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Status: Done started: 2016-Nov-07 09:58:52 UTC
Project Name4cpl85
SequenceEPEWTYPRLSCPGSTFQKALLISPHRFGETKGNSAPLIIREPFIACGPKECKHFALTHYAAQPGGYYNGTREDRNKLRHL ISVKLGKIPTVENSIFHMAAWSGSACHDGREWTYIGVDGPDSNALLKIKYGEAYTDTYHSYAKNILRTQESACNCIGGDC YLMITDGPASGISECRFLKIREGRIIKEIFPTGRVKHTEECTCGFASNKTIECACRDNSYTAKRPFVKLNVETDTAEIRL MCTETYLDTPRPNDGSITGPCESNGDKGSGGIKGGFVHQRMASKIGRWYSRTMSKTERMGMGLYVKYDGDPWADSDALAF SGVMVSMKEPGWYSFGFEIKDKKCDVPCIGIEMVHDGGKETWHSAATAIYCLMGSGQLLWDTVTGVNMAL
Secondary structure

CCCCCCCCCCCCCCCCCCEEECCCCCCCCCCCCCCCEEEECCCCCCCCCCCCCEEEEECCCCCCCCCCCCHHHHCCCCEE EEEECCCCCCCCCCEEEEECCCCCCCCCCCCEEEEEECCCCCCCEEEEEECCCCHHHHHHHHHHHHHHCCCCCCEECCCE EEEEECCCCCCCCCEEEEEEECCCEEEEECCCCCCCCCCCCCCCCCCCCEEEEEECCCCCCCCCCEEEEEECCCCEEEEE EECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHCHHHHCCCCCCCCCCEEEEEECCCCCCCCCCCCC CCEEEEECCCCEEEEEEEEECCCCCCCEEEEEEEECCCCHHHHHHHHEEEECCCCCCEEEEEECCCCCCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2016-Nov-07 22:53 UTC

Provided templates.

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

Cluster #12345678
Cluster density182.1129.5120.593.490.589.886.841.7
Cluster size6561474645404412
Average cluster RMSD0.40.50.40.50.50.40.50.3

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 0.82 0.74 0.83 1.04 0.70 0.80 0.93
2 0.82 0.00 0.73 0.71 1.06 0.68 0.69 0.85
3 0.74 0.73 0.00 0.70 1.08 0.66 0.80 0.92
4 0.83 0.71 0.70 0.00 0.95 0.63 0.71 0.94
5 1.04 1.06 1.08 0.95 0.00 0.98 0.86 1.11
6 0.70 0.68 0.66 0.63 0.98 0.00 0.63 0.88
7 0.80 0.69 0.80 0.71 0.86 0.63 0.00 0.79
8 0.93 0.85 0.92 0.94 1.11 0.88 0.79 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 0.98 0.95 0.95 0.98 0.96 0.93
2 0.96 1.00 0.97 0.97 0.98 0.98 0.98 0.95
3 0.98 0.97 1.00 0.98 0.97 0.98 0.97 0.94
4 0.95 0.97 0.98 1.00 0.98 0.99 0.98 0.92
5 0.95 0.98 0.97 0.98 1.00 0.97 0.98 0.93
6 0.98 0.98 0.98 0.99 0.97 1.00 0.98 0.95
7 0.96 0.98 0.97 0.98 0.98 0.98 1.00 0.96
8 0.93 0.95 0.94 0.92 0.93 0.95 0.96 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