D-I-TASSER results for P51946

Summary of the Protein

Uniprot ID: P51946


Protein Name: Cyclin-H


Gene Name: CCNH

Input Sequence in FASTA format

>P51946 (323 residues)
MYHNSSQKRHWTFSSEEQLARLRADANRKFRCKAVANGKVLPNDPVFLEPHEEMTLCKYY
EKRLLEFCSVFKPAMPRSVVGTACMYFKRFYLNNSVMEYHPRIIMLTCAFLACKVDEFNV
SSPQFVGNLRESPLGQEKALEQILEYELLLIQQLNFHLIVHNPYRPFEGFLIDLKTRYPI
LENPEILRKTADDFLNRIALTDAYLLYTPSQIALTAILSSASRAGITMESYLSESLMLKE
NRTCLSQLLDIMKSMRNLVKKYEPPRSEEVAVLKQKLERCHSAELALNVITKKRKGYEDD
DYVSKKSKHEEEEWTDDDLVESL

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

D-I-TASSER simulation is guided by the consensus contact map (left figure) and distance map (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.

Information of Domain

No. of Domain	Domain	Domain Boundary	Length of Domain	Sequence
1	P51946-D1	1-323	323	MYHNSSQKRHWTFSSEEQLARLRADANRKFRCKAVANGKVLPNDPVFLEPHEEMTLCKYYEKRLLEFCSVFKPAMPRSVVGTACMYFKRFYLNNSVMEYHPRIIMLTCAFLACKVDEFNVSSPQFVGNLRESPLGQEKALEQILEYELLLIQQLNFHLIVHNPYRPFEGFLIDLKTRYPILENPEILRKTADDFLNRIALTDAYLLYTPSQIALTAILSSASRAGITMESYLSESLMLKENRTCLSQLLDIMKSMRNLVKKYEPPRSEEVAVLKQKLERCHSAELALNVITKKRKGYEDDDYVSKKSKHEEEEWTDDDLVESL

Top 1 final models from D-I-TASSER

Rank^a	Estimated TM-score^b
1	0.827


(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.
1	1jkwA	0.85	0.67	0.996	0.858
2	6z3uA	0.83	2.44	0.270	0.907
3	7kpvB	0.71	2.71	0.213	0.799
4	6y0aB	0.68	2.49	0.245	0.752
5	2w2hA	0.63	2.79	0.174	0.715
6	2i53A	0.62	2.94	0.174	0.709
7	3ddpD	0.58	3.07	0.138	0.684
8	2w96A	0.58	3.33	0.185	0.687
9	1zp2A1	0.30	2.92	0.205	0.338
10	3mdyA2	0.30	4.85	0.093	0.421



(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:0016538	0.97	cyclin-dependent protein serine/threonine kinase regulator activity






(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:

Biological Process (BP)


GO term	Cscore^GO	Name
GO:0080090	0.98	regulation of primary metabolic process
GO:0060255	0.98	regulation of macromolecule metabolic process
GO:0031323	0.98	regulation of cellular metabolic process
GO:0048518	0.97	positive regulation of biological process
GO:0000079	0.97	regulation of cyclin-dependent protein serine/threonine kinase activity
GO:1901409	0.96	positive regulation of phosphorylation of RNA polymerase II C-terminal domain
GO:0045944	0.96	positive regulation of transcription from RNA polymerase II promoter
GO:0045737	0.96	positive regulation of cyclin-dependent protein serine/threonine kinase activity
GO:0009987	0.60	cellular process






(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:

Cellular Component (CC)


GO term	Cscore^GO	Name
GO:0044424	1.00	intracellular part
GO:0032991	1.00	macromolecular complex
GO:1902554	0.99	serine/threonine protein kinase complex
GO:0043226	0.96	organelle
GO:0000307	0.96	cyclin-dependent protein kinase holoenzyme complex
GO:0005634	0.95	nucleus






(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:

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	0.079	1xo2A	0.556	3.66	0.108	0.690	2.7.11.22	NA
2	0.060	1ileA	0.370	6.56	0.065	0.641	6.1.1.5	NA
3	0.060	2g36A	0.362	6.67	0.051	0.619	6.1.1.2	NA
4	0.060	1y2mB	0.370	5.77	0.051	0.570	4.3.1.24	NA
5	0.060	1yi8A	0.364	6.45	0.038	0.607	6.1.1.2	NA



(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	Predicted binding site residues
1	0.01	1g3n1	0.564	3.50	0.107	0.687	0.21	III	114,115,147,148,151,152,156,157,158,160
2	0.01	3s29B	0.410	6.49	0.062	0.684	0.13	UDP	72,80,84
3	0.01	1qhaA	0.350	6.55	0.033	0.604	0.18	GLC	160,161,204
4	0.01	1bg3A	0.353	6.70	0.036	0.625	0.24	G6P	82,83,163,202
5	0.01	3s27B	0.410	6.47	0.036	0.687	0.17	FRU	71,79,80,117



(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.

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.