MetaGO result for job id PF12314

User Input

>37770711/1-66 (66 residues)
TTKKTVSDMKTFQRYLSSISKGDEEILYLPADVLDHLLAKFFKDIRKMNGDEYEPDRRYR
VSSEAS

Download query sequence and structure

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	2rfoA1	0.55	2.63	0.058	0.788	Download
2	5jnqA	0.54	3.41	0.033	0.833	Download
3	5ijnC	0.54	2.87	0.019	0.818	Download
4	2rjsB2	0.53	3.45	0.063	0.879	Download
5	6barA1	0.53	2.64	0.048	0.788	Download
6	5uv0A	0.52	2.85	0.031	0.773	Download
7	4fjqA	0.52	3.07	0.031	0.788	Download
8	3i39X	0.52	3.97	0.030	0.909	Download
9	3p5pA	0.52	3.74	0.000	0.879	Download
10	1t11A	0.52	3.38	0.082	0.879	Download

(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:0000981	0.12	RNA polymerase II transcription factor activity, sequence-specific DNA binding
GO:0003677	0.10	DNA binding
GO:0016840	0.03	carbon-nitrogen lyase activity
GO:0003682	0.01	chromatin 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:

[0.13,0.5)

[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:0016043	0.42	cellular component organization
GO:0044699	0.29	single-organism process
GO:0006996	0.11	organelle organization
GO:0050794	0.10	regulation of cellular process
GO:1901362	0.07	organic cyclic compound biosynthetic process
GO:0044283	0.07	small molecule biosynthetic process
GO:0044249	0.07	cellular biosynthetic process
GO:0044763	0.06	single-organism cellular process
GO:0006725	0.06	cellular aromatic compound metabolic process
GO:0022604	0.04	regulation of cell morphogenesis

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:

[0.08,0.5)

[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:0005654	0.02	nucleoplasm
GO:0035012	0.01	polytene chromosome, telomeric region
GO:0031965	0.01	nuclear membrane
GO:0005737	0.01	cytoplasm
GO:0005705	0.01	polytene chromosome interband
GO:0005643	0.01	nuclear pore
GO:0000792	0.01	heterochromatin
GO:0000791	0.01	euchromatin

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:

[0.14,0.5)

[0.5,0.6)

[0.6,0.7)

[0.7,0.8)

[0.8,0.9)

[0.9,1.0]

Reference:

Chengxin Zhang, Peter L Freddolino, and Yang Zhang. (2018) MetaGO: A Structure and Protein-Protein Interaction Network Based Pipeline for Automated Protein Function Annotations. Journal of Molecular Biology.

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