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Status: Done started: 2016-Nov-06 22:04:12 UTC
Project Name4cpl75
SequenceEPEWTYPRLSCPGSTFQKALLISPHRFGETKGNSAPLIIREPFIACGPKECKHFALTHYAAQPGGYYNGTREDRNKLRHL ISVKLGKIPTVENSIFHMAAWSGSACHDGREWTYIGVDGPDSNALLKIKYGEAYTDTYHSYAKNILRTQESACNCIGGDC YLMITDGPASGISECRFLKIREGRIIKEIFPTGRVKHTEECTCGFASNKTIECACRDNSYTAKRPFVKLNVETDTAEIRL MCTETYLDTPRPNDGSITGPCESNGDKGSGGIKGGFVHQRMASKIGRWYSRTMSKTKRMGMGLYVKYDGDPWTDSEALAL SGVMVSMEEPGWYSFGFEIKDKKCDVPCIGIEMVHDGGKTTWHSAATAIYCLMGSGQLLWDTVTGVNMTL
Secondary structure

CCCCCCCCCCCCCCCCCCEEECCCCCCCCCCCCCCCEEEECCCCCCCCCCCCCEEEEECCCCCCCCCCCCHHHHCCCCEE EEEECCCCCCCCCCEEEEECCCCCCCCCCCCEEEEEECCCCCCCEEEEEECCCCHHHHHHHHHHHHHHCCCCCCEECCCE EEEEECCCCCCCCCEEEEEEECCCEEEEECCCCCCCCCCCCCCCCCCCCEEEEEECCCCCCCCCCEEEEEECCCCEEEEE EECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHCCCCCCCCCCEEEEEECCCCCCCHHHHHC CCEEEEECCCCEEEEEEEEECCCCCCCEEEEEEEECCCCEEEECHHHEEEECCCCCCEEEEEEEEECCCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2016-Nov-07 10:59 UTC

Provided templates.

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

Cluster #12345678
Cluster density170.7143.8130.094.587.986.273.249.1
Cluster size6764614843352715
Average cluster RMSD0.40.40.50.50.50.40.40.3

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 0.69 0.69 0.61 0.78 0.64 0.74 1.02
2 0.69 0.00 0.69 0.72 0.83 0.62 0.87 0.92
3 0.69 0.69 0.00 0.66 0.64 0.70 0.73 0.90
4 0.61 0.72 0.66 0.00 0.76 0.67 0.76 0.97
5 0.78 0.83 0.64 0.76 0.00 0.81 0.82 0.98
6 0.64 0.62 0.70 0.67 0.81 0.00 0.69 0.92
7 0.74 0.87 0.73 0.76 0.82 0.69 0.00 1.03
8 1.02 0.92 0.90 0.97 0.98 0.92 1.03 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 0.98 0.98 0.99 0.99 0.98 0.98 0.93
2 0.98 1.00 0.98 0.98 0.98 0.99 0.96 0.94
3 0.98 0.98 1.00 0.99 0.98 0.98 0.98 0.95
4 0.99 0.98 0.99 1.00 0.99 0.98 0.98 0.94
5 0.99 0.98 0.98 0.99 1.00 0.97 0.97 0.95
6 0.98 0.99 0.98 0.98 0.97 1.00 0.98 0.95
7 0.98 0.96 0.98 0.98 0.97 0.98 1.00 0.93
8 0.93 0.94 0.95 0.94 0.95 0.95 0.93 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