D-I-TASSER Q9BRA2

D-I-TASSER results for Q9BRA2

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Summary of the Protein

Uniprot ID: Q9BRA2
Protein Name: Thioredoxin domain-containing protein 17
Gene Name: TXNDC17

Input Sequence in FASTA format

>Q9BRA2 (123 residues)
MARYEEVSVSGFEEFHRAVEQHNGKTIFAYFTGSKDAGGKSWCPDCVQAEPVVREGLKHI
SEGCVFIYCQVGEKPYWKDPNNDFRKNLKVTAVPTLLKYGTPQKLVESECLQANLVEMLF
SED

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 DeepPotential. 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	Q9BRA2-D1	1-123	123		MARYEEVSVSGFEEFHRAVEQHNGKTIFAYFTGSKDAGGKSWCPDCVQAEPVVREGLKHISEGCVFIYCQVGEKPYWKDPNNDFRKNLKVTAVPTLLKYGTPQKLVESECLQANLVEMLFSED

Top 1 final models from D-I-TASSER

Click to view	Rank^a	Download	Estimated TM-score^b
	1	model1.pdb.gz	0.949

(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 DeepPotential, 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	7xpwA	0.93	1.18	0.562	0.984	model1_7xpwA.pdb.gz
2	1v9wA	0.89	1.76	0.789	1.000	model1_1v9wA.pdb.gz
3	7rzbA	0.66	2.82	0.124	0.870	model1_7rzbA.pdb.gz
4	2vlvB	0.66	2.57	0.248	0.854	model1_2vlvB.pdb.gz
5	1uc7A	0.66	2.83	0.182	0.870	model1_1uc7A.pdb.gz
6	2xbiA	0.66	2.62	0.183	0.846	model1_2xbiA.pdb.gz
7	3fhkA	0.65	2.78	0.108	0.854	model1_3fhkA.pdb.gz
8	1thxA	0.65	2.54	0.165	0.837	model1_1thxA.pdb.gz
9	1tofA	0.65	2.73	0.173	0.846	model1_1tofA.pdb.gz
10	1gh2A	0.65	2.57	0.147	0.829	model1_1gh2A.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:0047134	1.00	protein-disulfide reductase activity

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:

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[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:0065007	0.79	biological regulation
GO:0050794	0.78	regulation of cellular process
GO:0044699	0.65	single-organism process
GO:0009987	0.63	cellular process
GO:0007165	0.63	signal transduction
GO:0033209	0.62	tumor necrosis factor-mediated signaling pathway
GO:0008152	0.54	metabolic process

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:0005829	1.00	cytosol

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	0.105	1cqgA	0.615	2.66	0.149	0.821	1.8.4.10	NA
2	0.101	1dbyA	0.641	2.48	0.158	0.821	1.8.4.10	NA
3	0.076	1t00A	0.638	2.87	0.170	0.862	1.8.1.8	NA
4	0.072	1nswA	0.622	2.63	0.160	0.813	1.8.1.9	NA
5	0.072	1uc7A	0.660	2.83	0.182	0.870	1.8.1.8	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:

Rank	Cscore^LB	PDB Hit	TM-score	RMSD^a	IDEN^a	Cov.	BS-score	Lig. Name	Download Complex	Predicted binding site residues
1	0.09	1cqgA	0.615	2.66	0.149	0.821	0.84	III	complex1.pdb.gz	42,43,45,46,71,72,90,91,92,93,94,105,106
2	0.03	2o8v2	0.637	2.46	0.136	0.813	0.96	III	complex2.pdb.gz	34,42,43,44,45,47,71,72,90,91,92,93,94,106,107
3	0.03	2pvo2	0.627	2.71	0.113	0.837	0.86	III	complex3.pdb.gz	33,34,42,43,44,45,48,72,91,92,93

	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, Qiqige Wuyun, Yang Li, Quancheng Liu, Xiaogen Zhou, Yiheng Zhu, P. Lydia Freddolino, Yang Zhang. Integrating deep learning potentials with I-TASSER for single- and multi-domain protein structure prediction. Submitted. 2023.