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I-TASSER results for job id S773224

(Click on S773224_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
MWLRLGPPSLSLSPKPTVGRSLCLTLWFLSLALRASTQAPAPTVNTHFGKLRGARVPLPS
EILGPVDQYLGVPYAAPPIGEKRFLPPEPPPSWSGIRNATHFPPVCPQNIHTAVPEVMLP
VWFTANLDIVATYIQEPNEDCLYLNVYVPTEDVKRISKECARKPNKKICRKGGSGAKKQG
EDLADNDGDEDEDIRDSGAKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITLNYRVG
VLGFLSTGDQAAKGNYGLLDQIQALRWVSENIAFFGGDPRRITVFGSGIGASCVSLLTLS
HHSEGLFQRAIIQSGSALSSWAVNYQPVKYTSLLADKVGCNVLDTVDMVDCLRQKSAKEL
VEQDIQPARYHVAFGPVIDGDVIPDDPEILMEQGEFLNYDIMLGVNQGEGLKFVEGVVDP
EDGVSGTDFDYSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADRDNPETRRKTLVALFTD
HQWVEPSVVTADLHARYGSPTYFYAFYHHCQSLMKPAWSDAAHGDEVPYVFGVPMVGPTD
LFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNKPVPQDTKFIHTKANRFEEVAWSKYNPRD
QLYLHIGLKPRVRDHYRATKVAFWKHLVPHLYNLHDMFHYTSTTTKVPPPDTTHSSHITR
RPNGKTWSTKRPAISPAYSNENAQGSWNGDQDAGPLLVENPRDYSTELSVTIAVGASLLF
LNVLAFAALYYRKDKRRQEPLRQPSPQRGAGAPELGAAPEEELAALQLGPTHHECEAGPP
HDTLRLTALPDYTLTLRRSPDDIPLMTPNTITMIPNSLVGLQTLHPYNTFAAGFNSTGLP
HSHSTTRV

  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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |        
MWLRLGPPSLSLSPKPTVGRSLCLTLWFLSLALRASTQAPAPTVNTHFGKLRGARVPLPSEILGPVDQYLGVPYAAPPIGEKRFLPPEPPPSWSGIRNATHFPPVCPQNIHTAVPEVMLPVWFTANLDIVATYIQEPNEDCLYLNVYVPTEDVKRISKECARKPNKKICRKGGSGAKKQGEDLADNDGDEDEDIRDSGAKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITLNYRVGVLGFLSTGDQAAKGNYGLLDQIQALRWVSENIAFFGGDPRRITVFGSGIGASCVSLLTLSHHSEGLFQRAIIQSGSALSSWAVNYQPVKYTSLLADKVGCNVLDTVDMVDCLRQKSAKELVEQDIQPARYHVAFGPVIDGDVIPDDPEILMEQGEFLNYDIMLGVNQGEGLKFVEGVVDPEDGVSGTDFDYSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADRDNPETRRKTLVALFTDHQWVEPSVVTADLHARYGSPTYFYAFYHHCQSLMKPAWSDAAHGDEVPYVFGVPMVGPTDLFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNKPVPQDTKFIHTKANRFEEVAWSKYNPRDQLYLHIGLKPRVRDHYRATKVAFWKHLVPHLYNLHDMFHYTSTTTKVPPPDTTHSSHITRRPNGKTWSTKRPAISPAYSNENAQGSWNGDQDAGPLLVENPRDYSTELSVTIAVGASLLFLNVLAFAALYYRKDKRRQEPLRQPSPQRGAGAPELGAAPEEELAALQLGPTHHECEAGPPHDTLRLTALPDYTLTLRRSPDDIPLMTPNTITMIPNSLVGLQTLHPYNTFAAGFNSTGLPHSHSTTRV
PredictionCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHCCCCCCCSSSSCCSSSSSSSSCCCCCCCCCSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSCCCCCCCCCCCCCCCCCCCCHHHCCCCCCCCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSSCCCCSSSCCCCCCCHHHHHCCCCSSSSSSCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCSSSSSSSCHHHHHHHHHHHCCCCCCCCCSSSSSCCCCCCCCCCCHHHHHHHHHHHHHHCCCCCCHHHHHHHHHCCCHHHHHHHHHHHCCCCCCSSSSSCCCCCCCCHHHHHHCCCCCCCCSSSSSSHHHHHHHHHHHCCCCCCCCHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCSSSSSSSCCCCCCCCCCCCCCCCHHHHHHHHCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSCCCCCHHCCCCCHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCHHHHCHHHCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCCCCCCCSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC
Conf.Score97612687561213269999999999999999861357999979979857972895157767885588830326889875024789977988766165235897388558656643233111001212245677778767448888622776666666666677654333567653333442111234444456778886089998699434604887787898564997999953245511307799899885758999999999999989870998550699966799999999984826344006899815873667547765999999999984879999999999995699999985335423653200678898368838999986488899988999655777899987516433235677999999999986246654589999999987436788988999999999998399999999999999985899699998336765555565788723446787188666754346789899999999999999999997786988877755456666666565555677788855188899850211638888778999999872333445666665677999777776777689998878888988999988888888898745677787765442078999999999999999999988632046444442246566678888866778413342323146788876788654456789821101445798877888987554057877787788853356788889989998887779
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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |        
MWLRLGPPSLSLSPKPTVGRSLCLTLWFLSLALRASTQAPAPTVNTHFGKLRGARVPLPSEILGPVDQYLGVPYAAPPIGEKRFLPPEPPPSWSGIRNATHFPPVCPQNIHTAVPEVMLPVWFTANLDIVATYIQEPNEDCLYLNVYVPTEDVKRISKECARKPNKKICRKGGSGAKKQGEDLADNDGDEDEDIRDSGAKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITLNYRVGVLGFLSTGDQAAKGNYGLLDQIQALRWVSENIAFFGGDPRRITVFGSGIGASCVSLLTLSHHSEGLFQRAIIQSGSALSSWAVNYQPVKYTSLLADKVGCNVLDTVDMVDCLRQKSAKELVEQDIQPARYHVAFGPVIDGDVIPDDPEILMEQGEFLNYDIMLGVNQGEGLKFVEGVVDPEDGVSGTDFDYSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADRDNPETRRKTLVALFTDHQWVEPSVVTADLHARYGSPTYFYAFYHHCQSLMKPAWSDAAHGDEVPYVFGVPMVGPTDLFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNKPVPQDTKFIHTKANRFEEVAWSKYNPRDQLYLHIGLKPRVRDHYRATKVAFWKHLVPHLYNLHDMFHYTSTTTKVPPPDTTHSSHITRRPNGKTWSTKRPAISPAYSNENAQGSWNGDQDAGPLLVENPRDYSTELSVTIAVGASLLFLNVLAFAALYYRKDKRRQEPLRQPSPQRGAGAPELGAAPEEELAALQLGPTHHECEAGPPHDTLRLTALPDYTLTLRRSPDDIPLMTPNTITMIPNSLVGLQTLHPYNTFAAGFNSTGLPHSHSTTRV
Prediction40221233313133200000000000000000001024443020305303020222304434433010000000021121631043143364063012004100000020101123111122122314222333442200000000000233344344423333333333334433334433333343333443464320000000001000000001010200002210000000011000000002164000200000010002001400530101241000000000000000000001023001100000000000000244024103300430306362253004103713153014132422311000000012400153034006426034000000002100000010013244203343033003300320130443352034003300331434722340030001000100000000100210063613030110002044122231000000000000000000344422334126402400310030000001002133334432232324434244142331337433003023413235403441030034002302523432333643343222423433323331434323243232212233442523444443334243743441200000000110111220110000000123344454344444444444463443344212324343343624413243123312122111224311642231324111101331232332112111233333321114123426
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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |        
Sec.Str
Seq
CCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHCCCCCCCSSSSCCSSSSSSSSCCCCCCCCCSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSCCCCCCCCCCCCCCCCCCCCHHHCCCCCCCCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSSCCCCSSSCCCCCCCHHHHHCCCCSSSSSSCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCSSSSSSSCHHHHHHHHHHHCCCCCCCCCSSSSSCCCCCCCCCCCHHHHHHHHHHHHHHCCCCCCHHHHHHHHHCCCHHHHHHHHHHHCCCCCCSSSSSCCCCCCCCHHHHHHCCCCCCCCSSSSSSHHHHHHHHHHHCCCCCCCCHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCSSSSSSSCCCCCCCCCCCCCCCCHHHHHHHHCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSCCCCCHHCCCCCHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCHHHHCHHHCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCCCCCCCSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC
MWLRLGPPSLSLSPKPTVGRSLCLTLWFLSLALRASTQAPAPTVNTHFGKLRGARVPLPSEILGPVDQYLGVPYAAPPIGEKRFLPPEPPPSWSGIRNATHFPPVCPQNIHTAVPEVMLPVWFTANLDIVATYIQEPNEDCLYLNVYVPTEDVKRISKECARKPNKKICRKGGSGAKKQGEDLADNDGDEDEDIRDSGAKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITLNYRVGVLGFLSTGDQAAKGNYGLLDQIQALRWVSENIAFFGGDPRRITVFGSGIGASCVSLLTLSHHSEGLFQRAIIQSGSALSSWAVNYQPVKYTSLLADKVGCNVLDTVDMVDCLRQKSAKELVEQDIQPARYHVAFGPVIDGDVIPDDPEILMEQGEFLNYDIMLGVNQGEGLKFVEGVVDPEDGVSGTDFDYSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADRDNPETRRKTLVALFTDHQWVEPSVVTADLHARYGSPTYFYAFYHHCQSLMKPAWSDAAHGDEVPYVFGVPMVGPTDLFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNKPVPQDTKFIHTKANRFEEVAWSKYNPRDQLYLHIGLKPRVRDHYRATKVAFWKHLVPHLYNLHDMFHYTSTTTKVPPPDTTHSSHITRRPNGKTWSTKRPAISPAYSNENAQGSWNGDQDAGPLLVENPRDYSTELSVTIAVGASLLFLNVLAFAALYYRKDKRRQEPLRQPSPQRGAGAPELGAAPEEELAALQLGPTHHECEAGPPHDTLRLTALPDYTLTLRRSPDDIPLMTPNTITMIPNSLVGLQTLHPYNTFAAGFNSTGLPHSHSTTRV
13bl8A 0.76 0.50 0.66 6.11Download ---------------------------------------QKPVVNTAYGRVRGVRRELNNEILGPVVQFLGVPYATPPLGARRFQPPEAPASWPGVRNATTLPPACPQNLHGALPAIMLPVWFTDNLEAAATYVQNQSEDCLYLNLYVPTEDGPLTKK-------------------------------------DSGKKPVMLFLHGGSYMEGTGNMFDGSVLAAYGNVIVVTLNYRLGVLGFLSTGDQAAKGNYGLLDQIQALRWLSENIAHFGGDPERITIFGSGAGASCVNLLILSHHSEGLFQKAIAQSGTAISSWSVNYQPLKYTRLLAAKVGCDREDSTEAVECLRRKSSRELVDQDVQPARYHIAFGPVVDGDVVPDDPEILMQQGEFLNYDMLIGVNQGEGLKFVEDSAESEDGVSASAFDFTVSNFVDNLYGYPEGKDVLRETIKFMYTDWADRDNGEMRRKTLLALFTDHQWVAPAVATAKLHADYQSPVYFYTFYHHCQAEGRPEWADAAHGDELPYVFGVPMVGATDLFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNQPVPQDTKFIHTKPNRFEEVVWSKFNSKEKQYLHIGLKPRVRDNYRANKVAFWLELVPHLH------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
28gs4A 0.76 0.48 0.62 3.53Download -----------------------------------------PVVNTAYGRVRGVRRELNNEILGPVVQFLGVPYATPPLGARRFQPPEAPASWPGVRNATTLPPACPQNLHGALPAIMLPVWFTDNLEAAATYVQNQSEDCLYLNLYVP------------------------------------------------GKKPVMLFLHGGSYMEGTGNMFDGSVLAAYGNVIVATLNYRLGVLGFLSTGDQAAKGNYGLLDQIQALRWLSENIAHFGGDPERITIFGSGAGASCVNLLILSHHSEGLFQKAIAQSGTAISSWSVNYQPLKYTRLLAAKVGCDREDSAEAVECLRRKPSRELVDQDVQPARYHIAFGPVVDGDVVPDDPEILMQQGEFLNYDMLIGVNQGEGLKFV--------EVSASAFDFTVSNFVDNLYGYPEGKDVLRETIKFMYTDWADRDNGEMRRKTLLALFTDHQWVAPAVATAKLHADYQSPVYFYTFYHHCQAEGRPEWADAAHGDELPYVFGVPMVGATDLFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNQPVPNRFEEVV----------WSKFNSKEKQYLHIGLKPRVRDNYRANKVAFWLELVPHLH------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
33i6m 0.36 0.24 0.61 2.32Download -------------------------------------DHSELLVNTKSGKVMGTRVPV---LSSHISAFLGIPFAEPPVGNMRFRRPEPKKPWSGVWNASTYPNNCQQYVDEQFPGF--S----GS--EMWNPNREMSEDCLYLNIWVPSPR--------------------------------------------PKSTTVMVWIYGGGFYSGSSTVYNGKYLAYTEEVVLVSLSYRVGAFGFLALHGQEAPGNVGLLDQRMALQWVHDNIQFFGGDPKTVTIFGESAGGASVGMHILSPGSRDLFRRAILQSGSPNCPWASVSEGRRRAVELGRNLNCNLNSDEELIHCLREKKPQELIDVEWNVSIFRFSFVPVIDGEFFPTSLESMLNSGNFKKTQILLGVNKDEGSFFLLYGAPGESKISREDFMS----GVKLSVPHA--NDLGLDAVTLQYTDWMDDNNGIKNRDGLDDIVGDHNVICPLMHFVNKYTKFGNGTYLYFFNHRASNLVWPEWMGVIHGYEIEFVFGLPLVKE-----LNYTAEEEALSRRIMHYWATFAKTGNPNEPHS-------------QESKWPLFTTKEQKFIDLNTEPKVHQRLRVQMCVFWNQFLPKLLNAT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
43i6m 0.35 0.24 0.61 1.74Download -------------------------------------DHSELLVNTKSGKVMGTRVPV---LSSHISAFLGIPFAEPPVGNMRFRRPEPKKPWSGVWNASTYPNNCQQYVDEQFPGFSGS--------EMWNPNREMSEDCLYLNIWVPSPR--------------------------------------------PKSTTVMVWIYGGGFYSGSSTVYNGKYLAYTEEVVLVSLSYRVGAFGFLALHSQEAPGNVGLLDQRMALQWVHDNIQFFGGDPKTVTIFGESAGGASVGMHILSPGSRDLFRRAILQSGSPNCPWASVSEGRRRAVELGRNLNCNLNSDEELIHCLREKKPQELIDVEWNVLIFRFSFVPVIDGEFFPTSLESMLNSGNFKKTQILLGVNKDEGSFFLLYGAPGESKISREDFMS----GVKLSVP--HANDLGLDAVTLQYTDWMDDNNGIKNRDGLDDIVGDHNVICPLMHFVNKYTKFGNGTYLYFFNHRASNLVWPEWMGVIHGYEIEFVFGLPLVKE-----LNYTAEEEALSRRIMHYWATFAKTGNPNEPHS-------------QESKWPLFTTKEQKFIDLNTEMKVHQRLRVQMCVFWNQFLPKLLNAT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
52wqzA 0.81 0.52 0.64 4.28Download ------------------------------------AAAQYPVVNTNYGKIRGLRTPLPNEILGPVEQYLGVPYASPPTGERRFQPPEPPSSWTGIRNTTQFAAVCPQHDERSLLHDMLPIWFTANLDTLMTYVQDQNEDCLYLNIYVPTEDDIH------------------------------------------SKKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITINYRLGILGFLSTGDQAAKGNYGLLDQIQALRWIEENVGAFGGDPKRVTIFGSGAGASCVSLLTLSHYSEGLFQKAIIQSGTALSSWAVNYQPAKYTRILADKVGCNMLDTTDMVECLRNKNYKELIQQTITPATYHIAFGPVIDGDVIPDDPQILMEQGEFLNYDIMLGVNQGEGLKFVDGIVDNEDGVTPNDFDFSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADKENPETRRKTLVALFTDHQWVAPAVATADLHAQYGSPTYFYAFYHHCQSEMKPSWADSAHGDEVPYVFGIPMIGPTELFSCNFSKNDVMLSAVVMTYWTNFAKTGDPNQP---------------EEVAWSRYNPKDQLYLHIGLKPRVRDHYRATKVAFWLELVPHLH------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
63i6m 0.36 0.24 0.61 2.54Download --------------------------------------HSELLVNTKSGKVMGTRVPVL---SSHISAFLGIPFAEPPVGNMRFRRPEPKKPWSGVWNASTYPNNCQQYVDEQFPGF--S----G--SEMWNPNREMSEDCLYLNIWVPSPR--------------------------------------------PKSTTVMVWIYGGGFYSGSSTVYNGKYLAYTEEVVLVSLSYRVGAFGFLALHSQEAPGNVGLLDQRMALQWVHDNIQFFGGDPKTVTIFGESAGGASVGMHILSPGSRDLFRRAILQSGSPNCPWASVSEGRRRAVELGRNLNCNLNSDEELIHCLREKKPQELIDVEWNVLIFRFSFVPVIDGEFFPTSLESMLNSGNFKKTQILLGVNKDEGSFFLLYGAPSESKISREDFMSGVK----LSVP--HANDLGLDAVTLQYTDWMDDNNGIKNRDGLDDIVGDHNVICPLMHFVNKYTKFGNGTYLYFFNHRASNLVWPEWMGVIHGYEIEFVFGLPLVKE-----LNYTAEEEALSRRIMHYWATFAKTGNPNEPHS-------------QESKWPLFTTKEQKFIDLNTEPKVHQRLRVQMCVFWNQFLPKLLN-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
76g1uA 0.37 0.24 0.6110.38Download ---------------------------------------SELLVNTKSGKVMGTRVPVLS---SHISAFLGIPFAEPPVGNMRFRRPEPKKPWSGVWNASTYPNNCQQYVDEQFPGFSGSEMW--------NPNREMSEDCLYLNIWVP---------------------------------------------SPRPKSTVMVWIYGGGFYSGSSTLYNGKYLAYTEEVVLVSLSYRVGAFGFLALGSQEAPGNVGLLDQRMALQWVHDNIQFFGGDPKTVTIFGESAGGASVGMHILSPGSRDLFRRAILQSGSPNCPWASVAEGRRRAVELGRNLNCNLNSDEELIHCLREKKPQELIDVEWNVLPFRFSFVPVIDGEFFPTSLESMLNSGNFKKTQILLGVNKDEGSFFLLYGADSESKISREDFMSGVKLSV------PHANDLGLDAVTLQYTDWMDDNNGIKNRDGLDDIVGDHNVICPLMHFVNKYTKFGNGTYLYFFNHRASNLVWPEWMGVIHGYEIEFVFGLPLVKEL-----NYTAEEEALSRRIMHYWATFAKTGNPNEPHSQESK-------------WPLFTTKEQKFIDLNTEPKVHQRLRVQMCVFWNQFLPKLLNAT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
82wqzA 0.80 0.52 0.64 3.33Download -------------------------------DDDKLAAAQYPVVNTNYGKIRGLRTPLPNEILGPVEQYLGVPYASPPTGERRFQPPEPPSSWTGIRNTTQFAAVCPQHLDERSLLDMLPIWFTANLDTLMTYVQDQNEDCLYLNIYVPTED------------------------------------------DIHSKKPVMVYIHGGSYMEGTGNMIDGSILASYGNVIVITINYRLGILGFLSTGDQAAKGNYGLLDQIQALRWIEENVGAFGGDPKRVTIFGSGAGASCVSLLTLSHYSEGLFQKAIIQSGTALSSWAVNYQPAKYTRILADKVGCNMLDTTDMVECLRNKNYKELIQQTITPATYHIAFGPVIDGDVIPDDPQILMEQGEFLNYDIMLGVNQGEGLKFVDGIVDNEDGVTPNDFDFSVSNFVDNLYGYPEGKDTLRETIKFMYTDWADKENPETRRKTLVALFTDHQWVAPAVATADLHAQYGSPTYFYAFYHHCQSEMKPSWADSAHGDEVPYVFGIPMIGPTELFSCNFSKNDVMLSAVVMTYWTNFAKTGDPNQP---------------EEVAWSRYNPKDQLYLHIGLKPRVRDHYRATKVAFWLELVPHLH------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
97aisA 0.35 0.24 0.61 4.04Download ---------------------------------------SELLVNTKSGKVMGTRVPVLS---SHISAFLGIPFAEPPVGNMRFRRPEPKKPWSGVWNASTYPNNCQQYVDEQFPGFSGSE--------MWNPNREMSEDCLYLNIWVPS--------------------------------------------PRPKSTTVMVWIYGGGFYSGSSTLYNGKYLAYTEEVVLVSLSYRVGAFGFLALGSQEAPGNVGLLDQRMALQWVHDNIQFFGGDPKTVTIFGESAGGASVGMHILSPGSRDLFRRAILQSGSPNCPWASVAEGRRRAVELGRNLNCNLNSDEELIHCLREKKPQELIDVEWNVLPFRFSFVPVIDGEFFPTSLESMLNSGNFKKTQILLGVNKDEGSFFLLYGAPGFSKDSESKIREDFMSGVKLS--VPHANDLGLDAVTLQYTDWMDDNNGIKNRDGLDDIVGDHNVICPLMHFVNKYTKFGNGTYLYFFNHRASNLVWPEWMGVIHGYEIEFVFGLPLVKEL-----NYTAEEEALSRRIMHYWATFAKTGNPNEPHSQE-------------SKWPLFTTKEQKFIDLNTEMKVHQRLRVQMCVFWNQFLPKLLNAT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
105oj6A 0.78 0.51 0.64 7.05Download ---------------------------------------VDPLVATNFGKIRGIKKELNNEILGPVIQFLGVPYAAPPTGERRFQPPEPPSPWSDIRNATQFAPVCPQNIIDGLPEVMLPVWFTNNLDVVSSYVQDQSEDCLYLNIYVPTER------------------------------------------DSGGPKPVMVYIHGGSYMEGTGNLYDGSVLASYGNVIVITVNYRLGVLGFLSTGDQAAKGNYGLLDLIQALRWTSENIGFFGGDPLRITVFGSGAGGSCVNLLTLSHYSEGLFQRAIAQSGTALSSWAVSFQPAKYARMLATKVGCNVSDTVELVECLQKKPYKELVDQDIQPARYHIAFGPVIDGDVIPDDPQILMEQGEFLNYDIMLGVNQGEGLKFVENIVDSDDGISASDFDFAVSNFVDNLYGYPEGKDVLRETIKFMYTDWADRHNPETRRKTLLALFTDHQWVAPAVATADLHSNFGSPTYFYAFYHHCQTDQVPAWADAAHGDEVPYVLGIPMIGPTELFPCNFSKNDVMLSAVVMTYWTNFAKTGDPNQP-------VPQDPNRFEEVAWTRYSQKDQLYLHIGLKPRVKEHYRANKVNLWLELVPHLHNL----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
(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: FFAS-3D   2: SPARKS-X   3: HHSEARCH2   4: HHSEARCH I   5: Neff-PPAS   6: HHSEARCH   7: pGenTHREADER   8: wdPPAS   9: PROSPECT2   10: SP3   

   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=-2.75 (Read more about C-score)
  • Estimated TM-score = 0.40±0.13
  • Estimated RMSD = 15.5±3.3Å

  • Download Model 2
  • C-score = -2.95

  • Download Model 3
  • C-score = -2.87

  • Download Model 4
  • C-score = -3.25

  • Download Model 5
  • C-score = -3.11


  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
13bixA0.612 2.670.7810.647Download
23bl8A0.609 2.570.7510.643Download
33i6mA0.608 0.830.3560.612Download
41maaD0.607 1.220.3750.616Download
55x61B0.607 1.290.3670.617Download
62x8bA0.605 1.270.3690.614Download
72wqzA0.604 2.520.7920.636Download
84qwwA0.599 1.150.3740.606Download
93o9mA0.598 1.400.3620.609Download
101qo9A0.589 1.820.2860.606Download

(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
10.29 171 1amnA NAF Rep, Mult 131,209,210,212,287,288,289,321,370,372,413,523
20.13 108 1w4lA GL8 Rep, Mult 109,111,131,208,209,210,212,287,288,365,370,372,412,413,416,523
30.06 45 1gpnA HUB Rep, Mult 131,208,209,210,212,214,219,287,288,372,412,523
40.04 37 4b82A B3Z Rep, Mult 131,208,209,212,287,412,413,416,523,524
50.04 35 1yajK SIA N/A 71,97,98,99,101,102,103,104


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
10.1921eveA0.608 0.840.3560.612 3.1.1.7  NA
20.1881maaD0.607 1.220.3750.616 3.1.1.7  NA
30.1861b41A0.600 1.230.3720.609 3.1.1.7  NA
40.1202pm8A0.597 1.400.3570.607 3.1.1.8  NA
50.1181qo9A0.589 1.820.2860.606 3.1.1.7  NA

 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 0.260.6052 1.27 0.37 0.612x8bA GO:0003990 GO:0007517 GO:0009986 GO:0009611 GO:0006260 GO:0006581 GO:0043237 GO:0050804 GO:0002076 GO:0004104 GO:0060041 GO:0050770 GO:0007271 GO:0030054 GO:0007399 GO:0045212 GO:0030425 GO:0045211 GO:0005788 GO:0043083 GO:0001507 GO:0004091 GO:0005886 GO:0042803 GO:0042135 GO:0043621 GO:0042166 GO:0005518 GO:0042734 GO:0007155 GO:0050714 GO:0045202 GO:0007268 GO:0032223 GO:0019695 GO:0005515 GO:0001919 GO:0005634 GO:0051262 GO:0001540 GO:0007416 GO:0016020 GO:0043236 GO:0016787 GO:0048814 GO:0008283 GO:0031225 GO:0042982 GO:0031623 GO:0005576 GO:0017171 GO:0030424 GO:0005615 GO:0031594 GO:0005605 GO:0005794 GO:0048471 GO:0042136
2 0.250.6124 2.67 0.78 0.653bixA GO:0007155 GO:0016020
3 0.230.5822 2.43 0.35 0.611mx9D GO:0080030 GO:0008152 GO:0080031 GO:0004091 GO:0009636 GO:0050804 GO:0016787 GO:0080032 GO:0005788 GO:0005783
4 0.190.6080 0.84 0.36 0.611eveA GO:0030054 GO:0042135 GO:0004104 GO:0016787 GO:0043083 GO:0045202 GO:0003990 GO:0004091 GO:0001507 GO:0005886 GO:0031225 GO:0016020
5 0.190.6072 1.22 0.38 0.621maaD GO:0031623 GO:0031225 GO:0016020 GO:0051262 GO:0060041 GO:0048471 GO:0016787 GO:0042803 GO:0043236 GO:0006581 GO:0043621 GO:0042166 GO:0005576 GO:0004091 GO:0042135 GO:0003990 GO:0031594 GO:0045212 GO:0002076 GO:0005518 GO:0005794 GO:0043237 GO:0005605 GO:0030054 GO:0005615 GO:0009986 GO:0001919 GO:0017171 GO:0005886 GO:0045202 GO:0007155 GO:0004104
6 0.180.6038 2.52 0.79 0.642wqzA GO:0007155 GO:0016020
7 0.180.6091 2.57 0.75 0.643bl8A GO:0007155 GO:0016020
8 0.120.5980 1.40 0.36 0.613o9mA GO:0004104 GO:0051384 GO:0050804 GO:0005624 GO:0007612 GO:0050805 GO:0001540 GO:0004091 GO:0007271 GO:0019695 GO:0003824 GO:0042493 GO:0051593 GO:0050783 GO:0005615 GO:0005788 GO:0033265 GO:0003990 GO:0007584 GO:0019899 GO:0008152 GO:0005576 GO:0005641 GO:0016787 GO:0005783 GO:0043279 GO:0006581 GO:0016020
9 0.120.5891 1.82 0.29 0.611qo9A GO:0003990 GO:0006581 GO:0016020 GO:0005737 GO:0043083 GO:0016787 GO:0042426 GO:0030054 GO:0004104 GO:0005886 GO:0042803 GO:0045202 GO:0031225 GO:0042135 GO:0004091 GO:0007268 GO:0042331 GO:0001507
10 0.120.5764 2.99 0.37 0.621aknA GO:0005576 GO:0050804 GO:0016042 GO:0005737 GO:0004771 GO:0016787 GO:0004091 GO:0004806 GO:0005615 GO:0005829 GO:0047372


Consensus prediction of GO terms
 
Molecular Function GO:0004091 GO:0003990 GO:0043237 GO:0005518 GO:0042166 GO:0017171 GO:0043621 GO:0042803
GO-Score 0.62 0.51 0.40 0.40 0.40 0.40 0.40 0.40
Biological Process GO:0007155 GO:0009100 GO:0050773 GO:0032222 GO:0050808 GO:0061061 GO:0051222 GO:0010769 GO:0051047 GO:0050708
GO-Score 0.54 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51 0.51
Cellular Component GO:0097060 GO:0043005 GO:0031225 GO:0005886 GO:0030054 GO:0005788 GO:0043083 GO:0009986 GO:0005615 GO:0048471
GO-Score 0.51 0.51 0.51 0.51 0.51 0.42 0.40 0.40 0.40 0.40

(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 S773224_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.