MetaGO result for job id PF08463

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>93341509/1-82 (82 residues)
SEDPVTGLSPHHMRTLVRLNYAARFGLLSESVSRQSAAAAKGKAILKTMGLFLLFLGTIA
AFFAPVVSSAADKAIYYWVSHG

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	1qdmA	0.58	3.28	0.013	0.927	Download
2	6fkfd	0.56	3.48	0.062	0.915	Download
3	5t4oL	0.55	3.30	0.077	0.866	Download
4	2a7uB	0.54	3.07	0.103	0.842	Download
5	4hhrA	0.54	3.55	0.049	0.890	Download
6	2ww9A2	0.54	3.61	0.037	0.927	Download
7	3afhA	0.54	3.33	0.055	0.890	Download
8	1cvuA2	0.52	3.72	0.073	0.902	Download
9	3mp7A2	0.52	3.45	0.076	0.854	Download
10	1cqeB2	0.52	3.66	0.062	0.866	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:0030234	0.02	enzyme regulator activity
GO:0005102	0.02	receptor 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:1903205	0.02	regulation of hydrogen peroxide-induced cell death
GO:1903202	0.02	negative regulation of oxidative stress-induced cell death
GO:1902533	0.02	positive regulation of intracellular signal transduction
GO:1901564	0.02	organonitrogen compound metabolic process
GO:1901032	0.02	negative regulation of response to reactive oxygen species
GO:0071702	0.02	organic substance transport
GO:0050790	0.02	regulation of catalytic activity
GO:0045055	0.02	regulated exocytosis
GO:0044093	0.02	positive regulation of molecular function
GO:0043408	0.02	regulation of MAPK cascade

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:0005576	0.02	extracellular region
GO:0070062	0.01	extracellular exosome
GO:0043202	0.01	lysosomal lumen
GO:0016021	0.01	integral component of membrane
GO:0005765	0.01	lysosomal membrane
GO:0005764	0.01	lysosome
GO:0005739	0.01	mitochondrion
GO:0005615	0.01	extracellular space

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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