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I-TASSER results for job id S693108

(Click on S693108_results.tar.bz2 to download the tarball file including all modeling results listed on this page. Click on Annotation of I-TASSER Output to read the instructions for how to interpret the results on this page. Model results are kept on the server for 60 days, there is no way to retrieve the modeling data older than 2 months)

  Submitted Sequence in FASTA format

>protein
MTSKPDFYLQRGTADPQRSSETSKKSTVLAVPAFASPVEDDDDDRKYTYTPSTVEKVINI
LLCRGDLANRVLEVKPVSIFGLFRYATKWDRFCIFIGVICSIISGVSQPIMALVSGRVTN
VLLVYPPNSKEFRNEAYENVYIFLGIGVFVLITNFIQFMCFHSCCTRVISKMRHEYVRAI
LRQNAGWFDRNHSGALSTKLNDNMERIREGIGDKLGLLLRGCAMFTAAVIIAFIYEWRLA
LMMLGVTPTTCAIMSIMARKMTSTTMRELVGVGKAGSIAEESLMGVRTVQAFNGQQEMVD
RYSTELERGKSIAIWKGFWSGLLGGLFFFALFSFLGCGMLYGGYLLKVNIIKTPGDVFIV
VMSLLLGAYFLGLISPHLMVLLNARVAAATIYQTIDRVPKIDVYSEKGRKPDRIHGRVVF
ENVHFRYPSRKDVKVLNGLNLVIEPGQTVALVGHSGCGKSTSVGLLTRLYEPESGRVTID
GEDVRELNIDWLRNAVGIVQQEPCLFNDTVAGNLRMGNPTMSLEQMVYVCKMANAHDFIG
KLPNAYETYIGDGGVQLSGGQKQRIAIARTLARDPKVLLLDEATSALDAQSESIVQSALN
NASRGRTTIVIAHRLSTIRDANKIVFFEKGQIVEQGTHQELVASRGRYYELVKAQQFEPE
AEEVEEEEVDLGDNDGGSLLSGRSTLTQSKRSGSEAFVRGQALNDSFGRQSYNAEADAEN
EALALEVKRIMEEDGVISAGYIDIYKNATGNYHWIFLGFVTAVFRGMELPALSLVFAYVF
EAFQMVPWGADMMHRLCMAVIIFGSIGVGVVIFQLLISVFFAIVSYNLAMRFRVESFKNL
LYQDASYFDNPAHTPGKLITRLASDAPNIKAVVDGRALQVIYAMTAVIACIIIGFISSWQ
VTLMGIGMLIILATSMIWLALTIMNKNIELVKDDEAGRIAIETIENVRTIQLLTRMSTFY
GRYKAASKLGKRSESIKGIFEAINFTISQSFTYLMVCVCYAVGIHIIYTEQKTPDNVFRT
IIAMLLASVAVMNSSSYFPEFVKARTAAGLLFSVIYRKPRTGDANVGDKVTIRGNILFDD
VKFSYPQRPRQPIMRGLQFSAQRGQTVALVGPSGSGKSTIISMLERFYDTTGGYVRFDGK
DIKTLSLNHLRTQMALVGQEPRLFSGTIKQNICFGLGVVPMEKIDRALELANAKGFLANL
PAGIDTEVGEKGTQLSGGQKQRIAIARALVRDPKILLLDEATSALDSESERAVQKALDLA
REGRTCITIAHRLSSIQNADLIVYVENGKVRESGTHSQLMQRRGCYYQLIKKQDLTT

  Predicted Secondary Structure

Sequence                  20                  40                  60                  80                 100                 120                 140                 160                 180                 200                 220                 240                 260                 280                 300                 320                 340                 360                 380                 400                 420                 440                 460                 480                 500                 520                 540                 560                 580                 600                 620                 640                 660                 680                 700                 720                 740                 760                 780                 800                 820                 840                 860                 880                 900                 920                 940                 960                 980                1000                1020                1040                1060                1080                1100                1120                1140                1160                1180                1200                1220                1240                1260                1280                1300
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                 
MTSKPDFYLQRGTADPQRSSETSKKSTVLAVPAFASPVEDDDDDRKYTYTPSTVEKVINILLCRGDLANRVLEVKPVSIFGLFRYATKWDRFCIFIGVICSIISGVSQPIMALVSGRVTNVLLVYPPNSKEFRNEAYENVYIFLGIGVFVLITNFIQFMCFHSCCTRVISKMRHEYVRAILRQNAGWFDRNHSGALSTKLNDNMERIREGIGDKLGLLLRGCAMFTAAVIIAFIYEWRLALMMLGVTPTTCAIMSIMARKMTSTTMRELVGVGKAGSIAEESLMGVRTVQAFNGQQEMVDRYSTELERGKSIAIWKGFWSGLLGGLFFFALFSFLGCGMLYGGYLLKVNIIKTPGDVFIVVMSLLLGAYFLGLISPHLMVLLNARVAAATIYQTIDRVPKIDVYSEKGRKPDRIHGRVVFENVHFRYPSRKDVKVLNGLNLVIEPGQTVALVGHSGCGKSTSVGLLTRLYEPESGRVTIDGEDVRELNIDWLRNAVGIVQQEPCLFNDTVAGNLRMGNPTMSLEQMVYVCKMANAHDFIGKLPNAYETYIGDGGVQLSGGQKQRIAIARTLARDPKVLLLDEATSALDAQSESIVQSALNNASRGRTTIVIAHRLSTIRDANKIVFFEKGQIVEQGTHQELVASRGRYYELVKAQQFEPEAEEVEEEEVDLGDNDGGSLLSGRSTLTQSKRSGSEAFVRGQALNDSFGRQSYNAEADAENEALALEVKRIMEEDGVISAGYIDIYKNATGNYHWIFLGFVTAVFRGMELPALSLVFAYVFEAFQMVPWGADMMHRLCMAVIIFGSIGVGVVIFQLLISVFFAIVSYNLAMRFRVESFKNLLYQDASYFDNPAHTPGKLITRLASDAPNIKAVVDGRALQVIYAMTAVIACIIIGFISSWQVTLMGIGMLIILATSMIWLALTIMNKNIELVKDDEAGRIAIETIENVRTIQLLTRMSTFYGRYKAASKLGKRSESIKGIFEAINFTISQSFTYLMVCVCYAVGIHIIYTEQKTPDNVFRTIIAMLLASVAVMNSSSYFPEFVKARTAAGLLFSVIYRKPRTGDANVGDKVTIRGNILFDDVKFSYPQRPRQPIMRGLQFSAQRGQTVALVGPSGSGKSTIISMLERFYDTTGGYVRFDGKDIKTLSLNHLRTQMALVGQEPRLFSGTIKQNICFGLGVVPMEKIDRALELANAKGFLANLPAGIDTEVGEKGTQLSGGQKQRIAIARALVRDPKILLLDEATSALDSESERAVQKALDLAREGRTCITIAHRLSSIQNADLIVYVENGKVRESGTHSQLMQRRGCYYQLIKKQDLTT
PredictionCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCHHHHCCCCCCCCHHHHHHHCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHHCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSSSSSSSSCCCCCCCCCCCCSSSSSCCCCSSSSSCCCCCCHHHHHHHHHCCCCCCCCSSSSCCSSHHHCCHHHHHHHCCSSCCCCCCCCCHHHHHHHCCCCCCCHHHHHHHHHHHCHHHHHHHCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHCCCCHHHCCCCCCCCHHHHHHHHHHHHHHHCCCCSSSSSCCHHHHHCCCSSSSSSCCSSSSSSCHHHHHHCCCHHHHHHHHHHCCCCCCCCCCHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCHHHHHHCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSSSSSSCCCCCCCHHHCCCSSSSCCCCSSSSSCCCCCCHHHHHHHHHHCCCCCCCSSSSCCSSHHHCCHHHHHHHCCSSCCCCCSSCCCHHHHHHCCCCCCCHHHHHHHHHHHCCHHHHHCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHCCCCSSSSSCCCCCCCHHHHHHHHHHHHHHHCCCSSSSSHHHHHHHHHCCSSSSSSCCSSSSSCCHHHHHHCCCHHHHHHHHHCCCC
Conf.Score988875443547778543343346665556766678866765421123587410001232222221122025679878999998547888999999999999999999999999999999996279867999999999999999999999999999999999999999999999999999879904543898219999999769999999998999999999999999999999829999999999999999999999999999999999999999999999757899992087899999999999999999999999999999999999999999999999999976998987699999999999999999999999999999999999999976899999987788688888605999877887979999802267427977989899989999979999999960158889879899998312889999961745687753302039999962799999999999999968699997177645875478988578999999999999971798242317301254877999999999995799379970226567518989999899898872699998689889999998721355421110110123322221111234444443444322111233343210012344443332211101333210244565149999998557999999999999999999999999999999986078853779999999999999999999999999999999999999999999999999849904546899988999999998799999999878999999999999999999999599999999999999999999999998767889999999999999982269999862769999999999999999999999999999999999999999999999999995699789999999999999999999999987899999999999999976899999988888888876189988898895999973544950687799989998999998999999997463899987989999821279899996186668878200845999986589999999999999981839899716575688768998838889999999999997089964433602265598899999999999479939995543889982898999989889986279999878988999998645679
H:Helix; S:Strand; C:Coil

  Predicted Solvent Accessibility

Sequence                  20                  40                  60                  80                 100                 120                 140                 160                 180                 200                 220                 240                 260                 280                 300                 320                 340                 360                 380                 400                 420                 440                 460                 480                 500                 520                 540                 560                 580                 600                 620                 640                 660                 680                 700                 720                 740                 760                 780                 800                 820                 840                 860                 880                 900                 920                 940                 960                 980                1000                1020                1040                1060                1080                1100                1120                1140                1160                1180                1200                1220                1240                1260                1280                1300
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                 
MTSKPDFYLQRGTADPQRSSETSKKSTVLAVPAFASPVEDDDDDRKYTYTPSTVEKVINILLCRGDLANRVLEVKPVSIFGLFRYATKWDRFCIFIGVICSIISGVSQPIMALVSGRVTNVLLVYPPNSKEFRNEAYENVYIFLGIGVFVLITNFIQFMCFHSCCTRVISKMRHEYVRAILRQNAGWFDRNHSGALSTKLNDNMERIREGIGDKLGLLLRGCAMFTAAVIIAFIYEWRLALMMLGVTPTTCAIMSIMARKMTSTTMRELVGVGKAGSIAEESLMGVRTVQAFNGQQEMVDRYSTELERGKSIAIWKGFWSGLLGGLFFFALFSFLGCGMLYGGYLLKVNIIKTPGDVFIVVMSLLLGAYFLGLISPHLMVLLNARVAAATIYQTIDRVPKIDVYSEKGRKPDRIHGRVVFENVHFRYPSRKDVKVLNGLNLVIEPGQTVALVGHSGCGKSTSVGLLTRLYEPESGRVTIDGEDVRELNIDWLRNAVGIVQQEPCLFNDTVAGNLRMGNPTMSLEQMVYVCKMANAHDFIGKLPNAYETYIGDGGVQLSGGQKQRIAIARTLARDPKVLLLDEATSALDAQSESIVQSALNNASRGRTTIVIAHRLSTIRDANKIVFFEKGQIVEQGTHQELVASRGRYYELVKAQQFEPEAEEVEEEEVDLGDNDGGSLLSGRSTLTQSKRSGSEAFVRGQALNDSFGRQSYNAEADAENEALALEVKRIMEEDGVISAGYIDIYKNATGNYHWIFLGFVTAVFRGMELPALSLVFAYVFEAFQMVPWGADMMHRLCMAVIIFGSIGVGVVIFQLLISVFFAIVSYNLAMRFRVESFKNLLYQDASYFDNPAHTPGKLITRLASDAPNIKAVVDGRALQVIYAMTAVIACIIIGFISSWQVTLMGIGMLIILATSMIWLALTIMNKNIELVKDDEAGRIAIETIENVRTIQLLTRMSTFYGRYKAASKLGKRSESIKGIFEAINFTISQSFTYLMVCVCYAVGIHIIYTEQKTPDNVFRTIIAMLLASVAVMNSSSYFPEFVKARTAAGLLFSVIYRKPRTGDANVGDKVTIRGNILFDDVKFSYPQRPRQPIMRGLQFSAQRGQTVALVGPSGSGKSTIISMLERFYDTTGGYVRFDGKDIKTLSLNHLRTQMALVGQEPRLFSGTIKQNICFGLGVVPMEKIDRALELANAKGFLANLPAGIDTEVGEKGTQLSGGQKQRIAIARALVRDPKILLLDEATSALDSESERAVQKALDLAREGRTCITIAHRLSSIQNADLIVYVENGKVRESGTHSQLMQRRGCYYQLIKKQDLTT
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
Values range from 0 (buried residue) to 9 (highly exposed residue)

   Predicted normalized B-factor

(B-factor is a value to indicate the extent of the inherent thermal mobility of residues/atoms in proteins. In I-TASSER, this value is deduced from threading template proteins from the PDB in combination with the sequence profiles derived from sequence databases. The reported B-factor profile in the figure below corresponds to the normalized B-factor of the target protein, defined by B=(B'-u)/s, where B' is the raw B-factor value, u and s are respectively the mean and standard deviation of the raw B-factors along the sequence. Click here to read more about predicted normalized B-factor)


  Top 10 threading templates used by I-TASSER

(I-TASSER modeling starts from the structure templates identified by LOMETS from the PDB library. LOMETS is a meta-server threading approach containing multiple threading programs, where each threading program can generate tens of thousands of template alignments. I-TASSER only uses the templates of the highest significance in the threading alignments, the significance of which are measured by the Z-score, i.e. the difference between the raw and average scores in the unit of standard deviation. The templates in this section are the 10 best templates selected from the LOMETS threading programs. Usually, one template of the highest Z-score is selected from each threading program, where the threading programs are sorted by the average performance in the large-scale benchmark test experiments.)

Rank PDB
Hit
Iden1Iden2CovNorm.
Z-score
Download
Align.
                   20                  40                  60                  80                 100                 120                 140                 160                 180                 200                 220                 240                 260                 280                 300                 320                 340                 360                 380                 400                 420                 440                 460                 480                 500                 520                 540                 560                 580                 600                 620                 640                 660                 680                 700                 720                 740                 760                 780                 800                 820                 840                 860                 880                 900                 920                 940                 960                 980                1000                1020                1040                1060                1080                1100                1120                1140                1160                1180                1200                1220                1240                1260                1280                1300
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                 
Sec.Str
Seq
CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCHHHHCCCCCCCCHHHHHHHCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHHCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSSSSSSSSCCCCCCCCCCCCSSSSSCCCCSSSSSCCCCCCHHHHHHHHHCCCCCCCCSSSSCCSSHHHCCHHHHHHHCCSSCCCCCCCCCHHHHHHHCCCCCCCHHHHHHHHHHHCHHHHHHHCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHCCCCHHHCCCCCCCCHHHHHHHHHHHHHHHCCCCSSSSSCCHHHHHCCCSSSSSSCCSSSSSSCHHHHHHCCCHHHHHHHHHHCCCCCCCCCCHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCHHHHHHCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSSSSSSCCCCCCCHHHCCCSSSSCCCCSSSSSCCCCCCHHHHHHHHHHCCCCCCCSSSSCCSSHHHCCHHHHHHHCCSSCCCCCSSCCCHHHHHHCCCCCCCHHHHHHHHHHHCCHHHHHCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHCCCCSSSSSCCCCCCCHHHHHHHHHHHHHHHCCCSSSSSHHHHHHHHHCCSSSSSSCCSSSSSCCHHHHHHCCCHHHHHHHHHCCCC
MTSKPDFYLQRGTADPQRSSETSKKSTVLAVPAFASPVEDDDDDRKYTYTPSTVEKVINILLCRGDLANRVLEVKPVSIFGLFRYATKWDRFCIFIGVICSIISGVSQPIMALVSGRVTNVLLVYPPNSKEFRNEAYENVYIFLGIGVFVLITNFIQFMCFHSCCTRVISKMRHEYVRAILRQNAGWFDRNHSGALSTKLNDNMERIREGIGDKLGLLLRGCAMFTAAVIIAFIYEWRLALMMLGVTPTTCAIMSIMARKMTSTTMRELVGVGKAGSIAEESLMGVRTVQAFNGQQEMVDRYSTELERGKSIAIWKGFWSGLLGGLFFFALFSFLGCGMLYGGYLLKVNIIKTPGDVFIVVMSLLLGAYFLGLISPHLMVLLNARVAAATIYQTIDRVPKIDVYSEKGRKPDRIHGRVVFENVHFRYPSRKDVKVLNGLNLVIEPGQTVALVGHSGCGKSTSVGLLTRLYEPESGRVTIDGEDVRELNIDWLRNAVGIVQQEPCLFNDTVAGNLRMGNPTMSLEQMVYVCKMANAHDFIGKLPNAYETYIGDGGVQLSGGQKQRIAIARTLARDPKVLLLDEATSALDAQSESIVQSALNNASRGRTTIVIAHRLSTIRDANKIVFFEKGQIVEQGTHQELVASRGRYYELVKAQQFEPEAEEVEEEEVDLGDNDGGSLLSGRSTLTQSKRSGSEAFVRGQALNDSFGRQSYNAEADAENEALALEVKRIMEEDGVISAGYIDIYKNATGNYHWIFLGFVTAVFRGMELPALSLVFAYVFEAFQMVPWGADMMHRLCMAVIIFGSIGVGVVIFQLLISVFFAIVSYNLAMRFRVESFKNLLYQDASYFDNPAHTPGKLITRLASDAPNIKAVVDGRALQVIYAMTAVIACIIIGFISSWQVTLMGIGMLIILATSMIWLALTIMNKNIELVKDDEAGRIAIETIENVRTIQLLTRMSTFYGRYKAASKLGKRSESIKGIFEAINFTISQSFTYLMVCVCYAVGIHIIYTEQKTPDNVFRTIIAMLLASVAVMNSSSYFPEFVKARTAAGLLFSVIYRKPRTGDANVGDKVTIRGNILFDDVKFSYPQRPRQPIMRGLQFSAQRGQTVALVGPSGSGKSTIISMLERFYDTTGGYVRFDGKDIKTLSLNHLRTQMALVGQEPRLFSGTIKQNICFGLGVVPMEKIDRALELANAKGFLANLPAGIDTEVGEKGTQLSGGQKQRIAIARALVRDPKILLLDEATSALDSESERAVQKALDLAREGRTCITIAHRLSSIQNADLIVYVENGKVRESGTHSQLMQRRGCYYQLIKKQDLTT
14f4cA 0.41 0.40 0.93 7.87Download -------------------------SLRQSLRTLDSFSLAPEDVLKTAIKTVEDYEGDNIDSNGEIKITRDEVVNKVSIPQLYRYTTTLEKLLLFIGTLVAVITGAGLPLMSILQGKVSQAFINENYTKTDFEHDVMNVVWSYAAMTVGMWAAGQITVTCYLYVAEQMNNRLRREFVKSILRQEISWFDTNHSGTLATKLFDNLERVKEGTGDKIGMAFQYLSQFITGFIVAFTHSWQLTLVMLAVTPIQALCGFAIAKSMSTFAIRETLRYAKAGKVVEETISSIRTVVSLNGLRYELERYSTAVEEAKKAGVLKGLFLGISFGAMQASNFISFALAFYIGVGWVHDGSL-NFGDMLTTFSSVMMGSMALGLAGPQLAVLGTAQGAASGIYEVLDRKPVIDSSSKAGRKDMKIKGDITVENVHFTYPSRPDVPILRGMNLRVNAGQTVALVGSSGCGKSTIISLLLRYYDVLKGKITIDGVDVRDINLEFLRKNVAVVSQEPALFNCTIEENISLGKEGITREEMVAACKMANAEKFIKTLPNGYNTLVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDAESEGIVQQALDKAAKGRTTIIIAHRLSTIRNADLIISCKNGQVVEVGDHRALMAQQGLYYDLVTAQTFTDAVDSAAEG-------------------------------------------------ERIGKDALSRLKQELEENNAQKTNLFEILYHARPHALSLFIGMSTATIGGFIYPTYSVFFTSFMNVFAGNP--ADFLSQGHFWALMFLVLAAAQGICSFLMTFFMGIASESLTRDLRNKLFRNVLSQHIGFFDSPQNASGKISTRLATDVPNLRTAIDFRFSTVITTLVSMVAGIGLAFFYGWQMALLIIAILPIVAFGQYLRGRRFTGKNVKASEFADSGKIAIEAIENVRTVQALAREDTFYENFCEKLDIPHKEAIKEAFIQGLSYGCASSVLYLLNTCAYRMGLALIITDPPTPMRVLRVMYAITISTSTLGFATSYFPEYAKATFAGGIIFGMLRKISKIDLSLAGEKKKLYGKVIFKNVRFAYPERPEIEILKGLSFSVEPGQTLALVGPSGCGKSTVVALLERFYDTLGGEIFIDGSEIKTLNPEHTRSQIAIVSQEPTLFDCSIAENIIYGLDSVTMAQVEEAARLANIHNFIAELPEGFETRVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEKVVQEALDRAREGRTCIVIAHRLNTVMNADCIAVVSNGTIIEKGTHTQLMSEK--------------
24m1mA 0.42 0.39 0.8913.12Download -------------------------------------------------------------------------KPAVSVLTMFRYAGWLDRLYMLVGTLAAIIHGVALPLMMLIFGDMTDSFASKRAMFAKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHAIMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGFIIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFLLIYASYALAFWYGTSLVISKEY-SIGQVLTVFFSVLIGAFSVGQASPNIEAFANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSRKEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSIDGQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAVKEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGGVIVEQGNHDELMREKGIYFKLVMTQTKEALDEDVPPASFW------------------------------------------------------------------------RILKLNSTEWPYFVVGIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPETQRQNSNLFSLLFLILGIISFITFFLQGFTFGKAGEILTKRLRYMVFKSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKLEGSGKIATEAIENFRTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYAAAFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVSASHIIRIIEKTPEIDSTQGLKPNMLEGNVQFSGVVFNYPTRPSIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQLNVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSVSYEEIVRAAKEANIHQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEHGTHQQLLAQKGIYFSMVSVQA---
34f4cA 0.41 0.40 0.93 6.00Download --------------------NGSLRQSLRTLDSFSLAPEDVLKTAIKTVEDYEGDNIDSNGEIKIT---RDEVVNKVSIPQLYRYTTTLEKLLLFIGTLVAVITGAGLPLMSILQGKVSQAFINEQYTKTDFEHDVMNVVWSYAAMTVGMWAAGQITVTCYLYVAEQMNNRLRREFVKSILRQEISWFDTNHSGTLATKLFDNLERVKEGTGDKIGMAFQYLSQFITGFIVAFTHSWQLTLVMLAVTPIQALCGFAIAKSMSTFAIRETLRYAKAGKVVEETISSIRTVVSLNGLRYELERYSTAVEEAKKAGVLKGLFLGISFGAMQASNFISFALAFYIGVGWVHDGSL-NFGDMLTTFSSVMMGSMALGLAGPQLAVLGTAQGAASGIYEVLDRKPVIDSSSKAGRKDMKIKGDITVENVHFTYPSRPDVPILRGMNLRVNAGQTVALVGSSGCGKSTIISLLLRYYDVLKGKITIDGVDVRDINLEFLRKNVAVVSQEPALFNCTIEENISLGKEGITREEMVAACKMANAEKFIKTLPNGYNTLVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDAESEGIVQQALDKAAKGRTTIIIAHRLSTIRNADLIISCKNGQVVEVGDHRALMAQQGLYYDLVTAQTFTDAVDSAAE-------------------------------------------------GERIGKDALSRLKQELEENNAQKTNLFEILYHARPHALSLFIGMSTATIGGFIYPTYSVFFTSFMNVFAGNP--ADFLSQGHFWALMFLVLAAAQGICSFLMTFFMGIASESLTRDLRNKLFRNVLSQHIGFFDSPQNASGKISTRLATDVPNLRTAIDFRFSTVITTLVSMVAGIGLAFFYGWQMALLIIAILPIVAFGQYLRGRRFTGKNVKASEFADSGKIAIEAIENVRTVQALAREDTFYENFCEKLDIPHKEAIKEAFIQGLSYGCASSVLYLLNTCAYRMGLALIITDPPTPMRVLRVMYAITISTSTLGFATSYFPEYAKATFAGGIIFGMLRKISKIDSLSLAGKKKLYGKVIFKNVRFAYPERPEIEILKGLSFSVEPGQTLALVGPSGCGKSTVVALLERFYDTLGGEIFIDGSEIKTLNPEHTRSQIAIVSQEPTLFDCSIAENIIYGLDSVTMAQVEEAARLANIHNFIAELPEGFETRVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEKVVQEALDRAREGRTCIVIAHRLNTVMNADCIAVVSNGTIIEKGTHTQLMSEK--------------
47otgA 0.42 0.38 0.88 4.34Download ----------------------------------------------------------------------------VSVLTMFRYAGWLDRLYMLVGTLAAIIHGVALPLMMLIFGDMTDSFASVRAMFAKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHAIMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGFIIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFLLIYASYALAFWYGTSL-VISKEYSIGQVLTVFFSVLIGAFSVGQASPNIEAFANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSRKEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSIDGQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAVKEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGGVIVEQGNHDELMREKGIYFKLVMTQTDVPP---------------------------ASFWRILKLNSTEWPYFVV---------------------------------------------------GIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPETQRQNSNLFSLLFLILGIISFITFFLQGFTFGKAGEILTKRLRYMVFKSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYGWLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENFRTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYAACFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVSASHIIRIIEKTPEIDSYSTQGLKMLEGNVQFSGVVFNYPTRPSIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQLNVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSVSYEEIVRAAKEANIHQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEHGTHQQLLAQKGIYFSMVSVQA---
54f4c 0.41 0.40 0.93 1.51Download ----------NG--SLRQSLRTL---DSFSLAPED-VLKTAIKTVEDYEGDNIDSN-------GEIKITRDEVVNKVSIPQLYRYTTTLEKLLLFIGTLVAVITGAGLPLMSILQGKVSQAFINEQNYKTDFEHDVMNVVWSYAAMTVGMWAAGQITVTCYLYVAEQMNNRLRREFVKSILRQEISWFDTNHSGTLATKLFDNLERVKEGTGDKIGMAFQYLSQFITGFIVAFTHSWQLTLVMLAVTPIQALCGFAIAKSMSTFAIRETLRYAKAGKVVEETISSIRTVVSLNGLRYELERYSTAVEEAKKAGVLKGLFLGISFGAMQASNFISFALAFYIGVGWVHDGS-LNFGDMLTTFSSVMMGSMALGLAGPQLAVLGTAQGAASGIYEVLDRKPVIDSSSKAGRKDMKIKGDITVENVHFTYPSRPDVPILRGMNLRVNAGQTVALVGSSGCGKSTIISLLLRYYDVLKGKITIDGVDVRDINLEFLRKNVAVVSQEPALFNCTIEENISLGKEGITREEMVAACKMANAEKFIKTLPNGYNTLVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDAESEGIVQQALDKAAKGRTTIIIAHRLSTIRNADLIISCKNGQVVEVGDHRALMAQQGLYYDLVTAQTFTDAV-D----SAAE----GERI------------------G----K-D----------ALS-----RLK-QELEEN-NAQKTNLFEILYHARPHALSLFIGMSTATIGGFIYPTYSVFFTSFMNVFAGNPA-DFLSQGHFWALMLVLAAQGICSFLM---TFFMGIASESLTRDLRNKLFRNVLSQHIGFFDSPQNASGKISTRLATDVPNLRTAIDFRFSTVITTLVSMVAGIGLAFFYGWQMALLIIAILPIVAFGQYLRGRRFTGKNVKSASFADSGKIAIEAIENVRTVQALAREDTFYENFCEKLDIPHKEAIKEAFIQGLSYGCASSVLYLLNTCAYRMGLALIIPPTMQPMRVLRVMYAITISTSTLGFATSYFPEYAKATFAGGIIFGMLRKISKIDSLSLGEKKKLYGKVIFKNVRFAYPERPEIEILKGLSFSVEPGQTLALVGPSGCGKSTVVALLERFYDTLGGEIFIDGSEIKTLNPEHTRSQIAIVSQEPTLFDCSIAENIIYGLDPVTMAQVEEAARLANIHNFIAELPEGFETRVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEKVVQEALDRAREGRTCIVIAHRLNTVMNADCIAVVSNGTIIEKGTHTQLMSEK--------------
67otg 0.42 0.38 0.88 1.54Download ----------------------------------------------------------------------------VSVLTMFRYAGWLDRLYMLVGTLAAIIHGVALPLMMLIFGDMTDSFASVGNVSAKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHAIMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGFIIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFLLIYASYALAFWYGTSLVISKE-YSIGQVLTVFFSVLIGAFSVGQASPNIEAFANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSRKEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSIDGQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAVKEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGGVIVEQGNHDELMREKGIYFKLVMTQTDVPPA----------------S--------------------------------------------------------------FWRILKLNSTEWPYFVVGIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPTQRQNSNLFSLLLILGISFITFFLQ---GFTFGKAGEILTKRLRYMVFKSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKLEGSGKIATEAIENFRTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYAACFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVSASHIIRIIEKTPEIDSYSTGLKNMLEGNVQFSGVVFNYPTRPSIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQLNVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSVSYEEIVRAAKEANIHQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEHGTHQQLLAQKGIYFSMVSVQA---
74f4c 0.40 0.40 0.93 1.20Download -------------------NGSLRQSLRTLDSFSLAPEDVLKTAIKTVED--YEGDNIDSN--GEIKITRDEVVNKVSIPQLYRYTTTLEKLLLFIGTLVAVITGAGLPLMSILQGKVSQAFINEQYTKTDFEHDVMNVVWSYAAMTVGMWAAGQITVTCYLYVAEQMNNRLRREFVKSILRQEISWFDTNHSGTLATKLFDNLERVKEGTGDKIGMAFQYLSQFITGFIVAFTHSWQLTLVMLAVTPIQALCGFAIAKSMSTFAIRETLRYAKAGKVVEETISSIRTVVSLNGLRYELERYSTAVEEAKKAGVLKGLFLGISFGAMQASNFISFALAFYIGVGWVHDGSL-NFGDMLTTFSSVMMGSMALGLAGPQLAVLGTAQGAASGIYEVLDRKPVIDSSSKAGRKDMKIKGDITVENVHFTYPSRPDVPILRGMNLRVNAGQTVALVGSSGCGKSTIISLLLRYYDVLKGKITIDGVDVRDINLEFLRKNVAVVSQEPALFNCTIEENISLGKEGITREEMVAACKMANAEKFIKTLPNGYNTLVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDAESEGIVQQALDKAAKGRTTIIIAHRLSTIRNADLIISCKNGQVVEVGDHRALMAQQGLYYDLVTAQTFTDAV---D--------SAAE---------GER---IG--------------K-----D---A-LS---RLKQELEENNAQKTNLFEILYHARPHALSLFIGMSTATIGGFIYPTYSVFFTSFMNVFAGNPA--DFLSQGHFWALMFLVLAAAQGICSFLMTFFMGIASESLTRDLRNKLFRNVLSQHIGFFDSPQNASGKISTRLATDVPNLRTAIDFRFSTVITTLVSMVAGIGLAFFYGWQMALLIIAILPIVAFGQYLRGRRFTGNVKSASEFADSGKIAIEAIENVRTVQALAREDTFYENFCEKLDIPHKEAIKEAFIQGLSYGCASSVLYLLNTCAYRMGLALIIPPTMQPMRVLRVMYAITISTSTLGFATSYFPEYAKATFAGGIIFGMLRKISKIDSLSLAEKKKLYGKVIFKNVRFAYPERPEIEILKGLSFSVEPGQTLALVGPSGCGKSTVVALLERFYDTLGGEIFIDGSEIKTLNPEHTRSQIAIVSQEPTLFDCSIAENIIYGLDPVTMAQVEEAARLANIHNFIAELPEGFETRVGDRGTQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEKVVQEALDRAREGRTCIVIAHRLNTVMNADCIAVVSNGTIIEKGTHTQLMSEK--------------
87otg 0.42 0.38 0.88 1.22Download ----------------------------------------------------------------------------VSVLTMFRYAGWLDRLYMLVGTLAAIIHGVALPLMMLIFGDMTDSFASVGNMFAKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHAIMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGFIIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFLLIYASYALAFWYGTSLVISKEY-SIGQVLTVFFSVLIGAFSVGQASPNIEAFANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSRKEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSIDGQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAVKEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGGVIVEQGNHDELMREKGIYFKLVMTQTDV------------------------------------------------------------------------------PPASFWRILKLNSTEWPYFVVGIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPETQRQNSNLFSLLFLILGIISFITFFLQGFTFGKAGEILTKRLRYMVFKSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYGWQLTLLLLAIVPIIAIAGVVEMKMLSGALKDKKELEGSGKIATEAIENFRTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYAACFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVSASHIIRIIEKTPEIDSYSGLKPNMLEGNVQFSGVVFNYPTRPSIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQLNVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSVSYEEIVRAAKEANIHQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEHGTHQQLLAQKGIYFSMVSVQA---
97w4oB 0.17 0.24 0.90 2.47Download GMLLLVEVNVIRVRRYIFFKTPREVKPPEDLQDLGVRFLKKPIDLRAIGKLPIAMRALTNYQRLCVAFDAQARPQG--ARAIWRALCHAFGRRLILSSTFRILADLLGFAGPLCIFGIVDHLGQFLGSSQEFLGNAYVLAVLLFLALLLQRTFLQASYYVAIETGINLRGAIQTKIYNKIMHLSTSNLSMGEAGQICNLVAIDTNQLMWFFFLCPNLWAMPVQIIVGVILLYYILGV-SALIGAAVIILLAPVQYFVATKLSQAQRSTLEHSNERLKQTNEMLRGMKLLKLYAWESIFCSRVEVTRRKEMTSLRAFAVYTSISIFMNTAIPIAAVLITFVGH-VSFFKESDLSPSVAFASLSLFHILVTPLFLLSSVVRSTVKALVSVQKLSEFLSSA-----------EIREDNFCVQIIGGFFTWTPDGI-PTLSNITIRIPRGQLTMIVGQVGCGKSSLLLATLGEMQKVSGAVFWNSS----------RGPVAYASQKPWLLNATVEENITFESP-FNKQRYKMVIEACSLQPDIDILPHGDQTQIGERGINLSGGQRQRISVARALYQQTNVVFLDDPFSALDHLSDHLMQAGILELLRKRTVVLVTHKLQYLPHADWIIAMKDGTIQREGTLKDFQ-------------RSECQLFEHWKTLMNELEKERACT---------------------------------------------------------------KYLSSAGLLLSLLVFSQLLKHMVLVAIDYWLAKWTD--------SDQ-------SVYAMVFTLLCSLGIVLCLVTSVTVEWTGLKVAKRLHRSLLNRIILAPMRFFETT--PLGSILNRFSSDCNTIDQHIPSTLECLSRSTLLCVSALTVISYVTPV---FLVALLPLAVVCYFIQKYFRVASRDLQQLDDTTLSHFAETVEGLTTIRAFRYEARFQQKLLEYTDSNNIASLFLTAANRWLEVRMEYIGACVVLIAAATSISNSLHRELSAGLVGLGLTYALMVSNYLNWMVRNLADMEIQLGAVKRIHALLKTAESYEGLLAPSLIPDQGKIQIQNLSVRY--DSSLPVLKHVNALISPGQKIGICGRTGSGKSSFSLAFFRMVDMFEGRIIIDGIDIAKLPLHTLRSRLSIILQDPVLFSGTIRFNLDP-EKKCSDSTLWEALEIAQLKLVVKALPGGLDAIITEGGENFSQGQRQLFCLARAFVRKTSIFIMDEATASIDMATENILQKVVMTAFADRTVVTIAHRVHTILSADLVMVLKRGAILEFDKPETLLSQKSVFASFVRA-----
107otg 0.42 0.38 0.88 1.79Download ----------------------------------------------------------------------------VSVLTMFRYAGWLDRLYMLVGTLAAIIHGVALPLMMLIFGDMTDSFASVGNVFAKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHAIMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGFIIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVAEEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFLLIYASYALAFWYGTSLVISKEY-SIGQVLTVFFSVLIGAFSVGQASPNIEAFANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSRKEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSIDGQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAVKEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLLDEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGGVIVEQGNHDELMREKGIYFKLVMTQTDVP-------------------------------------------------P-----------------------------ASFWRILKLNSTEWPYFVVGIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPETQRQNSNLFSLLFLILGIISFITFFLQGFTFGKAGEILTKRLRYMVFKSMLRQDVSWFDDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYGWQLTLLLLAIVPIIAIAGVVEMKMLGQALKDKKELEGSGKIATEAIENFRTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYAACFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVSASHIIRIIEKTPEIDSYSTLKPNMLEGNVQFSGVVFNYPTRPSIPVLQGLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQLNVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSVSYEEIVRAAKEANIHQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATSALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEHGTHQQLLAQKGIYFSMVSVQA---
(a)All the residues are colored in black; however, those residues in template which are identical to the residue in the query sequence are highlighted in color. Coloring scheme is based on the property of amino acids, where polar are brightly coloured while non-polar residues are colored in dark shade. (more about the colors used)
(b)Rank of templates represents the top ten threading templates used by I-TASSER.
(c)Ident1 is the percentage sequence identity of the templates in the threading aligned region with the query sequence.
(d)Ident2 is the percentage sequence identity of the whole template chains with query sequence.
(e)Cov represents the coverage of the threading alignment and is equal to the number of aligned residues divided by the length of query protein.
(f)Norm. Z-score is the normalized Z-score of the threading alignments. Alignment with a Normalized Z-score >1 mean a good alignment and vice versa.
(g)Download Align. provides the 3D structure of the aligned regions of the threading templates.
(h)The top 10 alignments reported above (in order of their ranking) are from the following threading programs:
       1: Neff-PPAS   2: FFAS-3D   3: wdPPAS   4: SPARKS-X   5: HHSEARCH2   6: HHSEARCH2   7: HHSEARCH I   8: HHSEARCH I   9: SPARKS-X   10: HHSEARCH   

   Top 5 final models predicted by I-TASSER

(For each target, I-TASSER simulations generate a large ensemble of structural conformations, called decoys. To select the final models, I-TASSER uses the SPICKER program to cluster all the decoys based on the pair-wise structure similarity, and reports up to five models which corresponds to the five largest structure clusters. The confidence of each model is quantitatively measured by C-score that is calculated based on the significance of threading template alignments and the convergence parameters of the structure assembly simulations. C-score is typically in the range of [-5, 2], where a C-score of a higher value signifies a model with a higher confidence and vice-versa. TM-score and RMSD are estimated based on C-score and protein length following the correlation observed between these qualities. Since the top 5 models are ranked by the cluster size, it is possible that the lower-rank models have a higher C-score in rare cases. Although the first model has a better quality in most cases, it is also possible that the lower-rank models have a better quality than the higher-rank models as seen in our benchmark tests. If the I-TASSER simulations converge, it is possible to have less than 5 clusters generated; this is usually an indication that the models have a good quality because of the converged simulations.)
    (By right-click on the images, you can export image file or change the configurations, e.g. modifying the background color or stopping the spin of your models)
  • Download Model 1
  • C-score=-0.05 (Read more about C-score)
  • Estimated TM-score = 0.71±0.12
  • Estimated RMSD = 9.7±4.6Å

  • Download Model 2
  • C-score = -0.40

  • Download Model 3
  • C-score = -1.94

  • Download Model 4
  • C-score = -2.79

  • Download Model 5
  • C-score = -3.14


  Proteins structurally close to the target in the PDB (as identified by TM-align)

(After the structure assembly simulation, I-TASSER uses the TM-align structural alignment program to match the first I-TASSER model to all structures in the PDB library. This section reports the top 10 proteins from the PDB that have the closest structural similarity, i.e. the highest TM-score, to the predicted I-TASSER model. Due to the structural similarity, these proteins often have similar function to the target. However, users are encouraged to use the data in the next section 'Predicted function using COACH' to infer the function of the target protein, since COACH has been extensively trained to derive biological functions from multi-source of sequence and structure features which has on average a higher accuracy than the function annotations derived only from the global structure comparison.)


Top 10 Identified stuctural analogs in PDB

Click
to view
RankPDB HitTM-scoreRMSDaIDENaCovAlignment
14f4cA0.922 1.280.4100.932Download
27otgA0.834 2.900.4070.880Download
36lr0U0.800 4.160.3190.885Download
47mpeA0.687 6.210.1270.845Download
55uj9A0.685 5.710.1460.822Download
65u71A0.625 6.530.1120.792Download
75tsiA0.618 7.170.0980.812Download
87mitE0.594 7.480.0910.791Download
95twvB0.568 7.520.1010.754Download
107vlrA0.501 5.910.1270.592Download

(a)Query structure is shown in cartoon, while the structural analog is displayed using backbone trace.
(b)Ranking of proteins is based on TM-score of the structural alignment between the query structure and known structures in the PDB library.
(c)RMSDa is the RMSD between residues that are structurally aligned by TM-align.
(d)IDENa is the percentage sequence identity in the structurally aligned region.
(e)Cov represents the coverage of the alignment by TM-align and is equal to the number of structurally aligned residues divided by length of the query protein.


  Predicted function using COFACTOR and COACH

(This section reports biological annotations of the target protein by COFACTOR and COACH based on the I-TASSER structure prediction. While COFACTOR deduces protein functions (ligand-binding sites, EC and GO) using structure comparison and protein-protein networks, COACH is a meta-server approach that combines multiple function annotation results (on ligand-binding sites) from the COFACTOR, TM-SITE and S-SITE programs.)

  Ligand binding sites


Click
to view
RankC-scoreCluster
size
PDB
Hit
Lig
Name
Download
Complex
Ligand Binding Site Residues
10.11 6 4m2sB 0JZ Rep, Mult 112,115,335,362,365,366,369,769,772,776,996,1018,1022,1026
20.07 4 4aytA MG Rep, Mult 460,501,581
30.06 3 4m2tA 2J8 Rep, Mult 108,112,115,362,776,996,1000,1018,1021,1026,1029
40.05 3 4aytA ACP Rep, Mult 189,427,429,435,455,456,457,458,459,460,461,501
50.04 3 4m2sA 0JZ Rep, Mult 112,331,332,335,361,362,365,366,369,769,772,776,1026,1029,1033


Download the residue-specific ligand binding probability, which is estimated by SVM.
Download the all possible binding ligands and detailed prediction summary.
Download the templates clustering results.
(a)C-score is the confidence score of the prediction. C-score ranges [0-1], where a higher score indicates a more reliable prediction.
(b)Cluster size is the total number of templates in a cluster.
(c)Lig Name is name of possible binding ligand. Click the name to view its information in the BioLiP database.
(d)Rep is a single complex structure with the most representative ligand in the cluster, i.e., the one listed in the Lig Name column.
Mult is the complex structures with all potential binding ligands in the cluster.

  Enzyme Commission (EC) numbers and active sites


Click
to view
RankCscoreECPDB
Hit
TM-scoreRMSDaIDENaCovEC NumberActive Site Residues
10.3133g61A0.714 5.530.2760.843 3.6.3.44  96
20.1041ofdA0.233 9.770.0400.362 1.4.7.1  NA
30.1042pffA0.242 9.870.0260.377 2.3.1.41 2.3.1.86  NA
40.1031ej6A0.231 9.660.0200.352 2.7.7.50  NA
50.1002pffD0.241 9.760.0270.374 2.3.1.86  207

 Click on the radio buttons to visualize predicted active site residues.
(a)CscoreEC is the confidence score for the EC number prediction. CscoreEC values range in between [0-1];
where a higher score indicates a more reliable EC number prediction.
(b)TM-score is a measure of global structural similarity between query and template protein.
(c)RMSDa is the RMSD between residues that are structurally aligned by TM-align.
(d)IDENa is the percentage sequence identity in the structurally aligned region.
(e)Cov represents the coverage of global structural alignment and is equal to the number of structurally aligned residues divided
by length of the query protein.

  Gene Ontology (GO) terms
Top 10 homologous GO templates in PDB 
RankCscoreGOTM-scoreRMSDaIDENaCovPDB HitAssociated GO Terms
1 0.460.3536 4.92 0.28 0.403b5wA GO:0005319 GO:0042626 GO:0008289 GO:0055085 GO:0005886 GO:0017111 GO:0006810 GO:0034040 GO:0006869 GO:0016021 GO:0006200 GO:0000166 GO:0015437 GO:0005524 GO:0008144 GO:0016787 GO:0016887 GO:0016020
2 0.310.7091 5.63 0.28 0.843g5uA GO:0005886 GO:0005524 GO:0042623 GO:0008559 GO:0006200 GO:0000166 GO:0015893 GO:0016787 GO:0016020 GO:0046581 GO:0016021 GO:0006810 GO:0016887 GO:0017111 GO:0042626 GO:0055085
3 0.150.3466 4.28 0.27 0.382hydA GO:0017111 GO:0000166 GO:0016787 GO:0005886 GO:0005524 GO:0016887 GO:0006200 GO:0016021 GO:0006810 GO:0055085 GO:0042626 GO:0016020
4 0.150.3526 4.76 0.25 0.403b5xA GO:0006200 GO:0055085 GO:0006869 GO:0005524 GO:0006810 GO:0016887 GO:0005886 GO:0016020 GO:0000166 GO:0016787 GO:0017111 GO:0042626 GO:0016021
5 0.120.2513 8.05 0.04 0.342o8eB GO:0005524 GO:0006298 GO:0030983
6 0.110.2417 9.87 0.04 0.382pffA GO:0008610 GO:0000287 GO:0009058 GO:0005829 GO:0005835 GO:0006633 GO:0004316 GO:0004321 GO:0005515 GO:0009059 GO:0016740 GO:0005488 GO:0008897 GO:0004312 GO:0008152 GO:0005737 GO:0016491 GO:0004315 GO:0005739 GO:0055114 GO:0003824
7 0.110.2412 7.22 0.05 0.311ng9A GO:0006298 GO:0008094 GO:0000166 GO:0016887 GO:0006200 GO:0030983 GO:0005515 GO:0006281 GO:0032136 GO:0005524 GO:0006974 GO:0003677 GO:0003684 GO:0006310
8 0.110.2492 9.65 0.02 0.381vt4I GO:0005524 GO:0006915
9 0.110.2358 7.33 0.04 0.311nneA GO:0006974 GO:0005524 GO:0000166 GO:0003677 GO:0006281 GO:0006298 GO:0030983
10 0.100.2308 9.66 0.02 0.351ej6A GO:0005524 GO:0019012 GO:0003824 GO:0000166 GO:0006370 GO:0016740 GO:0008152 GO:0019028 GO:0005525 GO:0032259 GO:0006397 GO:0004482 GO:0016779 GO:0008168 GO:0004484


Consensus prediction of GO terms
 
Molecular Function GO:0005524 GO:0015437 GO:0008144 GO:0034040 GO:0008289 GO:0008559
GO-Score 0.76 0.46 0.46 0.46 0.46 0.31
Biological Process GO:0055085 GO:0006200 GO:0006869 GO:0015893
GO-Score 0.73 0.73 0.54 0.31
Cellular Component GO:0016021 GO:0005886 GO:0046581
GO-Score 0.73 0.73 0.31

(a)CscoreGO is a combined measure for evaluating global and local similarity between query and template protein. It's range is [0-1] and higher values indicate more confident predictions.
(b)TM-score is a measure of global structural similarity between query and template protein.
(c)RMSDa is the RMSD between residues that are structurally aligned by TM-align.
(d)IDENa is the percentage sequence identity in the structurally aligned region.
(e)Cov represents the coverage of global structural alignment and is equal to the number of structurally aligned residues divided by length of the query protein.
(f)The second table shows a consensus GO terms amongst the top scoring templates. The GO-Score associated with each prediction is defined as the average weight of the GO term, where the weights are assigned based on CscoreGO of the template.


[Click on S693108_results.tar.bz2 to download the tarball file including all modeling results listed on this page]



Please cite the following articles when you use the I-TASSER server:
  • Wei Zheng, Chengxin Zhang, Yang Li, Robin Pearce, Eric W. Bell, Yang Zhang. Folding non-homology proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods, 1: 100014 (2021).
  • Chengxin Zhang, Peter L. Freddolino, and Yang Zhang. COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information. Nucleic Acids Research, 45: W291-299 (2017).
  • Jianyi Yang, Yang Zhang. I-TASSER server: new development for protein structure and function predictions, Nucleic Acids Research, 43: W174-W181, 2015.