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Status: Done started: 2017-Nov-11 10:20:31 UTC
Project Namenb102
SequenceEREWTYPRLSCPGSTFQKALLISPHRFGETKGNSAPLIIREPFIACGPTECKHFALTHYAAQPGGYYNGTREDRNKLRHL ISVKLGKIPTVENSIFHMAAWSGSACHDGKEWTYVGVDGPDSNALLKIKYGEAYTDTYHSYAKNILRTQESACNCIGGDC YLMITDGPASGISECRFLKIREGRIIKEIFPTGRVKHTEECTCGFASNKTIECACRDNSYTAKRPFVKLNVETDTAEIRL MCTETYLDTPRPNDGSITGPCESDGDKGSGGIKGGFVHQRMASKIGRWYSRTMSKNKRMGMGLYVKYDGDPWTDSEALAL SGVMVSMEEPGWYSFGFEIKDKKCDVPCIGIEMVHDGG
Secondary structure

CCCCCCCCCCCCCCCCCCEEECCCCCCCCCCCCCCCEEEECCCCCCCCCCCCCEEEEECCCCCCCCCCCCHHHHCCCCEE EEEECCCCCCCCCCEEEEECCCCCCCCCCCCEEEEEECCCCCCCEEEEEECCCCHHHHHHHHHHHHHHCCCCCCEECCCE EEEEECCCCCCCCCEEEEEEECCCEEEEECCCCCCCCCCCCCCCCCCCCEEEEEECCCCCCCCCCEEEEEECCCCEEEEE EECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHCHHHHCCCCCCCCCEEEEEEECCCCCCCHHHHHH CCEEEEECCCCEEEEEEEEECCCCCCCEEEEEEEECCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2017-Nov-11 23:15 UTC

Provided templates.

Time evolution of structural features: CABS energy, End-to-end distance and Radius of gyration.

Cluster #12345678
Cluster density228.2173.8136.2129.5108.994.192.852.8
Cluster size7649515737422820
Average cluster RMSD0.30.30.40.40.30.40.30.4

Clustering of protein models is the task of separating a set of protein models (here a protein dynamics trajectory) into groups (called clusters). The clustering is done in such a way that models are more similar in the same group to each other (here in the sense of RMSD measure), than those in other groups (clusters). CABSfold utilizes classical K-means clustering method.
After clustering is done, each cluster representative is chosen (always the model which average dissimilarity to all models in a cluster is minimal). Predicted protein models, presented in the Predicted structures tab, are each cluster representatives (the clusters and the corresponding models are marked by the same numbers, e.g. Model 1 represents Cluster 1).
The clusters are numbered/ranked according to cluster density values, from the most dense (numbered as a first) to the least dense one.

#12345678
1 0.00 0.80 0.83 0.95 0.95 0.93 0.85 0.78
2 0.80 0.00 0.71 0.79 0.86 0.86 0.84 0.86
3 0.83 0.71 0.00 0.72 0.92 0.92 0.85 0.93
4 0.95 0.79 0.72 0.00 0.82 0.86 0.87 0.88
5 0.95 0.86 0.92 0.82 0.00 1.10 0.91 1.00
6 0.93 0.86 0.92 0.86 1.10 0.00 1.04 0.88
7 0.85 0.84 0.85 0.87 0.91 1.04 0.00 0.97
8 0.78 0.86 0.93 0.88 1.00 0.88 0.97 0.00

The table contains RMSD values (calculated on the Cα atoms) between the predicted models.
Read more about the root-mean-square deviation (RMSD) measure.

#12345678
1 1.00 0.96 0.95 0.94 0.96 0.93 0.97 0.96
2 0.96 1.00 0.98 0.97 0.97 0.96 0.96 0.95
3 0.95 0.98 1.00 0.97 0.94 0.94 0.96 0.95
4 0.94 0.97 0.97 1.00 0.96 0.96 0.95 0.95
5 0.96 0.97 0.94 0.96 1.00 0.94 0.95 0.95
6 0.93 0.96 0.94 0.96 0.94 1.00 0.94 0.96
7 0.97 0.96 0.96 0.95 0.95 0.94 1.00 0.97
8 0.96 0.95 0.95 0.95 0.95 0.96 0.97 1.00

The table contains GDT_TS values (calculated on the Cα atoms) between the predicted models.
Read more about the global distance test (GDT, also written as GDT_TS to represent "total score") measure.


 

© Laboratory of Theory of Biopolymers 2013