D-I-TASSER W6CW81

D-I-TASSER results for W6CW81

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

Summary of the Protein

Uniprot ID: W6CW81
Protein Name: Pyrin domain-containing protein 5
Gene Name: PYDC5

Input Sequence in FASTA format

>W6CW81 (113 residues)
MESKYKEILLLTSLDNITDEELDRFKCFLPDEFNIATGKLHTLNSTSSQLDLKRWHGVCS
EEDRIFQKLNYMLVAKCLREEQETGICGSPSSARSVSQSRLGLSFHGISGNAC

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	W6CW81-D1	1-113	113		MESKYKEILLLTSLDNITDEELDRFKCFLPDEFNIATGKLHTLNSTSSQLDLKRWHGVCSEEDRIFQKLNYMLVAKCLREEQETGICGSPSSARSVSQSRLGLSFHGISGNAC

Top 1 final models from D-I-TASSER

Click to view	Rank^a	Download	Estimated TM-score^b
	1	model1.pdb.gz	0.6832

(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	4o7qA	0.74	1.37	0.511	0.796	model1_4o7qA.pdb.gz
2	6ncvA	0.67	1.43	0.214	0.743	model1_6ncvA.pdb.gz
3	2a5yB	0.65	3.40	0.099	0.920	model1_2a5yB.pdb.gz
4	3qf2A	0.64	1.64	0.160	0.717	model1_3qf2A.pdb.gz
5	2mpcA	0.64	1.48	0.160	0.717	model1_2mpcA.pdb.gz
6	2kn6A	0.64	2.02	0.145	0.743	model1_2kn6A.pdb.gz
7	2km6A	0.63	2.30	0.184	0.770	model1_2km6A.pdb.gz
8	2hm2Q	0.62	1.62	0.225	0.708	model1_2hm2Q.pdb.gz
9	2do9A	0.62	2.05	0.140	0.726	model1_2do9A.pdb.gz
10	4ewiA	0.60	2.03	0.195	0.690	model1_4ewiA.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	0.81	heterocyclic compound binding
GO:0097159	0.81	organic cyclic compound binding
GO:0003676	0.78	nucleic acid binding
GO:0003677	0.71	DNA binding
GO:0042802	0.69	identical protein binding
GO:0003690	0.69	double-stranded DNA 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:0065007	0.95	biological regulation
GO:0050789	0.95	regulation of biological process
GO:0050794	0.92	regulation of cellular process
GO:0048522	0.89	positive regulation of cellular process
GO:0048583	0.86	regulation of response to stimulus
GO:0080090	0.84	regulation of primary metabolic process
GO:0060255	0.84	regulation of macromolecule metabolic process
GO:0051239	0.84	regulation of multicellular organismal process
GO:0031323	0.84	regulation of cellular metabolic process
GO:0050896	0.83	response to stimulus
GO:0001817	0.83	regulation of cytokine production
GO:0031347	0.82	regulation of defense response
GO:0065009	0.81	regulation of molecular function
GO:0032268	0.81	regulation of cellular protein metabolic process
GO:0009987	0.81	cellular process
GO:2000116	0.80	regulation of cysteine-type endopeptidase activity
GO:0051240	0.80	positive regulation of multicellular organismal process
GO:0051046	0.80	regulation of secretion
GO:0044699	0.80	single-organism process
GO:0032652	0.80	regulation of interleukin-1 production
GO:0032101	0.80	regulation of response to external stimulus
GO:0010604	0.80	positive regulation of macromolecule metabolic process
GO:0050707	0.79	regulation of cytokine secretion
GO:0044093	0.79	positive regulation of molecular function
GO:0032651	0.79	regulation of interleukin-1 beta production
GO:0031325	0.79	positive regulation of cellular metabolic process
GO:0001819	0.79	positive regulation of cytokine production
GO:2001056	0.78	positive regulation of cysteine-type endopeptidase activity
GO:0051222	0.78	positive regulation of protein transport
GO:0002682	0.78	regulation of immune system process
GO:0050715	0.77	positive regulation of cytokine secretion
GO:0050704	0.77	regulation of interleukin-1 secretion
GO:0048519	0.77	negative regulation of biological process
GO:0042221	0.77	response to chemical
GO:0050718	0.76	positive regulation of interleukin-1 beta secretion
GO:0006355	0.76	regulation of transcription, DNA-templated
GO:0051716	0.75	cellular response to stimulus
GO:0051128	0.75	regulation of cellular component organization
GO:0048584	0.75	positive regulation of response to stimulus
GO:0002684	0.75	positive regulation of immune system process
GO:0050776	0.74	regulation of immune response
GO:0043254	0.74	regulation of protein complex assembly
GO:0002376	0.74	immune system process
GO:0070887	0.73	cellular response to chemical stimulus
GO:0050778	0.73	positive regulation of immune response
GO:0044092	0.73	negative regulation of molecular function
GO:0007165	0.73	signal transduction
GO:0032088	0.72	negative regulation of NF-kappaB transcription factor activity
GO:0031334	0.72	positive regulation of protein complex assembly
GO:0002697	0.72	regulation of immune effector process
GO:0050691	0.71	regulation of defense response to virus by host
GO:0044763	0.71	single-organism cellular process
GO:0051092	0.70	positive regulation of NF-kappaB transcription factor activity
GO:0045088	0.70	regulation of innate immune response
GO:0042493	0.70	response to drug
GO:0032459	0.70	regulation of protein oligomerization
GO:0031349	0.70	positive regulation of defense response
GO:0007166	0.70	cell surface receptor signaling pathway
GO:0002253	0.70	activation of immune response
GO:0033209	0.69	tumor necrosis factor-mediated signaling pathway
GO:0002218	0.69	activation of innate immune response
GO:0008219	0.65	cell death
GO:0006810	0.64	transport
GO:0012501	0.63	programmed cell death
GO:0050701	0.61	interleukin-1 secretion
GO:0002230	0.61	positive regulation of defense response to virus by host
GO:0070269	0.60	pyroptosis
GO:0050702	0.60	interleukin-1 beta secretion
GO:0035690	0.60	cellular response to drug
GO:0032461	0.60	positive regulation of protein oligomerization
GO:0010033	0.50	response to organic substance

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:0005737	0.97	cytoplasm
GO:0044444	0.84	cytoplasmic part
GO:0043234	0.79	protein complex
GO:0005829	0.79	cytosol
GO:0044445	0.75	cytosolic part
GO:0061702	0.73	inflammasome complex
GO:0043227	0.71	membrane-bounded organelle
GO:0097169	0.68	AIM2 inflammasome complex
GO:0043231	0.64	intracellular membrane-bounded organelle
GO:0005634	0.63	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	1fr1A	0.405	4.16	0.046	0.681	3.5.2.6	NA
2	0.060	3lezA	0.501	4.57	0.115	0.911	3.5.2.6	NA
3	0.060	1alqA	0.475	4.47	0.069	0.850	3.5.2.6	NA
4	0.060	2zc7A	0.491	4.57	0.076	0.911	3.5.2.6	NA
5	0.060	2pa6B	0.479	4.10	0.065	0.788	4.2.1.11	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	0.01	2y4aD	0.512	4.54	0.092	0.920	0.30	UUU	complex1.pdb.gz	26,48,49
2	0.01	1d2z1	0.366	4.13	0.049	0.611	0.21	III	complex2.pdb.gz	58,59,60,63,105
3	0.01	1xg70	0.512	3.59	0.043	0.752	0.19	III	complex3.pdb.gz	12,44,46,47,50,54,98

	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.