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I-TASSER results for job id S693417

(Click on S693417_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
MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISS
VHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCP
EYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPA
LLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGD
NFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYK
ENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSS
NCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRS
LQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCG
SCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDS
TNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY

  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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |               
MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY
PredictionCCCCSSSCCSSSSCCCSSSSSSCCCSSSSHHHHHHHHHHHSSSSSSSSCCCCCCCCCCSSSSSSSSSSSSSCCCCCCCCCCCCCCCSSCHHHCCCCCCCCSSSSSSSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSCCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCCCCCCCCSSSSSCCCCCCCCCCCCCCCCCCCCCCSSCCCCCCCCCCSSSHHHHHHHHCCCHHHHHHCCCSSSSSSSSSCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCSSSSSSSSCCCCCSSSSSSSCCCCSSSSSSCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHCCCCCCCCHHHHHHHHHHCCCCCCCSSSCCCCCCCCCCCCHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCCCCHHHHHHHCCHHHHHHHHHHCCCCCCCCCCCHHHHHHHHHHHSSSSSSSCCCCCCCCCCCCHHHHHHHHHHCCCCCCCCCCCCCCC
Conf.Score9962220207850574499991250452047888875420678899860431257863048998732388735445667666776242412121478887499997568870304055877898887456888997885247889736887505699974289987657657887887522111011157775342475445654665866676230088789899688877999883827899986085699999865258887214762363477787667742145632554211426893277776134236999982665431111102335444455445667668789775013343032304432264443312445454220377552014313687432346655541244305776666776774112346766456788999866455567678876689987108969447787423464010402589987040685686662789998777753121024674214577777754505666404656666786847779999986889778532666899
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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |               
MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY
Prediction2000000000011413110103132000000000000122101000012111443412100101010002023334533136112100011100100342000000111213333343033334452303225404414333312102103013364532000010001014364233430145153110002210310314143431364233303135633010000101200430332032003300000020302000023363020201023033453633313323131031035463421101101001000000030120000000011010100000000000000000144224234212331264143552124411442444444141042243420412445323431441624635346341541453425356463334424414315553446646313002023032262266344112000353643101324302310023300110021123225244533242001000000000001013473111000000210163014672313103337
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
                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |               
Sec.Str
Seq
CCCCSSSCCSSSSCCCSSSSSSCCCSSSSHHHHHHHHHHHSSSSSSSSCCCCCCCCCCSSSSSSSSSSSSSCCCCCCCCCCCCCCCSSCHHHCCCCCCCCSSSSSSSSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSCCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCCCCCCCCSSSSSCCCCCCCCCCCCCCCCCCCCCCSSCCCCCCCCCCSSSHHHHHHHHCCCHHHHHHCCCSSSSSSSSSCCCCCCCCCCCSSSSSSSCCCCCCCCCCCCCCSSSSSSSSCCCCCSSSSSSSCCCCSSSSSSCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHCCCCCCCCHHHHHHHHHHCCCCCCCSSSCCCCCCCCCCCCHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHCCCCCCCCCCCCCCHHHHHHHCCHHHHHHHHHHCCCCCCCCCCCHHHHHHHHHHHSSSSSSSCCCCCCCCCCCCHHHHHHHHHHCCCCCCCCCCCCCCC
MPACCSCSDVFQYETNKVTRIQSMNYGTIKWFFHVIIFSYVCFALVSDKLYQRKEPVISSVHTKVKGIAEVKEEIVENGVKKLVHSVFDTADYTFPLQGNSFFVMTNFLKTEGQEQRLCPEYPTRRTLCSSDRGCKKGWMDPQSKGIQTGRCVVYEGNQKTCEVSAWCPIEAVEEAPRPALLNSAENFTVLIKNNIDFPGHNYTTRNILPGLNITCTFHKTQNPQCPIFRLGDIFRETGDNFSDVAIQGGIMGIEIYWDCNLDRWFHHCRPKYSFRRLDDKTTNVSLYPGYNFRYAKYYKENNVEKRTLIKVFGIRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLAAVFIDFLIDTYSSNCCRSHIYPWCKCCQPCVVNEYYYRKKCESIVEPKPTLKYVSFVDESHIRMVNQQLLGRSLQDVKGQEVPRPAMDFTDLSRLPLALHDTPPIPGQPEEIQLLRKEATPRSRDSPVWCQCGSCLPSQLPESHRCLEELCCRKKPGACITTSELFRKLVLSRHVLQFLLLYQEPLLALDVDSTNSRLRHCAYRCYATWRFGSQDMADFAILPSCCRWRIRKEFPKSEGQYSGFKSPY
16u9wA 0.80 0.76 0.94 7.12Download ----CSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENVTEGGVTKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLEL-----------------------------SRLDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
27whmA 0.07 0.16 0.79 0.81Download NILKTLIADYNLRMRRDALLGELARLDELRDISQVKGVEYKVTIPL------------------LPVISTLNQHEFEITQANITDFIAD-----------NVTFVTSFV-------PADLDLEQTIQRVFFRTTAT----TPHFQSNLVIEILNYDQDSGDVELHVKIMIVRPNSDVVNYYGKDYERISVCYNLISHLQRIDGPHGRDAEMPIYRIIRRDSGSI--PSY------------------ASGEHLYVISSHLHVDREHKSI--SVDVTQLSLILPIIRTFNPVDLREV--------RIEDITPGIEFTINMEVSTYLAESSVDMQRAIMNHADKIVGNYTGQQWNVQSNMLSEV---RTQMLEE--EDEEARQRGDYTTSTLVQTMAQVSDLFSHTQNAHGT------------SDTVLPAMRVYYRPLGFLDKRVGEALHKGITRPELRSDVANVGTRAYEDAGSYIVSKELNRFGRTTSDKNAKYRVNKITADGKYIIDRLSHTESGYTAADVDRLYRSLFG--KQGDGLSTEQKWMDISRGVDAKIISADM---------------------------------
36u9v 0.81 0.76 0.94 7.22Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENV-----TKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSR---------------------------LSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
46u9v 0.81 0.76 0.94 4.91Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENV-----TKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSR---------------------------LSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
56u9vA 0.81 0.76 0.94 8.09Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENV-----TKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSR---------------------------LSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
66u9v 0.81 0.76 0.94 7.74Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTENV-----TKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSR---------------------------LSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYP-
74dw1A 0.49 0.27 0.53 5.88Download ------------------------------RFTQALVIAYVGYVCVYNKGYQDTDTVLSSVTTKVKGIALTKTS-------ELGERIWDVADYIIPPQEDSFFVLTNMIITTNQTQSKCAENPTPASTCTSHRDCKRGFNDARGDGVRTGRCVSYSASVKTCEVLSWCPLEKIVDPPNPPLLADAERFTVLIKNNIRYPKFNFNKRNILPNINTHCVFSRKTDPDCPIFRLGDIVGEAEEDFQIMAVRGGVMGVQIRWDCDLDMPQSWCVPRYTFRRLDNKDPDNNVAPGYNFRFAKYYKNDGTETRTLIKGYGIRFDVMVFGQAGKFNIIPTLLNIGAGLALLGLVNVICDWI-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
86u9vA 0.81 0.76 0.94 3.99Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVT-----ENVTKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSR---------------------------LSRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
97s62A 0.07 0.17 0.78 1.50Download KSGETQRACVNLIGYHQSVVLEHQRVNISIFSEKVQPPHYFKCNKFMVPTVITNAPDFVTLSVSGGGEDIKDRKAVVIAPLNTICLIQMDKPVYKPGC----KVRFRLISLNTMLLPISEKYTAVYLEDPSGSRIAQWQNQESVGGVVQLEFLISDAAPGSYTITAEGESCESAR----------------------QGFTVDEYIRFYSETGSFLDIQGSSVELNC---------------------GQVHNISVRYILSLDGMGEGATTATFYYLAMSRAKIV-----QHGQRDVHLNQSKSGLFNIGDLAPGAELIVYCILDLELIADTISLDI----------------------------EKCFQNQVSLSFSDDLGPTASNVSNLSAAPGSLCGVKVIDSSLLLINPYESLSASGVYYSIPYLSLFGYNYGGFNLEEPEPPCEDPNTVIFCKGRYYLPVSSSTEGDTYQNLRRVGLVLGTSSKIRKP----VVCGMEAKLRKNFSET------------------------------------------FLWRLVSVDSEGQN------TITETVPDTITKWEGFKYSA
106u9vA 0.81 0.76 0.94 9.71Download ---CCSWNDVFQYETNKVTRIQSVNYGTIKWILHMTVFSYVSFALMSDKLYQRKEPLISSVHTKVKGVAEVTEN-----VTKLVHGIFDTADYTLPLQGNSFFVMTNYLKSEGQEQKLCPEYPSRGKQCHSDQGCIKGWMDPQSKGIQTGRCIPYDQKRKTCEIFAWCPAEEGKEAPRPALLRSAENFTVLIKNNIDFPGHNYTTRNILPGMNISCTFHKTWNPQCPIFRLGDIFQEIGENFTEVAVQGGIMGIEIYWDCNLDSWSHRCQPKYSFRRLDDKYTNESLFPGYNFRYAKYYKENGMEKRTLIKAFGVRFDILVFGTGGKFDIIQLVVYIGSTLSYFGLATVCIDLIINTYASTCCRSRVYPSCKCCEPCAVNEYYYRKKCEPIVEPKPTLKYVSFVDEPHIWMVDQQLLGKSLQDVKGQEVPRPQTDFLELSRL---------------------------SRDSPDWCQCGNCLPSQLPENRRALEELCCRRKPGQCITTSELFSKIVLSREALQLLLLYQEPLLALEGEAINSKLRHCAYRSYATWRFVSQDMADFAILPSCCRWKIRKEFPKTQGQYSGFKYPY
(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=0.24 (Read more about C-score)
  • Estimated TM-score = 0.75±0.11
  • Estimated RMSD = 7.2±4.2Å

  • Download Model 2
  • C-score = -1.54

  • Download Model 3
  • C-score = -0.70

  • Download Model 4
  • C-score = 0.01

  • Download Model 5
  • C-score = -2.56


  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
16u9vA0.920 1.060.8000.931Download
25u1lA0.515 1.730.8640.533Download
33h9vA0.509 2.380.4570.541Download
45xw6C0.508 2.000.5110.533Download
55f1cA0.499 2.800.3750.543Download
65svjA0.497 2.320.3950.528Download
72vz8A0.359 7.650.0280.582Download
86g2dC0.339 7.560.0320.536Download
93jcrA0.335 8.030.0400.556Download
105cskA0.334 7.330.0390.514Download

(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
10.17 7 5f1cB ATP Rep, Mult 174,292,294,311
20.12 4 5f1cB ATP Rep, Mult 64,65,66,189,190,191,193
30.04 2 3H9VA 3H9VA00 Rep, Mult 113,115,117,168,169,306
40.02 1 2x2vF DPV Rep, Mult 46,49
50.02 1 3kziT CLA Rep, Mult 33,37


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
10.1532uv8G0.272 7.870.0330.444 2.3.1.86  NA
20.1472vkzG0.272 8.110.0250.454 2.3.1.38 3.1.2.14  NA
30.1302vz8B0.355 8.210.0340.600 2.3.1.85  NA
40.1292qf7A0.277 8.360.0380.479 6.4.1.1  NA
50.1232pffD0.278 7.690.0260.456 2.3.1.86  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 0.220.5089 2.38 0.46 0.543h9vA GO:0045296 GO:0033198 GO:0030054 GO:0051899 GO:0004872 GO:0006811 GO:0016021 GO:0005216 GO:0050850 GO:0008217 GO:0048471 GO:0010524 GO:0042981 GO:0001614 GO:0010614 GO:0034405 GO:0035590 GO:0055117 GO:0055119 GO:0006810 GO:0004931 GO:0016020 GO:0007165 GO:0005524
2 0.140.3028 7.59 0.04 0.471ldjA GO:0000084 GO:0000082 GO:0008285 GO:0008283 GO:0006915 GO:0005654 GO:0051437 GO:0009887 GO:0031145 GO:0051439 GO:0005829 GO:0016567 GO:0044419 GO:0006511 GO:0007050 GO:0031461 GO:0019005 GO:0005515 GO:0000278 GO:0031625 GO:0031146 GO:0008629
3 0.140.3127 7.83 0.04 0.512uvaG GO:0003824 GO:0004312 GO:0005835 GO:0006633 GO:0008152 GO:0016491 GO:0016740 GO:0055114
4 0.130.2938 7.85 0.04 0.481g8xA GO:0003774 GO:0005524 GO:0016459 GO:0005515
5 0.130.2814 8.30 0.03 0.483k1qA GO:0004482 GO:0004484 GO:0005524 GO:0019028 GO:0006370
6 0.130.2715 7.87 0.03 0.442uv8G GO:0016829 GO:0004318 GO:0016409 GO:0008152 GO:0016491 GO:0004317 GO:0005737 GO:0004314 GO:0005811 GO:0004313 GO:0004320 GO:0003824 GO:0008610 GO:0004312 GO:0016296 GO:0055114 GO:0005739 GO:0005829 GO:0004319 GO:0004321 GO:0016297 GO:0019171 GO:0006633 GO:0005835 GO:0005515 GO:0016295 GO:0016740 GO:0016787
7 0.130.2768 8.36 0.04 0.482qf7A GO:0004736 GO:0016874 GO:0046872 GO:0003824 GO:0004075 GO:0005524 GO:0006094 GO:0008152
8 0.130.3548 8.21 0.03 0.602vz8B GO:0016740 GO:0000166 GO:0000036 GO:0003824 GO:0004312 GO:0004313 GO:0004314 GO:0004315 GO:0004316 GO:0004317 GO:0004319 GO:0004320 GO:0005488 GO:0008152 GO:0008270 GO:0009058 GO:0016295 GO:0016296 GO:0016297 GO:0016491 GO:0016747 GO:0016788 GO:0031177 GO:0048037 GO:0055114
9 0.120.3024 7.51 0.04 0.472pffB GO:0004312 GO:0016296 GO:0055114 GO:0005739 GO:0005829 GO:0004319 GO:0004321 GO:0016297 GO:0019171 GO:0005737 GO:0006633 GO:0005835 GO:0005515 GO:0016295 GO:0016740 GO:0016829 GO:0004318 GO:0016409 GO:0008152 GO:0016491 GO:0004317 GO:0016787 GO:0004314 GO:0005811 GO:0004313 GO:0004320 GO:0003824 GO:0008610
10 0.120.2252 8.56 0.03 0.403hhdC GO:0003824 GO:0005488 GO:0008152 GO:0009058 GO:0016740


Consensus prediction of GO terms
 
Molecular Function GO:0035381 GO:0035586 GO:0050839 GO:0005231 GO:0016502 GO:0005261 GO:0005524
GO-Score 0.43 0.43 0.43 0.43 0.43 0.43 0.41
Biological Process GO:0051928 GO:0090075 GO:0042391 GO:0043067 GO:0032846 GO:0010033 GO:0010611 GO:0014741 GO:0050848 GO:0009967
GO-Score 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43
Cellular Component GO:0044444 GO:0031224
GO-Score 0.43 0.43

(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 S693417_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.