D-I-TASSER results for Q4L235-D1

Input Sequence in FASTA format

>Q4L235 (1098 residues)
MTLQELVHKAASCYMDRVAVCFDECNNQLPVYYTYKTVVNAASELSNFLLLHCDFQGIRE
IGLYCQPGIDLPSWILGILQVPAAYVPIEPDSPPSLSTHFMKKCNLKYILVEKKQINKFK
SFHETLLNYDTFTVEHNDLVLFRLHWKNTEVNLMLNDGKEKYEKEKIKSISSEHVNEEKA
EEHMDLRLKHCLAYVLHTSGTTGIPKIVRVPHKCIVPNIQHFRVLFDITQEDVLFLASPL
TFDPSVVEIFLALSSGASLLIVPTSVKLLPSKLASVLFSHHRVTVLQATPTLLRRFGSQL
IKSTVLSATTSLRVLALGGEAFPSLTVLRSWRGEGNKTQIFNVYGITEVSSWATIYRIPE
KTLNSTLKCELPVQLGFPLLGTVVEVRDTNGFTIQEGSGQVFLGGRNRVCFLDDEVTVPL
GTMRATGDFVTVKDGEIFFLGRKDSQIKRHGKRLNIELVQQVAEELQQVESCAVTWYNQE
KLILFMVSKDASVKEYIFKELQKYLPSHAVPDELVLIDSLPFTSHGKIDVSELNKIYLNY
INLKSENKLSGKEDLWEKLQYLWKSTLNLPEDLLRVPDESLFLNSGGDSLKSIRLLSEIE
KLVGTSVPGLLEIILSSSILEIYNHILQTVVPDEDVTFRKSCATKRKLSDINQEEASGTS
LHQKAIMTFTCHNEINAFVVLSRGSQILSLNSTRFLTKLGHCSSACPSDSVSQTNIQNLK
GLNSPVLIGKSKDPSCVAKVSEEGKPAIGTQKMELHVRWRSDTGKCVDASPLVVIPTFDK
SSTTVYIGSHSHRMKAVDFYSGKVKWEQILGDRIESSACVSKCGNFIVVGCYNGLVYVLK
SNSGEKYWMFTTEDAVKSSATMDPTTGLIYIGSHDQHAYALDIYRKKCVWKSKCGGTVFS
SPCLNLIPHHLYFATLGGLLLAVNPATGNVIWKHSCGKPLFSSPQCCSQYICIGCVDGNL
LCFTHFGEQVWQFSTSGPIFSSPCTSPSEQKIFFGSHDCFIYCCNMKGHLQWKFETTSRV
YATPFAFHNYNGSNEMLLAAASTDGKVWILESQSGQLQSVYELPGEVFSSPVVLESMLII
GCRDNYVYCLDLLGGNQK

Predicted Secondary Structure

                  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
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Sequence
MTLQELVHKAASCYMDRVAVCFDECNNQLPVYYTYKTVVNAASELSNFLLLHCDFQGIREIGLYCQPGIDLPSWILGILQVPAAYVPIEPDSPPSLSTHFMKKCNLKYILVEKKQINKFKSFHETLLNYDTFTVEHNDLVLFRLHWKNTEVNLMLNDGKEKYEKEKIKSISSEHVNEEKAEEHMDLRLKHCLAYVLHTSGTTGIPKIVRVPHKCIVPNIQHFRVLFDITQEDVLFLASPLTFDPSVVEIFLALSSGASLLIVPTSVKLLPSKLASVLFSHHRVTVLQATPTLLRRFGSQLIKSTVLSATTSLRVLALGGEAFPSLTVLRSWRGEGNKTQIFNVYGITEVSSWATIYRIPEKTLNSTLKCELPVQLGFPLLGTVVEVRDTNGFTIQEGSGQVFLGGRNRVCFLDDEVTVPLGTMRATGDFVTVKDGEIFFLGRKDSQIKRHGKRLNIELVQQVAEELQQVESCAVTWYNQEKLILFMVSKDASVKEYIFKELQKYLPSHAVPDELVLIDSLPFTSHGKIDVSELNKIYLNYINLKSENKLSGKEDLWEKLQYLWKSTLNLPEDLLRVPDESLFLNSGGDSLKSIRLLSEIEKLVGTSVPGLLEIILSSSILEIYNHILQTVVPDEDVTFRKSCATKRKLSDINQEEASGTSLHQKAIMTFTCHNEINAFVVLSRGSQILSLNSTRFLTKLGHCSSACPSDSVSQTNIQNLKGLNSPVLIGKSKDPSCVAKVSEEGKPAIGTQKMELHVRWRSDTGKCVDASPLVVIPTFDKSSTTVYIGSHSHRMKAVDFYSGKVKWEQILGDRIESSACVSKCGNFIVVGCYNGLVYVLKSNSGEKYWMFTTEDAVKSSATMDPTTGLIYIGSHDQHAYALDIYRKKCVWKSKCGGTVFSSPCLNLIPHHLYFATLGGLLLAVNPATGNVIWKHSCGKPLFSSPQCCSQYICIGCVDGNLLCFTHFGEQVWQFSTSGPIFSSPCTSPSEQKIFFGSHDCFIYCCNMKGHLQWKFETTSRVYATPFAFHNYNGSNEMLLAAASTDGKVWILESQSGQLQSVYELPGEVFSSPVVLESMLIIGCRDNYVYCLDLLGGNQK
Prediction
CCHHHHHHHHHHHCCCCSSSSSCCCCCCCCCCSCHHHHHHHHHHHHHHHHHHCCCCCCCSSSSSSCCCHHHHHHHHHHHHCCCSSSCCCCCCHHHHHHHHHHHCCCCSSSSCHHHHHHCCCCCCSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSSSCCCCCCCCCSSSSCHHHHHHHHHHHHHHHCCCCCCSSSSSCCCSHHHHHHHHHHHHHCCCSSSSCCCCCCCCHHHHHHHHHHHHCCSSSSSCHHHHHHHHHHHHHCCCCCCCCCCCSSSSSCCCCCHHHHHHHHHHHCCCCSSSSCSCCCCCSSSSSSSSCCCCCCCCCCCCCCCCCCCCSCCCCSSSSSCCCCCSCCCCCCSSSSCCCCCCCCCCCCCCCCCCSCSCCCCSSSSCCCSSSSCCCCCCSSSSCCSSCCHHHHHHHHHHCCCCCSSSSSSCCCCSSSSSSSCCCCCCHHHHHHHHHHHCCHHHCCCSSSSSCCCCCCCCCCHHHHHCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHCCCCCCCCCCCCCCHHHCCCHHHHHHHHHHHHHHHHCCCCCHHHHHHCCCCHHHHHHHHHHHCCCCCCCCCCCCCHHHHHHHHHHHCCCCCCCSSSSSSSSSSCCCCHHHHHHHHHHHHHHHCCCCSSSCSCCSSSSSSCCCCCCCCSSSSCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCSSSSSSSCCCCCCCCCCSSSSSSCCCCCCSSSSSSCCCSSSSSSSCCCCSSSSSSCCCCSSSSSSSSCCCCSSSSSSCCCSSSSSSCCCCSSSSSSSCCCCCCCCCCSCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSSCCCCSSCCCCCCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSCCCCCCSCCCSSCCCCSSSSSCCCSSSSSCCCCCSSSSSSCCCCSCCCCSSCCCCCSSSSSSCCCSSSSSCCCCCSSSSSSCCCCSSSCCSSCCCCCCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSSCCCCCCCCCSSSCCSSSSSSCCCCSSSSSSCCCCCC
Confidence
978999999999789972999688356787523299999999999999999689999958999937998999999999810816845797892999999999719949998555775424456427841542112343221234555544331135542112332223344112355776566778998880899983788999957787217799999999997199978679986785024579999999970999999482122799999999999819829992789999999987534553458876299995036999999999997589978998237434245678898463334666667876877542289699998899992899886699857893320689999998710324648983698499925346526546655277999999985966123899991898799999879999999999999976926419828999635688998550044479987544444555667999999999999999996999767864788881430756999999999999997998742999970886999999999742676666778887224443343322799872221289997368779999999987777621551677128868899578877552699856799688765542245555566402433332125315899860576556775189864057872499972241489998114848999970762022256645898699985275499985589728999735981024540236788499962586489985568918999855871450354157898499996687599970678836776216996211534538947999737818975589965789865897335323358897499971798189971688579998469952312312368888887479999769859999668894777421787520464575767999964894899984378769

H:Helix; S:Strand; C:Coil

Predicted Solvent Accessibility

                  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
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Sequence
MTLQELVHKAASCYMDRVAVCFDECNNQLPVYYTYKTVVNAASELSNFLLLHCDFQGIREIGLYCQPGIDLPSWILGILQVPAAYVPIEPDSPPSLSTHFMKKCNLKYILVEKKQINKFKSFHETLLNYDTFTVEHNDLVLFRLHWKNTEVNLMLNDGKEKYEKEKIKSISSEHVNEEKAEEHMDLRLKHCLAYVLHTSGTTGIPKIVRVPHKCIVPNIQHFRVLFDITQEDVLFLASPLTFDPSVVEIFLALSSGASLLIVPTSVKLLPSKLASVLFSHHRVTVLQATPTLLRRFGSQLIKSTVLSATTSLRVLALGGEAFPSLTVLRSWRGEGNKTQIFNVYGITEVSSWATIYRIPEKTLNSTLKCELPVQLGFPLLGTVVEVRDTNGFTIQEGSGQVFLGGRNRVCFLDDEVTVPLGTMRATGDFVTVKDGEIFFLGRKDSQIKRHGKRLNIELVQQVAEELQQVESCAVTWYNQEKLILFMVSKDASVKEYIFKELQKYLPSHAVPDELVLIDSLPFTSHGKIDVSELNKIYLNYINLKSENKLSGKEDLWEKLQYLWKSTLNLPEDLLRVPDESLFLNSGGDSLKSIRLLSEIEKLVGTSVPGLLEIILSSSILEIYNHILQTVVPDEDVTFRKSCATKRKLSDINQEEASGTSLHQKAIMTFTCHNEINAFVVLSRGSQILSLNSTRFLTKLGHCSSACPSDSVSQTNIQNLKGLNSPVLIGKSKDPSCVAKVSEEGKPAIGTQKMELHVRWRSDTGKCVDASPLVVIPTFDKSSTTVYIGSHSHRMKAVDFYSGKVKWEQILGDRIESSACVSKCGNFIVVGCYNGLVYVLKSNSGEKYWMFTTEDAVKSSATMDPTTGLIYIGSHDQHAYALDIYRKKCVWKSKCGGTVFSSPCLNLIPHHLYFATLGGLLLAVNPATGNVIWKHSCGKPLFSSPQCCSQYICIGCVDGNLLCFTHFGEQVWQFSTSGPIFSSPCTSPSEQKIFFGSHDCFIYCCNMKGHLQWKFETTSRVYATPFAFHNYNGSNEMLLAAASTDGKVWILESQSGQLQSVYELPGEVFSSPVVLESMLIIGCRDNYVYCLDLLGGNQK
Prediction
723331002003421400000012344444220001001310120021015305145120000000000000000000100100000011610420021004003010000034014304424220011232324333332342424323131113333432443413413344145444442444241300000000111143320000000000000100132040444000000000000100101100000000000035411210330041016413001000000001001420254541640310000000000010620140046222301001042000000000002034432444444421000000002000000144231100000000001100110022403443310000000001420200001020200011021010110110036143031000002523100000004542215201510372001100000001022000001111023102414354443544423214440042004033400414544420001000100100000000000202630634022033004120023004203642445664532312101310000100126310000000010414002500320141020011220201345330201014625140302304314363144424434123302433422242441412120202044101000000001133430000000100000000012240201130422010000014433100000120000002042020102031533030200104332000000000000000044430103140420010000013133000000110000000042031103241631000000004300000001000000011112003131401000000102142100000100000001142302021406230000000032342422100000013000000206423330415041110000001210000002100000020444658

Values range from 0 (buried residue) to 8 (highly exposed residue)

Predicted Contact, Hydrogen and Distance Map Used in D-I-TASSER simulation

D-I-TASSER simulation is guided by the consensus contact map (left figure), distance map (middle figure) and Hydrogen bond network (right figure) derived based on confidence scores of AttentionPotential. In the contact, distance map and hydrogen bond networks, the axes mark the residue index along the sequence. For the contact map, each dot represents a residue pair with predicted contact, while for the distance map and hydrogen bond network, a color scale represents a distance of 1-20+ angstroms or a angle of 0-180 degree.

Top 10 threading templates used by D-I-TASSER

Rank	PDB hit	ID1	ID2	Cov	Norm. Zscore	Download alignment		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                    |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |                   |
							SS	CCHHHHHHHHHHHCCCCSSSSSCCCCCCCCCCSCHHHHHHHHHHHHHHHHHHCCCCCCCSSSSSSCCCHHHHHHHHHHHHCCCSSSCCCCCCHHHHHHHHHHHCCCCSSSSCHHHHHHCCCCCCSSSSCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCSSSSSSCCCCCCCCCSSSSCHHHHHHHHHHHHHHHCCCCCCSSSSSCCCSHHHHHHHHHHHHHCCCSSSSCCCCCCCCHHHHHHHHHHHHCCSSSSSCHHHHHHHHHHHHHCCCCCCCCCCCSSSSSCCCCCHHHHHHHHHHHCCCCSSSSCSCCCCCSSSSSSSSCCCCCCCCCCCCCCCCCCCCSCCCCSSSSSCCCCCSCCCCCCSSSSCCCCCCCCCCCCCCCCCCSCSCCCCSSSSCCCSSSSCCCCCCSSSSCCSSCCHHHHHHHHHHCCCCCSSSSSSCCCCSSSSSSSCCCCCCHHHHHHHHHHHCCHHHCCCSSSSSCCCCCCCCCCHHHHHCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHCCCCCCCCCCCCCCHHHCCCHHHHHHHHHHHHHHHHCCCCCHHHHHHCCCCHHHHHHHHHHHCCCCCCCCCCCCCHHHHHHHHHHHCCCCCCCSSSSSSSSSSCCCCHHHHHHHHHHHHHHHCCCCSSSCSCCSSSSSSCCCCCCCCSSSSCCCCCHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCSSSSSSSCCCCCCCCCCSSSSSSCCCCCCSSSSSSCCCSSSSSSSCCCCSSSSSSCCCCSSSSSSSSCCCCSSSSSSCCCSSSSSSCCCCSSSSSSSCCCCCCCCCCSCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSSCCCCSSCCCCCCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSCCCCCCSCCCSSCCCCSSSSSCCCSSSSSCCCCCSSSSSSCCCCSCCCCSSCCCCCSSSSSSCCCSSSSSCCCCCSSSSSSCCCCSSSCCSSCCCCCCCCCCSSSSSSCCCSSSSSSCCCCCSSSSSSCCCCCCCCCSSSCCSSSSSSCCCCSSSSSSCCCCCC
							Seq	MTLQELVHKAASCYMDRVAVCFDECNNQLPVYYTYKTVVNAASELSNFLLLHCDFQGIREIGLYCQPGIDLPSWILGILQVPAAYVPIEPDSPPSLSTHFMKKCNLKYILVEKKQINKFKSFHETLLNYDTFTVEHNDLVLFRLHWKNTEVNLMLNDGKEKYEKEKIKSISSEHVNEEKAEEHMDLRLKHCLAYVLHTSGTTGIPKIVRVPHKCIVPNIQHFRVLFDITQEDVLFLASPLTFDPSVVEIFLALSSGASLLIVPTSVKLLPSKLASVLFSHHRVTVLQATPTLLRRFGSQLIKSTVLSATTSLRVLALGGEAFPSLTVLRSWRGEGNKTQIFNVYGITEVSSWATIYRIPEKTLNSTLKCELPVQLGFPLLGTVVEVRDTNGFTIQEGSGQVFLGGRNRVCFLDDEVTVPLGTMRATGDFVTVKDGEIFFLGRKDSQIKRHGKRLNIELVQQVAEELQQVESCAVTWYNQEKLILFMVSKDASVKEYIFKELQKYLPSHAVPDELVLIDSLPFTSHGKIDVSELNKIYLNYINLKSENKLSGKEDLWEKLQYLWKSTLNLPEDLLRVPDESLFLNSGGDSLKSIRLLSEIEKLVGTSVPGLLEIILSSSILEIYNHILQTVVPDEDVTFRKSCATKRKLSDINQEEASGTSLHQKAIMTFTCHNEINAFVVLSRGSQILSLNSTRFLTKLGHCSSACPSDSVSQTNIQNLKGLNSPVLIGKSKDPSCVAKVSEEGKPAIGTQKMELHVRWRSDTGKCVDASPLVVIPTFDKSSTTVYIGSHSHRMKAVDFYSGKVKWEQILGDRIESSACVSKCGNFIVVGCYNGLVYVLKSNSGEKYWMFTTEDAVKSSATMDPTTGLIYIGSHDQHAYALDIYRKKCVWKSKCGGTVFSSPCLNLIPHHLYFATLGGLLLAVNPATGNVIWKHSCGKPLFSSPQCCSQYICIGCVDGNLLCFTHFGEQVWQFSTSGPIFSSPCTSPSEQKIFFGSHDCFIYCCNMKGHLQWKFETTSRVYATPFAFHNYNGSNEMLLAAASTDGKVWILESQSGQLQSVYELPGEVFSSPVVLESMLIIGCRDNYVYCLDLLGGNQK
1	6eqoA	0.13	0.07	2.27	0.67	DEthreader		ICTFNEVDRHVSGHGDEAMIFEGDRWPVDSEVISRRKLLLESAKCALALKALGLEAGD-RIALNMPSIPEQIYWTEGAKRMGIVYTPVFGGFSDKTLSDRIADAGARVVVTADKPTDPALDNFIAVALAVDSPPRVDA-------------------------------EELKAARAIWAGAPVLAVDAEYPNFIIYTSGSTGKPKGVVHVHGGYASGVAATMPAFGAEPGDVMYVVADPGWITGQSYIAASLLSRVTTVITEGSPVFPHAGRFASIIERYGVNVFKAGVTFLKSVMPENLKDIQRYDLSSLKVATFCAEPVSPAVQAFAMEH--ITHRYINSYWATEHGGMVWTHFADADGFPLE-ADAHTYPLPWIMG---GPVEYERDTPWRVGEIVIPYPYLTRVRVAGGWRGDEVRYATYTQGDFAMRP-GSFSLHGRDDVINVSGHRIGTEEIEGAILRDKAVGNVIVIGAPHVTPIAFVTPVEGRRLDKRLDLVRTEKGAVAVPDFIELSEFPETRSGKYMRRMVRVLDELARAVD---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ET-----------------G-VD----HAHAMVREF------------VRSGDDSLGKFAARKT---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ARMV-----------------------------------------------------------------L---RLSDFHWPD-------------
2	4zxjA	0.23	0.12	3.71	3.00	SPARKS-K		TTLSALVAEQAAKTPDAPALADARYL------FSYREMREQVVALANLLRERGV-KPGDSVAVALPRSVFLTLALHAIVEAGAAWLPLDTGYPDDRLKMMLEDARPSLLITTDDQLPRFSDVP----NLTSLCYNA-------------------------------------PLTPQGSAPL-QLSQPHHTAYIIFTSGSTGRPKGVMVGQTAIVNRLLWMQNHYPLTGEDVVAQKTPCSFDVSVWEFFWPFIAGAKLVMAEPEAHRDPLAMQQFFAEYG-VTTTHFVPSMLAAFVASLTPQTARQSCATLKQVFCSGEALPA-DLCREWQQLTG-APLHNLYGPTEAAVDVSWYPAFGEELAQVR--GSSVPIGYPVWNTGLRILDAMMHPVPPGAGDLYLTGIQASRFIADPF-APGERMYRTGDVARWDNGAVEYLGRSDDQLKIRGQRIELGEIDRVMQALPDVEQAVTHACATGQLVGYLVSQSGLDTSALQAQLRETLPPHMVPVVLLQLPQLPLSANGKLDRKALPLPEL----KAQAPGRAPKAGSETIIAAAFSSLLGCD----VQDADADFFALGGHSLLAMKLAAQLSRQVARQVT-PGQVMVASTVAKLATIIDAE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
3	6mfzA	0.15	0.14	4.60	1.08	MapAlign		KTFHQLFEQQVEMTPDHVAVVDR------GQSLTYKQLNERANQLAHHLRG-KGVKPDDQVAIMLDKSLDMIVSILAVMKAGGAYVPIDPDYPGERIAYMLADSSAAILLTNALHEEKA---NGACD-----------IIDVH----------------------------DPDSYSENTNNLPHVNRPDDLVYVMYTSGSTGLAKGVMIEHHNLVNFCEWYRPYFGVTPADKALVYSSFSFDGSALDIFTHLLAGAALHIVPSERKYDLDALNDYCNQ-EGITISYLPTGAAEQFMQ-M-------DNQSFRVVITGGDVLK---KIERN----GTYKLYNGYGPTECTIMVTMFEV--------DKPYANIPIGKPIDRTRILILDEALALQIGVAGELFIVGEGGRGYLFIVHPQTGERMYRTGDRARFLPGNIEFLGRLDNLVKIRGYRIEPGEIEPFLMNHPLIELTTVLAKGRKYLVGYYVAPEE-IHGELREWLGNDLPDYMIPTYFVHMKAFPLTANGKVDRRAL--PDVQA-------DVAPTDELEQQLAQVWSHVLGIPQ----MGIDDHFLERGGDSIKVMQLIHQLKNIG-LSLR-YDQLFTHPTIRQLKRLLTEKRMYIIQQQDVESIAYNVVYTINFPLTVDTEQIRVALEQLVLRHEGLRSTYHMRGDEIVKRIVPRAELSFVRQTGEEESVQSLLAEQIKPFDLAKAPLLRAGVITRKLKATAAKHDLTLYMLMLTIVSIWLSKMNSDSNQVILGTVTDGRQMFVNTLMFMMQGDLTLEVLERGLNIVFEYNWAAATPDKTALVFREQRVTYRELNMLMAFAVLKAGGAYLPIDPAERIAYIFADSGAKLVLAQSPFVEKAVVLDLNSASSGALLNVLHGMQDEYPLLQDDAFLLKTTYIFDISEIWVPGRGKLNPDELVPKVYEVLPEVKLENIYGPATIYASRYSLSPVPIGKPLPNYRMYIINQPIGVPGELCIAYRTGDLARYREDGNIEYLGRMDIELDEIRSKLIQEETIQDAVVVARNGQAYLCAYLLSEQEWYMIPAH---------FVLLKQFPLTANGKLDRKALPE----
4	4zxjA	0.22	0.11	3.56	0.38	CEthreader		TTLSALVAEQAAKTPDAPALADARYL------FSYREMREQVVALANLLRERGVK-PGDSVAVALPRSVFLTLALHAIVEAGAAWLPLDTGYPDDRLKMMLEDARPSLLITTDDQLPRFSDVPNLTSLCY------------------------------------------NAPLTPQGSAPLQLSQPHHTAYIIFTSGSTGRPKGVMVGQTAIVNRLLWMQNHYPLTGEDVVAQKTPCSFDVSVWEFFWPFIAGAKLVMAEPEAHRDPLAMQQFFAEY-GVTTTHFVPSMLAAFVASLTPQTARQSCATLKQVFCSGEALPADLCREWQQLT--GAPLHNLYGPTEAAVDVSWYPAFGEELAQ--VRGSSVPIGYPVWNTGLRILDAMMHPVPPGAGDLYLTGIQLAQRFIADPFAPGERMYRTGDVARWDNGAVEYLGRSDDQLKIRGQRIELGEIDRVMQALPDVEQAVTHACDARQLVGYLVSQSPLDTSALQAQLRETLPPHMVPVVLLQLPQLPLSANGKLDRKALPLPE----LKAQAPGRAPKAGSETIIAAAFSSLLGCD----VQDADADFFALGGHSLLAMKLAAQLSRQVARQVT-PGQVMVASTVAKLATIIDAE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5	5u89A	0.22	0.18	5.59	2.20	MUSTER		ENFLQLFEKQAERIPEAIAVICEDQ------ALSYTELNQQANRLAHFLMEYGVG-PEQYVALALPRSAEMVIAMLAVLKTGAAYLPLDLDYPDERIAFMLEDTKPVCIVTSSSVQSKLSHFPSC--------------STIILDHPETEQAI----------------------KHYPDTNVPKTQSPLHPAYVIYTSGSTGKPKGVVVPFHSLNNFLLAMREKFALKEHDRLLAVTTIAFDISALEIFLPLISGASLVVAKKETIQDPQALAAVISDKE-ITIMQATPTLWHMLVTH-----HPDCIAGL-RVLVGGEALS-SGLASALHRLA--CEVTNLYGPTETTIWSTMSPLP--------------SIGRPIWNTQVYVLDEQLQPVPPGVGELYIAGSGAERFVANPYGPPGSRMYRTGDLVRW-DGSLDYIGRVDHQIKLRGFRIEIGEIEAVLSQCDLVERALVVAREDQRLVAYVIPCEL---AELRRYVSERLPDYMVPSAFMVLNEFPLTPNGKIDRKALPAPDF---------TRKPRNPQEEILCELFAEVLEIP----VVGIDDHFFELGGHSLLAARLISRIRDVLGVEIT-IGKLFASPTVASLVKR-KPPVKAYACKEDIPLSFAQRRLWFLYHLEGPSPTYNIPVVVHLTGELHYQALYDVIERHEPLR---TIFPEHS---RQVILEPHQARPELMIKE--ISESELSDELNAAVRYRFDLAAEPA-----------IRA---------QLFVL---GPNRHVLLLLMH-H--MIVDGWS----LTPLTRD-------IAA--------AYNAH------CRNQ-------------KVEWAPLPVALWQQEILGDETNPDSLIAKQLWKKTLAGLPEELELPTDYPRP--ESSYEGGIVDFCMDAELHK--RENKASLFM--LGAGTDIPIGSP-GLVLRMDTSGNPSFR------------VREVNLSAY---NQDI-------ERLV---ILNHPLFQVMFVFQNTPEPKLESRLEIRSVGTLELRERRGDGLIGLFEYSRDLFD--VVMNPDLPIG--------IDMLLPEER
6	6mfzA	0.18	0.16	5.33	1.74	HHsearch		KTFHQLFEQQVEMTPDHVAVVDRGQS------LTYKQLNERANQLAHHLRGKGVK-PDDQVAIMLDKSLDMIVSILAVMKAGGAYVPIDPDYPGERIAYMLADSSAAILLTNALHEEKANGAC--------------DIIDVH----DPD---S---------------------YSENTNNLPHVNRPDDLVYVMYTSGSTGLAKGVMIEHHNLVNFCEWYRPYFGVTPADKALVYSSFSFDGSALDIFTHLLAGAALHIVPSERKYDLDALNDYCNQ-EGITISYLPTGAAEQFMQM--------DNQSFRVVITGGDVLKK---IER----NGTYKLYNGYGPTECTIMVTMFEVDK--------PYANIPIGKPIDRTRILILDEALALQPIGAGELFIVGEGGRGYLNRPEFQTGERMYRTGDRARFPDGNIEFLGRLDNLVKIRGYRIEPGEIEPFLMNHPLIELTTVLAKERKYLVGYYVAPEEIPHGELREWLGNDLPDYMIPTYFVHMKAFPLTANGKVDRRALPDVQAD---------VAPTDELEQQLAQVWSHVLGIP----QMGIDDHFLERGGDSIKVMQLIHQLK-NIGLSLR-YDQLFTHPTIRQLKRLLTEQKQVSDEQAEYETSAVEKRMYIIQQQDVESIAYNVVYTINFPLHEAPLLAGVIETADKVLWFGLSILARELQLLVEKTYKSFAYWKTLLQGELLPTKKRPPQLTFDGAIQRKLKATAKHDLTLYMLMLTIVSIWLGMFVNTLPLLLSIDHEESDRVKREGNRHPLFDVMMMQGAP-------ETELESNMHHIN----AGISKFDLTLEVLERENGNIVFEYNTHLFDKRFELVTEDERDLVNDTYNKLITALVFREQRVTYEKGVQDDAYLNPPVNQPGDLVYVMYTSGSTGMIEHGLNVLHGMQDLAFLLKTTYIFDSAEIFGWVPGGKLVILEPAGITHINFVPSMPFVEGRTEANRLRYILACGELPEVKLENIYGP------TEATIYASRYSLAKGSQESPVPIGKPLPNYRMYIINRHGGASLARGALTEEKFTPKRIYGNIEYLGRMDHQVRGYRIELDEIK
7	6mfzA	0.19	0.17	5.49	3.28	FFAS-3D		-TFHQLFEQQVEMTPDHVAVVDRGQ------SLTYKQLNERANQLAHHLRGKGVKPDD-QVAIMLDKSLDMIVSILAVMKAGGAYVPIDPDYPGERIAYMLADSSAAILLTNALHEEKANGACDIID------------------------------------------VHDPDSYSENTNNLPHVNRPDDLVYVMYTSGSTGLAKGVMIEHHNLVNFCEWYRPYFGVTPADKALVYSSFSFDGSALDIFTHLLAGAALHIVPSERKYDLDALNDYCNQE-GITISYLPTGAAEQFMQM--------DNQSFRVVITGGDVLKK-------IERNGTYKLYNGYGPTECTIMVTMFEVD--------KPYANIPIGKPIDRTRILILDEALALQPIGVGELFIVGEGLGKFIVHPQ--TGERMYRTGDRARFPDGNIEFLGRLDNLVKIRGYRIEPGEIEPFLMNHPLIELTTVLAKEQAYLVGYYVAPEEIPHGELREWLGNDLPDYMIPTYFVHMKAFPLTANGKVDRRALPDV---------QADVAPTDELEQQLAQVWSHVLGIP----QMGIDDHFLERGGDSIKVMQLIHQLKNI-GLSL-RYDQLFTHPTIRQLKRLLTEQKQVSLEPLREETSAVEKRMYIIQQQDVESIAYNVVYTINFPLTVDTEQSTYHMRGDEIVKRIVPRAELSFVRQTGEEESVQSLLAEQIKPFDLAKAPLLRAQGELPAVQLPTKKRPPQLTFDGAIQMYRVNPEITRKLKATAAIWLSKMNSDSNQVILGTVTDGRQHPDT-RELLGMLLSIDHNMHHINAGISKFDLTLEVLERENGLNIV-------FEYNTHLFDEGMALVFREQRVTYRGVQPDDLVMLMAERSVEVLKA---GGAYHSPIFADSGAKLVLAQQPGDLVYVMYTSG------STGKPKKTTYIFDISVIFGWVPGRGKLVILEPEAGITHINFVPSMLIPFVEANRLRYILACGEAMPVKLENIYG------PTEATIYASRYSLAKGSQESPVPIGKPLPNYRMYIINRHGGELCIAYALTEEKFPHPIYRTGDLARYREDGNIEYLGRMDHQVK
8	6mfzA	0.13	0.11	3.99	0.85	EigenThreader		KTFHQLFEQQVEMTPDHVAVVDR------GQSLTYKQLNERANQLAHHLRGKG-VKPDDQVAIMLDKSLDMIVSILAVMKAGGAYVPIDPDYPGERIAYMLADSSAAILLTN---------------ALHEEKANGACDIIDVHDPDSYSE------------------NTNNLPH---------VNRPDDLVYVMYTSGSTGLAKGVMIEHHNLVNFCEWYRPYFGVTPADKALVYSSFSFDGSALDIFTHLLAGAALHIVPSERKYDLDALNDYCNQEG-ITISYLPTGAAEQFM--------QMDNQSFRVVITGDVLKKI-----------ERNGNGYGPTEC-TIMVTMFEVD---------KPYANIPIGKPIDRTRILILDEALALQPIGVAGELFIGLGRGYLN--RPELTAEKFIVHPQRARFLPGNIEFLGRLDNLVKIRGYRIEPGEIEPFLMNHLIELTTVLAKEQADGLVGYYVAPEEIPHGELREWLGNDLPDYMIPTYFVHMKAFPLTANGKVDR---------RALPDVQADVAPTDELEQQLAQVWSHVLGIPQMGIDDHFLERG---GDSIKVMQLIHQLKN---IGLSLRYDQLFTHPTIRQLKRLL--TEQKQVSLEPLRELDSLLAEQIKPFD---LAKAPLAGVIETAD--KKVLWFDSHHILLDGLSKSILARELQALLGQQVLSPVEKTQGELPAVQLPTKKRPPQLTFDLMLTIVSIWLSKMNSDSNQVILGTVTDGRQHPDTRELLLLLSIDHEESVMFMMQGAPETMHHINAGISKFLEVLERENGLNIVFEYNTHLFDEALVFRPDDLVMLMAERSGAYLPIDPHSPSGAKLVLAQPGDLVYVMYTKPKGVMIEHLQDDAFLLKTTYIFDISVAEIFGWVPG------RGKLVILEPEAEKITHINFVPSMLEGRTEANRLRYILACGEVKLENIYGIYASRYSLAKGSQESPVPIGKPLPNYRMYIINRHGQL-QPIGVPGELCIAGASLAGYLNNTP-HPLEKGERIYRTG-----DLARYREDGNIEYLGRMDHQVKIRGDAVV--VARNDQNGQAAYLLSEQEWTV
9	4zxjA	0.23	0.12	3.66	4.46	CNFpred		TTLSALVAEQAAKTPDAPALADA------RYLFSYREMREQVVALANLLRERGVK-PGDSVAVALPRSVFLTLALHAIVEAGAAWLPLDTGYPDDRLKMMLEDARPSLLITTDDQLPRFSDVPN-----------LTSLCYNAP-------------------------------LTPQGSAPLQLSQPHHTAYIIFTSGSTGRPKGVMVGQTAIVNRLLWMQNHYPLTGEDVVAQKTPCSFDVSVWEFFWPFIAGAKLVMAEPEAHRDPLAMQQFFAEY-GVTTTHFVPSMLAAFVASLTPQTARQSCATLKQVFCSGEALP-ADLCREWQQLT-GAPLHNLYGPTEAAVDVSWYPAFGEELAQVR--GSSVPIGYPVWNTGLRILDAMMHPVPPVAGDLYLTGIQLQGYLGRPD-APGERMYRTGDVARWLNGAVEYLGRSDDQLKIRGQRIELGEIDRVMQALPDVEQAVTHACVARQLVGYLVSQLPLDTSALQAQLRETLPPHMVPVVLLQLPQLPLSANGKLDRKALPLPELKAQ----APGRAPKAGSETIIAAAFSSLLGC----DVQDADADFFALGGHSLLAMKLAAQLSRQVARQV-TPGQVMVASTVAKLATIIDAE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
10	4zxjA	0.18	0.08	2.70	0.67	DEthreader		TTLSALVAEQAAKTPDAPALADA------RYLFSYREMREQVVALANLLRERGVKPGD-SVAVALPRSVFLTLALHAIVEAGAAWLPLDTGYPDDRLKMMLEDARPSLLITTDDQLPRFSDV---P--N-----LTS-------------------------------------TPQGSAPLQLS-QPH-HTAYIIFTSGSTGRPKGVMVGQTAIVNRLLWMQNHYPLTGEDVVAQKTPCSFDVSVWEFFWPFIAGAKLVMAEPEAHRDPLAMQQFFAEYGVTTTHFVMLAAFVASLTPQTAR-QS-CA-TLKQVFCSGEALPADLCRE-WQQL-TGAPLHNLYGPTEAAVDVSWYPAFGEELAQVRGSSVPIGYPVWN--TGLRILDA-MMHPVAGDLYLTGIQLAQGYLGRPDLTASRFIRMYRTGDVARWLDGAVEYLGRDQLKIR-GQRIELGEIDRVMQALPDVEQAVTHACVARQLVGYLVSQSGLPLDALQAQLRETLPPHMVPVVLLQLPQLPLSAN-GKLDRKALPLPELK-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------II--A------S---------------------------------------------------------------------LLG------------------LGGHSLL-AM--------------------------------------------------------------------------------------------------------------------------------------------------------K----------SRQVARQVTPGQVM------------------------------------


(a) ID1 is the number of template residues identical to query divided by number of aligned residues.
(b) ID2 is the number of template residues identical to query divided by query sequence length.
(c) Cov is equal the number of aligned template residues divided by query sequence length.
(d) Norm. Zscore is the normalized Z-score of the threading alignments. A Normalized Z-score >1 means a good alignment and is highlighted in bold.
(e) Download alignment lists the threading program used to identify the template, and provide the 3D structure of aligned regions of threading templates (threading[1-10].pdb.gz).
(f) Template residues identical to query sequence are highlighted in color.

Top 1 final models from D-I-TASSER

Rank^a	Estimated TM-score^b
1	0.5865


(a) D-I-TASSER simulations generate a large ensemble of structural conformations, i.e. decoys. These decoys are clustered by SPICKER based on pairwise structure similarity to report up to five final models from the five largest clusters. Models are ranked in descending order of cluster size. If the simulations converge well, it is possible to have less than 5 models generated, which is usually an indication of good model quality.
(b) The model confidence is quantitatified by estimated TM-score (eTM-score), calculated based on significance of threading template alignments, contact map satisfaction rate, mean absolute error between distance of model and distance of AttentionPotential, and convergence of D-I-TASSER simulations. eTM-score is typically in the range of [0, 1], with higher eTM-score signifies higher model confidence.

Proteins with similar structure

Top 10 structural analogs in PDB (as identified by TM-align)


Rank	PDB Hit	TM-score	RMSD^a	IDEN^a	Cov.
1	6mfzA	0.84	3.74	0.169	0.905
2	6n8eA	0.51	5.07	0.163	0.575
3	2vsqA	0.45	5.57	0.141	0.528
4	4zxhA	0.43	4.06	0.157	0.465
5	1ry2A	0.42	3.80	0.191	0.463
6	5ifiA	0.42	3.81	0.151	0.461
7	1amuA	0.42	1.48	0.247	0.428
8	3fccA	0.42	2.42	0.214	0.438
9	2d1tA	0.42	3.35	0.153	0.452
10	6ulwA	0.42	5.04	0.112	0.484



(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) RMSD^a is the RMSD between residues that are structurally aligned by TM-align.
(d) IDEN^a 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 Gene Ontology (GO) Terms

Molecular Function (MF)


GO term	Cscore^GO	Name
GO:0003824	0.95	catalytic activity
GO:0016874	0.73	ligase activity
GO:0016877	0.54	ligase activity, forming carbon-sulfur bonds






(a) Cscore^GO is the confidence score of predicted GO terms. Cscore^GO values range in between [0-1]; where a higher value indicates a better confidence in predicting the function using the template.
(b) The graph shows the predicted terms within the Gene Ontology hierachy for Molecular Function. Confidently predicted terms are color coded by Cscore^GO:

Biological Process (BP)


GO term	Cscore^GO	Name
GO:0008152	0.96	metabolic process
GO:0044699	0.89	single-organism process
GO:0044710	0.84	single-organism metabolic process
GO:0009987	0.83	cellular process
GO:0044237	0.77	cellular metabolic process
GO:0071704	0.76	organic substance metabolic process
GO:0044763	0.59	single-organism cellular process
GO:0044238	0.59	primary metabolic process
GO:0019748	0.50	secondary metabolic process
GO:0006807	0.50	nitrogen compound metabolic process






(a) Cscore^GO is the confidence score of predicted GO terms. Cscore^GO values range in between [0-1]; where a higher value indicates a better confidence in predicting the function using the template.
(b) The graph shows the predicted terms within the Gene Ontology hierachy for Biological Process. Confidently predicted terms are color coded by Cscore^GO:

Cellular Component (CC)


GO term	Cscore^GO	Name
GO:0044464	1.00	cell part
GO:0044424	0.98	intracellular part
GO:0044444	0.80	cytoplasmic part
GO:0043229	0.67	intracellular organelle
GO:0043227	0.64	membrane-bounded organelle
GO:0043231	0.63	intracellular membrane-bounded organelle
GO:0005737	0.55	cytoplasm






(a) Cscore^GO is the confidence score of predicted GO terms. Cscore^GO values range in between [0-1]; where a higher value indicates a better confidence in predicting the function using the template.
(b) The graph shows the predicted terms within the Gene Ontology hierachy for Cellular Component. Confidently predicted terms are color coded by Cscore^GO:

Predicted Enzyme Commission (EC) Numbers

Top 5 enzyme homologs in PDB


Rank	Cscore^EC	PDB Hit	TM-score	RMSD^a	IDEN^a	Cov.	EC Number	Predicted Active Site Residues
1	0.146	3fccA	0.420	2.42	0.214	0.438	6.1.1.13	448,453
2	0.143	1amuA	0.421	1.48	0.247	0.428	5.1.1.11	448,453
3	0.060	2vuaA	0.152	7.48	0.036	0.211	3.4.24.69	194,242,258
4	0.060	3dlpX	0.393	3.97	0.151	0.434	6.2.1.33	NA
5	0.060	2vz8A	0.259	9.24	0.036	0.403	2.3.1.85	NA



(a) Cscore^EC is the confidence score for the Enzyme Commission (EC) number prediction. Cscore^EC 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) RMSD^a is the RMSD between residues that are structurally aligned by TM-align.
(d) IDEN^a 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.

Predicted Ligand Binding Sites

Template proteins with similar binding site:


Rank	Cscore^LB	PDB Hit	TM-score	RMSD^a	IDEN^a	Cov.	BS-score	Lig. Name	Predicted binding site residues
1	0.04	1amuB	0.420	1.49	0.243	0.427	0.18	PHE	7,72,257
2	0.01	1t5d0	0.396	3.82	0.153	0.434	0.25	III	339,378,379,380,381,382
3	0.01	3ni2A	0.352	3.82	0.142	0.383	0.10	AYL	84,85,242
4	0.01	3o82A	0.337	3.14	0.141	0.360	0.11	HP8	70,79,80,84



(a) Cscore^LB is the confidence score of predicted binding site. Cscore^LB values range in between [0-1]; where a higher score indicates a more reliable ligand-binding site prediction.
(b) BS-score is a measure of local similarity (sequence & structure) between template binding site and predicted binding site in the query structure. Based on large scale benchmarking analysis, we have observed that a BS-score >1 reflects a significant local match between the predicted and template binding site.
(c) TM-score is a measure of global structural similarity between query and template protein.
(d) RMSD^a the RMSD between residues that are structurally aligned by TM-align.
(e) IDEN^a is the percentage sequence identity in the structurally aligned region.
(f) 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.

References:
1. 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. In preparation, 2020.