 -2 7 0 0 14 A 3 -2 -1 -2 -1 -1 -2 4 -2 -2 -2 -1 -2 -3 -1 1 -1 -3 -3 -1 15 A 2 -1 0 -1 -2 2 0 2 -1 -3 -3 0 -2 -3 -1 3 0 -3 -2 -2 16 A 4 -2 -1 -2 -1 -1 -1 3 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 -1... 37 S 2 -1 0 -1 -1 0 0 0 -1 -2 -3 0 -2 -3 -1 4 1 -3 -2 -2 38 G 0 -3 -1 -2 -3 -2 -2 6 -2 -4 -4 -2 -3 -4 -2 0 -2 -3 -3 -4 39 T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5 -3 -2 0 40 W -3 -3 -4 -5 -3 -2 -3 -3 -3 -3 -2 -3 -2 1 -4 -3 -3 12 2 -3 41 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -2 -1 -2 -1 3 -3 -2 -2 2 7 -1 42 A 4 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0

29. PSI-BLAST [1] Select a query and search it against a protein database [2] PSI-BLAST constructs a multiple sequence alignment then creates a “profile” or specialized position-specific scoring matrix (PSSM) [3] The PSSM is used as a query against the database [4] PSI-BLAST estimates statistical significance (E values) [5] Repeat steps [3] and [4] iteratively, typically 5 times. At each new search, a new profile is used as the query. Page 138

30. Searching for remote homology using PSI-BLAST

31. The universe of lipocalins (each dot is a protein) retinol-binding protein odorant-binding protein apolipoprotein D Retinol binding Protein B-lactoglubolin

32. Score = 46.2 bits (108), Expect = 2e-04 Identities = 40/150 (26%), Positives = 70/150 (46%), Gaps = 37/150 (24%) Query: 27 VKENFDKARFSGTWYAMAKKDPEGLFLQDNIVAEFSVDETGQMSATAKGRVRLLNNWDVC 86 V+ENFD ++ G WY + +K P + I A +S+ E G + K ++ Sbjct: 33 VQENFDVKKYLGRWYEI-EKIPASFEKGNCIQANYSLMENGNIEVLNK---------ELS 82 Query: 87 ADMVGTF---------TDTEDPAKFKMKYWGVASFLQKGNDDHWIVDTDYDTYAVQYSCR 137 D GT ++ +PAK +++++ + +WI+ TDY+ YA+ YSC Sbjct: 83 PD--GTMNQVKGEAKQSNVSEPAKLEVQFFPLMP-----PAPYWILATDYENYALVYSCT 135 Query: 138 ----LLNLDGTCADSYSFVFSRDPNGLPPE 163 L ++D + ++ R+P LPPE Sbjct: 136 TFFWLFHVD------FFWILGRNPY-LPPE 158 PSI-BLAST alignment of RBP (retinol binding protein) and  -lactoglobulin: iteration 1 Example is taken from Bioinformatics and Functional Genomics by Jonathan Pevsner (ISBN 0-471-21004-8). Copyright © 2003 by John Wiley & Sons, Inc.

33. PSI-BLAST alignment of RBP and  -lactoglobulin: iteration 2 Score = 140 bits (353), Expect = 1e-32 Identities = 45/176 (25%), Positives = 78/176 (43%), Gaps = 33/176 (18%) Query: 4 VWALLLLAAWAAAERDCRVSSF--------RVKENFDKARFSGTWYAMAKKDPEGLFLQD 55 V L+ LA A + +F V+ENFD ++ G WY + +K P + Sbjct: 2 VTMLMFLATLAGLFTTAKGQNFHLGKCPSPPVQENFDVKKYLGRWYEI-EKIPASFEKGN 60 Query: 56 NIVAEFSVDETGQMSATAKGRVRLLNNWDVCADMV---GTFTDTEDPAKFKMKYWGVASF 112 I A +S+ E G + K + D + V ++ +PAK +++++ + Sbjct: 61 CIQANYSLMENGNIEVLNKEL-----SPDGTMNQVKGEAKQSNVSEPAKLEVQFFPL--- 112 Query: 113 LQKGNDDHWIVDTDYDTYAVQYSCR----LLNLDGTCADSYSFVFSRDPNGLPPEA 164 +WI+ TDY+ YA+ YSC L ++D + ++ R+P LPPE Sbjct: 113 --MPPAPYWILATDYENYALVYSCTTFFWLFHVD------FFWILGRNPY-LPPET 159

34. PSI-BLAST alignment of RBP and  -lactoglobulin: iteration 3 Score = 159 bits (404), Expect = 1e-38 Identities = 41/170 (24%), Positives = 69/170 (40%), Gaps = 19/170 (11%) Query: 3 WVWALLLLAAWAAAERD--------CRVSSFRVKENFDKARFSGTWYAMAKKDPEGLFLQ 54 V L+ LA A + S V+ENFD ++ G WY + K Sbjct: 1 MVTMLMFLATLAGLFTTAKGQNFHLGKCPSPPVQENFDVKKYLGRWYEIEKIPASFE-KG 59 Query: 55 DNIVAEFSVDETGQMSATAKGRVRLLNNWDVCADMVGTFTDTEDPAKFKMKYWGVASFLQ 114 + I A +S+ E G + K V + ++ +PAK +++++ + Sbjct: 60 NCIQANYSLMENGNIEVLNKELSPDGTMNQVKGE--AKQSNVSEPAKLEVQFFPL----- 112 Query: 115 KGNDDHWIVDTDYDTYAVQYSCRLLNLDGTCADSYSFVFSRDPNGLPPEA 164 +WI+ TDY+ YA+ YSC + ++ R+P LPPE Sbjct: 113 MPPAPYWILATDYENYALVYSCTTFFWL--FHVDFFWILGRNPY-LPPET 159

35. Score = 159 bits (404), Expect = 1e-38 Identities = 41/170 (24%), Positives = 69/170 (40%), Gaps = 19/170 (11%) Query: 3 WVWALLLLAAWAAAERD--------CRVSSFRVKENFDKARFSGTWYAMAKKDPEGLFLQ 54 V L+ LA A + S V+ENFD ++ G WY + K Sbjct: 1 MVTMLMFLATLAGLFTTAKGQNFHLGKCPSPPVQENFDVKKYLGRWYEIEKIPASFE-KG 59 Query: 55 DNIVAEFSVDETGQMSATAKGRVRLLNNWDVCADMVGTFTDTEDPAKFKMKYWGVASFLQ 114 + I A +S+ E G + K V + ++ +PAK +++++ + Sbjct: 60 NCIQANYSLMENGNIEVLNKELSPDGTMNQVKGE--AKQSNVSEPAKLEVQFFPL----- 112 Query: 115 KGNDDHWIVDTDYDTYAVQYSCRLLNLDGTCADSYSFVFSRDPNGLPPEA 164 +WI+ TDY+ YA+ YSC + ++ R+P LPPE Sbjct: 113 MPPAPYWILATDYENYALVYSCTTFFWL--FHVDFFWILGRNPY-LPPET 159 Score = 46.2 bits (108), Expect = 2e-04 Identities = 40/150 (26%), Positives = 70/150 (46%), Gaps = 37/150 (24%) Query: 27 VKENFDKARFSGTWYAMAKKDPEGLFLQDNIVAEFSVDETGQMSATAKGRVRLLNNWDVC 86 V+ENFD ++ G WY + +K P + I A +S+ E G + K ++ Sbjct: 33 VQENFDVKKYLGRWYEI-EKIPASFEKGNCIQANYSLMENGNIEVLNK---------ELS 82 Query: 87 ADMVGTF---------TDTEDPAKFKMKYWGVASFLQKGNDDHWIVDTDYDTYAVQYSCR 137 D GT ++ +PAK +++++ + +WI+ TDY+ YA+ YSC Sbjct: 83 PD--GTMNQVKGEAKQSNVSEPAKLEVQFFPLMP-----PAPYWILATDYENYALVYSCT 135 Query: 138 ----LLNLDGTCADSYSFVFSRDPNGLPPE 163 L ++D + ++ R+P LPPE Sbjct: 136 TFFWLFHVD------FFWILGRNPY-LPPE 158 1 3

36. The universe of lipocalins (each dot is a protein) retinol-binding protein odorant-binding protein apolipoprotein D

37. Scoring matrices let you focus on the big (or small) picture retinol-binding protein

38. Scoring matrices let you focus on the big (or small) picture retinol-binding protein retinol-binding protein PAM250 PAM30 Blosum45 Blosum80

39. PSI-BLAST generates scoring matrices more powerful than PAM or BLOSUM retinol-binding protein retinol-binding protein

40. PSI-BLAST -PSI-BLAST is useful to detect weak but biologically meaningful relationships between proteins. -The main source of false positives is the spurious amplification of sequences not related to the query. -Once even a single spurious protein is included in a PSI-BLAST search above threshold, it will not go away. Page 144

41. PSI-BLAST Three approaches to prevent false positive results: [1] Apply filtering [2] Adjust E value to a lower value [3] Visually inspect the output from each iteration. Remove suspicious hits. Page 144