D-I-TASSER O76024

D-I-TASSER results for O76024

[Click result.zip to download all results on this page]

Summary of the Protein

Uniprot ID: O76024
Protein Name: Wolframin
Gene Name: WFS1

Input Sequence in FASTA format

>O76024 (890 residues)
MDSNTAPLGPSCPQPPPAPQPQARSRLNATASLEQERSERPRAPGPQAGPGPGVRDAAAP
AEPQAQHTRSRERADGTGPTKGDMEIPFEEVLERAKAGDPKAQTEVGKHYLQLAGDTDEE
LNSCTAVDWLVLAAKQGRREAVKLLRRCLADRRGITSENEREVRQLSSETDLERAVRKAA
LVMYWKLNPKKKKQVAVAELLENVGQVNEHDGGAQPGPVPKSLQKQRRMLERLVSSESKN
YIALDDFVEITKKYAKGVIPSSLFLQDDEDDDELAGKSPEDLPLRLKVVKYPLHAIMEIK
EYLIDMASRAGMHWLSTIIPTHHINALIFFFIVSNLTIDFFAFFIPLVIFYLSFISMVIC
TLKVFQDSKAWENFRTLTDLLLRFEPNLDVEQAEVNFGWNHLEPYAHFLLSVFFVIFSFP
IASKDCIPCSELAVITGFFTVTSYLSLSTHAEPYTRRALATEVTAGLLSLLPSMPLNWPY
LKVLGQTFITVPVGHLVVLNVSVPCLLYVYLLYLFFRMAQLRNFKGTYCYLVPYLVCFMW
CELSVVILLESTGLGLLRASIGYFLFLFALPILVAGLALVGVLQFARWFTSLELTKIAVT
VAVCSVPLLLRWWTKASFSVVGMVKSLTRSSMVKLILVWLTAIVLFCWFYVYRSEGMKVY
NSTLTWQQYGALCGPRAWKETNMARTQILCSHLEGHRVTWTGRFKYVRVTDIDNSAESAI
NMLPFFIGDWMRCLYGEAYPACSPGNTSTAEEELCRLKLLAKHPCHIKKFDRYKFEITVG
MPFSSGADGSRSREEDDVTKDIVLRASSEFKSVLLSLRQGSLIEFSTILEGRLGSKWPVF
ELKAISCLNCMAQLSPTRRHVKIEHDWRSTVHGAVKFAFDFFFFPFLSAA

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

Contact Map

Distance Map

D-I-TASSER simulation is guided by the consensus contact map (left figure) and distance map (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.

Information of Domain

No. of Domain	Domain	Domain Boundary	Length of Domain	Models of Domain	Sequence
1	O76024-D1	1-336	336		MDSNTAPLGPSCPQPPPAPQPQARSRLNATASLEQERSERPRAPGPQAGPGPGVRDAAAPAEPQAQHTRSRERADGTGPTKGDMEIPFEEVLERAKAGDPKAQTEVGKHYLQLAGDTDEELNSCTAVDWLVLAAKQGRREAVKLLRRCLADRRGITSENEREVRQLSSETDLERAVRKAALVMYWKLNPKKKKQVAVAELLENVGQVNEHDGGAQPGPVPKSLQKQRRMLERLVSSESKNYIALDDFVEITKKYAKGVIPSSLFLQDDEDDDELAGKSPEDLPLRLKVVKYPLHAIMEIKEYLIDMASRAGMHWLSTIIPTHHINALIFFFIVSNL
2	O76024-D2	337-563	227		TIDFFAFFIPLVIFYLSFISMVICTLKVFQDSKAWENFRTLTDLLLRFEPNLDVEQAEVNFGWNHLEPYAHFLLSVFFVIFSFPIASKDCIPCSELAVITGFFTVTSYLSLSTHAEPYTRRALATEVTAGLLSLLPSMPLNWPYLKVLGQTFITVPVGHLVVLNVSVPCLLYVYLLYLFFRMAQLRNFKGTYCYLVPYLVCFMWCELSVVILLESTGLGLLRASIGY
3	O76024-D3	564-710,773-890	265		FLFLFALPILVAGLALVGVLQFARWFTSLELTKIAVTVAVCSVPLLLRWWTKASFSVVGMVKSLTRSSMVKLILVWLTAIVLFCWFYVYRSEGMKVYNSTLTWQQYGALCGPRAWKETNMARTQILCSHLEGHRVTWTGRFKYVRVTYKFEITVGMPFSSGADGSRSREEDDVTKDIVLRASSEFKSVLLSLRQGSLIEFSTILEGRLGSKWPVFELKAISCLNCMAQLSPTRRHVKIEHDWRSTVHGAVKFAFDFFFFPFLSAA
4	O76024-D4	711-772	62		DIDNSAESAINMLPFFIGDWMRCLYGEAYPACSPGNTSTAEEELCRLKLLAKHPCHIKKFDR

Top 1 final models from D-I-TASSER

Click to view	Rank^a	Download	Estimated TM-score^b
	1	model1.pdb.gz	0.45

(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.	Download Alignment
1	6z2wE	0.41	8.26	0.040	0.625	model1_6z2wE.pdb.gz
2	6jxaA	0.41	8.74	0.042	0.645	model1_6jxaA.pdb.gz
3	5x6oC	0.38	8.10	0.042	0.558	model1_5x6oC.pdb.gz
4	5yz0A	0.38	8.58	0.042	0.583	model1_5yz0A.pdb.gz
5	6sytA	0.36	8.17	0.046	0.543	model1_6sytA.pdb.gz
6	2uvcG	0.35	9.00	0.053	0.566	model1_2uvcG.pdb.gz
7	6mu1A	0.35	8.38	0.059	0.529	model1_6mu1A.pdb.gz
8	6edoA	0.34	8.03	0.041	0.516	model1_6edoA.pdb.gz
9	7dxjA	0.34	7.92	0.048	0.491	model1_7dxjA.pdb.gz
10	2pffB	0.34	8.84	0.036	0.536	model1_2pffB.pdb.gz

(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:0019899	1.00	enzyme binding
GO:0051117	0.81	ATPase binding
GO:0031625	0.61	ubiquitin protein ligase binding

Download full result of the above consensus prediction.

Click the graph to show a high resolution version.

(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:

[0.4,0.5)

[0.5,0.6)

[0.6,0.7)

[0.7,0.8)

[0.8,0.9)

[0.9,1.0]

Biological Process (BP)

GO term	Cscore^GO	Name
GO:0080090	1.00	regulation of primary metabolic process
GO:0060255	1.00	regulation of macromolecule metabolic process
GO:0050821	1.00	protein stabilization
GO:0048523	1.00	negative regulation of cellular process
GO:0048513	1.00	animal organ development
GO:0044767	1.00	single-organism developmental process
GO:0031323	1.00	regulation of cellular metabolic process
GO:0009987	0.88	cellular process
GO:0008152	0.85	metabolic process
GO:0044763	0.84	single-organism cellular process
GO:0044238	0.84	primary metabolic process
GO:0043170	0.84	macromolecule metabolic process
GO:0048518	0.83	positive regulation of biological process
GO:0044260	0.83	cellular macromolecule metabolic process
GO:0032879	0.82	regulation of localization
GO:0032501	0.82	multicellular organismal process
GO:0031325	0.82	positive regulation of cellular metabolic process
GO:0019538	0.82	protein metabolic process
GO:0051928	0.81	positive regulation of calcium ion transport
GO:0045927	0.81	positive regulation of growth
GO:0043524	0.81	negative regulation of neuron apoptotic process
GO:0042593	0.81	glucose homeostasis
GO:0032469	0.81	endoplasmic reticulum calcium ion homeostasis
GO:0031398	0.81	positive regulation of protein ubiquitination
GO:0030433	0.81	ER-associated ubiquitin-dependent protein catabolic process
GO:0007605	0.81	sensory perception of sound
GO:0007601	0.81	visual perception
GO:0003091	0.81	renal water homeostasis
GO:0001822	0.81	kidney development
GO:0048583	0.64	regulation of response to stimulus
GO:0031326	0.63	regulation of cellular biosynthetic process
GO:0023051	0.63	regulation of signaling
GO:0019219	0.63	regulation of nucleobase-containing compound metabolic process
GO:0010646	0.63	regulation of cell communication
GO:1900101	0.62	regulation of endoplasmic reticulum unfolded protein response
GO:0051253	0.62	negative regulation of RNA metabolic process
GO:0044092	0.62	negative regulation of molecular function
GO:0010629	0.62	negative regulation of gene expression
GO:0009968	0.62	negative regulation of signal transduction
GO:0006357	0.62	regulation of transcription from RNA polymerase II promoter
GO:1903892	0.61	negative regulation of ATF6-mediated unfolded protein response
GO:0043433	0.61	negative regulation of sequence-specific DNA binding transcription factor activity
GO:0000122	0.61	negative regulation of transcription from RNA polymerase II promoter

Download full result of the above consensus prediction.

Click the graph to show a high resolution version.

(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:

[0.4,0.5)

[0.5,0.6)

[0.6,0.7)

[0.7,0.8)

[0.8,0.9)

[0.9,1.0]

Cellular Component (CC)

GO term	Cscore^GO	Name
GO:0044424	1.00	intracellular part
GO:0044444	0.86	cytoplasmic part
GO:0043226	0.86	organelle
GO:0043231	0.85	intracellular membrane-bounded organelle
GO:0044446	0.84	intracellular organelle part
GO:0044425	0.84	membrane part
GO:0044432	0.82	endoplasmic reticulum part
GO:0016021	0.82	integral component of membrane
GO:0030176	0.81	integral component of endoplasmic reticulum membrane
GO:0005783	0.81	endoplasmic reticulum
GO:0097458	0.63	neuron part
GO:0043005	0.62	neuron projection
GO:0030425	0.61	dendrite

Download full result of the above consensus prediction.

Click the graph to show a high resolution version.

(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:

[0.4,0.5)

[0.5,0.6)

[0.6,0.7)

[0.7,0.8)

[0.8,0.9)

[0.9,1.0]

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	0.060	3iydD	0.249	8.81	0.035	0.391	2.7.7.6	NA
2	0.060	2vumB	0.245	8.83	0.030	0.390	2.7.7.6	136
3	0.060	2np0A	0.256	8.79	0.052	0.405	3.4.24.69	NA
4	0.060	3ffzA	0.256	8.66	0.045	0.399	3.4.24.69	NA
5	0.060	1dceA	0.270	6.09	0.052	0.346	2.5.1.60	NA

	Click on the radio buttons to visualize predicted active site residues.
(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:

Click to view	Rank	Cscore^LB	PDB Hit	TM-score	RMSD^a	IDEN^a	Cov.	BS-score	Lig. Name	Download Complex	Predicted binding site residues
	1	0.01	3cmvE	0.261	8.82	0.050	0.413	0.48	ANP	complex1.pdb.gz	76,102,104,137,140

	Click on the radio buttons to visualize predicted binding site and residues.
(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.

[Click result.zip to download all results on this page]

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.