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Introduction to bioinformatics Lecture 7 Multiple sequence alignment (1)

Introduction to bioinformatics Lecture 7 Multiple sequence alignment (1). Global or Local Pairwise alignment. B. B. C. A. A. B. A. A. C. A. B. C. A. Local. B. Local. A. B. C. A. B. C. B. A. Global. Global. B. A. C. A. Globin fold  protein myoglobin PDB: 1MBN.

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Introduction to bioinformatics Lecture 7 Multiple sequence alignment (1)

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  1. Introduction to bioinformaticsLecture 7 Multiple sequence alignment (1)

  2. Global or Local Pairwise alignment B B C A A B A A C A B C A Local B Local A B C A B C B A Global Global B A C A

  3. Globin fold  protein myoglobin PDB: 1MBN Helices are labelled ‘A’ (blue) to ‘H’ (red). D helix can be missing in some globins: what happens with alignment?

  4.  sandwich  protein immunoglobulin PDB: 7FAB

  5. TIM barrel  /  protein Triose phosphate IsoMerase PDB: 1TIM

  6. Pyruvate kinase Phosphotransferase b barrel regulatory domain a/b barrel catalytic substrate binding domain a/b nucleotide binding domain

  7. What does this mean for alignments? • Alignments need to be able to skip secondary structural elements to complete domains (i.e. putting gaps opposite these motifs in the shorter sequence). • Depending on gap penalties chosen, the algorithm might have difficulty with making such long gaps (for example when using high affine gap penalties), resulting in incorrect alignment.

  8. There are three kinds of pairwise alignments • Global alignment – align all residues in both sequences; all gaps are penalised • Semi-global alignment – align all residues in both sequences; end gaps are not penalised (zero end gap penalties) • Local alignment – align part of each sequence; end gaps are not applicable

  9. Easy global DP recipe for using affine gap penalties (after Gotoh) j-1 Penalty = Pi + gap_length*Pe Max{S0<x<i-1, j-1- Pi - (i-x-1)Px} Si-1,j-1 Max{Si-1, 0<y<j-1 - Pi - (j-y-1)Px} Si,j = si,j + Max i-1 • M[i,j] is optimal alignment (highest scoring alignment until [i, j]) • At each cell [i, j] in search matrix, check Max coming from: any cell in preceding row until j-2: add score for cell[i, j] minus appropriate gap penalties; any cell in preceding column until i-2: add score for cell[i, j] minus appropriate gap penalties; or cell[i-1, j-1]: add score for cell[i, j] • Select highest scoring cell in bottom row and rightmost column and do trace-back

  10. Let’s do an example: global alignmentGotoh’s DP algorithm with affine gap penalties (PAM250, Pi=10, Pe=2) PAM250 Cell (D2, T4) can alternatively come from two cells (same score): ‘high-road’ or ‘low-road’ Row and column ‘0’ are filled with 0, -12, -14, -16, … if global alignment is used (for N-terminal end-gaps); also extra row and column at the end to calculate the score including C-terminal end-gap penalties.

  11. Let’s do another example: semi-global alignmentGotoh’s DP algorithm with affine gap penalties (PAM250, Pi=10, Pe=2) PAM250 Starting row and column ‘0’, and extra column at right or extra row at bottom is not necessary when using semi global alignment (zero end-gaps). Rest works as under global alignment.

  12. Easy local DP recipe for using affine gap penalties (after Gotoh) j-1 Penalty = Pi + gap_length*Pe Si,j + Max{S0<x<i-1,j-1 - Pi - (i-x-1)Px} Si,j + Si-1,j-1 Si,j + Max {Si-1,0<y<j-1 - Pi - (j-y-1)Px} 0 Si,j = Max i-1 • M[i,j] is optimal alignment (highest scoring alignment until [i, j]) • At each cell [i, j] in search matrix, check Max coming from: any cell in preceding row until j-2: add score for cell[i, j] minus appropriate gap penalties; any cell in preceding column until i-2: add score for cell[i, j] minus appropriate gap penalties; or cell[i-1, j-1]: add score for cell[i, j] • Select highest scoring cell anywhere in matrix and do trace-back until zero-valued cell or start of sequence(s)

  13. Let’s do yet another example: local alignmentGotoh’s DP algorithm with affine gap penalties (PAM250, Pi=10, Pe=2) PAM250 Extra start/end columns/rows not necessary (no end-gaps). Each negative scoring cell is set to zero. Highest scoring cell may be found anywhere in search matrix after calculating it. Trace highest scoring cell back to first cell with zero value (or the beginning of one or both sequences)

  14. For your first exam D1:Make sure you understand and can carry out Gotoh’s algorithm for global, semi-global and local alignment!This is the most general Dynamic Programming (DP) algorithm (and perhaps the easiest to understand) Gotoh, O. An Improved Algorithm for Matching Biological Sequences. J. Mol. Biol., 162, pp. 705-708,1982.

  15. Pairwise alignment • Now we know how to do it: • How do we get a multiple alignment (three or more sequences)? • Multiple alignment: much greater combinatorial explosion than with pairwise alignment…..

  16. Multiple sequence alignment (MSA) Why • One of he most important means to find out about: • Conservation patterns leading to functional clues • Possible protein structure • Multiple sequence alignment contains far more information about conservation than pairwise alignment • Many bioinformatics methods use MSA as input: e.g. secondary structure prediction (later lecture)

  17. Multiple sequence alignment Wanted • Quality • Quality • Quality • Programs need to be fully automatic for genomic pipelines • With available genomes (data explosion), speed becomes crucial

  18. Simultaneous Multiple alignmentMulti-dimensional dynamic programming (Murata et al. 1985)

  19. Simultaneous Multiple alignmentMulti-dimensional dynamic programming MSA (Lipman et al., 1989, PNAS86, 4412) • extremely slow and memory intensive • up to 8-9 sequences of ~250 residues DCA (Stoye et al., 1997, CABIOS13, 625) • still very slow

  20. Alternative multiple alignment methods • Biopat (first complete MSA method ever; Hogeweg Hesper 1984) • MULTAL (Taylor 1987) • DIALIGN (Morgenstern 1996) • PRRP (Gotoh 1996) • Clustal (Thompson Higgins Gibson 1994) • Praline (Heringa 1999) • T-Coffee (Notredame et al. 2000) • HMMER (Eddy 1998) [Hidden Markov Models] • SAGA (Notredame 1996) [Genetic algorithm] • POA (Lee et al. 2002) • MUSCLE (Edgar 2004)

  21. The following three slides are examples of multiple alignments of 13 flavodoxin and 1 cheY sequence (PDB code 3chy).The cheY sequence is a very distant relative of the flavodoxin family, but has the same basic fold

  22. CLUSTAL X (1.64b) multiple sequence alignment Flavodoxin-cheY 1fx1 -PKALIVYGSTTGNTEYTAETIARQLANAG-Y-EVDSRDAASVEAGGLFEGFDLVLLGCSTWGDDSIE------LQDDFIPLFD-SLEETGAQGRK FLAV_DESVH MPKALIVYGSTTGNTEYTAETIARELADAG-Y-EVDSRDAASVEAGGLFEGFDLVLLGCSTWGDDSIE------LQDDFIPLFD-SLEETGAQGRK FLAV_DESGI MPKALIVYGSTTGNTEGVAEAIAKTLNSEG-M-ETTVVNVADVTAPGLAEGYDVVLLGCSTWGDDEIE------LQEDFVPLYE-DLDRAGLKDKK FLAV_DESSA MSKSLIVYGSTTGNTETAAEYVAEAFENKE-I-DVELKNVTDVSVADLGNGYDIVLFGCSTWGEEEIE------LQDDFIPLYD-SLENADLKGKK FLAV_DESDE MSKVLIVFGSSTGNTESIAQKLEELIAAGG-H-EVTLLNAADASAENLADGYDAVLFGCSAWGMEDLE------MQDDFLSLFE-EFNRFGLAGRK FLAV_CLOAB -MKISILYSSKTGKTERVAKLIEEGVKRSGNI-EVKTMNLDAVDKKFLQE-SEGIIFGTPTYYAN---------ISWEMKKWID-ESSEFNLEGKL FLAV_MEGEL --MVEIVYWSGTGNTEAMANEIEAAVKAAG-A-DVESVRFEDTNVDDVAS-KDVILLGCPAMGSE--E------LEDSVVEPFF-TDLAPKLKGKK 4fxn ---MKIVYWSGTGNTEKMAELIAKGIIESG-K-DVNTINVSDVNIDELLN-EDILILGCSAMGDE--V------LEESEFEPFI-EEISTKISGKK FLAV_ANASP SKKIGLFYGTQTGKTESVAEIIRDEFGNDVVT----LHDVSQAEVTDLND-YQYLIIGCPTWNIGELQ---SD-----WEGLYS-ELDDVDFNGKL FLAV_AZOVI -AKIGLFFGSNTGKTRKVAKSIKKRFDDETMSD---ALNVNRVSAEDFAQ-YQFLILGTPTLGEGELPGLSSDCENESWEEFLP-KIEGLDFSGKT 2fcr --KIGIFFSTSTGNTTEVADFIGKTLGAKADAP---IDVDDVTDPQALKD-YDLLFLGAPTWNTGADTERSGT----SWDEFLYDKLPEVDMKDLP FLAV_ENTAG MATIGIFFGSDTGQTRKVAKLIHQKLDGIADAP---LDVRRATREQFLS--YPVLLLGTPTLGDGELPGVEAGSQYDSWQEFTN-TLSEADLTGKT FLAV_ECOLI -AITGIFFGSDTGNTENIAKMIQKQLGKDVAD----VHDIAKSSKEDLEA-YDILLLGIPTWYYGEAQ-CD-------WDDFFP-TLEEIDFNGKL 3chy --ADKELKFLVVDDFSTMRRIVRNLLKELG----FNNVEEAEDGVDALN------KLQAGGYGFV--I------SDWNMPNMDG-LELLKTIR--- . ... : . . : 1fx1 VACFGCGDSSYEYF--CGAVDAIEEKLKNLGAEIVQDG----------------LRIDGDPRAARDDIVGWAHDVRGAI--------------- FLAV_DESVH VACFGCGDSSYEYF--CGAVDAIEEKLKNLGAEIVQDG----------------LRIDGDPRAARDDIVGWAHDVRGAI--------------- FLAV_DESGI VGVFGCGDSSYTYF--CGAVDVIEKKAEELGATLVASS----------------LKIDGEPDSAE--VLDWAREVLARV--------------- FLAV_DESSA VSVFGCGDSDYTYF--CGAVDAIEEKLEKMGAVVIGDS----------------LKIDGDPERDE--IVSWGSGIADKI--------------- FLAV_DESDE VAAFASGDQEYEHF--CGAVPAIEERAKELGATIIAEG----------------LKMEGDASNDPEAVASFAEDVLKQL--------------- FLAV_CLOAB GAAFSTANSIAGGS--DIALLTILNHLMVKGMLVYSGGVA----FGKPKTHLGYVHINEIQENEDENARIFGERIANKVKQIF----------- FLAV_MEGEL VGLFGSYGWGSGE-----WMDAWKQRTEDTGATVIGTA----------------IVN-EMPDNAPECKE-LGEAAAKA---------------- 4fxn VALFGSYGWGDGK-----WMRDFEERMNGYGCVVVETP----------------LIVQNEPDEAEQDCIEFGKKIANI---------------- FLAV_ANASP VAYFGTGDQIGYADNFQDAIGILEEKISQRGGKTVGYWSTDGYDFNDSKALR-NGKFVGLALDEDNQSDLTDDRIKSWVAQLKSEFGL------ FLAV_AZOVI VALFGLGDQVGYPENYLDALGELYSFFKDRGAKIVGSWSTDGYEFESSEAVV-DGKFVGLALDLDNQSGKTDERVAAWLAQIAPEFGLSL---- 2fcr VAIFGLGDAEGYPDNFCDAIEEIHDCFAKQGAKPVGFSNPDDYDYEESKSVR-DGKFLGLPLDMVNDQIPMEKRVAGWVEAVVSETGV------ FLAV_ENTAG VALFGLGDQLNYSKNFVSAMRILYDLVIARGACVVGNWPREGYKFSFSAALLENNEFVGLPLDQENQYDLTEERIDSWLEKLKPAVL------- FLAV_ECOLI VALFGCGDQEDYAEYFCDALGTIRDIIEPRGATIVGHWPTAGYHFEASKGLADDDHFVGLAIDEDRQPELTAERVEKWVKQISEELHLDEILNA 3chy AD--GAMSALPVL-----MVTAEAKKENIIAAAQAGAS----------------GYV-VKPFTAATLEEKLNKIFEKLGM-------------- . . : . .

  23. Flavodoxin-cheY: Global Pre-processing (prepro1500) 1fx1 -PKALIVYGSTTGNT-EYTAETIARQLANAG-YEVDSRDAASVEAGGLFEGFDLVLLGCSTWGDDSI------ELQDDFIPLF-DSLEETGAQGRKVACF FLAV_DESDE MSKVLIVFGSSTGNT-ESIaQKLEELIAAGG-HEVTLLNAADASAENLADGYDAVLFgCSAWGMEDL------EMQDDFLSLF-EEFNRFGLAGRKVAAf FLAV_DESVH MPKALIVYGSTTGNT-EYTaETIARELADAG-YEVDSRDAASVEAGGLFEGFDLVLLgCSTWGDDSI------ELQDDFIPLF-DSLEETGAQGRKVACf FLAV_DESSA MSKSLIVYGSTTGNT-ETAaEYVAEAFENKE-IDVELKNVTDVSVADLGNGYDIVLFgCSTWGEEEI------ELQDDFIPLY-DSLENADLKGKKVSVf FLAV_DESGI MPKALIVYGSTTGNT-EGVaEAIAKTLNSEG-METTVVNVADVTAPGLAEGYDVVLLgCSTWGDDEI------ELQEDFVPLY-EDLDRAGLKDKKVGVf 2fcr --KIGIFFSTSTGNT-TEVADFIGKTLGA---KADAPIDVDDVTDPQALKDYDLLFLGAPTWNTG----ADTERSGTSWDEFLYDKLPEVDMKDLPVAIF FLAV_AZOVI -AKIGLFFGSNTGKT-RKVaKSIKKRFDDET-MSDA-LNVNRVS-AEDFAQYQFLILgTPTLGEGELPGLSSDCENESWEEFL-PKIEGLDFSGKTVALf FLAV_ENTAG MATIGIFFGSDTGQT-RKVaKLIHQKLDG---IADAPLDVRRAT-REQFLSYPVLLLgTPTLGDGELPGVEAGSQYDSWQEFT-NTLSEADLTGKTVALf FLAV_ANASP SKKIGLFYGTQTGKT-ESVaEIIRDEFGN---DVVTLHDVSQAE-VTDLNDYQYLIIgCPTWNIGEL--------QSDWEGLY-SELDDVDFNGKLVAYf FLAV_ECOLI -AITGIFFGSDTGNT-ENIaKMIQKQLGK---DVADVHDIAKSS-KEDLEAYDILLLgIPTWYYGE--------AQCDWDDFF-PTLEEIDFNGKLVALf 4fxn -MK--IVYWSGTGNT-EKMAELIAKGIIESG-KDVNTINVSDVNIDELL-NEDILILGCSAMGDEVL-------EESEFEPFI-EEIS-TKISGKKVALF FLAV_MEGEL MVE--IVYWSGTGNT-EAMaNEIEAAVKAAG-ADVESVRFEDTNVDDVA-SKDVILLgCPAMGSEEL-------EDSVVEPFF-TDLA-PKLKGKKVGLf FLAV_CLOAB -MKISILYSSKTGKT-ERVaKLIEEGVKRSGNIEVKTMNLDAVD-KKFLQESEGIIFgTPTYYAN---------ISWEMKKWI-DESSEFNLEGKLGAAf 3chy ADKELKFLVVDDFSTMRRIVRNLLKELGFN--NVEEAEDGVDALNKLQAGGYGFVI---SDWNMPNM----------DGLELL-KTIRADGAMSALPVLM T 1fx1 GCGDS-SY-EYFCGA-VDAIEEKLKNLGAEIVQD---------------------GLRIDGD--PRAARDDIVGWAHDVRGAI-------- FLAV_DESDE ASGDQ-EY-EHFCGA-VPAIEERAKELgATIIAE---------------------GLKMEGD--ASNDPEAVASfAEDVLKQL-------- FLAV_DESVH GCGDS-SY-EYFCGA-VDAIEEKLKNLgAEIVQD---------------------GLRIDGD--PRAARDDIVGwAHDVRGAI-------- FLAV_DESSA GCGDS-DY-TYFCGA-VDAIEEKLEKMgAVVIGD---------------------SLKIDGD--PE--RDEIVSwGSGIADKI-------- FLAV_DESGI GCGDS-SY-TYFCGA-VDVIEKKAEELgATLVAS---------------------SLKIDGE--PD--SAEVLDwAREVLARV-------- 2fcr GLGDAEGYPDNFCDA-IEEIHDCFAKQGAKPVGFSNPDDYDYEESKS-VRDGKFLGLPLDMVNDQIPMEKRVAGWVEAVVSETGV------ FLAV_AZOVI GLGDQVGYPENYLDA-LGELYSFFKDRgAKIVGSWSTDGYEFESSEA-VVDGKFVGLALDLDNQSGKTDERVAAwLAQIAPEFGLS--L-- FLAV_ENTAG GLGDQLNYSKNFVSA-MRILYDLVIARgACVVGNWPREGYKFSFSAALLENNEFVGLPLDQENQYDLTEERIDSwLEKLKPAV-L------ FLAV_ANASP GTGDQIGYADNFQDA-IGILEEKISQRgGKTVGYWSTDGYDFNDSKA-LRNGKFVGLALDEDNQSDLTDDRIKSwVAQLKSEFGL------ FLAV_ECOLI GCGDQEDYAEYFCDA-LGTIRDIIEPRgATIVGHWPTAGYHFEASKGLADDDHFVGLAIDEDRQPELTAERVEKwVKQISEELHLDEILNA 4fxn G-----SY-GWGDGKWMRDFEERMNGYGCVVVET---------------------PLIVQNE--PDEAEQDCIEFGKKIANI--------- FLAV_MEGEL G-----SY-GWGSGEWMDAWKQRTEDTgATVIGT----------------------AIVNEM--PDNA-PECKElGEAAAKA--------- FLAV_CLOAB STANSIAGGSDIA---LLTILNHLMVKgMLVYSG----GVAFGKPKTHLGYVHINEIQENEDENARIfGERiANkVKQIF----------- 3chy VTAEAKK--ENIIAA---------AQAGAS-------------------------GYVV-----KPFTAATLEEKLNKIFEKLGM------ G Iteration 0 SP= 136944.00 AvSP= 10.675 SId= 4009 AvSId= 0.313

  24. Flavodoxin-cheY: Local Pre-processing(locprepro300) • 1fx1 --PKALIVYGSTTGNTEYTAETIARQLANAGYEVDSRDAASVEAGGLFEGFDLVLLGCSTWGDDSI------ELQDDFIPL--FDSLEETGAQGRKVACF • FLAV_DESVH -MPKALIVYGSTTGNTEYTaETIARELADAGYEVDSRDAASVEAGGLFEGFDLVLLgCSTWGDDSI------ELQDDFIPL--FDSLEETGAQGRKVACf • FLAV_DESSA -MSKSLIVYGSTTGNTETAaEYVAEAFENKEIDVELKNVTDVSVADLGNGYDIVLFgCSTWGEEEI------ELQDDFIPL--YDSLENADLKGKKVSVf • FLAV_DESGI -MPKALIVYGSTTGNTEGVaEAIAKTLNSEGMETTVVNVADVTAPGLAEGYDVVLLgCSTWGDDEI------ELQEDFVPL--YEDLDRAGLKDKKVGVf • FLAV_DESDE -MSKVLIVFGSSTGNTESIaQKLEELIAAGGHEVTLLNAADASAENLADGYDAVLFgCSAWGMEDL------EMQDDFLSL--FEEFNRFGLAGRKVAAf • 4fxn --MK--IVYWSGTGNTEKMAELIAKGIIESGKDVNTINVSDVNIDELLN-EDILILGCSAMGDEVL------E-ESEFEPF--IEEIS-TKISGKKVALF • FLAV_MEGEL -MVE--IVYWSGTGNTEAMaNEIEAAVKAAGADVESVRFEDTNVDDVAS-KDVILLgCPAMGSEEL------E-DSVVEPF--FTDLA-PKLKGKKVGLf • 2fcr ---KIGIFFSTSTGNTTEVADFIGKTLGAKADAPI--DVDDVTDPQALKDYDLLFLGAPTWNTGAD----TERSGTSWDEFL-YDKLPEVDMKDLPVAIF • FLAV_ANASP -SKKIGLFYGTQTGKTESVaEIIRDEFGNDVVTLH--DVSQAEV-TDLNDYQYLIIgCPTWNIGEL--------QSDWEGL--YSELDDVDFNGKLVAYf • FLAV_AZOVI --AKIGLFFGSNTGKTRKVaKSIKKRFDDETMSDA-LNVNRVSA-EDFAQYQFLILgTPTLGEGELPGLSSDCENESWEEF--LPKIEGLDFSGKTVALf • FLAV_ENTAG -MATIGIFFGSDTGQTRKVaKLIHQKLDG--IADAPLDVRRATR-EQFLSYPVLLLgTPTLGDGELPGVEAGSQYDSWQEF--TNTLSEADLTGKTVALf • FLAV_ECOLI --AITGIFFGSDTGNTENIaKMIQKQLGKDVADVH--DIAKSSK-EDLEAYDILLLgIPTWYYGEA--------QCDWDDF--FPTLEEIDFNGKLVALf • FLAV_CLOAB --MKISILYSSKTGKTERVaKLIEEGVKRSGNIEVKTMNLDAVDKKFLQESEGIIFgTPTYYA-----------NISWEMKKWIDESSEFNLEGKLGAAf • 3chy ADKELKFLVVDDFSTMRRIVRNLLKELGFNNVEEAEDGVDALNKLQ-AGGYGFVI---SDWNMPNM----------DGLEL--LKTIRADGAMSALPVLM • 1fx1 GCGDS--SY-EYFCGA-VD--AIEEKLKNLGAEIVQD---------------------GLRID--GDPRAARDDIVGWAHDVRGAI-------- • FLAV_DESVH GCGDS--SY-EYFCGA-VD--AIEEKLKNLgAEIVQD---------------------GLRID--GDPRAARDDIVGwAHDVRGAI-------- • FLAV_DESSA GCGDS--DY-TYFCGA-VD--AIEEKLEKMgAVVIGD---------------------SLKID--GDPE--RDEIVSwGSGIADKI-------- • FLAV_DESGI GCGDS--SY-TYFCGA-VD--VIEKKAEELgATLVAS---------------------SLKID--GEPD--SAEVLDwAREVLARV-------- • FLAV_DESDE ASGDQ--EY-EHFCGA-VP--AIEERAKELgATIIAE---------------------GLKME--GDASNDPEAVASfAEDVLKQL-------- • 4fxn GS------Y-GWGDGKWMR--DFEERMNGYGCVVVET---------------------PLIVQ--NEPDEAEQDCIEFGKKIANI--------- • FLAV_MEGEL GS------Y-GWGSGEWMD--AWKQRTEDTgATVIGT---------------------AI-VN--EMPDNA-PECKElGEAAAKA--------- • 2fcr GLGDAE-GYPDNFCDA-IE--EIHDCFAKQGAKPVGFSNPDDYDYEESKSVRD-GKFLGLPLDMVNDQIPMEKRVAGWVEAVVSETGV------ • FLAV_ANASP GTGDQI-GYADNFQDA-IG--ILEEKISQRgGKTVGYWSTDGYDFNDSKALRN-GKFVGLALDEDNQSDLTDDRIKSwVAQLKSEFGL------ • FLAV_AZOVI GLGDQV-GYPENYLDA-LG--ELYSFFKDRgAKIVGSWSTDGYEFESSEAVVD-GKFVGLALDLDNQSGKTDERVAAwLAQIAPEFGLS--L-- • FLAV_ENTAG GLGDQL-NYSKNFVSA-MR--ILYDLVIARgACVVGNWPREGYKFSFSAALLENNEFVGLPLDQENQYDLTEERIDSwLEKLKPAV-L------ • FLAV_ECOLI GCGDQE-DYAEYFCDA-LG--TIRDIIEPRgATIVGHWPTAGYHFEASKGLADDDHFVGLAIDEDRQPELTAERVEKwVKQISEELHLDEILNA • FLAV_CLOAB STANSIAGGSDIALLTILNHLMVKgMLVYSGGVAFGKPKTHLGYVH----------INEIQENEDENARIfGERiANkVKQIF----------- • 3chy VTAEA---KKENIIAA-----------AQAGAS-------------------------GYVVK-----PFTAATLEEKLNKIFEKLGM------ • G

  25. Flavodoxin-cheY: Pre-processing (prepro1500)

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