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Date: Thu, 3 Feb 2000 04:34:20 -0500 (EST)
From: phd@dodo.cpmc.columbia.edu (PredictProtein)
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Subject: PredictProtein
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The following information has been received by the server:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
reference predict_h6314640 (Feb 3, 2000 04:29:42)
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prediction of: - threading (TOPITS)-
return msf format
ret topits strip
# default: single protein sequence description=course
TTLSCKVTSV EAITDTVYRV RIVPDAAFSF RAGQYLMVVM DERDKRPFSM ASTPDEKGFI
ELHIGASEIN LYAKAVMDRI LKDHQIVVDI PHGEAWLRDD EERPMILIAG GTGFSYARSI
LLTALARNPN RDITIYWGGR EEQHLYDLCE LEALSLKHPG LQVVPVVEQP EAGWRGRTGT
VLTAVLQDHG TLAEHDIYIA GRFEMAKIAR DLFCSERNAR EDRLFGDAFA FI
________________________________________________________________________________
Result of PROSITE search (Amos Bairoch):
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
please quote: A Bairoch, P Bucher & K Hofmann: The PROSITE database,
its status in 1997. Nucl. Acids Res., 1997, 25, 217-221.
________________________________________________________________________________
--------------------------------------------------------
Pattern-ID: PKC_PHOSPHO_SITE PS00005 PDOC00005
Pattern-DE: Protein kinase C phosphorylation site
Pattern: [ST].[RK]
4 SCK
29 SFR
155 SLK
215 SER
Pattern-ID: CK2_PHOSPHO_SITE PS00006 PDOC00006
Pattern-DE: Casein kinase II phosphorylation site
Pattern: [ST].{2}[DE]
8 TSVE
52 STPD
191 TLAE
Pattern-ID: MYRISTYL PS00008 PDOC00008
Pattern-DE: N-myristoylation site
Pattern: G[^EDRKHPFYW].{2}[STAGCN][^P]
111 GTGFSY
179 GTVLTA
________________________________________________________________________________
Result of ProDom domain search (Sonnhammer; Corpet, Gouzy, Kahn):
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
- please quote: ELL Sonnhammer & D Kahn, Prot. Sci., 1994, 3, 482-492
________________________________________________________________________________
--- ------------------------------------------------------------
--- Results from running BLAST against PRODOM domains
---
--- PLEASE quote:
--- F Corpet, J Gouzy, D Kahn (1998). The ProDom database
--- of protein domain families. Nucleic Ac Res 26:323-326.
---
--- BEGIN of BLASTP output
BLASTP 1.4.7 [16-Oct-94] [Build 12:52:03 Oct 30 1994]
Reference: Altschul, Stephen F., Warren Gish, Webb Miller, Eugene W. Myers,
and David J. Lipman (1990). Basic local alignment search tool. J. Mol. Biol.
215:403-10.
Query= prot (#) ppOld, default: single protein sequence description=course
/home/phd/server/work/predict_h6314640
(232 letters)
Database: prodom_99_2
157,167 sequences; 18,560,502 total letters.
Searching..................................................done
Smallest
Sum
High Probability
Sequences producing High-scoring Segment Pairs: Score P(N) N
PD150097 p99.2 (9) UBIB(4) LUXG(3) O85219(1) // REDUCTA... 182 2.7e-37 3
PD023013 p99.2 (3) UBIB(2) P94148(1) // REDUCTASE NADPH... 154 5.8e-15 1
PD175909 p99.2 (1) O86363_MYCTU // HYPOTHETICAL 43.3 KD ... 84 0.00086 1
PD000183 p99.2 (214) NIA(17) FENR(15) NCPR(13) // REDUC... 69 0.0032 2
PD152063 p99.2 (3) ASCD(1) RFBI(1) O31003(1) // CDP6DEO... 43 0.0078 2
PD109318 p99.2 (1) LUXG_VIBHA // PROBABLE FLAVIN REDUCTA... 63 0.066 1
>PD150097 p99.2 (9) UBIB(4) LUXG(3) O85219(1) // REDUCTASE OXIDOREDUCTASE
FLAVOPROTEIN FAD LUMINESCENCE FLAVIN PROBABLE NADPHFLAVIN FERRISIDEROPHORE C
Length = 106
Score = 182 (84.4 bits), Expect = 2.7e-37, Sum P(3) = 2.7e-37
Identities = 32/54 (59%), Positives = 43/54 (79%)
Query: 1 TTLSCKVTSVEAITDTVYRVRIVPDAAFSFRAGQYLMVVMDERDKRPFSMASTP 54
TT++CKV +E +T +YRV + PD F F+AGQYLMVVM+E+DKRPFS+A+ P
Sbjct: 1 TTINCKVEKIEPLTSNIYRVFLKPDQPFEFKAGQYLMVVMNEKDKRPFSIANCP 54
Score = 73 (33.9 bits), Expect = 2.7e-37, Sum P(3) = 2.7e-37
Identities = 11/18 (61%), Positives = 16/18 (88%)
Query: 84 HQIVVDIPHGEAWLRDDE 101
++I +D PHG+AWLRD+E
Sbjct: 89 NEIEIDAPHGDAWLRDEE 106
Score = 69 (32.0 bits), Expect = 2.7e-37, Sum P(3) = 2.7e-37
Identities = 15/23 (65%), Positives = 16/23 (69%)
Query: 59 FIELHIGASEINLYAKAVMDRIL 81
FIELHIG SE N YA VM+ L
Sbjct: 60 FIELHIGGSEHNEYALEVMEHFL 82
>PD023013 p99.2 (3) UBIB(2) P94148(1) // REDUCTASE NADPHFLAVIN OXIDOREDUCTASE
FAD FLAVOPROTEIN FLAVIN FERRISIDEROPHORE C NADP IRON
Length = 31
Score = 154 (71.4 bits), Expect = 5.8e-15, P = 5.8e-15
Identities = 30/31 (96%), Positives = 30/31 (96%)
Query: 202 RFEMAKIARDLFCSERNAREDRLFGDAFAFI 232
RFEMAKIARD FCSERNAREDRLFGDAFAFI
Sbjct: 1 RFEMAKIARDAFCSERNAREDRLFGDAFAFI 31
>PD175909 p99.2 (1) O86363_MYCTU // HYPOTHETICAL 43.3 KD PROTEIN HYPOTHETICAL
PROTEIN
Length = 143
Score = 84 (39.0 bits), Expect = 0.00086, P = 0.00086
Identities = 19/64 (29%), Positives = 35/64 (54%)
Query: 105 MILIAGGTGFSYARSILLTALARNPNRDITIYWGGREEQHLYDLCELEALSLKHPGLQVV 164
++++AG TG + R++++ N + +++G R LYDL L ++ +P L V
Sbjct: 4 VLMVAGSTGLAPLRALIIDLSRFAVNPRVHLFFGARYACELYDLPTLWQIAAHNPWLSVS 63
Query: 165 PVVE 168
PV E
Sbjct: 64 PVSE 67
>PD000183 p99.2 (214) NIA(17) FENR(15) NCPR(13) // REDUCTASE OXIDOREDUCTASE
FAD FLAVOPROTEIN NADP NITRATE HEME NAD ELECTRON MEMBRANE
Length = 139
Score = 69 (32.0 bits), Expect = 0.0032, Sum P(2) = 0.0032
Identities = 14/20 (70%), Positives = 17/20 (85%)
Query: 102 ERPMILIAGGTGFSYARSIL 121
ERP+I+IAGGTG + RSIL
Sbjct: 1 ERPIIMIAGGTGIAPIRSIL 20
Score = 38 (17.6 bits), Expect = 0.0032, Sum P(2) = 0.0032
Identities = 7/23 (30%), Positives = 15/23 (65%)
Query: 132 DITIYWGGREEQHLYDLCELEAL 154
++ +++G R E+ +Y EL+ L
Sbjct: 35 EVYLFYGCRNEEDIYLYEELDEL 57
>PD152063 p99.2 (3) ASCD(1) RFBI(1) O31003(1) // CDP6DEOXYDELTA3 4GLUCOSEEN
REDUCTASE E3 OXIDOREDUCTASE ELECTRON TRANSPORT IRONSULFUR NAD RFBI
Length = 53
Score = 43 (19.9 bits), Expect = 0.0078, Sum P(2) = 0.0078
Identities = 8/20 (40%), Positives = 12/20 (60%)
Query: 2 TLSCKVTSVEAITDTVYRVR 21
T+ CKV S E +T + +R
Sbjct: 16 TIPCKVASFEFVTKDIVSLR 35
Score = 39 (18.1 bits), Expect = 0.0078, Sum P(2) = 0.0078
Identities = 7/18 (38%), Positives = 10/18 (55%)
Query: 19 RVRIVPDAAFSFRAGQYL 36
R R P F++ GQY+
Sbjct: 35 RFRFPPTTKFNYLPGQYI 52
>PD109318 p99.2 (1) LUXG_VIBHA // PROBABLE FLAVIN REDUCTASE EC 1...
LUMINESCENCE OXIDOREDUCTASE FLAVOPROTEIN FAD
Length = 22
Score = 63 (29.2 bits), Expect = 0.069, P = 0.066
Identities = 10/22 (45%), Positives = 16/22 (72%)
Query: 211 DLFCSERNAREDRLFGDAFAFI 232
D FC +R A ++L+ DAFA++
Sbjct: 1 DWFCDKRGAEPEQLYADAFAYL 22
Parameters:
E=0.1
B=500
V=500
-ctxfactor=1.00
Query ----- As Used ----- ----- Computed ----
Frame MatID Matrix name Lambda K H Lambda K H
+0 0 BLOSUM62 0.321 0.139 0.407 same same same
Query
Frame MatID Length Eff.Length E S W T X E2 S2
+0 0 232 232 0.10 72 3 11 22 0.19 33
Statistics:
Query Expected Observed HSPs HSPs
Frame MatID High Score High Score Reportable Reported
+0 0 62 (28.8 bits) 182 (84.4 bits) 10 10
Query Neighborhd Word Excluded Failed Successful Overlaps
Frame MatID Words Hits Hits Extensions Extensions Excluded
+0 0 5411 8213516 1724115 6479666 9733 2
Database: prodom_99_2
Release date: unknown
Posted date: 10:12 PM EDT Jul 29, 1999
# of letters in database: 18,560,502
# of sequences in database: 157,167
# of database sequences satisfying E: 6
No. of states in DFA: 566 (56 KB)
Total size of DFA: 115 KB (128 KB)
Time to generate neighborhood: 0.01u 0.00s 0.01t Real: 00:00:00
Time to search database: 10.95u 0.04s 10.99t Real: 00:00:11
Total cpu time: 10.97u 0.06s 11.03t Real: 00:00:11
--- END of BLASTP output
--- ------------------------------------------------------------
---
--- Again: these results were obtained based on the domain data-
--- base collected by Daniel Kahn and his coworkers in Toulouse.
---
--- PLEASE quote:
--- F Corpet, J Gouzy, D Kahn (1998). The ProDom database
--- of protein domain families. Nucleic Ac Res 26:323-326.
---
--- The general WWW page is on:
---- ---------------------------------------
--- http://www.toulouse.inra.fr/prodom.html
---- ---------------------------------------
---
--- For WWW graphic interfaces to PRODOM, in particular for your
--- protein family, follow the following links (each line is ONE
--- single link for your protein!!):
---
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD150097 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD150097
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD150097 ==> graphical output of all proteins having domain PD150097
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD023013 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD023013
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD023013 ==> graphical output of all proteins having domain PD023013
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD175909 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD175909
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD175909 ==> graphical output of all proteins having domain PD175909
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD000183 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD000183
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD000183 ==> graphical output of all proteins having domain PD000183
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD152063 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD152063
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD152063 ==> graphical output of all proteins having domain PD152063
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom1=PD109318 ==> multiple alignment, consensus, PDB and PROSITE links of domain PD109318
http://www.toulouse.inra.fr/prodom/cgi-bin/ReqProdomII.pl?id_dom2=PD109318 ==> graphical output of all proteins having domain PD109318
---
--- NOTE: if you want to use the link, make sure the entire line
--- is pasted as URL into your browser!
---
--- END of PRODOM
--- ------------------------------------------------------------
________________________________________________________________________________
The alignment that has been used as input to the network is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
---
--- Version of database searched for alignment:
--- SWISS-PROT release 38.0 (7/99) with 80000 proteins
---
--- ------------------------------------------------------------
--- MAXHOM multiple sequence alignment
--- ------------------------------------------------------------
---
--- MAXHOM ALIGNMENT HEADER: ABBREVIATIONS FOR SUMMARY
--- ID : identifier of aligned (homologous) protein
--- STRID : PDB identifier (only for known structures)
--- PIDE : percentage of pairwise sequence identity
--- WSIM : percentage of weighted similarity
--- LALI : number of residues aligned
--- NGAP : number of insertions and deletions (indels)
--- LGAP : number of residues in all indels
--- LSEQ2 : length of aligned sequence
--- ACCNUM : SwissProt accession number
--- NAME : one-line description of aligned protein
---
--- MAXHOM ALIGNMENT HEADER: SUMMARY
ID STRID IDE WSIM LALI NGAP LGAP LEN2 ACCNUM NAME
ubib_ecoli 100 100 232 0 0 232 P23486 NAD(P)H-FLAVIN REDUCTASE
ubib_pholu 73 83 232 0 0 232 P43129 NAD(P)H-FLAVIN REDUCTASE
ubib_vibor 54 69 158 2 5 164 P43128 NAD(P)H-FLAVIN REDUCTASE
ubib_vibfi 53 68 229 3 6 236 P43126 NAD(P)H-FLAVIN REDUCTASE
ubib_vibha 49 66 231 2 5 236 P43127 NAD(P)H-FLAVIN REDUCTASE
luxg_vibfi 41 56 222 2 4 236 P24273 PROBABLE FLAVIN REDUCTASE
luxg_vibha 39 55 229 2 5 233 P16447 PROBABLE FLAVIN REDUCTASE
luxg_phole 37 55 228 2 4 234 P29237 PROBABLE FLAVIN REDUCTASE
ascd_yerps 31 43 224 5 6 328 P37911 CDP-6-DEOXY-DELTA-3,4-GLU
dmpp_psesp 30 39 215 4 33 352 P19734 P5 COMPONENT).
ndor_psepu 28 37 221 2 2 328 Q52126 COMPONENT (EC 1.18.1.3).
rfbi_salty 28 36 222 6 7 330 P26395 RFBI PROTEIN.
benc_acica 25 27 225 6 11 348 P07771 FERREDOXIN; FERREDOXIN--N
---
--- MAXHOM ALIGNMENT: IN MSF FORMAT
MSF of: /home/phd/server/work/predict_h6314640.hsspFilter from: 1 to: 232
/home/phd/server/work/predict_h6314640.msfRet MSF: 232 Type: P 3-Feb-00 04:30:2 Check: 293 ..
Name: predict_h6310 Len: 232 Check: 7806 Weight: 1.00
Name: ubib_ecoli Len: 232 Check: 7806 Weight: 1.00
Name: ubib_pholu Len: 232 Check: 2836 Weight: 1.00
Name: ubib_vibor Len: 232 Check: 4005 Weight: 1.00
Name: ubib_vibfi Len: 232 Check: 5465 Weight: 1.00
Name: ubib_vibha Len: 232 Check: 6148 Weight: 1.00
Name: luxg_vibfi Len: 232 Check: 5710 Weight: 1.00
Name: luxg_vibha Len: 232 Check: 4217 Weight: 1.00
Name: luxg_phole Len: 232 Check: 669 Weight: 1.00
Name: ascd_yerps Len: 232 Check: 3940 Weight: 1.00
Name: dmpp_psesp Len: 232 Check: 6071 Weight: 1.00
Name: ndor_psepu Len: 232 Check: 1435 Weight: 1.00
Name: rfbi_salty Len: 232 Check: 9478 Weight: 1.00
Name: benc_acica Len: 232 Check: 4707 Weight: 1.00
//
1 50
predict_h6310 TTLSCKVTSV EAITDTVYRV RIVPDAAFSF RAGQYLMVVM DERDKRPFSM
ubib_ecoli TTLSCKVTSV EAITDTVYRV RIVPDAAFSF RAGQYLMVVM DERDKRPFSM
ubib_pholu TTLSCKVTSV EAITDTVYRV RLLPDSPFLF RAGQYLMVVM DERDKRPFSM
ubib_vibor .......... .......... .......... .......... .EKDKRPFSI
ubib_vibfi ..INCKVKSI EPLACNTFRI LLHPEQPVAF KAGQYLTVVM GEKDKRPFSI
ubib_vibha .TIQCKVKSI QPLACNTYQI LLHPESPVPF KAGQYLMVVM GEKDKRPFSI
luxg_vibfi .........L ASIKNNIYKV FITVNSPIKF IAGQFVMVTI NG.KKCPFSI
luxg_vibha ..MLCSIEKI EPLTSFIFRV LLKPDQPFEF RAGQYINVSL S.FGSLPFSI
luxg_phole ..FNCKVKKV EASDSHIYKV FIKPDKCFDF KAGQYVIVYL NG.KNLPFSI
ascd_yerps .TYPCKLDSI EFIGeaILSL RLPPTAKIQY LAGQYIDLII NG.QRRSYSI
dmpp_psesp ......VSAL VDLSPTIKGL HIKLDRPMPF QAGQYVNLAL PGIdtRAFSL
ndor_psepu ......VVAV ESPTHDIRRL RVRLSKPFEF SPGQYATLQF SPEHARPYSM
rfbi_salty ..VPCKVNSA VLVSgmTLKL RTPPTAKIGF LPGQYINLHY KG.VTRSYSI
benc_acica HHFEGTLARV ENLSDSTITF DIQLDddIHF LAGQYVNVTL PGteTRSYSF
51 100
predict_h6310 ASTPDEKGFI ELHIGASEIN LYAKAVMDRI LKDHQIVVDI PHGEAWLRDD
ubib_ecoli ASTPDEKGFI ELHIGASEIN LYAKAVMDRI LKDHQIVVDI PHGEAWLRDD
ubib_pholu ASTPSEKEFI ELHIGASELN LYAMAVMDRI LDQKVINIDI PHGKAWFRKS
ubib_vibor ASSPCreGEL ELHIGAAEQN AYALEVVEAM kqDGEITIDA PHGDAWVQEE
ubib_vibfi ASSPCreGEI ELHIGAAEHN AYAGEVVESM ktGGDILIDA PHGEAWIRED
ubib_vibha ASSPCreGEL ELHIGAAEHN AYALEVVEAM qtDGHIEIDA PHGDAWVQEE
luxg_vibfi ANCPTKNHEI ELHIGSSNKD CSLdyFVDAL VEEVAIELDA PHGNAWLRSE
luxg_vibha ASCPSNGAFL ELHIGGSDIS KKNTLVMEEL TNSwmVEVSE ARGKAWLRDE
luxg_phole ANCPTCNELL ELHVGGSVKE SAIEAISHFI NaqKEFTIDA PHGDAWLRDE
ascd_yerps ANAPGGNGNI ELHVRKVVNG VFSNIIFNEL KLQQLLRIEG PQGTFFVRED
dmpp_psesp ANPPSRNDEV ELHVRLVEGG AATGFIHKQL KVGDAVELSG PYGQFFVRDS
ndor_psepu AGLPDDQE.M EFHIRKVPGG RVTEYVFEHV REGTSIKLSG PLGTAYLRQK
rfbi_salty ANSDESNG.I ELHVRNVPNG QMSSLIFGEL QENTLMRIEG PCGTFFIRES
benc_acica SSQPGntGFV VRNVPQGKMS EY...LSVQA KAGDKMSFTG PFGSFYLRDV
101 150
predict_h6310 EERPMILIAG GTGFSYARSI LLTALARNPN RDITIYWGGR EEQHLYDLCE
ubib_ecoli EERPMILIAG GTGFSYARSI LLTALARNPN RDITIYWGGR EEQHLYDLCE
ubib_pholu SANPLLLIAG GTGFSYTRSI LLTALEEQPK RHISMYWGGR ESQHLYDLAE
ubib_vibor SERPLLLIAG GTGFSYVRSI LDHCVAQELK NDIHLYWGGR DECQLYAKSE
ubib_vibfi SDRSMLLIAG GTGFSYVRSI LDHCISQQIQ KPIYLYWGGR DECQLYAKAE
ubib_vibha SERPLLLIAG GTGFSYVRSI LDHCVAQNKT NPIYLYWGAR DNCQLYAKEE
luxg_vibfi SNNPLLLIAG GTGLSYINSI LTNCLNRNIP QDIYLYWGVK NSSLLYEDEE
luxg_vibha SVKPLLLVAG GTGMSYTLSI LKNSLAQGFN QPIYVYWGAK DMENLYVHDE
luxg_phole SQSPLLLIAG GTGLSYINSI LSCCISKQLS QPIYLYWGVN NCNLLYADQQ
ascd_yerps .NLPIVFLAG GTGFAPVKSM VEALINKNDQ RQVHIYWGMP AGHNFYS.DI
dmpp_psesp QAGDLIFIAG GSGLSSPQSM ILDLLERGDT RRITLFQGAR NRAELYNCEL
ndor_psepu HTGPMLCVGG GTGLAPVLSI VRGALKSGMT NPILLYFGVR SQQDLYDAER
rfbi_salty .DRPIIFLAG GTGFAPVKSM VEHLIQGKCR REIYIYWGMQ YSKDFYS.AL
benc_acica .KRPVLMLAG GTGIAPFLSM LQVLEQKGSE HPVRLVFGVT QDCDLVALEQ
151 200
predict_h6310 LEALSLKHPG LQVVPVVEQP EAGWRGRTGT VLTAVLQDHG TLAEHDIYIA
ubib_ecoli LEALSLKHPG LQVVPVVEQP EAGWRGRTGT VLTAVLQDHG TLAEHDIYIA
ubib_pholu LRLLTERYPN LKVIPVVEQS DNGWCGRTGT VLKAVLEDFG SLANYDIYIA
ubib_vibor LEEIAAKHNN VHFVPVVEEA PSEWAGKTGN VLQAVEQDFD SLAEFDIYI.
ubib_vibfi LESIAQAHSH ITFVPVVEKS E.GWTGKTGN VLEAVKADFN SLADMDIYIA
ubib_vibha LVEIADKFAN VHFVPVVEEA PADWQGKVGN VLQAVSEDFE SLENYDIYIA
luxg_vibfi LLELSLNNKN LHYIPVIEDK SEEWIGKKGT VLDAVMEDFT DLAHFDIYVC
luxg_vibha LVDIALENKN VSYVPVTEIS TCPQYAKQGK VLECVMSDFR NLSEFDIYLC
luxg_phole LKTLAAQYRN INYIPVVENL NTDWQGKIGN VIDAVIEDFS DLSDFDIYVC
ascd_yerps ANEWAIKHPN IHYVPVVSGD DSTWTGATGF VHQAVLEDIP DLSLFNVYAC
dmpp_psesp FEELAARHPN FSYVPALNQa dPEWQGFKGF VHDAAKAHfg RLFERDIFME
ndor_psepu LHKLAADHPQ LTVHTVIATG PINEGQRAGL ITDVIEKDIL SLAGWRAYLC
rfbi_salty PQQWSEQHDN VHYIPVVSGD DAEWGGRKGF VHHAVMDDFD SLEFFDIYAC
benc_acica LDALQQKLPW FEYRTVVAHA E.SQHERKGY VTGHIEYDWL NGGEVDVYLC
201 232
predict_h6310 GRFEMAKIAR DLFCSERNAR EDRLFGDAFA FI
ubib_ecoli GRFEMAKIAR DLFCSERNAR EDRLFGDAFA FI
ubib_pholu GRFEMAKIAR ERFCSERDAS ADSMYGDAFE FI
ubib_vibor .......... .......... .......... ..
ubib_vibfi GRFEMAGAAR EQFTTEKQAK KEQLFGDAFA FI
ubib_vibha GRFEMAGAAR EQFTQNKKAK SERMFADAYA FI
luxg_vibfi GPFMMAKTAK EKLIEEKKAK SEQMFADAFA YV
luxg_vibha GPYKMVEVAR DWFCDKRGAE PEQLYADAFA YL
luxg_phole GPFGMSRTAK DILISQKKAN IGKMYSDAFS Y.
ascd_yerps GSLAMITAAR NDFINHGLA. ENKFFSDAF. ..
dmpp_psesp RFYTAADGAG E...SSRSAL FKRI...... ..
ndor_psepu GAPAMV.EAL CTVTKHLGIS PEHIYADAF. ..
rfbi_salty GSPVMIDASK KDFMMKNLS. VEHFYSDAF. ..
benc_acica GPVPMVEAVR SWLDTQGIQP ANFLFEKFSA ..
________________________________________________________________________________
Result of COILS prediction (Andrei Lupas):
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A Lupas: Methods in Enzymology, 1996, 266, 513-525.
version 2.2: Rob B. Russell & Andrei N. Lupas, 1999
________________________________________________________________________________
no coiled-coil above probability 0.5
________________________________________________________________________________
Prediction of:
- secondary structure, by PHDsec
- solvent accessibility, by PHDacc
PHD: Profile fed neural network systems from HeiDelberg
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Author: Burkhard Rost
EMBL, Heidelberg, FRG
Meyerhofstrasse 1, 69 117 Heidelberg
Internet: Predict-Help@EMBL-Heidelberg.DE
All rights reserved.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Secondary structure prediction by PHDsec:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Author: Burkhard Rost
EMBL, Heidelberg, FRG
Meyerhofstrasse 1, 69 117 Heidelberg
Internet: Rost@EMBL-Heidelberg.DE
All rights reserved.
About the network method
~~~~~~~~~~~~~~~~~~~~~~~
The network procedure is described in detail in:
1) Rost, Burkhard; Sander, Chris:
Prediction of protein structure at better than 70% accuracy.
J. Mol. Biol., 1993, 232, 584-599.
A brief description is given in:
Rost, Burkhard; Sander, Chris:
Improved prediction of protein secondary structure by use of se-
quence profiles and neural networks.
Proc. Natl. Acad. Sci. U.S.A., 1993, 90, 7558-7562.
The PHD mail server is described in:
2) Rost, Burkhard; Sander, Chris; Schneider, Reinhard:
PHD - an automatic mail server for protein secondary structure
prediction.
CABIOS, 1994, 10, 53-60.
The latest improvement steps (up to 72%) are explained in:
3) Rost, Burkhard; Sander, Chris:
Combining evolutionary information and neural networks to predict
protein secondary structure.
Proteins, 1994, 19, 55-72.
To be quoted for publications of PHD output:
Papers 1-3 for the prediction of secondary structure and the pre-
diction server.
About the input to the network
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The prediction is performed by a system of neural networks.
The input is a multiple sequence alignment. It is taken from an HSSP
file (produced by the program MaxHom:
Sander, Chris & Schneider, Reinhard: Database of Homology-Derived
Structures and the Structural Meaning of Sequence Alignment.
Proteins, 1991, 9, 56-68.
For optimal results the alignment should contain sequences with varying
degrees of sequence similarity relative to the input protein.
The following is an ideal situation:
+-----------------+----------------------+
| sequence: | sequence identity |
+-----------------+----------------------+
| target sequence | 100 % |
| aligned seq. 1 | 90 % |
| aligned seq. 2 | 80 % |
| ... | ... |
| aligned seq. 7 | 30 % |
+-----------------+----------------------+
Estimated Accuracy of Prediction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A careful cross validation test on some 250 protein chains (in total
about 55,000 residues) with less than 25% pairwise sequence identity
gave the following results:
++================++-----------------------------------------+
|| Qtotal = 72.1% || ("overall three state accuracy") |
++================++-----------------------------------------+
+----------------------------+-----------------------------+
| Qhelix (% of observed)=70% | Qhelix (% of predicted)=77% |
| Qstrand(% of observed)=62% | Qstrand(% of predicted)=64% |
| Qloop (% of observed)=79% | Qloop (% of predicted)=72% |
+----------------------------+-----------------------------+
..........................................................................
These percentages are defined by:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| number of correctly predicted residues
|Qtotal = --------------------------------------- (*100)
| number of all residues
|
| no of res correctly predicted to be in helix
|Qhelix (% of obs) = -------------------------------------------- (*100)
| no of all res observed to be in helix
|
|
| no of res correctly predicted to be in helix
|Qhelix (% of pred)= -------------------------------------------- (*100)
| no of all residues predicted to be in helix
..........................................................................
Averaging over single chains
~~~~~~~~~~~~~~~~~~~~~~~~~~~
The most reasonable way to compute the overall accuracies is the above
quoted percentage of correctly predicted residues. However, since the
user is mainly interested in the expected performance of the prediction
for a particular protein, the mean value when averaging over protein
chains might be of help as well. Computing first the three state
accuracy for each protein chain, and then averaging over 250 chains
yields the following average:
+-------------------------------====--+
| Qtotal/averaged over chains = 72.2% |
+-------------------------------====--+
| standard deviation = 9.3% |
+-------------------------------------+
..........................................................................
Further measures of performance
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Matthews correlation coefficient:
+---------------------------------------------+
| Chelix = 0.63, Cstrand = 0.53, Cloop = 0.52 |
+---------------------------------------------+
..........................................................................
Average length of predicted secondary structure segments:
. +------------+----------+
. | predicted | observed |
+-----------+------------+----------+
| Lhelix = | 10.3 | 9.3 |
| Lstrand = | 5.0 | 5.3 |
| Lloop = | 7.2 | 5.9 |
+-----------+------------+----------+
..........................................................................
The accuracy matrix in detail:
+---------------------------------------+
| number of residues with H, E, L |
+---------+------+------+------+--------+
| |net H |net E |net L |sum obs |
+---------+------+------+------+--------+
| obs H |12447 | 1255 | 3990 | 17692 |
| obs E | 949 | 7493 | 3750 | 12192 |
| obs L | 2604 | 2875 |19962 | 25441 |
+---------+------+------+------+--------+
| sum Net |16000 |11623 |27702 | 55325 |
+---------+------+------+------+--------+
Note: This table is to be read in the following manner:
12447 of all residues predicted to be in helix, were observed to
be in helix, 949 however belong to observed strands, 2604 to
observed loop regions. The term "observed" refers to the DSSP
assignment of secondary structure calculated from 3D coordinates
of experimentally determined structures (Dictionary of Secondary
Structure of Proteins: Kabsch & Sander (1983) Biopolymers, 22,
2577-2637).
Position-specific reliability index
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The network predicts the three secondary structure types using real
numbers from the output units. The prediction is assigned by choosing
the maximal unit ("winner takes all"). However, the real numbers
contain additional information.
E.g. the difference between the maximal and the second largest output
unit can be used to derive a "reliability index". This index is given
for each residue along with the prediction. The index is scaled to
have values between 0 (lowest reliability), and 9 (highest).
The accuracies (Qtot) to be expected for residues with values above a
particular value of the index are given below as well as the fraction
of such residues (%res).:
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| index| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| %res |100.0| 99.2| 90.4| 80.9| 71.6| 62.5| 52.8| 42.3| 29.8| 14.1|
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| | | | | | | | | | | |
| Qtot | 72.1| 72.3| 74.8| 77.7| 80.3| 82.9| 85.7| 88.5| 91.1| 94.2|
| | | | | | | | | | | |
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| H%obs| 70.4| 70.6| 73.7| 77.1| 80.1| 83.1| 86.0| 89.3| 92.5| 96.4|
| E%obs| 61.5| 61.7| 63.7| 66.6| 69.1| 71.7| 74.6| 77.0| 77.8| 68.1|
| | | | | | | | | | | |
| H%prd| 77.8| 78.0| 80.0| 82.6| 84.7| 86.9| 89.2| 91.3| 93.1| 95.4|
| E%prd| 64.5| 64.7| 67.8| 71.0| 74.2| 77.6| 81.4| 85.1| 89.8| 93.5|
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
The above table gives the cumulative results, e.g. 62.5% of all
residues have a reliability of at least 5. The overall three-state
accuracy for this subset of almost two thirds of all residues is 82.9%.
For this subset, e.g., 83.1% of the observed helices are correctly
predicted, and 86.9% of all residues predicted to be in helix are
correct.
..........................................................................
The following table gives the non-cumulative quantities, i.e. the
values per reliability index range. These numbers answer the question:
how reliable is the prediction for all residues labeled with the
particular index i.
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| index| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| %res | 8.8| 9.5| 9.3| 9.1| 9.7| 10.5| 12.5| 15.7| 14.1|
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| | | | | | | | | | |
| Qtot | 46.6| 50.6| 57.7| 62.6| 67.9| 74.2| 82.2| 88.3| 94.2|
| | | | | | | | | | |
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+
| H%obs| 36.8| 42.3| 49.5| 55.2| 61.7| 69.9| 78.8| 87.4| 96.4|
| E%obs| 44.7| 44.5| 52.1| 55.4| 60.9| 68.0| 75.9| 81.0| 68.1|
| | | | | | | | | | |
| H%prd| 49.9| 52.5| 60.3| 64.2| 69.2| 77.5| 85.4| 89.9| 95.4|
| E%prd| 41.7| 47.1| 53.6| 57.0| 64.0| 71.6| 78.8| 88.8| 93.5|
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+
For example, for residues with Relindex = 5 64% of all predicted betha-
strand residues are correctly identified.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Solvent accessibility prediction by PHDacc:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Author: Burkhard Rost
EMBL, Heidelberg, FRG
Meyerhofstrasse 1, 69 117 Heidelberg
Internet: Rost@EMBL-Heidelberg.DE
All rights reserved.
About the network method
~~~~~~~~~~~~~~~~~~~~~~~
The network for prediction of secondary structure is described in
detail in:
Rost, Burkhard; Sander, Chris:
Prediction of protein structure at better than 70% accuracy.
J. Mol. Biol., 1993, 232, 584-599.
The analysis of the prediction of solvent exposure is given in:
Rost, Burkhard; Sander, Chris:
Conservation and prediction of solvent accessibility in protein
families. Proteins, 1994, 20, 216-226.
To be quoted for publications of PHD exposure prediction:
Both papers quoted above.
Definition of accessibility
~~~~~~~~~~~~~~~~~~~~~~~~~~
For training the residue solvent accessibility the DSSP (Dictionary of
Secondary Structure of Proteins; Kabsch & Sander (1983) Biopolymers, 22,
2577-2637) values of accessible surface area have been used. The
prediction provides values for the relative solvent accessibility. The
normalisation is the following:
| ACCESSIBILITY (from DSSP in Angstrom)
|RELATIVE_ACCESSIBILITY = ------------------------------------- * 100
| MAXIMAL_ACC (amino acid type i)
where MAXIMAL_ACC (i) is the maximal accessibility of amino acid type i.
The maximal values are:
+----+----+----+----+----+----+----+----+----+----+----+----+
| A | B | C | D | E | F | G | H | I | K | L | M |
| 106| 160| 135| 163| 194| 197| 84| 184| 169| 205| 164| 188|
+----+----+----+----+----+----+----+----+----+----+----+----+
| N | P | Q | R | S | T | V | W | X | Y | Z |
| 157| 136| 198| 248| 130| 142| 142| 227| 180| 222| 196|
+----+----+----+----+----+----+----+----+----+----+----+
Notation: one letter code for amino acid, B stands for D or N; Z stands
for E or Q; and X stands for undetermined.
The relative solvent accessibility can be used to estimate the number
of water molecules (W) in contact with the residue:
W = ACCESSIBILITY /10
The prediction is given in 10 states for relative accessibility, with
RELATIVE_ACCESSIBILITY = (PREDICTED_ACC * PREDICTED_ACC)
where PREDICTED_ACC = 0 - 9.
Estimated Accuracy of Prediction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A careful cross validation test on some 238 protein chains (in total
about 62,000 residues) with less than 25% pairwise sequence identity
gave the following results:
Correlation
...........
The correlation between observed and predicted solvent accessibility
is:
-----------
corr = 0.53
-----------
This value ought to be compared to the worst and best case prediction
scenario: random prediction (corr = 0.0) and homology modelling
(corr = 0.66). (Note: homology modelling yields a relative accurate
prediction in 3D if, and only if, a significantly identical sequence
has a known 3D structure.)
3-state accuracy
................
Often the relative accessibility is projected onto, e.g., 3 states:
b = buried (here defined as < 9% relative accessibility),
i = intermediate ( 9% <= rel. acc. < 36% ),
e = exposed ( rel. acc. >= 36% ).
A projection onto 3 states or 2 states (buried/exposed) enables the
compilation of a 3- and 2-state prediction accuracy. PHD reaches an
overall 3-state accuracy of:
Q3 = 57.5%
(compared to 35% for random prediction and 70% for homology modelling).
In detail:
+-----------------------------------+-------------------------+
| Qburied (% of observed)=77% | Qb (% of predicted)=60% |
| Qintermediate (% of observed)= 9% | Qi (% of predicted)=44% |
| Qexposed (% of observed)=78% | Qe (% of predicted)=56% |
+-----------------------------------+-------------------------+
10-state accuracy
.................
The network predicts relative solvent accessibility in 10 states, with
state i (i = 0-9) corresponding to a relative solvent accessibility of
i*i %. The 10-state accuracy of the network is:
Q10 = 24.5%
..........................................................................
These percentages are defined by:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| number of correctly predicted residues
|Q3 = --------------------------------------- (*100)
| number of all residues
|
| no of res. correctly predicted to be buried
|Qburied (% of obs) = ------------------------------------------- (*100)
| no of all res. observed to be buried
|
|
| no of res. correctly predicted to be buried
|Qburied (% of pred)= ------------------------------------------- (*100)
| no of all residues predicted to be buried
..........................................................................
Averaging over single chains
~~~~~~~~~~~~~~~~~~~~~~~~~~~
The most reasonable way to compute the overall accuracies is the above
quoted percentage of correctly predicted residues. However, since the
user is mainly interested in the expected performance of the prediction
for a particular protein, the mean value when averaging over protein
chains might be of help as well. Computing first the correlation
between observed and predicted accessibility for each protein chan, and
then averaging over all 238 chains yields the following average:
+-------------------------------====--+
| corr/averaged over chains = 0.53 |
+-------------------------------====--+
| standard deviation = 0.11 |
+-------------------------------------+
..........................................................................
Further details of performance accuracy
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The accuracy matrix in detail:
..............................
-------+----------------------------------------------------+-----------
\ PHD | 0 1 2 3 4 5 6 7 8 9 | SUM %obs
-------+----------------------------------------------------+-----------
OBS 0 | 8611 140 8 44 82 169 772 334 27 0 | 10187 16.6
OBS 1 | 4367 164 0 50 106 231 738 346 44 3 | 6049 9.8
OBS 2 | 3194 168 1 68 125 303 951 513 42 7 | 5372 8.7
OBS 3 | 2760 159 8 80 136 327 1246 746 58 19 | 5539 9.0
OBS 4 | 2312 144 2 72 166 396 1615 1245 124 19 | 6095 9.9
OBS 5 | 1873 96 3 84 138 425 1979 1834 187 27 | 6646 10.8
OBS 6 | 1387 67 1 60 80 278 2237 2627 231 51 | 7019 11.4
OBS 7 | 1082 35 0 32 56 225 1871 3107 302 60 | 6770 11.0
OBS 8 | 660 25 0 27 43 136 1206 2374 325 87 | 4883 7.9
OBS 9 | 325 20 2 27 29 74 648 1159 366 214 | 2864 4.7
-------+----------------------------------------------------+-----------
SUM |26571 1018 25 544 961 2564 13263 14285 1706 487 |
%pred | 43.3 1.7 0.0 0.9 1.6 4.2 21.6 23.3 2.8 0.8 |
-------+----------------------------------------------------+-----------
Note: This table is to be read in the following manner:
8611 of all residues predicted to be in exposed by 0%, were
observed with 0% relative accessibility. However, 325 of all
residues predicted to have 0% are observed as completely exposed
(obs = 9 -> rel. acc. >= 81%). The term "observed" refers to the
DSSP compilation of area of solvent accessibility calculated from
3D coordinates of experimentally determined structures (Diction-
ary of Secondary Structure of Proteins: Kabsch & Sander (1983)
Biopolymers, 22, 2577-2637).
Accuracy for each amino acid:
.............................
+---+------------------------------+-----+-------+------+
|AA | Q3 b%o b%p i%o i%p e%o e%p | Q10 | corr | N |
+---+------------------------------+-----+-------+------+
| A | 59.0 87 60 2 38 66 57 | 31 | 0.530 | 5054 |
| C | 62.0 91 67 5 39 25 21 | 34 | 0.244 | 893 |
| D | 56.5 21 45 6 49 94 57 | 20 | 0.321 | 3536 |
| E | 60.8 9 40 3 41 98 61 | 21 | 0.347 | 3743 |
| F | 63.3 94 67 9 46 29 37 | 27 | 0.366 | 2436 |
| G | 52.1 75 51 1 31 67 53 | 22 | 0.405 | 4787 |
| H | 50.9 63 53 23 45 71 50 | 18 | 0.442 | 1366 |
| I | 64.9 95 68 6 41 30 38 | 34 | 0.360 | 3437 |
| K | 66.6 2 11 2 37 98 67 | 23 | 0.267 | 3652 |
| L | 61.6 93 65 8 44 31 40 | 31 | 0.368 | 5016 |
| M | 60.1 92 64 5 39 45 44 | 29 | 0.452 | 1371 |
| N | 55.5 45 45 8 38 87 59 | 17 | 0.410 | 2923 |
| P | 53.0 48 48 9 39 83 56 | 18 | 0.364 | 2920 |
| Q | 54.3 27 44 7 44 92 56 | 20 | 0.344 | 2225 |
| R | 49.9 15 47 36 47 76 51 | 18 | 0.372 | 2765 |
| S | 55.6 69 53 3 51 81 56 | 22 | 0.464 | 3981 |
| T | 51.8 61 51 8 38 78 53 | 21 | 0.432 | 3740 |
| V | 61.1 93 65 5 40 39 42 | 34 | 0.418 | 4156 |
| W | 56.2 85 62 20 49 29 27 | 21 | 0.318 | 891 |
| Y | 49.7 73 52 33 49 36 38 | 19 | 0.359 | 2301 |
+---+------------------------------+-----+-------+------+
Abbreviations:
AA: amino acid in one-letter code
b%o, i%o, e%o: = Qburied, Qintermediate, Qexposed (% of observed),
i.e. percentage of correct prediction in each state, see above
b%p, i%p, e%p: = Qburied, Qintermediate, Qexposed (% of predicted),
i.e. probability of correct prediction in each state, see above
b%o: = Qburied (% of observed), see above
Q10: percentage of correctly predicted residues in each of the 10
states of predicted relative accessibility.
corr: correlation between predicted and observed rel. acc.
N: number of residues in data set
Accuracy for different secondary structure:
...........................................
+--------+------------------------------+----+-------+-------+
| type | Q3 b%o b%p i%o i%p e%o e%p |Q10 | corr | N |
+--------+------------------------------+----+-------+-------+
| helix | 59.5 79 64 8 44 80 56 | 27 | 0.574 | 20100 |
| strand | 61.3 84 73 9 46 69 37 | 35 | 0.524 | 13356 |
| loop | 54.4 64 43 11 44 78 61 | 18 | 0.442 | 27968 |
+--------+------------------------------+----+-------+-------+
Abbreviations as before.
Position-specific reliability index
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The network predicts the 10 states for relative accessibility using real
numbers from the output units. The prediction is assigned by choosing
the maximal unit ("winner takes all"). However, the real numbers
contain additional information.
E.g. the difference between the maximal and the second largest output
unit (with the constraint that the second largest output is compiled
among all units at least 2 positions off the maximal unit) can be used
to derive a "reliability index". This index is given for each residue
along with the prediction. The index is scaled to have values between
0 (lowest reliability), and 9 (highest).
The accuracies (Q3, corr, asf.) to be expected for residues with values
above a particular value of the index are given below as well as the
fraction of such residues (%res).:
+---+------------------------------+----+-------+-------+
|RI | Q3 b%o b%p i%o i%p e%o e%p |Q10 | corr | %res |
+---+------------------------------+----+-------+-------+
| 0 | 57.5 77 60 9 44 78 56 | 24 | 0.535 | 100.0 |
| 1 | 59.1 76 63 9 45 82 57 | 25 | 0.560 | 91.2 |
| 2 | 61.7 79 66 4 47 87 58 | 27 | 0.594 | 77.1 |
| 3 | 66.6 87 70 1 51 89 63 | 30 | 0.650 | 57.1 |
| 4 | 70.0 89 72 0 83 91 67 | 32 | 0.686 | 45.8 |
| 5 | 72.9 92 75 0 0 93 70 | 34 | 0.722 | 35.6 |
| 6 | 76.3 95 77 0 0 93 75 | 36 | 0.769 | 24.7 |
| 7 | 79.0 97 79 0 0 93 78 | 39 | 0.803 | 16.0 |
| 8 | 80.9 98 80 0 0 91 81 | 43 | 0.824 | 9.6 |
| 9 | 81.2 99 80 0 0 88 83 | 45 | 0.828 | 5.9 |
+---+------------------------------+----+-------+-------+
Abbreviations as before.
The above table gives the cumulative results, e.g. 45.8% of all
residues have a reliability of at least 4. The correlation for this
most reliably predicted half of the residues is 0.686, i.e. a value
comparable to what could be expected if homology modelling were
possible. For this subset of 45.8% of all residues, 89% of the buried
residues are correctly predicted, and 72% of all residues predicted to
be buried are correct.
..........................................................................
The following table gives the non-cumulative quantities, i.e. the
values per reliability index range. These numbers answer the question:
how reliable is the prediction for all residues labeled with the
particular index i.
+---+------------------------------+----+-------+-------+
|RI | Q3 b%o b%p i%o i%p e%o e%p |Q10 | corr | %res |
+---+------------------------------+----+-------+-------+
| 0 | 40.9 79 40 16 41 21 40 | 14 | 0.175 | 8.8 |
| 1 | 45.4 61 46 28 44 48 44 | 17 | 0.278 | 14.1 |
| 2 | 47.4 53 52 10 46 80 44 | 19 | 0.343 | 19.9 |
| 3 | 52.9 75 59 4 50 77 47 | 23 | 0.439 | 11.4 |
| 4 | 60.0 81 63 0 83 84 56 | 25 | 0.547 | 10.1 |
| 5 | 65.2 82 70 0 0 93 62 | 28 | 0.607 | 10.9 |
| 6 | 71.3 90 72 0 0 94 70 | 31 | 0.692 | 8.8 |
| 7 | 76.0 94 76 0 0 95 75 | 34 | 0.762 | 6.3 |
| 8 | 80.5 97 81 0 0 94 79 | 39 | 0.808 | 3.8 |
| 9 | 81.2 99 80 0 0 88 83 | 45 | 0.828 | 5.9 |
+---+------------------------------+----+-------+-------+
For example, for residues with RI = 4 83% of all predicted intermediate
residues are correctly predicted as such.
The resulting network (PHD) prediction is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
PHD: Profile fed neural network systems from HeiDelberg
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Prediction of:
secondary structure, by PHDsec
solvent accessibility, by PHDacc
and helical transmembrane regions, by PHDhtm
Author:
Burkhard Rost
EMBL, 69012 Heidelberg, Germany
Internet: Rost@EMBL-Heidelberg.DE
All rights reserved.
The network systems are described in:
PHDsec: B Rost & C Sander: JMB, 1993, 232, 584-599.
B Rost & C Sander: Proteins, 1994, 19, 55-72.
PHDacc: B Rost & C Sander: Proteins, 1994, 20, 216-226.
PHDhtm: B Rost et al.: Prot. Science, 1995, 4, 521-533.
Some statistics
~~~~~~~~~~~~~~~
Percentage of amino acids:
+--------------+--------+--------+--------+--------+--------+
| AA: | A | L | R | E | I |
| % of AA: | 9.9 | 9.1 | 8.2 | 7.8 | 7.3 |
+--------------+--------+--------+--------+--------+--------+
| AA: | D | V | G | T | S |
| % of AA: | 7.3 | 6.9 | 6.9 | 5.6 | 4.3 |
+--------------+--------+--------+--------+--------+--------+
| AA: | F | P | Y | K | H |
| % of AA: | 4.3 | 3.9 | 3.0 | 3.0 | 3.0 |
+--------------+--------+--------+--------+--------+--------+
| AA: | Q | M | N | W | C |
| % of AA: | 2.6 | 2.6 | 1.7 | 1.3 | 1.3 |
+--------------+--------+--------+--------+--------+--------+
Percentage of secondary structure predicted:
+--------------+--------+--------+--------+
| SecStr: | H | E | L |
| % Predicted: | 33.6 | 26.3 | 40.1 |
+--------------+--------+--------+--------+
According to the following classes:
all-alpha: %H>45 and %E< 5; all-beta : %H<5 and %E>45
alpha-beta : %H>30 and %E>20; mixed: rest,
this means that the predicted class is: alpha-beta
PHD output for your protein
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Thu Feb 3 04:30:32 2000
Jury on: 10 different architectures (version 5.94_317 ).
Note: differently trained architectures, i.e., different versions can
result in different predictions.
About the protein
~~~~~~~~~~~~~~~~~
HEADER /home/phd/server/work/predict_h6314640.f
COMPND
SOURCE
AUTHOR
SEQLENGTH 232
NCHAIN 1 chain(s) in predict_h6314640 data set
NALIGN 12
(=number of aligned sequences in HSSP file)
Abbreviations: PHDsec
~~~~~~~~~~~~~~~~~~~~~
sequence:
AA : amino acid sequence
secondary structure:
HEL: H=helix, E=extended (sheet), blank=other (loop)
PHD: Profile network prediction HeiDelberg
Rel: Reliability index of prediction (0-9)
detail:
prH: 'probability' for assigning helix
prE: 'probability' for assigning strand
prL: 'probability' for assigning loop
note: the 'probabilites' are scaled to the interval 0-9, e.g.,
prH=5 means, that the first output node is 0.5-0.6
subset:
SUB: a subset of the prediction, for all residues with an expected
average accuracy > 82% (tables in header)
note: for this subset the following symbols are used:
L: is loop (for which above " " is used)
".": means that no prediction is made for this residue, as the
reliability is: Rel < 5
Abbreviations: PHDacc
~~~~~~~~~~~~~~~~~~~~~
SS : secondary structure
HEL: H=helix, E=extended (sheet), blank=other (loop)
solvent accessibility:
3st: relative solvent accessibility (acc) in 3 states:
b = 0-9%, i = 9-36%, e = 36-100%.
PHD: Profile network prediction HeiDelberg
Rel: Reliability index of prediction (0-9)
O_3: observed relative acc. in 3 states: B, I, E
note: for convenience a blank is used intermediate (i).
P_3: predicted relative accessibility in 3 states
10st:relative accessibility in 10 states:
= n corresponds to a relative acc. of n*n %
subset:
SUB: a subset of the prediction, for all residues with an expected
average correlation > 0.69 (tables in header)
note: for this subset the following symbols are used:
"I": is intermediate (for which above " " is used)
".": means that no prediction is made for this residue, as the
reliability is: Rel < 4
protein: predict length 232
....,....1....,....2....,....3....,....4....,....5....,....6
AA |TTLSCKVTSVEAITDTVYRVRIVPDAAFSFRAGQYLMVVMDERDKRPFSMASTPDEKGFI|
PHD sec | EEEEE EEE EEEEEEE EE EEEEEEE EE EE|
Rel sec |992226741111322126888834998314266289999837989971221399998289|
detail:
prH sec |000000001233333321000000000100000000000000000000000000000000|
prE sec |003557864433101247888863000346322589999831000015534300000389|
prL sec |985442124332555431000136998542577310000168889984455599998510|
subset: SUB sec |LL...EE..........EEEEE..LLL....LL.EEEEEE.LLLLLL.....LLLLL.EE|
accessibility
3st: P_3 acc |eebebebebbeebeeebbeb beeeeebebebbbbbbbbbeeeee bbbbbb eeeeeeb|
10st: PHD acc |960706060067067700604067766060600000000077777500000047877760|
Rel acc |501351522510302042170220202215063239391331322114555001122108|
subset: SUB acc |e...b.b..b......b..b.........b.b...b.b.........bbbb........b|
....,....7....,....8....,....9....,....10...,....11...,....12
AA |ELHIGASEINLYAKAVMDRILKDHQIVVDIPHGEAWLRDDEERPMILIAGGTGFSYARSI|
PHD sec |EEEE HHHHHHHHHHHH EEEEE EEE EEEEE HHHHHHH|
Rel sec |997335544157899999993288179968997311433799996989399527999999|
detail:
prH sec |000001123467899999995400000000001321000000000000000247899999|
prE sec |998531110000000000000000589971000034653100007988600000000000|
prL sec |001356666421100000003588410028897644235899992000398752000000|
subset: SUB sec |EEE..LL...HHHHHHHHHH..LL.EEEELLLL......LLLLLEEEE.LLL.HHHHHHH|
accessibility
3st: P_3 acc |bbbbebbeeeeebebbbeebeeeeebebebeebebbb eeeeebbbbbbbbbbbb b bb|
10st: PHD acc |000060077776070007607777606070760600057777600000000000050500|
Rel acc |062720112100210732042311151500013132712113127887843042306076|
subset: SUB acc |.b.b...........b...b.....b.b........b.......bbbbbb..b...b.bb|
....,....13...,....14...,....15...,....16...,....17...,....18
AA |LLTALARNPNRDITIYWGGREEQHLYDLCELEALSLKHPGLQVVPVVEQPEAGWRGRTGT|
PHD sec |HHHHHHH EEEEE HHHHHHHHHHHHHHHH EEEEEE |
Rel sec |999999579992799874875478844899999999549955999743799665557653|
detail:
prH sec |999999710000000000012678866899999999730000000000000122210011|
prE sec |000000000004899873000000000000000000000027998863100000111122|
prL sec |000000279995100016877311123000000000269972000136889776667765|
subset: SUB sec |HHHHHHHLLLL.EEEEE.LLL.HHH..HHHHHHHHHH.LLLEEEEE..LLLLLLLLLLL.|
accessibility
3st: P_3 acc |bebbbeeeeeeebbbbbbbeeeeebbbeeebeebbee eebebbbbbeeeeeeeebeebe|
10st: PHD acc |060007776766000000066676000676067007747706000007767977707706|
Rel acc |711322410310829243120001601111422231201030454751102020201131|
subset: SUB acc |b.....e.....b.b.b.......b.....b...........bbbbb.............|
....,....19...,....20...,....21...,....22...,....23...,....24
AA |VLTAVLQDHGTLAEHDIYIAGRFEMAKIARDLFCSERNAREDRLFGDAFAFI|
PHD sec |HHHHHHHHHHHH E EEEE HHHHHHHHHHHHHH HHHHHHHHHH |
Rel sec |1479999896303412654155479999999998213367236778887519|
detail:
prH sec |4579999897543210011001689999999998553321567778888640|
prE sec |3210000000000143766421000000000000000000000000000000|
prL sec |2110000002346645112476210000000001346678432111001259|
subset: SUB sec |..HHHHHHHH......EE..LL.HHHHHHHHHHH....LL..HHHHHHHH.L|
accessibility
3st: P_3 acc |bbebbeebbeebbebbbbbbb bebbebbeeebeeeeebeeeebbbebbbbb|
10st: PHD acc |0060067007600600000005060070067606777707776000600000|
Rel acc |7207802032141232937550017320713150212202211542085332|
subset: SUB acc |b..bb......b....b.bbb...b...b...b..........bb..bb...|
_
_______________________________________________________________________________
The resulting prediction of globularity is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
---
--- GLOBE: prediction of protein globularity
---
--- nexp = 116 (number of predicted exposed residues)
--- nfit = 102 (number of expected exposed residues
--- diff = 14.00 (difference nexp-nfit)
--- =====> your protein appears as compact, as a globular domain
---
---
--- GLOBE: further explanations preliminaryily in:
--- http://www.columbia.edu/~rost/Papers/98globe.html
---
--- END of GLOBE
The resulting prediction is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
---
--- ------------------------------------------------------------
--- TOPITS prediction-based threading
--- ------------------------------------------------------------
---
--- TOPITS ALIGNMENTS HEADER: PARAMETERS
--- str:seq= 50 : structure (sec str, acc)= 50%, sequence= 50%
--- str:seq = 50 : weight structure/sequence,i.e. str= 50%, seq= 50%
--- smin = -1.00 : minimal value of alignment metric
--- smax = 2.00 : maximal value of alignment metric
--- go = 2 : gap open penalty
--- ge = 0.2 : gap elongation penalty
--- len1 = 232 : length of search sequence, i.e., your protein
---
--- TOPITS ALIGNMENTS HEADER: ABBREVIATIONS
--- RANK : rank in alignment list, sorted according to z-score
--- EALI : alignment score
--- LALI : length of alignment
--- IDEL : number of residues inserted
--- NDEL : number of insertions
--- ZALI : alignment zcore; note: hits with z>3 more reliable
--- PIDE : percentage of pairwise sequence identity
--- LEN2 : length of aligned protein structure
--- ID2 : PDB identifier of aligned structure
--- NAME2 : name of aligned protein structure
--- IFIR : position of first residue of search sequence
--- ILAS : position of last residue of search sequence
--- JFIR : PDB position of first residue of remote homologue
--- JLAS : PDB position of last residue of remote homologue
---
--- TOPITS ALIGNMENTS HEADER: ACCURACY
--- : Tested on 80 proteins, TOPITS found the
--- : correct remote homologue in about 30% of
--- : the cases, detection accuracy was higher
--- : for higher z-scores (ZALI):
--- ZALI>0 : 1st hit correct in 33% of cases
--- ZALI>3 : 1st hit correct in 50% of cases
--- ZALI>3.5 : 1st hit correct in 60% of cases
---
--- TOPITS ALIGNMENTS HEADER: SUMMARY
RANK EALI LALI IDEL NDEL ZALI PIDE LEN2 ID2 NAME2
1 82.80 210 69 18 2.31 31 270 1ndh OCHROME B=5= REDUCTASE (E
2 76.13 220 85 19 1.97 28 321 2pia HALATE DIOXYGENASE REDUCT
3 75.67 229 128 23 1.95 33 525 1der_A OL_ID: 1;
4 74.87 222 47 13 1.91 27 296 1fnc REDOXIN:NADP+ OXIDOREDUCT
5 74.67 207 60 25 1.90 31 295 1uox _ID: 1;
6 74.40 220 84 21 1.89 31 698 1aa6 _ID: 1;
7 74.27 224 112 25 1.88 31 785 1pys_B OL_ID: 1;
8 73.73 226 100 27 1.85 34 436 4enl LASE (E.C.4.2.1.11) (2-PH
9 73.60 217 78 21 1.84 30 619 1sqc _ID: 1;
10 73.27 217 78 21 1.83 30 487 1bpo_A MOL_ID: 1;
11 72.73 208 59 16 1.80 26 378 1ba1 L_ID: 1;
12 72.67 204 60 20 1.80 30 839 1yge L_ID: 1;
13 72.47 217 50 24 1.79 28 500 1ecf_B MOL_ID: 1;
14 72.47 214 77 26 1.79 33 720 1oac_A MOL_ID: 1;
15 72.27 210 76 24 1.78 30 316 1onr_A MOL_ID: 1;
16 72.27 217 87 25 1.78 32 447 1nhp DH PEROXIDASE (NPX) (E.C.
17 72.00 226 92 27 1.76 33 452 1pii (5'PHOSPHORIBOSYL)ANTHRAN
18 71.93 197 75 23 1.76 32 602 1kfs_A MOL_ID: 1;
19 71.87 220 148 34 1.76 40 420 1adj_A MOL_ID: 1;
20 71.73 220 61 23 1.75 30 405 1eft ONGATION FACTOR TU (EF-TU
---
--- TOPITS ALIGNMENTS HEADER: PDB_POSITIONS FOR ALIGNED PAIR
RANK PIDE IFIR ILAS JFIR JLAS LALI LEN2 ID2
---
--- TOPITS ALIGNMENTS: SYMBOLS AND EXPLANATIONS
--- BLOCK 1 : your protein and its predicted 1D structure,
--- : i.e., secondary structure and solvent accessibility
--- line 1 : amino acid sequence (one-letter-code)
--- line 2 : predicted secondary structure:
--- H : helix
--- E : strand (extended)
--- L : other (no regular secondary structure)
--- line 3 : predicted residue relative solvent accessibility
--- B : buried, i.e., relative accessibility < 15%
--- O : exposed (outside), i.e., relative accessibility >= 15%
--- :
--- BLOCKS 1-20 : 20 best hits of the prediction-based threading
--- ATTENTION : We chose to include all first 20 hit. However,
--- ATTENTION : most of them will not constitute true remote
--- ATTENTION : homologues. Instead, all hits with a zscore
--- ATTENTION : (ZALI) < 3.5 are, at best, rather speculative!
--- : for each aligned protein:
--- line 1 : amino acids conserved between guide (yours) and the
--- : aligned protein (putative homologue)
--- line 1 : sequence of aligned protein
--- line 3 : secondary structure, taken from DSSP (assignment
--- : of secondary structure based on experimental coordinates)
--- line 4 : relative solvent accessibility, taken from DSSP
---
--- TOPITS ALIGNMENTS
1 - 51 ....:....1....:....2....:....3....:....4....:....5
pred TTLSCKVTSVEAITDTVYRVRIVPDAAFSFRAGQYLMVVMDERDKRPFSMA
EEEEE EEE EEEEEEE EE EEEEEEE EE
OOBOBOBOBBOOBOOOBBOBOBOOOOOBOBOBBBBBBBBBOOOOOOBBBBB
1. 1ndh 82.80 PAItdIKYPLRLipEHILGLPVGqyLSARIDGNLvrPYTPV
LLELLLEEEEEEELLLELLLLLLLEEEEEELLEEEEEELLL
TTL K S E I P A F AG L V R S
2. 2pia 76.13 TtlRLKIASKEKIARDIWSFELtpQGapPFEAGANLTVAVPNGSRRTYSLC
LLEEEEEEEEEEEELLEEEEEEELLLLLLLLLLLEEEEELLLLLEEEEELL
TT V IT V AA G V S
3. 1der_A 75.67 TTTA.TVLAQAIITEGLKAV.....AamDLKRGIDKAVTVAVEELKALSVP
HHHH.HHHHHHHHHHHHHHH.....HLHHHHHHHHHHHHHHHHHHHHHLEL
L K T A T R GQ V D DKR S A
4. 1fnc 74.87 LNTKITGDDAPGET.WHMVFSHEGEIPYREGQSVGVIPDGEDkrLYSIA
EEEELLLLLLLLLE.EEEEEELLLLLLLLLLLEEEEELLLELLEEEELL
KV E TVY V S A V D A
5. 1uox 74.67 KVHKDEKtvQTVYevLLEGEIETSykADNSVIVATDSIKNTIYITA
EEEELLLLLEEEEEEEEEELLHHHHLLLHHHLLLHHHHHHHHHHHH
S TD V IV R G V D R A
6. 1aa6 74.40 MSNAINEIDN.TDLVfsHPIVANHVINarNGAKIIV....CDPRKIETA
LLLLHHHHHH.LLEEEHLHHHHHHHHHHHLLLEEEE....ELLLLLHHH
T S E V R P AAF R Q L VMD D R F
7. 1pys_B 74.27 TPPSHRllRLEelVEEVARIqtIPLaafpYRKEQRLREvmDPEDARRFRL.
ELLLLLLLLLHHHHHHHHHHHHLLLLLLHHHHHHHHHHHELLLHHHHLLL.
S A V D S Y VV F A
8. 4enl 73.73 VSLAASRAAAAEKNVPLYKHLADLSKS.KTSPYVlvvLNGGShqEFMIA
HHHHHHHHHHHHHLLLHHHHHHHHHLL.LLLLEEEEEEELHHHLEEEEE
T EA Y D A F Q L V K P
9. 1sqc 73.60 TTIEAYVALKY.IGMSRDeaLRFIQSqwLALVGepWEKVPM...
HHHHHHHHHHH.HLLLLLLHHHHHHHLHHHHLLLLHHHLLL...
T VT I V V D A S G V M R S A
10. 1bpo_A 73.27 HTMTDDVTFWKWI..SLNTVALVTDNawSM.EGESQPVKMFDRHS...SLa
EELLLLLLEEEEE..ELLEEEEELLLEEEL.LLLLLLEEEEELLH...HHL
V T Y V F G D P A
11. 1ba1 72.73 AVGIDLGTTykVGV.......FQHGKVEIIANDQGNrtPSYVA
LEEEELLLLEEEEE.......EELLEEEELLLLLLLLEELLEE
S A T IV AAF D DK P
12. 1yge 72.67 HLKSKDALegTKSLSQIVQPaaFDLKSTPifHSFQDVHdkLPRDVI
LLLHHHLHHHHHHHHHLHHHHHHHLLLLLLLLLHHHHHHELLHHHH
T S Y A E KR
13. 1ecf_B 72.47 TAGSSSASEAQpyVNSPYGITLAHNGNLT.NAHELRKKLFEE..KRRH.IN
ELLELLLLLLLLEELLLLLEEEEEEEEEL.LHHHHHHHHHHH..HLLL.LL
LS V TVY IVPD F AG Y M R K S A
14. 1oac_A 72.47 HLSMN.SRVGPMISTvyEGsivpDIGWYFKagDYGMGTLTsrGKDAPSNA
EEEEE.LLLEEEEEEEEEEEEELLLLLLLLEHHHLLLLLELLLLLLLLLL
TT I YR DAA RA Q D DK
15. 1onr_A 72.27 TTNPSLILNAAQIPE..YR.KLIDDaawnDRAQQ....IVDATDKLAVNIg
ELLHHHHHHHLLLHH..HH.HHHHHHHHLLHHHH....HHHHHHHHHHHHH
T V V I Y I AF AG V D DK F
16. 1nhp 72.27 TVDPEVNNVVVI.GSGY.IGIEAAEAFA.KAGKKVTviLDRpdK.EFTDV
HLLLLLLEEEEE.LLLH.HHHHHHHHHH.HLLLEEEELLLLLLH.HHHHH
L CK S I D RI A A V DE F
17. 1pii 72.00 LECKKASPsvIRDDFDPARI..AAIYKHYASA.ISVLTDEKyqGSFniV
EEELLEELLELLLLLLHHHH..HHHHLLLLLE.EEEELLLLLLLLLLHH
S I I P AA A YL D D R
18. 1kfs_A 71.93 FDTETDSLDNISANLVGLsiEPgaAYIPVAHDYL....DAPDqrALElp
EEEEELLLLLLLLLEEEEEEELLEEEEELLLLLL....LLLLLHHHHHH
T K V A TD IV F FR G LMV K P MA
19. 1adj_A 71.87 TQVFEK..GVGAATD......IVRKEMFTfrGGRSlmvyLEHGMkqplWMa
HHHHHH..HHLLLLH......HHHHLLLEELLLLEEHHHHHLLHHLLEEEE
TTL T V A V I D A RA V E KR S
20. 1eft 71.73 TTLTAALTFVTAAENPNVEVki..DKAPEERARGITihVEYETAKRHYSHV
HHHHHHHHHHHHLLLLLLLLLL..LLLHHHHHHLLLLEEEEELLLLEEEEE
---
--- TOPITS ALIGNMENTS CONTINUED
---
1. 1ndh 82.80 VSSDDDKGFVDLVIKVYFKDTHPkgKMSQYLESMKIGDTIerGpaIRPDKK
LLLLLLLLLLLEEEEELLLLLLLLLHHHHHHHHLLLLLEEEEEEEELLLLL
E I I D V P E D
2. 2pia 76.13 CNDSQERnvIAVKRDSnsISF.....IDDTSEGDAVEVSLPRNE.FPLDKR
LLLLLLLLEEEEELLLLHHHH.....HHLLLLLLEEEELLLELL.LLLLLL
D K I A E L A A MD K I V G L D E
3. 1der_A 75.67 PCS.DSKAIAQvtISAnetkLIAEA.MDKVGKEGVITVEDGTG...LQDee
LLL.LHHHHHHHHHHLLHHHHHHHH.HHHLLLLLEEEEELLLL...LLLEL
AS D K L A E K V L D P GE D
4. 1fnc 74.87 ASSadAKS.VSLCvdAGET...IKGVCSNFLCdaEVKLTGPVgeMLMPKDP
LLLLLLLE.EEEEELLLLE...EELHHHHHHHLLEEEEEEEELLLLLELLL
A TP E FIE HI A N V R DIPH RD E
5. 1uox 74.67 AktPPetHFIEkhIHAAHVNI....VCHRWTR.....MDipHPHSFIRDSE
HHLLHHHHHHHHLEEEEEEEE....EEELLEE.....EEEEEEEEEELLLL
A D I L G E NLY KAV RI V DI A
6. 1aa6 74.40 ARIADMH..IALKNGSneENLYDKavASriVEGyeSVEDItrQAARMYAQA
HHHLLEE..ELLLLLLHHLLLLLHHHHHHHHLLLHHHHHHHHHHHHHHHHL
D L A E L V R LK D EA LR E
7. 1pys_B 74.27 ....DPPRLLLLNPLAPetHLFPGLV..RVLKEN...LDLDRPeaLlrERE
....LLLLLEELLLLLHHLLLHHHHH..HHHHHH...HHHLLLLEEELLLE
A T K F EL IG SE NL K V G A E
8. 4enl 73.73 APT.GAKTFAelRIG.SEvnL..KSLTKKRYGASAGNVGDEGGVaiQTAEE
ELL.LLLLHHHHHHH.HHHHH..HHHHHHHHLHHHHLELLLLLELLLLHHH
P E F L I E A AVM R L V D P G W D
9. 1sqc 73.60 ..VPPEIMfmPLNI..YEFGSWARavMSrpLPERARvtDVPpgGGWIFDAL
..LLHHHHHLLLLH..HHLLHHHHHHHHHLLLHHHLLLLLLLLLLHHHHHH
A T L I A LY V I HQ E LR
10. 1bpo_A 73.27 arTDAKQKWLLLtiSAQqmQLYsrKVSQPI.EGhqFKMEGNAEESTlrGQA
LEELLLLLEEEEEEEEELEEEEELLLEEEE.LLLEEELLLLLLEEEELLLL
A T E I AK R D D H D
11. 1ba1 72.73 AFTDTER.LiqVAMNPTNTVFDAKRLIGRRFDDAVVQSDMKHWPFMVVNDA
EELLLLE.EELLLLLHHHEELLHHHLLLLLLLLHHHHHHHLLLLLEEEEEL
ST I L I LY ILK Q VV AW D E
12. 1yge 72.67 IST.....IIPLPV....ieLY.RTDGQHILKFPqhVVQVSQ.SAWMTDEe
HHH.....HLLLLL....HHHL.EELLLLEEELLLHHHLLLL.LHHHLHHH
T D I L I ASE N A A R V I HG RD
13. 1ecf_B 72.47 NTTSDSE..ILLNIFASElnIFAaaATNRLIRGAYACVaiGHGMVAFRDPN
LLLLHHH..HHHHHHHHHHHHHHHHHHHHHLLEEEEEEELLLEEEEEELLL
A E I G EI A AV R K V E R D
14. 1oac_A 72.47 AVLLNET..IADYTgpMEI.PRAIAVFERyyKHQEMgvSTERRELVVrxdh
LEEEEEE..EELLLLEEEE.EEEEEEEEEEEEELLLLEEEEEEEEEEEEEE
ST E I I LY A DRILK I E
15. 1onr_A 72.27 gsTEVDARltEASIAKAkiKLYNDAGidRIlkLASTWQGIRAAEQLEKEGI
HEEELLHHHHHHHHHHHHHHHHHHLLLHHEEEEELLHHHHHHHHHHHHLLL
T E I G Y K V D D VV AWL E
16. 1nhp 72.27 VLTEeeANNITIATGET.VERYekVVTDKNAYDADLVvgVRPNTAWLKGte
HHHHHHLLLEEEEELLL.EEEEEEEEELLLEEELLEEELEEELLHHHLLLL
S P K FI I I LYA A M L D Q H E
17. 1pii 72.00 VsaPQpkDFI...IDPYQIYlyaDalMLSVLDDDQylAAVAHseVSNEEEQ
HHLLLLELLL...LLHHHHHHHLLEEELLLLLHHHHHHHHHHHEELLHHHH
DEK L G NLY DRIL I G A E
18. 1kfs_A 71.93 pLLEDEK...ALKVGQ...Nly.....DriLANYGIEL...RGIAFDTMLE
HHHLLLL...LLEEEL...LHH.....HHHHHLLLLLL...LLEEEEHHHH
A KGF ASE NL A AV LK V PH EA L DE
19. 1adj_A 71.87 aaERPQKgfHQVNYEasE.nlDAEAvlYECLKerRLKVKlpHREA.LSEde
ELLLLLLLEEEEEEEELL.LHHHHHHHHHHHHHLLLEEEEHHHHH.LLHHL
P I IGA L A M IL QIVVD L E
20. 1eft 71.73 VDCPGHADYIKNMigAAQMdlVVSAameHILLARqivvDMVDDPEllVEME
EELLLLHHHHHHHHHHLLLLEEEELLLHHHHHHHLEEHHHLLLLLHHHHHH
---
--- TOPITS ALIGNMENTS CONTINUED
---
1. 1ndh 82.80 KSSPVimIAGGTGIT...PMliRAIMKDPD.DHtlLFANQTEKDILLRPEL
LLEEELEEEEHHHHH...HHHHHHHHHLLL.LLLEEEEEEEHHHLLLHHHH
IL AGG G S ARS L L R P D I W QH Y C
2. 2pia 76.13 RAKSFILVAGGIglSMarSFRLYYLTRDPesDVKifwkSKPAQHVYC.CGP
LLLEEEEEEEHHHHHHHLEEEEEEEELLHHLLEEEHHLLLLLEEEEE.ELL
EE P IL A S R LL A A N R I G R L D EL
3. 1der_A 75.67 eeSPFILLA.DKKISNIREMllEAVAknTMRGIVKvfGDRRKAMLQDimEL
LELLEEEEE.LLEELLLHHHHHHHHLLHHLLLLLLELLHHHHHHHHHHHHH
I GTG RS L N G L E
4. 1fnc 74.87 PNATIIMLGTGTGIAPFRSFLWKMFFEKhnGLAWLFLGVPTSSSLLYKEEF
LLLEEEEEEEHHHHHHHHHHHHHHHLLLELLEEEEEEEELLHHHLLLHHHH
EE G G S LT L N WG R E L DL
5. 1uox 74.67 EEKRNVqvVEGKGIDIKSSLslTVL.KSTNSQ...FWglRDetTlwdltDV
LLEEEEEEELLLLEEEEEEEEEEEE.ELLLEL...ELLLLLLLLLLLEEEE
IL G T F Y RS LT LA N R C
6. 1aa6 74.40 AKSAAILwmGVTQF.yvRS..LTSLagNLGKPHAGVNPVRGQNNVQGACDM
LLLEEEEEHHHHLL.LHHH..HHHHHLLLLLLLLLEEELLLELLHHHHHHL
EE L G G A LL ALAR P G E L L
7. 1pys_B 74.27 EETHllLFGEGVGLPWAKERllEAlarhPGVSGRVLVEGEEVGFLGALHPE
EEEEEEEEELLEELLLLLLEEHHHHHHEEEEEEEEEELLEEEEEEEEELHH
E I IA G G A S L NPN D G LY L
8. 4enl 73.73 EALDLIviaAGhgLDCASSEFFkdLdkNPNSDKSKWLTGPQLADLYhlmdW
HHHHHHHHHLLLEEELLHHHHEELLLLLLLLLHHHLELHHHHHHHHHHHLH
R R AL R WGG Y L L
9. 1sqc 73.60 LDRALHGYQKLSVHPFRRAAEIRALDWLLERQadGSWGGIQPPWFYALIAL
HHHHHHHHHLLLLLLLHHHHHHHHHHHHHHHLLLLLLLLEHHHHHHHHHHH
I GT F A A N D HLYDL
10. 1bpo_A 73.27 AGGKLHIIEVGtpfkKAVDVFFPPEAQneKHDVVFLITKYGYIHLYDLETG
LLLEEEEEELLLLLLEEEELLLLLLLLLLLLLEEEEEELLLEEEEEELLLL
RP G T Y S LT A N T Y Q D
11. 1ba1 72.73 AGRPKVQVegETKSFYpsSMVLteIAEatNAVVTvyFNDSQRQATKD....
LLEEEEEEELEEEEELHHHHHHHHHHHHLEEEEEELLLHHHHHHHHH....
E R MI I G F S L A IT LY EL
12. 1yge 72.67 eaREMivIRGLEEFP.PKSNLDPAIYGDQSSKIT.....ADSLDlyTMDel
HHHHHHLLEELLLLL.LLLLLLHHHHLLLLLLLL.....HHHLLLLLHHHE
RP LI T A S L L RD IY EE L C
13. 1ecf_B 72.47 NgrPLVlieNRTEYMVAssVALDTLGFDFLRDvaIYI..TEEGQLFtqCAD
LLLLLEEELLEEEEEEELLHHHHHLLLEEEEELEEEE..ELLLLEEEELLL
E I IAG TG A R T G QH Y L
14. 1oac_A 72.47 hENGTIGiaGATGIEAVKGvmHDETAKDDTRYGTLiiVGTTHQHIYNF.RL
ELLLLEEEEEEEELLLEEELLLLLLHHHHLLLEEEEEEEELEEEEEEE.EE
L FS A L I Y
15. 1onr_A 72.27 INCNLTLL.....FSFAQafLISPFVGR....ILDWYKANTDKKEYA....
LLEEEEEE.....LLHHHHLEEEEELHH....HHHHHHHLLLLLLLL....
E P LIA GT YA ALA N GG D E
16. 1nhp 72.27 eLHPNGLiaVgtLIKyaDTEVNIALATNARKqvKPFPggSSGLAVFdiNEV
LELLLLLEELHLLEEEHLEEELLLLHHHHHHHLLLLLLLLEEEEELLLLHH
ER L A G RSI L LA T Y RE H L L
17. 1pii 72.00 QERAIALGAKVVGIN.NrsIDlrELAPKLGHNVTvyAQVRELSHFAnlsAL
HHHHHHLLLLEEEEE.LEEELLHHHHHHHLLLLEEHHHHHHHLLLLLEHHH
E AG S A I A T EE YD L
18. 1kfs_A 71.93 ESYILNSVAGRHDmsLakTITFEEIAGKGKNQLTFNQIALEEAGRydV.TL
HHHHHLLLLLLLLHHHHLLLLHHHHHLLHHHLLLHHHLLHHHHHHHHH.HH
EE PM A LL L P D G EE HL L EL
19. 1adj_A 71.87 eENPMRILDSKSERDQA...LLKELGVRPMLD....FLGEeeRHLERLseL
LLLHHHHLLLLLHHHHH...HHHHHLLLLHHH....HLLHHHHHHHHLLEE
E R G R L AL NP G E L L
20. 1eft 71.73 EVRDLlyEFPGDEVPVIRGSALLALekNPKTK.....RGENedKIWEL..L
HHHHHHLLLLLLLLLEEELLHHHHHHHLLLLL.....LLLLHHHHHHH..H
---
--- TOPITS ALIGNMENTS CONTINUED
---
1. 1ndh 82.80 LEELRNEhaRFKLWYTVDRAPEAWDYSQGFVNEEMIRDHLPPPEEevLMCG
HHLLHHHHLLEEEEEEEEELLLLLLLEELLLLLHHHHHHLLLHHHLEELLL
AL G VE A R T T L GT A I
2. 2pia 76.13 PQAltVRdtGHWPSGTveSFGanTNARENTPFTVRLSRSGTsaNRSILEVL
LHHHHHHHLLLLLLLLEELLLLLLLLLLLLLEEEEELLLLLELLLLHHHHH
LE L G VV V E EA GR D L E AG
3. 1der_A 75.67 LEKATLEDLGqrVvgVGE..EAAIQGRVAQIRQQIEedREKLQERVAKLAG
HLLLLLLLLEEEEEELLL..LHHHHHHHHHHHHHLLLHHHHHHHHHHHHLL
E K P V G T Q L E D Y G
4. 1fnc 74.87 FEKMKEKApnFRLDFAVSREQTNEKGEKMYIQTRMAQYAVELWekdvYMCG
HHHHHHHLLLEEEEEEELLLLELLLLLELLHHHHHHLLHHHHHHLLEEEEE
A GLQV V A W R T T D Y
5. 1uox 74.67 VDATWqnFSGLqvRSHVPKFDATwtAREVTLKT.FAEDNSASVQATMY...
EEEEEELELLHHHHHLHHHHHHHHHHHHHHHHH.HHHLLELLHHHHHH...
AL PG Q VP VE AG R G V A L A
6. 1aa6 74.40 MGALPDTYPGYQYvpavESLPagyrAAHGEVRAAYIMGEDPLQTDAELSAV
LLLELLEELLLEELHHLLLLLLLLHHHLLLLLEEEEELLLHHHHLLLLHHH
A L P P P A R V A LA D Y
7. 1pys_B 74.27 EIAQELELPPVHllPLPDKppAAFRDLAVVvvEALVREaeSLALFDLYQGP
HHHHHHLLLLLEELLLLLLLLLEEEEEEEEEHHHHHHHHEEEEEEEEELLL
EA S K G Q V V P A L V Q GTLA D AG
8. 4enl 73.73 WEAWsfKTAGIQIVatVTNptAIEKKAADALLLKVNQ.IGTlaAQDSFAAG
HHHHHHHHHLLEEEELLLLHHHHHLLLLLEEEELHHH.HLLHHHHHHHHLL
L L HPGL VE GW TG A L G A HD AG
9. 1sqc 73.60 LKILDmqHpgLELYG.VELDYGGwqAstGLAVLA.LRAAGLPADHdlVKAG
HHHLLLLLHHHHHHE.EELLLLLELLEHHHHHHH.HHHHLLLLLLHHHHHH
V EAG GR G VLT VLQ LA A
10. 1bpo_A 73.27 GTCIYMNRISGETIFVTAPHeaGIIgrKGQVltNVLQN.PDLA...LRMAV
LLEEEEEELLLLLEEEEEEELLEEEELLLEEEHHLLLL.HHHH...HHHHH
A GL V P A A D AE I G
11. 1ba1 72.73 ..AGTI..AGLNVLRIINEPTA........AAIAYGLDKKVGAERNVLigG
..HHHH..LLLEEEEEEEHHHH........HHHHLLLLLLLLLLEEEEELL
L L V Q T T L L GTL A
12. 1yge 72.67 lFMLDYHDIFMPYVRQINQLNSAKTYATRTIL..FLREDGTLKP....VAI
EEEEELHHHHHHHHHHHHLLLLLLLLEEEEEE..EELLLLLEEE....EEE
S P L P V A GTL E IA
13. 1ecf_B 72.47 DNPVS..NPCLFEYVYFARPDS.FIDKI.SVYSARV.NMGtlGEK...IAR
LLLLL..LLEHHHHHLLLLLLL.EELLE.EHHHHHH.HHHHHHHH...HHH
L L VPVV AG RT T E D A
14. 1oac_A 72.47 LD.LDVDGENNSLvpVVKPNTAG.GPRTSTMQ...VNQYNIGNEQD..AAQ
EE.ELLLLLEEEEEEEEEELLLL.LLLLEEEE...EEEEEELEHHH..HLE
A PG VV V EQ E G V A G LA D IA
15. 1onr_A 72.27 .PA...EDPG..VVSVSeqkEHGY...ETVVMGASFRNIgeLAGCdlTIAP
.HH...HLHH..HHHHHHHHHLLL...LLEEEEELLLLHHHLLLLLEEELH
A L V VVE P A T L A L L I A
16. 1nhp 72.27 VMAQKLGKE.TKAVTVVenPdaWFkpETTQILGAQLMSKADLTanAISLAI
HHHHHHLLL.LEEEEEEELLLEEEELLLLEEEEEEEEELLLLLLHHHHHHH
L A H V E AG G V A LQ G HD IA
17. 1pii 72.00 LMAHDDLHAAVRRVLLGENkdAgyGgqAQEVMAAalQYVGVFRNHD..IAD
HHLLLLHHHHHHHHHHLLLEHHLEEEHHHHHHHHLLEEEEEELLLL..HHH
L L LK P LQ VPV E R G VL H E A
18. 1kfs_A 71.93 LQ.LHLkwPDLqlVPVLSRIE.....RNGVKIDpvLHNHS..EELTLRLA.
HH.HHHHHHHLLHHHHHHHHH.....HHLELELHHHHHHH..HHHHHHHH.
LEA H GL P V P G R L A G E D Y A
19. 1adj_A 71.87 LeaFEVHHegLSElpRV..PGVGfvERVALALEA..EGFGLPEEkdLyvAE
ELEEEEELLLHHHHLLL..LEEEEHHHHHHHHHH..LLLLLLLLLLEEHHH
L A P V P E GR GTV T G D I G
20. 1eft 71.73 LDAiyIPTPVRDvkPFLMPVEDVftGR.GTVATGRI.ERGKVKVGdvEIVG
HHHHHLLLLLLLLLLLEEEEEEEELLL.EEEEEEEL.LELEEELLLEEELL
---
--- TOPITS ALIGNMENTS CONTINUED
---
1. 1ndh 82.80 GPPPMIQYapNL...ErgHPKERCF..AF
LLLHHHLLLHHH...HHLLLHHHEE..LL
R CS D D
2. 2pia 76.13 LRDANVRVpkTALCSGEADHRDMVLRD
HHHLLLLLLEEEEEELLEELLLLLLLL
G K A E ARED L G A I
3. 1der_A 75.67 GGVAVIKvaTEVEMKEKKAreDALhgGGVALI
LLEEEEELLLLLHHHHHHHHHHHHHLLLHHHH
G M K D S A R A
4. 1fnc 74.87 GLKGMEKGIDDIMVSLAAAEgkRQLKKA
ELHHHHHHHHHHHHHHHHLLLHHHHHHL
MA AR E F
5. 1uox 74.67 ...KMAelARQQLIeeYSLPNKHYFEIDLSW
...HHHHHHHLLLEEEEEEEELLEEELLLLL
RFE I D F D
6. 1aa6 74.40 VrfEDLeiVQDIFMTKTASAADVIL
HHHHHLLEEEELELLHHHHLLLEEE
E K A LF R R A
7. 1pys_B 74.27 PPleGHklAFHlfhPKRTLRDEEV.EEAVS
LLLLLEEEEEEEELLLLLLLHHHH.HHHHH
G M IA DL SER A L GD FA
8. 4enl 73.73 GWGVMVsiA.DLvrSERLAKLNQllGdvFA
LLEEEEEHH.HHHLHHHHHHHHHHHHHEEL
G D N G AF F
9. 1sqc 73.60 GEWLLDrvPGDWAVKRPNLKPG...GFAFQF
HHHHHHLLLLHHHHLLLLLLLL...LLLLLL
R A A LF NA LF
10. 1bpo_A 73.27 VRNNLAG.AEELFARKFNA....LFAQ
HHLLLLL.LHHHHHHHHHH....HHHL
G F I F A L G F FI
11. 1ba1 72.73 GTFDVstIEDGIFEVKSTAGDTHLGGEDfhFI
LLEEEEEEELLEEEEEEEEEELLLLHHHHHHH
A DL A E L A
12. 1yge 72.67 IELSLPHSAGDLSAAVSqaKEgwLLAKAYVIV
EEEELLLLLLLLLLLLLELLLHHHHHHHHHHH
E I E A E R G F
13. 1ecf_B 72.47 REWEDLDIDVVIPIPETsaLeaRILGKPygFV
HHLLLLLLLEEEELLLLLHHHHHHHLLLELEE
F I R L S N E R G
14. 1oac_A 72.47 QKFDPGTI.RLL..SNPN.KENRM.GNPVSY
ELLLLLLE.EEE..EEEE.EELLL.LLEEEE
E A I R L E AR R F
15. 1onr_A 72.27 PAleLAeiERKlyTGEVKARPARITESEFLW
HHHHHHHLLLLLLLLLLLLLLLLLLHHHHHH
AK DL A D F AF
16. 1nhp 72.27 IQ...AKMteDL......AYADFFFQPAF
HH...LLLEHHH......HLLLLLLLLLL
AK A L E D L A A
17. 1pii 72.00 DVVDKAKvaVQLHGNEEQLYIDTL.REAlaHV
HHHHHHHHEEEELLLLLHHHHHHH.HHHLLLL
E K A E N LF
18. 1kfs_A 71.93 ...ELEKKAHEIAGEEFNLSSTklF
...HHHHHHHHHLLLLLLLLLLLHL
F A R ER A E L G AFAF
19. 1adj_A 71.87 EAFYLAEALRPRLRAerkakeEAlrGAAFafL
HHHHHHHHHLLLLLEELLHHHHHHLLLLEEEE
G A R R GD
20. 1eft 71.73 G...LAPETRKTVVTgrKTLQEGIAGDNVGLL
L...LLLLLEEEEEEELEEELEEELLLEEEEE
---
--- TOPITS ALIGNMENTS END
---
The alignments from threading in MSF format:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
MSF of: /home/phd/server/work/predict_h6314640.hsspTopits from: 1 to: 232
/home/phd/server/work/predict_h6314640.msfTopits MSF: 232 Type: P 3-Feb-00 04:34:2 Check: 6594 ..
Name: predict_h6310 Len: 232 Check: 7806 Weight: 1.00
Name: 1ndh Len: 232 Check: 3236 Weight: 1.00
Name: 2pia Len: 232 Check: 8303 Weight: 1.00
Name: 1der_A Len: 232 Check: 255 Weight: 1.00
Name: 1fnc Len: 232 Check: 5648 Weight: 1.00
Name: 1uox Len: 232 Check: 4613 Weight: 1.00
Name: 1aa6 Len: 232 Check: 9992 Weight: 1.00
Name: 1pys_B Len: 232 Check: 5752 Weight: 1.00
Name: 4enl Len: 232 Check: 5130 Weight: 1.00
Name: 1sqc Len: 232 Check: 8389 Weight: 1.00
Name: 1bpo_A Len: 232 Check: 2196 Weight: 1.00
Name: 1ba1 Len: 232 Check: 7766 Weight: 1.00
Name: 1yge Len: 232 Check: 5639 Weight: 1.00
Name: 1ecf_B Len: 232 Check: 9634 Weight: 1.00
Name: 1oac_A Len: 232 Check: 4992 Weight: 1.00
Name: 1onr_A Len: 232 Check: 737 Weight: 1.00
Name: 1nhp Len: 232 Check: 1863 Weight: 1.00
Name: 1pii Len: 232 Check: 2824 Weight: 1.00
Name: 1kfs_A Len: 232 Check: 5538 Weight: 1.00
Name: 1adj_A Len: 232 Check: 4043 Weight: 1.00
Name: 1eft Len: 232 Check: 2238 Weight: 1.00
//
1 50
predict_h6310 TTLSCKVTSV EAITDTVYRV RIVPDAAFSF RAGQYLMVVM DERDKRPFSM
1ndh .......... PAItdIKYPL RLipEHILGL PVGqyLSARI DGNLvrPYTP
2pia TtlRLKIASK EKIARDIWSF ELtpQGapPF EAGANLTVAV PNGSRRTYSL
1der_A TTTA.TVLAQ AIITEGLKAV .....AamDL KRGIDKAVTV AVEELKALSV
1fnc ..LNTKITGD DAPGET.WHM VFSHEGEIPY REGQSVGVIP DGEDkrLYSI
1uox .....KVHKD EKtvQTVYev LLEGEIETSy kADNSVIVAT DSIKNTIYIT
1aa6 ..MSNAINEI DN.TDLVfsH PIVANHVINa rNGAKIIV.. ..CDPRKIET
1pys_B TPPSHRllRL EelVEEVARI qtIPLaafpY RKEQRLREvm DPEDARRFRL
4enl ..VSLAASRA AAAEKNVPLY KHLADLSKS. KTSPYVlvvL NGGShqEFMI
1sqc .......TTI EAYVALKY.I GMSRDeaLRF IQSqwLALVG epWEKVPM..
1bpo_A HTMTDDVTFW KWI..SLNTV ALVTDNawSM .EGESQPVKM FDRHS...SL
1ba1 ........AV GIDLGTTykV GV.......F QHGKVEIIAN DQGNrtPSYV
1yge .....HLKSK DALegTKSLS QIVQPaaFDL KSTPifHSFQ DVHdkLPRDV
1ecf_B TAGSSSASEA QpyVNSPYGI TLAHNGNLT. NAHELRKKLF EE..KRRH.I
1oac_A .HLSMN.SRV GPMISTvyEG sivpDIGWYF KagDYGMGTL TsrGKDAPSN
1onr_A TTNPSLILNA AQIPE..YR. KLIDDaawnD RAQQ....IV DATDKLAVNI
1nhp .TVDPEVNNV VVI.GSGY.I GIEAAEAFA. KAGKKVTviL DRpdK.EFTD
1pii ..LECKKASP svIRDDFDPA RI..AAIYKH YASA.ISVLT DEKyqGSFni
1kfs_A ..FDTETDSL DNISANLVGL siEPgaAYIP VAHDYL.... DAPDqrALEl
1adj_A TQVFEK..GV GAATD..... .IVRKEMFTf rGGRSlmvyL EHGMkqplWM
1eft TTLTAALTFV TAAENPNVEV ki..DKAPEE RARGITihVE YETAKRHYSH
51 100
predict_h6310 ASTPDEKGFI ELHIGASEIN LYAKAVMDRI LKDHQIVVDI PHGEAWLRDD
1ndh VSSDDDKGFV DLVIKVYFKD THPkgKMSQY LESMKIGDTI erGpaIRPDK
2pia CNDSQERnvI AVKRDSnsIS F.....IDDT SEGDAVEVSL PRNE.FPLDK
1der_A PCS.DSKAIA QvtISAnetk LIAEA.MDKV GKEGVITVED GTG...LQDe
1fnc ASSadAKS.V SLCvdAGET. ..IKGVCSNF LCdaEVKLTG PVgeMLMPKD
1uox AktPPetHFI EkhIHAAHVN I....VCHRW TR.....MDi pHPHSFIRDS
1aa6 ARIADMH..I ALKNGSneEN LYDKavASri VEGyeSVEDI trQAARMYAQ
1pys_B ....DPPRLL LLNPLAPetH LFPGLV..RV LKEN...LDL DRPeaLlrER
4enl APT.GAKTFA elRIG.SEvn L..KSLTKKR YGASAGNVGD EGGVaiQTAE
1sqc ..VPPEIMfm PLNI..YEFG SWARavMSrp LPERARvtDV PpgGGWIFDA
1bpo_A arTDAKQKWL LLtiSAQqmQ LYsrKVSQPI .EGhqFKMEG NAEESTlrGQ
1ba1 AFTDTER.Li qVAMNPTNTV FDAKRLIGRR FDDAVVQSDM KHWPFMVVND
1yge IST.....II PLPV....ie LY.RTDGQHI LKFPqhVVQV SQ.SAWMTDE
1ecf_B NTTSDSE..I LLNIFASEln IFAaaATNRL IRGAYACVai GHGMVAFRDP
1oac_A AVLLNET..I ADYTgpMEI. PRAIAVFERy yKHQEMgvST ERRELVVrxd
1onr_A gsTEVDARlt EASIAKAkiK LYNDAGidRI lkLASTWQGI RAAEQLEKEG
1nhp VLTEeeANNI TIATGET.VE RYekVVTDKN AYDADLVvgV RPNTAWLKGt
1pii VsaPQpkDFI ...IDPYQIY lyaDalMLSV LDDDQylAAV AHseVSNEEE
1kfs_A pLLEDEK... ALKVGQ...N ly.....Dri LANYGIEL.. .RGIAFDTML
1adj_A aaERPQKgfH QVNYEasE.n lDAEAvlYEC LKerRLKVKl pHREA.LSEd
1eft VDCPGHADYI KNMigAAQMd lVVSAameHI LLARqivvDM VDDPEllVEM
101 150
predict_h6310 EERPMILIAG GTGFSYARSI LLTALARNPN RDITIYWGGR EEQHLYDLCE
1ndh KSSPVimIAG GTGIT...PM liRAIMKDPD .DHtlLFANQ TEKDILLRPE
2pia RAKSFILVAG GIglSMarSF RLYYLTRDPe sDVKifwkSK PAQHVYC.CG
1der_A eeSPFILLA. DKKISNIREM llEAVAknTM RGIVKvfGDR RKAMLQDimE
1fnc PNATIIMLGT GTGIAPFRSF LWKMFFEKhn GLAWLFLGVP TSSSLLYKEE
1uox EEKRNVqvVE GKGIDIKSSL slTVL.KSTN SQ...FWglR DetTlwdltD
1aa6 AKSAAILwmG VTQF.yvRS. .LTSLagNLG KPHAGVNPVR GQNNVQGACD
1pys_B EETHllLFGE GVGLPWAKER llEAlarhPG VSGRVLVEGE EVGFLGALHP
4enl EALDLIviaA GhgLDCASSE FFkdLdkNPN SDKSKWLTGP QLADLYhlmd
1sqc LDRALHGYQK LSVHPFRRAA EIRALDWLLE RQadGSWGGI QPPWFYALIA
1bpo_A AGGKLHIIEV GtpfkKAVDV FFPPEAQneK HDVVFLITKY GYIHLYDLET
1ba1 AGRPKVQVeg ETKSFYpsSM VLteIAEatN AVVTvyFNDS QRQATKD...
1yge eaREMivIRG LEEFP.PKSN LDPAIYGDQS SKIT.....A DSLDlyTMDe
1ecf_B NgrPLVlieN RTEYMVAssV ALDTLGFDFL RDvaIYI..T EEGQLFtqCA
1oac_A hENGTIGiaG ATGIEAVKGv mHDETAKDDT RYGTLiiVGT THQHIYNF.R
1onr_A INCNLTLL.. ...FSFAQaf LISPFVGR.. ..ILDWYKAN TDKKEYA...
1nhp eLHPNGLiaV gtLIKyaDTE VNIALATNAR KqvKPFPggS SGLAVFdiNE
1pii QERAIALGAK VVGIN.NrsI DlrELAPKLG HNVTvyAQVR ELSHFAnlsA
1kfs_A ESYILNSVAG RHDmsLakTI TFEEIAGKGK NQLTFNQIAL EEAGRydV.T
1adj_A eENPMRILDS KSERDQA... LLKELGVRPM LD....FLGE eeRHLERLse
1eft EVRDLlyEFP GDEVPVIRGS ALLALekNPK TK.....RGE NedKIWEL..
151 200
predict_h6310 LEALSLKHPG LQVVPVVEQP EAGWRGRTGT VLTAVLQDHG TLAEHDIYIA
1ndh LEELRNEhaR FKLWYTVDRA PEAWDYSQGF VNEEMIRDHL PPPEEevLMC
2pia PQAltVRdtG HWPSGTveSF GanTNARENT PFTVRLSRSG TsaNRSILEV
1der_A LEKATLEDLG qrVvgVGE.. EAAIQGRVAQ IRQQIEedRE KLQERVAKLA
1fnc FEKMKEKApn FRLDFAVSRE QTNEKGEKMY IQTRMAQYAV ELWekdvYMC
1uox VDATWqnFSG LqvRSHVPKF DATwtAREVT LKT.FAEDNS ASVQATMY..
1aa6 MGALPDTYPG YQYvpavESL PagyrAAHGE VRAAYIMGED PLQTDAELSA
1pys_B EIAQELELPP VHllPLPDKp pAAFRDLAVV vvEALVREae SLALFDLYQG
4enl WEAWsfKTAG IQIVatVTNp tAIEKKAADA LLLKVNQ.IG TlaAQDSFAA
1sqc LKILDmqHpg LELYG.VELD YGGwqAstGL AVLA.LRAAG LPADHdlVKA
1bpo_A GTCIYMNRIS GETIFVTAPH eaGIIgrKGQ VltNVLQN.P DLA...LRMA
1ba1 ..AGTI..AG LNVLRIINEP TA........ AAIAYGLDKK VGAERNVLig
1yge lFMLDYHDIF MPYVRQINQL NSAKTYATRT IL..FLREDG TLKP....VA
1ecf_B DNPVS..NPC LFEYVYFARP DS.FIDKI.S VYSARV.NMG tlGEK...IA
1oac_A LD.LDVDGEN NSLvpVVKPN TAG.GPRTST MQ...VNQYN IGNEQD..AA
1onr_A .PA...EDPG ..VVSVSeqk EHGY...ETV VMGASFRNIg eLAGCdlTIA
1nhp VMAQKLGKE. TKAVTVVenP daWFkpETTQ ILGAQLMSKA DLTanAISLA
1pii LMAHDDLHAA VRRVLLGENk dAgyGgqAQE VMAAalQYVG VFRNHD..IA
1kfs_A LQ.LHLkwPD LqlVPVLSRI E.....RNGV KIDpvLHNHS ..EELTLRLA
1adj_A LeaFEVHHeg LSElpRV..P GVGfvERVAL ALEA..EGFG LPEEkdLyvA
1eft LDAiyIPTPV RDvkPFLMPV EDVftGR.GT VATGRI.ERG KVKVGdvEIV
201 232
predict_h6310 GRFEMAKIAR DLFCSERNAR EDRLFGDAFA FI
1ndh GPPPMIQYap NL...ErgHP KERCF..AF. ..
2pia LRDANVRVpk TALCSGEADH RDMVLRD... ..
1der_A GGVAVIKvaT EVEMKEKKAr eDALhgGGVA LI
1fnc GLKGMEKGID DIMVSLAAAE gkRQLKKA.. ..
1uox ...KMAelAR QQLIeeYSLP NKHYFEIDLS W.
1aa6 VrfEDLeiVQ DIFMTKTASA ADVIL..... ..
1pys_B PPleGHklAF HlfhPKRTLR DEEV.EEAVS ..
4enl GWGVMVsiA. DLvrSERLAK LNQllGdvFA ..
1sqc GEWLLDrvPG DWAVKRPNLK PG...GFAFQ F.
1bpo_A VRNNLAG.AE ELFARKFNA. ...LFAQ... ..
1ba1 GTFDVstIED GIFEVKSTAG DTHLGGEDfh FI
1yge IELSLPHSAG DLSAAVSqaK EgwLLAKAYV IV
1ecf_B REWEDLDIDV VIPIPETsaL eaRILGKPyg FV
1oac_A QKFDPGTI.R LL..SNPN.K ENRM.GNPVS Y.
1onr_A PAleLAeiER KlyTGEVKAR PARITESEFL W.
1nhp IQ...AKMte DL......AY ADFFFQPAF. ..
1pii DVVDKAKvaV QLHGNEEQLY IDTL.REAla HV
1kfs_A ...ELEKKAH EIAGEEFNLS STklF..... ..
1adj_A EAFYLAEALR PRLRAerkak eEAlrGAAFa fL
1eft G...LAPETR KTVVTgrKTL QEGIAGDNVG LL
________________________________________________________________________________
TOPITS (threading) results in STRIP format:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
================================================== MAXHOM-STRIP =====================================================
test sequence : /home/phd/server/work/predict_h6314640.phdDssp
list name : /home/phd/server/pub/topits/mat/Topits_dssp_99_01.
last name was : /data/dssp/2plc.dssp
seq_length : 232
alignments : 500
sort-mode : ZSCORE
weights 1 : NO
weights 2 : NO
smin : -1.00
smax : 2.00
maplow : 0.00
maphigh : 0.00
epsilon : 0.00
gamma : 0.00
gap_open : 2
gap_elongation : 0.2
INDEL in sec-struc of SEQ 1: YES
INDEL in sec-struc of SEQ 2: YES
NBEST alignments : 1
secondary structure alignment: NO
=================================================== SUMMARY ===========================================================
IAL VAL LEN IDEL NDEL ZSCORE %IDEN STRHOM LEN2 RMS SIGMA NAME
1 82.80 210 69 18 2.31 0.31 0.58 270 -1.00 0.000 1ndh CYTOCHROME B=5= REDUCTASE (E.C.1.6.2.2) .
2 76.13 220 85 19 1.97 0.29 0.54 321 -1.00 0.000 2pia PHTHALATE DIOXYGENASE REDUCTASE (E.C.1.18.1.) .
3 75.67 229 128 23 1.95 0.33 0.40 525 -1.00 0.000 1der_A MOL_ID: 1; .
4 74.87 222 47 13 1.91 0.27 0.75 296 -1.00 0.000 1fnc FERREDOXIN:NADP+ OXIDOREDUCTASE (FERREDOXIN REDUCTASE, .
5 74.67 207 60 25 1.90 0.31 0.27 295 -1.00 0.000 1uox MOL_ID: 1; .
6 74.40 220 84 21 1.89 0.31 0.39 698 -1.00 0.000 1aa6 MOL_ID: 1; .
7 74.27 224 112 25 1.88 0.31 0.44 785 -1.00 0.000 1pys_B MOL_ID: 1; .
8 73.73 226 100 27 1.85 0.34 0.44 436 -1.00 0.000 4enl ENOLASE (E.C.4.2.1.11) (2-PHOSPHO-*D-GLYCERATE HYDROLASE) .
9 73.60 217 78 21 1.84 0.30 0.40 619 -1.00 0.000 1sqc MOL_ID: 1; .
10 73.27 217 78 21 1.83 0.30 0.44 487 -1.00 0.000 1bpo_A MOL_ID: 1; .
11 72.73 208 59 16 1.80 0.26 0.46 378 -1.00 0.000 1ba1 MOL_ID: 1; .
12 72.67 204 60 20 1.80 0.30 0.23 839 -1.00 0.000 1yge MOL_ID: 1; .
13 72.47 217 50 24 1.79 0.29 0.38 500 -1.00 0.000 1ecf_B MOL_ID: 1; .
14 72.47 214 77 26 1.79 0.33 0.31 720 -1.00 0.000 1oac_A MOL_ID: 1; .
15 72.27 210 76 24 1.78 0.30 0.26 316 -1.00 0.000 1onr_A MOL_ID: 1; .
16 72.27 217 87 25 1.78 0.32 0.34 447 -1.00 0.000 1nhp NADH PEROXIDASE (NPX) (E.C.1.11.1.1) MUTANT WITH CYS 42 .
17 72.00 226 92 27 1.76 0.33 0.33 452 -1.00 0.000 1pii N-(5'PHOSPHORIBOSYL)ANTHRANILATE ISOMERASE (E.C.5.3.1.24) .
18 71.93 197 75 23 1.76 0.32 0.45 602 -1.00 0.000 1kfs_A MOL_ID: 1; .
19 71.87 220 148 34 1.76 0.40 0.43 420 -1.00 0.000 1adj_A MOL_ID: 1; .
20 71.73 220 61 23 1.75 0.30 0.35 405 -1.00 0.000 1eft ELONGATION FACTOR TU (EF-TU) COMPLEXED WITH .
==================================== ALIGNMENTS ===================================
1 - 51 ....:....1....:....2....:....3....:....4....:....5
pred TTLSCKVTSVEAITDTVYRVRIVPDAAFSFRAGQYLMVVMDERDKRPFSMA
EEEEE EEE EEEEEEE EE EEEEEEE EE
OOBOBOBOBBOOBOOOBBOBOBOOOOOBOBOBBBBBBBBBOOOOOOBBBBB
LLLLLLLLLHHHHLLHHHHHLLLLLLHHHHLLLLHHHHHHLLLLLLLLLLL
AITD Y R P GQYL D RP
1. 1ndh 82.80 PAItdIKYPLRLipEHILGLPVGqyLSARIDGNLvrPYTPV
LLELLLEEEEEEELLLELLLLLLLEEEEEELLEEEEEELLL
TTL K S E I P A F AG L V R S
2. 2pia 76.13 TtlRLKIASKEKIARDIWSFELtpQGapPFEAGANLTVAVPNGSRRTYSLC
LLEEEEEEEEEEEELLEEEEEEELLLLLLLLLLLEEEEELLLLLEEEEELL
TT V IT V AA G V S
3. 1der_A 75.67 TTTA.TVLAQAIITEGLKAV.....AamDLKRGIDKAVTVAVEELKALSVP
HHHH.HHHHHHHHHHHHHHH.....HLHHHHHHHHHHHHHHHHHHHHHLEL
L K T A T R GQ V D DKR S A
4. 1fnc 74.87 LNTKITGDDAPGET.WHMVFSHEGEIPYREGQSVGVIPDGEDkrLYSIA
EEEELLLLLLLLLE.EEEEEELLLLLLLLLLLEEEEELLLELLEEEELL
KV E TVY V S A V D A
5. 1uox 74.67 KVHKDEKtvQTVYevLLEGEIETSykADNSVIVATDSIKNTIYITA
EEEELLLLLEEEEEEEEEELLHHHHLLLHHHLLLHHHHHHHHHHHH
S TD V IV R G V D R A
6. 1aa6 74.40 MSNAINEIDN.TDLVfsHPIVANHVINarNGAKIIV....CDPRKIETA
LLLLHHHHHH.LLEEEHLHHHHHHHHHHHLLLEEEE....ELLLLLHHH
T S E V R P AAF R Q L VMD D R F
7. 1pys_B 74.27 TPPSHRllRLEelVEEVARIqtIPLaafpYRKEQRLREvmDPEDARRFRL.
ELLLLLLLLLHHHHHHHHHHHHLLLLLLHHHHHHHHHHHELLLHHHHLLL.
S A V D S Y VV F A
8. 4enl 73.73 VSLAASRAAAAEKNVPLYKHLADLSKS.KTSPYVlvvLNGGShqEFMIA
HHHHHHHHHHHHHLLLHHHHHHHHHLL.LLLLEEEEEEELHHHLEEEEE
T EA Y D A F Q L V K P
9. 1sqc 73.60 TTIEAYVALKY.IGMSRDeaLRFIQSqwLALVGepWEKVPM...
HHHHHHHHHHH.HLLLLLLHHHHHHHLHHHHLLLLHHHLLL...
T VT I V V D A S G V M R S A
10. 1bpo_A 73.27 HTMTDDVTFWKWI..SLNTVALVTDNawSM.EGESQPVKMFDRHS...SLa
EELLLLLLEEEEE..ELLEEEEELLLEEEL.LLLLLLEEEEELLH...HHL
V T Y V F G D P A
11. 1ba1 72.73 AVGIDLGTTykVGV.......FQHGKVEIIANDQGNrtPSYVA
LEEEELLLLEEEEE.......EELLEEEELLLLLLLLEELLEE
S A T IV AAF D DK P
12. 1yge 72.67 HLKSKDALegTKSLSQIVQPaaFDLKSTPifHSFQDVHdkLPRDVI
LLLHHHLHHHHHHHHHLHHHHHHHLLLLLLLLLHHHHHHELLHHHH
T S Y A E KR
13. 1ecf_B 72.47 TAGSSSASEAQpyVNSPYGITLAHNGNLT.NAHELRKKLFEE..KRRH.IN
ELLELLLLLLLLEELLLLLEEEEEEEEEL.LHHHHHHHHHHH..HLLL.LL
LS V TVY IVPD F AG Y M R K S A
14. 1oac_A 72.47 HLSMN.SRVGPMISTvyEGsivpDIGWYFKagDYGMGTLTsrGKDAPSNA
EEEEE.LLLEEEEEEEEEEEEELLLLLLLLEHHHLLLLLELLLLLLLLLL
TT I YR DAA RA Q D DK
15. 1onr_A 72.27 TTNPSLILNAAQIPE..YR.KLIDDaawnDRAQQ....IVDATDKLAVNIg
ELLHHHHHHHLLLHH..HH.HHHHHHHHLLHHHH....HHHHHHHHHHHHH
T V V I Y I AF AG V D DK F
16. 1nhp 72.27 TVDPEVNNVVVI.GSGY.IGIEAAEAFA.KAGKKVTviLDRpdK.EFTDV
HLLLLLLEEEEE.LLLH.HHHHHHHHHH.HLLLEEEELLLLLLH.HHHHH
L CK S I D RI A A V DE F
17. 1pii 72.00 LECKKASPsvIRDDFDPARI..AAIYKHYASA.ISVLTDEKyqGSFniV
EEELLEELLELLLLLLHHHH..HHHHLLLLLE.EEEELLLLLLLLLLHH
S I I P AA A YL D D R
18. 1kfs_A 71.93 FDTETDSLDNISANLVGLsiEPgaAYIPVAHDYL....DAPDqrALElp
EEEEELLLLLLLLLEEEEEEELLEEEEELLLLLL....LLLLLHHHHHH
T K V A TD IV F FR G LMV K P MA
19. 1adj_A 71.87 TQVFEK..GVGAATD......IVRKEMFTfrGGRSlmvyLEHGMkqplWMa
HHHHHH..HHLLLLH......HHHHLLLEELLLLEEHHHHHLLHHLLEEEE
TTL T V A V I D A RA V E KR S
20. 1eft 71.73 TTLTAALTFVTAAENPNVEVki..DKAPEERARGITihVEYETAKRHYSHV
HHHHHHHHHHHHLLLLLLLLLL..LLLHHHHHHLLLLEEEEELLLLEEEEE
================================== ALIGNMENTS ==================================
51 - 101 ....:....1....:....2....:....3....:....4....:....5
pred ASTPDEKGFIELHIGASEINLYAKAVMDRILKDHQIVVDIPHGEAWLRDDE
EEEEEE HHHHHHHHHHHH EEEEE EEE
BBOOOOOOOBBBBBOBBOOOOOBOBBBOOBOOOOOBOBOBOOBOBBBOOOO
LLLLLLLLHHHHHLLLLHHHHHHHHHHHHHHLLLLEEELLLLLLHHHLLLL
S D KGF L I K M L I I G A D
1. 1ndh 82.80 VSSDDDKGFVDLVIKVYFKDTHPkgKMSQYLESMKIGDTIerGpaIRPDKK
LLLLLLLLLLLEEEEELLLLLLLLLHHHHHHHHLLLLLEEEEEEEELLLLL
E I I D V P E D
2. 2pia 76.13 CNDSQERnvIAVKRDSnsISF.....IDDTSEGDAVEVSLPRNE.FPLDKR
LLLLLLLLEEEEELLLLHHHH.....HHLLLLLLEEEELLLELL.LLLLLL
D K I A E L A A MD K I V G L D E
3. 1der_A 75.67 PCS.DSKAIAQvtISAnetkLIAEA.MDKVGKEGVITVEDGTG...LQDee
LLL.LHHHHHHHHHHLLHHHHHHHH.HHHLLLLLEEEEELLLL...LLLEL
AS D K L A E K V L D P GE D
4. 1fnc 74.87 ASSadAKS.VSLCvdAGET...IKGVCSNFLCdaEVKLTGPVgeMLMPKDP
LLLLLLLE.EEEEELLLLE...EELHHHHHHHLLEEEEEEEELLLLLELLL
A TP E FIE HI A N V R DIPH RD E
5. 1uox 74.67 AktPPetHFIEkhIHAAHVNI....VCHRWTR.....MDipHPHSFIRDSE
HHLLHHHHHHHHLEEEEEEEE....EEELLEE.....EEEEEEEEEELLLL
A D I L G E NLY KAV RI V DI A
6. 1aa6 74.40 ARIADMH..IALKNGSneENLYDKavASriVEGyeSVEDItrQAARMYAQA
HHHLLEE..ELLLLLLHHLLLLLHHHHHHHHLLLHHHHHHHHHHHHHHHHL
D L A E L V R LK D EA LR E
7. 1pys_B 74.27 ....DPPRLLLLNPLAPetHLFPGLV..RVLKEN...LDLDRPeaLlrERE
....LLLLLEELLLLLHHLLLHHHHH..HHHHHH...HHHLLLLEEELLLE
A T K F EL IG SE NL K V G A E
8. 4enl 73.73 APT.GAKTFAelRIG.SEvnL..KSLTKKRYGASAGNVGDEGGVaiQTAEE
ELL.LLLLHHHHHHH.HHHHH..HHHHHHHHLHHHHLELLLLLELLLLHHH
P E F L I E A AVM R L V D P G W D
9. 1sqc 73.60 ..VPPEIMfmPLNI..YEFGSWARavMSrpLPERARvtDVPpgGGWIFDAL
..LLHHHHHLLLLH..HHLLHHHHHHHHHLLLHHHLLLLLLLLLLHHHHHH
A T L I A LY V I HQ E LR
10. 1bpo_A 73.27 arTDAKQKWLLLtiSAQqmQLYsrKVSQPI.EGhqFKMEGNAEESTlrGQA
LEELLLLLEEEEEEEEELEEEEELLLEEEE.LLLEEELLLLLLEEEELLLL
A T E I AK R D D H D
11. 1ba1 72.73 AFTDTER.LiqVAMNPTNTVFDAKRLIGRRFDDAVVQSDMKHWPFMVVNDA
EELLLLE.EELLLLLHHHEELLHHHLLLLLLLLHHHHHHHLLLLLEEEEEL
ST I L I LY ILK Q VV AW D E
12. 1yge 72.67 IST.....IIPLPV....ieLY.RTDGQHILKFPqhVVQVSQ.SAWMTDEe
HHH.....HLLLLL....HHHL.EELLLLEEELLLHHHLLLL.LHHHLHHH
T D I L I ASE N A A R V I HG RD
13. 1ecf_B 72.47 NTTSDSE..ILLNIFASElnIFAaaATNRLIRGAYACVaiGHGMVAFRDPN
LLLLHHH..HHHHHHHHHHHHHHHHHHHHHLLEEEEEEELLLEEEEEELLL
A E I G EI A AV R K V E R D
14. 1oac_A 72.47 AVLLNET..IADYTgpMEI.PRAIAVFERyyKHQEMgvSTERRELVVrxdh
LEEEEEE..EELLLLEEEE.EEEEEEEEEEEEELLLLEEEEEEEEEEEEEE
ST E I I LY A DRILK I E
15. 1onr_A 72.27 gsTEVDARltEASIAKAkiKLYNDAGidRIlkLASTWQGIRAAEQLEKEGI
HEEELLHHHHHHHHHHHHHHHHHHLLLHHEEEEELLHHHHHHHHHHHHLLL
T E I G Y K V D D VV AWL E
16. 1nhp 72.27 VLTEeeANNITIATGET.VERYekVVTDKNAYDADLVvgVRPNTAWLKGte
HHHHHHLLLEEEEELLL.EEEEEEEEELLLEEELLEEELEEELLHHHLLLL
S P K FI I I LYA A M L D Q H E
17. 1pii 72.00 VsaPQpkDFI...IDPYQIYlyaDalMLSVLDDDQylAAVAHseVSNEEEQ
HHLLLLELLL...LLHHHHHHHLLEEELLLLLHHHHHHHHHHHEELLHHHH
DEK L G NLY DRIL I G A E
18. 1kfs_A 71.93 pLLEDEK...ALKVGQ...Nly.....DriLANYGIEL...RGIAFDTMLE
HHHLLLL...LLEEEL...LHH.....HHHHHLLLLLL...LLEEEEHHHH
A KGF ASE NL A AV LK V PH EA L DE
19. 1adj_A 71.87 aaERPQKgfHQVNYEasE.nlDAEAvlYECLKerRLKVKlpHREA.LSEde
ELLLLLLLEEEEEEEELL.LHHHHHHHHHHHHHLLLEEEEHHHHH.LLHHL
P I IGA L A M IL QIVVD L E
20. 1eft 71.73 VDCPGHADYIKNMigAAQMdlVVSAameHILLARqivvDMVDDPEllVEME
EELLLLHHHHHHHHHHLLLLEEEELLLHHHHHHHLEEHHHLLLLLHHHHHH
================================== ALIGNMENTS ==================================
101 - 151 ....:....1....:....2....:....3....:....4....:....5
pred EERPMILIAGGTGFSYARSILLTALARNPNRDITIYWGGREEQHLYDLCEL
EEEEE HHHHHHHHHHHHHH EEEEE HHHHHHHHHH
OOOBBBBBBBBBBBBOBOBBBOBBBOOOOOOOBBBBBBBOOOOOBBBOOOB
LLLLHHHHLLLLLLLHHHHHHHHHHHLLLLLLLEEELLLLLHHHHHHHHHH
P I IAGGTG L A P D T E EL
1. 1ndh 82.80 KSSPVimIAGGTGIT...PMliRAIMKDPD.DHtlLFANQTEKDILLRPEL
LLEEELEEEEHHHHH...HHHHHHHHHLLL.LLLEEEEEEEHHHLLLHHHH
IL AGG G S ARS L L R P D I W QH Y C
2. 2pia 76.13 RAKSFILVAGGIglSMarSFRLYYLTRDPesDVKifwkSKPAQHVYC.CGP
LLLEEEEEEEHHHHHHHLEEEEEEEELLHHLLEEEHHLLLLLEEEEE.ELL
EE P IL A S R LL A A N R I G R L D EL
3. 1der_A 75.67 eeSPFILLA.DKKISNIREMllEAVAknTMRGIVKvfGDRRKAMLQDimEL
LELLEEEEE.LLEELLLHHHHHHHHLLHHLLLLLLELLHHHHHHHHHHHHH
I GTG RS L N G L E
4. 1fnc 74.87 PNATIIMLGTGTGIAPFRSFLWKMFFEKhnGLAWLFLGVPTSSSLLYKEEF
LLLEEEEEEEHHHHHHHHHHHHHHHLLLELLEEEEEEEELLHHHLLLHHHH
EE G G S LT L N WG R E L DL
5. 1uox 74.67 EEKRNVqvVEGKGIDIKSSLslTVL.KSTNSQ...FWglRDetTlwdltDV
LLEEEEEEELLLLEEEEEEEEEEEE.ELLLEL...ELLLLLLLLLLLEEEE
IL G T F Y RS LT LA N R C
6. 1aa6 74.40 AKSAAILwmGVTQF.yvRS..LTSLagNLGKPHAGVNPVRGQNNVQGACDM
LLLEEEEEHHHHLL.LHHH..HHHHHLLLLLLLLLEEELLLELLHHHHHHL
EE L G G A LL ALAR P G E L L
7. 1pys_B 74.27 EETHllLFGEGVGLPWAKERllEAlarhPGVSGRVLVEGEEVGFLGALHPE
EEEEEEEEELLEELLLLLLEEHHHHHHEEEEEEEEEELLEEEEEEEEELHH
E I IA G G A S L NPN D G LY L
8. 4enl 73.73 EALDLIviaAGhgLDCASSEFFkdLdkNPNSDKSKWLTGPQLADLYhlmdW
HHHHHHHHHLLLEEELLHHHHEELLLLLLLLLHHHLELHHHHHHHHHHHLH
R R AL R WGG Y L L
9. 1sqc 73.60 LDRALHGYQKLSVHPFRRAAEIRALDWLLERQadGSWGGIQPPWFYALIAL
HHHHHHHHHLLLLLLLHHHHHHHHHHHHHHHLLLLLLLLEHHHHHHHHHHH
I GT F A A N D HLYDL
10. 1bpo_A 73.27 AGGKLHIIEVGtpfkKAVDVFFPPEAQneKHDVVFLITKYGYIHLYDLETG
LLLEEEEEELLLLLLEEEELLLLLLLLLLLLLEEEEEELLLEEEEEELLLL
RP G T Y S LT A N T Y Q D
11. 1ba1 72.73 AGRPKVQVegETKSFYpsSMVLteIAEatNAVVTvyFNDSQRQATKD....
LLEEEEEEELEEEEELHHHHHHHHHHHHLEEEEEELLLHHHHHHHHH....
E R MI I G F S L A IT LY EL
12. 1yge 72.67 eaREMivIRGLEEFP.PKSNLDPAIYGDQSSKIT.....ADSLDlyTMDel
HHHHHHLLEELLLLL.LLLLLLHHHHLLLLLLLL.....HHHLLLLLHHHE
RP LI T A S L L RD IY EE L C
13. 1ecf_B 72.47 NgrPLVlieNRTEYMVAssVALDTLGFDFLRDvaIYI..TEEGQLFtqCAD
LLLLLEEELLEEEEEEELLHHHHHLLLEEEEELEEEE..ELLLLEEEELLL
E I IAG TG A R T G QH Y L
14. 1oac_A 72.47 hENGTIGiaGATGIEAVKGvmHDETAKDDTRYGTLiiVGTTHQHIYNF.RL
ELLLLEEEEEEEELLLEEELLLLLLHHHHLLLEEEEEEEELEEEEEEE.EE
L FS A L I Y
15. 1onr_A 72.27 INCNLTLL.....FSFAQafLISPFVGR....ILDWYKANTDKKEYA....
LLEEEEEE.....LLHHHHLEEEEELHH....HHHHHHHLLLLLLLL....
E P LIA GT YA ALA N GG D E
16. 1nhp 72.27 eLHPNGLiaVgtLIKyaDTEVNIALATNARKqvKPFPggSSGLAVFdiNEV
LELLLLLEELHLLEEEHLEEELLLLHHHHHHHLLLLLLLLEEEEELLLLHH
ER L A G RSI L LA T Y RE H L L
17. 1pii 72.00 QERAIALGAKVVGIN.NrsIDlrELAPKLGHNVTvyAQVRELSHFAnlsAL
HHHHHHLLLLEEEEE.LEEELLHHHHHHHLLLLEEHHHHHHHLLLLLEHHH
E AG S A I A T EE YD L
18. 1kfs_A 71.93 ESYILNSVAGRHDmsLakTITFEEIAGKGKNQLTFNQIALEEAGRydV.TL
HHHHHLLLLLLLLHHHHLLLLHHHHHLLHHHLLLHHHLLHHHHHHHHH.HH
EE PM A LL L P D G EE HL L EL
19. 1adj_A 71.87 eENPMRILDSKSERDQA...LLKELGVRPMLD....FLGEeeRHLERLseL
LLLHHHHLLLLLHHHHH...HHHHHLLLLHHH....HLLHHHHHHHHLLEE
E R G R L AL NP G E L L
20. 1eft 71.73 EVRDLlyEFPGDEVPVIRGSALLALekNPKTK.....RGENedKIWEL..L
HHHHHHLLLLLLLLLEEELLHHHHHHHLLLLL.....LLLLHHHHHHH..H
================================== ALIGNMENTS ==================================
151 - 201 ....:....1....:....2....:....3....:....4....:....5
pred LEALSLKHPGLQVVPVVEQPEAGWRGRTGTVLTAVLQDHGTLAEHDIYIAG
HHHHHHH EEEEEE HHHHHHHHHHHH E EEEE
BOOBBOOOOOBOBBBBBOOOOOOOOBOOBOBBOBBOOBBOOBBOBBBBBBB
HHHHHHLLLLLLEEHELLLLLLLLLLLLLHHHHHHHHLLLLHHLLLHHHHL
LE L H V W G V DH E G
1. 1ndh 82.80 LEELRNEhaRFKLWYTVDRAPEAWDYSQGFVNEEMIRDHLPPPEEevLMCG
HHLLHHHHLLEEEEEEEEELLLLLLLEELLLLLHHHHHHLLLHHHLEELLL
AL G VE A R T T L GT A I
2. 2pia 76.13 PQAltVRdtGHWPSGTveSFGanTNARENTPFTVRLSRSGTsaNRSILEVL
LHHHHHHHLLLLLLLLEELLLLLLLLLLLLLEEEEELLLLLELLLLHHHHH
LE L G VV V E EA GR D L E AG
3. 1der_A 75.67 LEKATLEDLGqrVvgVGE..EAAIQGRVAQIRQQIEedREKLQERVAKLAG
HLLLLLLLLEEEEEELLL..LHHHHHHHHHHHHHLLLHHHHHHHHHHHHLL
E K P V G T Q L E D Y G
4. 1fnc 74.87 FEKMKEKApnFRLDFAVSREQTNEKGEKMYIQTRMAQYAVELWekdvYMCG
HHHHHHHLLLEEEEEEELLLLELLLLLELLHHHHHHLLHHHHHHLLEEEEE
A GLQV V A W R T T D Y
5. 1uox 74.67 VDATWqnFSGLqvRSHVPKFDATwtAREVTLKT.FAEDNSASVQATMY...
EEEEEELELLHHHHHLHHHHHHHHHHHHHHHHH.HHHLLELLHHHHHH...
AL PG Q VP VE AG R G V A L A
6. 1aa6 74.40 MGALPDTYPGYQYvpavESLPagyrAAHGEVRAAYIMGEDPLQTDAELSAV
LLLELLEELLLEELHHLLLLLLLLHHHLLLLLEEEEELLLHHHHLLLLHHH
A L P P P A R V A LA D Y
7. 1pys_B 74.27 EIAQELELPPVHllPLPDKppAAFRDLAVVvvEALVREaeSLALFDLYQGP
HHHHHHLLLLLEELLLLLLLLLEEEEEEEEEHHHHHHHHEEEEEEEEELLL
EA S K G Q V V P A L V Q GTLA D AG
8. 4enl 73.73 WEAWsfKTAGIQIVatVTNptAIEKKAADALLLKVNQ.IGTlaAQDSFAAG
HHHHHHHHHLLEEEELLLLHHHHHLLLLLEEEELHHH.HLLHHHHHHHHLL
L L HPGL VE GW TG A L G A HD AG
9. 1sqc 73.60 LKILDmqHpgLELYG.VELDYGGwqAstGLAVLA.LRAAGLPADHdlVKAG
HHHLLLLLHHHHHHE.EELLLLLELLEHHHHHHH.HHHHLLLLLLHHHHHH
V EAG GR G VLT VLQ LA A
10. 1bpo_A 73.27 GTCIYMNRISGETIFVTAPHeaGIIgrKGQVltNVLQN.PDLA...LRMAV
LLEEEEEELLLLLEEEEEEELLEEEELLLEEEHHLLLL.HHHH...HHHHH
A GL V P A A D AE I G
11. 1ba1 72.73 ..AGTI..AGLNVLRIINEPTA........AAIAYGLDKKVGAERNVLigG
..HHHH..LLLEEEEEEEHHHH........HHHHLLLLLLLLLLEEEEELL
L L V Q T T L L GTL A
12. 1yge 72.67 lFMLDYHDIFMPYVRQINQLNSAKTYATRTIL..FLREDGTLKP....VAI
EEEEELHHHHHHHHHHHHLLLLLLLLEEEEEE..EELLLLLEEE....EEE
S P L P V A GTL E IA
13. 1ecf_B 72.47 DNPVS..NPCLFEYVYFARPDS.FIDKI.SVYSARV.NMGtlGEK...IAR
LLLLL..LLEHHHHHLLLLLLL.EELLE.EHHHHHH.HHHHHHHH...HHH
L L VPVV AG RT T E D A
14. 1oac_A 72.47 LD.LDVDGENNSLvpVVKPNTAG.GPRTSTMQ...VNQYNIGNEQD..AAQ
EE.ELLLLLEEEEEEEEEELLLL.LLLLEEEE...EEEEEELEHHH..HLE
A PG VV V EQ E G V A G LA D IA
15. 1onr_A 72.27 .PA...EDPG..VVSVSeqkEHGY...ETVVMGASFRNIgeLAGCdlTIAP
.HH...HLHH..HHHHHHHHHLLL...LLEEEEELLLLHHHLLLLLEEELH
A L V VVE P A T L A L L I A
16. 1nhp 72.27 VMAQKLGKE.TKAVTVVenPdaWFkpETTQILGAQLMSKADLTanAISLAI
HHHHHHLLL.LEEEEEEELLLEEEELLLLEEEEEEEEELLLLLLHHHHHHH
L A H V E AG G V A LQ G HD IA
17. 1pii 72.00 LMAHDDLHAAVRRVLLGENkdAgyGgqAQEVMAAalQYVGVFRNHD..IAD
HHLLLLHHHHHHHHHHLLLEHHLEEEHHHHHHHHLLEEEEEELLLL..HHH
L L LK P LQ VPV E R G VL H E A
18. 1kfs_A 71.93 LQ.LHLkwPDLqlVPVLSRIE.....RNGVKIDpvLHNHS..EELTLRLA.
HH.HHHHHHHLLHHHHHHHHH.....HHLELELHHHHHHH..HHHHHHHH.
LEA H GL P V P G R L A G E D Y A
19. 1adj_A 71.87 LeaFEVHHegLSElpRV..PGVGfvERVALALEA..EGFGLPEEkdLyvAE
ELEEEEELLLHHHHLLL..LEEEEHHHHHHHHHH..LLLLLLLLLLEEHHH
L A P V P E GR GTV T G D I G
20. 1eft 71.73 LDAiyIPTPVRDvkPFLMPVEDVftGR.GTVATGRI.ERGKVKVGdvEIVG
HHHHHLLLLLLLLLLLEEEEEEEELLL.EEEEEEEL.LELEEELLLEEELL
================================== ALIGNMENTS ==================================
201 - 232 ....:....1....:....2....:....3....:....4....:....5
pred GRFEMAKIARDLFCSERNAREDRLFGDAFAFI
HHHHHHHHHHHHHH HHHHHHHHHH
BOBOBBOBBOOOBOOOOOBOOOOBBBOBBBBB
LLHHHHHHLHHHHLLLLLLLLLHHHLLHHHHH
G M A L ER R F AF
1. 1ndh 82.80 GPPPMIQYapNL...ErgHPKERCF..AF
LLLHHHLLLHHH...HHLLLHHHEE..LL
R CS D D
2. 2pia 76.13 LRDANVRVpkTALCSGEADHRDMVLRD
HHHLLLLLLEEEEEELLEELLLLLLLL
G K A E ARED L G A I
3. 1der_A 75.67 GGVAVIKvaTEVEMKEKKAreDALhgGGVALI
LLEEEEELLLLLHHHHHHHHHHHHHLLLHHHH
G M K D S A R A
4. 1fnc 74.87 GLKGMEKGIDDIMVSLAAAEgkRQLKKA
ELHHHHHHHHHHHHHHHHLLLHHHHHHL
MA AR E F
5. 1uox 74.67 ...KMAelARQQLIeeYSLPNKHYFEIDLSW
...HHHHHHHLLLEEEEEEEELLEEELLLLL
RFE I D F D
6. 1aa6 74.40 VrfEDLeiVQDIFMTKTASAADVIL
HHHHHLLEEEELELLHHHHLLLEEE
E K A LF R R A
7. 1pys_B 74.27 PPleGHklAFHlfhPKRTLRDEEV.EEAVS
LLLLLEEEEEEEELLLLLLLHHHH.HHHHH
G M IA DL SER A L GD FA
8. 4enl 73.73 GWGVMVsiA.DLvrSERLAKLNQllGdvFA
LLEEEEEHH.HHHLHHHHHHHHHHHHHEEL
G D N G AF F
9. 1sqc 73.60 GEWLLDrvPGDWAVKRPNLKPG...GFAFQF
HHHHHHLLLLHHHHLLLLLLLL...LLLLLL
R A A LF NA LF
10. 1bpo_A 73.27 VRNNLAG.AEELFARKFNA....LFAQ
HHLLLLL.LHHHHHHHHHH....HHHL
G F I F A L G F FI
11. 1ba1 72.73 GTFDVstIEDGIFEVKSTAGDTHLGGEDfhFI
LLEEEEEEELLEEEEEEEEEELLLLHHHHHHH
A DL A E L A
12. 1yge 72.67 IELSLPHSAGDLSAAVSqaKEgwLLAKAYVIV
EEEELLLLLLLLLLLLLELLLHHHHHHHHHHH
E I E A E R G F
13. 1ecf_B 72.47 REWEDLDIDVVIPIPETsaLeaRILGKPygFV
HHLLLLLLLEEEELLLLLHHHHHHHLLLELEE
F I R L S N E R G
14. 1oac_A 72.47 QKFDPGTI.RLL..SNPN.KENRM.GNPVSY
ELLLLLLE.EEE..EEEE.EELLL.LLEEEE
E A I R L E AR R F
15. 1onr_A 72.27 PAleLAeiERKlyTGEVKARPARITESEFLW
HHHHHHHLLLLLLLLLLLLLLLLLLHHHHHH
AK DL A D F AF
16. 1nhp 72.27 IQ...AKMteDL......AYADFFFQPAF
HH...LLLEHHH......HLLLLLLLLLL
AK A L E D L A A
17. 1pii 72.00 DVVDKAKvaVQLHGNEEQLYIDTL.REAlaHV
HHHHHHHHEEEELLLLLHHHHHHH.HHHLLLL
E K A E N LF
18. 1kfs_A 71.93 ...ELEKKAHEIAGEEFNLSSTklF
...HHHHHHHHHLLLLLLLLLLLHL
F A R ER A E L G AFAF
19. 1adj_A 71.87 EAFYLAEALRPRLRAerkakeEAlrGAAFafL
HHHHHHHHHLLLLLEELLHHHHHHLLLLEEEE
G A R R GD
20. 1eft 71.73 G...LAPETRKTVVTgrKTLQEGIAGDNVGLL
L...LLLLLEEEEEEELEEELEEELLLEEEEE
9 119 104
________________________________________________________________________________
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- PredictProtein (PP): News 1999 -
-----------------------------------------------------------------------------
- -
- PP home: -
New York http://cubic.bioc.columbia.edu/predictprotein
- -
- PP mirrors: -
Australia (ANGIS) http://molmod.angis.org.au//predictprotein
England (EBI) http://www.ebi.ac.uk/~rost/predictprotein
Germany (EMBL) http://www.embl-heidelberg.de/predictprotein
India (CDFC) http://iris.cdfd.org.in/~www/pp/predictprotein
India (Pune) http://202.41.70.33/predictprotein
Israel (Beer-Sheva) http://www.cs.bgu.ac.il/~dfischer/predictprotein
Italy (Rome) http://obelix.bio.uniroma2.it/www/predictprotein
Singapore (BIC) http://embl.bic.nus.edu.sg/predictprotein
Spain (CNB) http://www.es.embnet.org/Services/MolBio/PredictProtein
Switzerland (Glaxo) http://www.gwer.ch/tools/predictprotein
- -
- Tools to post-process PP results: -
- -
- Generate a PostScript (or GIF, or TIFF): -
ESPript (New York) http://cubic.bioc.columbia.edu/cgi/pp/ESPript
ESPript (Toulouse) http://www-pgm1.ipbs.fr:8080/ESPript
- -
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