D-I-TASSER Q9UKV8-D3

D-I-TASSER results for Q9UKV8-D3

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

Input Sequence in FASTA format

>Q9UKV8 (126 residues)
YKAQPVIEFVCEVLDFKSIEEQQKPLTDSQRVKFTKEIKGLKVEITHCGQMKRKYRVCNV
TRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQEQKHTYLPLEVC
NIVAGQ

Predicted Secondary Structure

Sequence	20 40 60 80 100 120 \| \| \| \| \| \| YKAQPVIEFVCEVLDFKSIEEQQKPLTDSQRVKFTKEIKGLKVEITHCGQMKRKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQEQKHTYLPLEVCNIVAGQ
Prediction	CCCCCHHHHHHHHHCCCCCHHHCCCCCHHHHHHHHHHHCCSSSSSCCCCCCCCSSSSSCCCCCCCCCSSSSSCCCCCCCSSSSHHHHHHHHHCCCCCCCCCCSSSSCCCCCCCSSCCSSSSSCCCC
Confidence	996569999999978875111114899999999999836859998479999854999604578873359984279996237719999999959857899998698379999617440326857999
	H:Helix; S:Strand; C:Coil

Predicted Solvent Accessibility

Sequence	20 40 60 80 100 120 \| \| \| \| \| \| YKAQPVIEFVCEVLDFKSIEEQQKPLTDSQRVKFTKEIKGLKVEITHCGQMKRKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQEQKHTYLPLEVCNIVAGQ
Prediction	857230040024117464264445414564144034204513030323775524120342365435523041547756534222341146427250523510002034773410000010402778
	Values range from 0 (buried residue) to 8 (highly exposed residue)

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

Contact Map

Distance Map

Hydrogen bond networks

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

                   |                   |                   |                   |                   |                   |

SS
Seq

CCCCCHHHHHHHHHCCCCCHHHCCCCCHHHHHHHHHHHCCSSSSSCCCCCCCCSSSSSCCCCCCCCCSSSSSCCCCCCCSSSSHHHHHHHHHCCCCCCCCCCSSSSCCCCCCCSSCCSSSSSCCCC
YKAQPVIEFVCEVLDFKSIEEQQKPLTDSQRVKFTKEIKGLKVEITHCGQMKRKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQEQKHTYLPLEVCNIVAGQ

4ei1A

0.97

0.90

25.13

1.33

DEthreader

YKAQPVIEFVCEVLDFKSIE--QKPLTDSQRVKFTKEIKGLKVEIT------RKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQV-GQ-EHTYLPLEVCNIVAGQ

4ei1A1

0.99

0.87

24.45

3.15

SPARKS-K

---QPVIEFVCEVLDFKSIE--QKPLTDSQRVKFTKEIKGLKVEIT------RKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQEH--TYLPLEVCNIVA--

4ei1A

0.98

0.90

25.35

1.45

MapAlign

YKAQPVIEFVCEVLDFKSI--EQKPLTDSQRVKFTKEIKGLKVEIT------RKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQ--EHTYLPLEVCNIVAGQ

4ei1A

0.99

0.91

25.56

1.46

CEthreader

YKAQPVIEFVCEVLDFKSIE--QKPLTDSQRVKFTKEIKGLKVEIT------RKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVGQ--EHTYLPLEVCNIVAGQ

4ei1A1

0.98

0.87

24.24

2.61

MUSTER

---QPVIEFVCEVLDFKSIEQ--KPLTDSQRVKFTKEIKGLKVEIT------RKYRVCNVTRRPASHQTFPLQQESGQTVECTVAQYFKDRHKLVLRYPHLPCLQVG--QEHTYLPLEVCNIVA--

1r4kA

0.83

23.29

3.10

HHsearch

YKAQPVIDFMCEVLDIRDINEQRKPLTDSQRVKFTKEIKGLKIEITHCGQMRRKYRVCNVTRRPAQMQSFPLQLENGQTVECTVAKYFLDKYRMKLRYPHLPCLQVGQEHKHTYLPLEVCNIVAGQ

1r4kA

0.83

23.29

2.03

FFAS-3D

YKAQPVIDFMCEVLDIRDINEQRKPLTDSQRVKFTKEIKGLKIEITHCGQMRRKYRVCNVTRRPAQMQSFPLQLENGQTVECTVAKYFLDKYRMKLRYPHLPCLQVGQEHKHTYLPLEVCNIVAGQ

1r4kA

0.74

0.73

20.70

1.55

EigenThreader

YKAQPVIDFMCEVLDIRDINEQRKPLTDSQRVKFTKEIKGLKIEITHCGQMRRKYRVCNVTRRPAQMQSFPLENG--QTVECTVAKYFLDKYRMKLRYPHLPCLQVGQEHKHTYLPLVCNIVAGQR

4kxtA

0.88

24.79

2.47

CNFpred

YKAQPVIEFMCEVLDIRNIDEQPKPLTDSQRVRFTKEIKGLKVEVTHCGQMKRKYRVCNVTRRPASHQTFPLQLESGQTVECTVAQYFKQKYNLQLKYPHLPCLQVGQEQKHTYLPLEVCNIVAGQ

1r4kA

0.79

0.78

21.98

1.33

DEthreader

-KAQPVIDFMCEVLDIRDINEQRKPLTDSQRVKFTKEIKGLKIEITHCGQMRRKYRVCNVTRRPAQMQSFPLQLNGQTV-ECTVAKYFLDKYRMKLRYPHLPCLQVGQEHKHTYLPLEVCNIVAGQ

(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

Click to view	Rank^a	Download	Estimated TM-score^b
	1	model1.pdb.gz	0.8844

(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	4ei1A	0.88	0.91	0.983	0.921	model1_4ei1A.pdb.gz
2	1r4kA	0.87	2.16	0.817	1.000	model1_1r4kA.pdb.gz
3	1t2rA	0.77	2.15	0.331	0.929	model1_1t2rA.pdb.gz
4	3o3iX	0.71	2.34	0.178	0.841	model1_3o3iX.pdb.gz
5	4f1nA	0.70	2.55	0.220	0.857	model1_4f1nA.pdb.gz
6	5guhA	0.69	2.45	0.223	0.818	model1_5guhA.pdb.gz
7	2fflA	0.65	1.99	0.191	0.746	model1_2fflA.pdb.gz
8	3o7xA	0.62	1.68	0.152	0.706	model1_3o7xA.pdb.gz
9	3avrA2	0.37	4.80	0.059	0.667	model1_3avrA2.pdb.gz
10	3iyhA	0.35	4.96	0.040	0.635	model1_3iyhA.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:1901363	0.97	heterocyclic compound binding
GO:0097159	0.97	organic cyclic compound binding
GO:0003676	0.96	nucleic acid binding
GO:0003723	0.95	RNA binding
GO:0035198	0.62	miRNA binding
GO:0003824	0.53	catalytic 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:

[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:0009987	0.96	cellular process
GO:0065007	0.88	biological regulation
GO:0044237	0.88	cellular metabolic process
GO:0071704	0.87	organic substance metabolic process
GO:0050789	0.87	regulation of biological process
GO:0044260	0.86	cellular macromolecule metabolic process
GO:0044238	0.86	primary metabolic process
GO:0034641	0.85	cellular nitrogen compound metabolic process
GO:0090304	0.84	nucleic acid metabolic process
GO:0016070	0.83	RNA metabolic process
GO:0060255	0.82	regulation of macromolecule metabolic process
GO:0048519	0.81	negative regulation of biological process
GO:0010468	0.81	regulation of gene expression
GO:0050794	0.80	regulation of cellular process
GO:0044699	0.80	single-organism process
GO:0010605	0.80	negative regulation of macromolecule metabolic process
GO:0010629	0.79	negative regulation of gene expression
GO:0010608	0.77	posttranscriptional regulation of gene expression
GO:0080090	0.76	regulation of primary metabolic process
GO:0031323	0.76	regulation of cellular metabolic process
GO:0051171	0.75	regulation of nitrogen compound metabolic process
GO:0031326	0.75	regulation of cellular biosynthetic process
GO:2000112	0.74	regulation of cellular macromolecule biosynthetic process
GO:0048523	0.74	negative regulation of cellular process
GO:0031324	0.73	negative regulation of cellular metabolic process
GO:2000113	0.72	negative regulation of cellular macromolecule biosynthetic process
GO:0051172	0.72	negative regulation of nitrogen compound metabolic process
GO:0032268	0.71	regulation of cellular protein metabolic process
GO:0016071	0.71	mRNA metabolic process
GO:0032269	0.69	negative regulation of cellular protein metabolic process
GO:0006417	0.69	regulation of translation
GO:0017148	0.68	negative regulation of translation
GO:0006396	0.66	RNA processing
GO:0044763	0.62	single-organism cellular process
GO:0035278	0.55	miRNA mediated inhibition of translation
GO:0016458	0.53	gene silencing
GO:0031047	0.51	gene silencing by RNA

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:0032991	0.93	macromolecular complex
GO:0030529	0.89	intracellular ribonucleoprotein complex
GO:0043226	0.76	organelle
GO:0043229	0.75	intracellular organelle
GO:0044444	0.74	cytoplasmic part
GO:0005737	0.71	cytoplasm
GO:0043231	0.59	intracellular membrane-bounded organelle
GO:0035068	0.58	micro-ribonucleoprotein complex
GO:0070578	0.54	RISC-loading complex
GO:0005634	0.52	nucleus

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	2qzwA	0.421	5.06	0.052	0.778	3.4.23.24	NA
2	0.060	1ibqA	0.432	5.15	0.055	0.778	3.4.23.18	NA
3	0.060	1yqwR	0.406	4.38	0.092	0.706	1.12.2.1	NA
4	0.060	1wnlA	0.430	3.67	0.095	0.603	6.3.4.15	NA
5	0.060	11asA	0.444	4.38	0.045	0.738	6.3.1.1	108

	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	0.60	1si2A	0.888	1.41	0.874	0.944	1.81	RQA	complex1.pdb.gz	42,47,51,53,56,70,72,87,88,92,108,111,112,113,114,115,125
2	0.08	2xfmA	0.658	2.74	0.151	0.825	0.80	UUU	complex2.pdb.gz	42,47,54,55,56,72,113,114,115
3	0.05	3dlhB	0.572	2.45	0.089	0.706	0.54	QNA	complex3.pdb.gz	46,48,54,88,93,113,114
4	0.01	3ho1A	0.329	5.02	0.036	0.627	0.78	QNA	complex4.pdb.gz	45,47,53,87,88,111,113,114

	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.