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Status: Done started: 2013-Oct-16 07:57:43 UTC
Project NameAEG74034.1
SequenceMHQSEAMKIFMKSVLLVAAIAGQLLNSSHIAQAAGLTLPPILDPIINPINNLTSPILDPLNNLTTPLLSPITNLTSPILD PLNNLTSAPIVGLNLTTVLGSLNLTAGTPALNLSTILGPLNLTAGTGLNLSNIIGPWNNLTGPLQTILSNFTGPASNLTV ATNVTVTVTLNLPSTMLNLASVFPNGMTIVPLGMTEVSISLRSLQGTNLSTVPVQFMVPVISYLNFPVSGSAGVTLDIAP GTKLAITGLTTPITRLFFGVSWQTFPQLTNVLISKILPGSSQPVPLYNFAVPALM
Secondary structure

CCHHHHHHHHHHHHHHHHHHHHHHCCCHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC CCCCCCCCCEEEECCCEECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHEECCCCCCCCCCCEE EEEEEEEEEECCCCHHHCHHCCCCCCCEEEECCCCEEEEEEECCCCCCCCCCCEEEEEEEEEEECCCCCCCCCEEEECCC CCEEEEECCCCCCHHHEECCCCCCCHHHHHHHHHHCCCCCCCCCCCCCCCCCCCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2013-Oct-16 21:52 UTC

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

Cluster #12345678910
Cluster density18.15.53.12.82.61.41.20.90.80.6
Cluster size126462329471923181712
Average cluster RMSD6.98.47.410.418.414.019.719.020.120.9

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.

#12345678910
1 0.00 8.29 23.70 27.90 27.20 27.40 26.00 27.80 29.10 28.20
2 8.29 0.00 22.40 27.40 26.60 26.40 25.70 27.80 28.60 27.50
3 23.70 22.40 0.00 26.00 24.40 28.00 24.40 28.40 26.50 29.90
4 27.90 27.40 26.00 0.00 20.10 26.90 25.40 26.90 24.70 28.90
5 27.20 26.60 24.40 20.10 0.00 24.90 28.00 25.70 25.70 29.30
6 27.40 26.40 28.00 26.90 24.90 0.00 24.50 28.10 30.40 29.10
7 26.00 25.70 24.40 25.40 28.00 24.50 0.00 29.60 26.50 29.20
8 27.80 27.80 28.40 26.90 25.70 28.10 29.60 0.00 26.90 32.10
9 29.10 28.60 26.50 24.70 25.70 30.40 26.50 26.90 0.00 29.70
10 28.20 27.50 29.90 28.90 29.30 29.10 29.20 32.10 29.70 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.

#12345678910
1 1.00 0.35 0.10 0.10 0.09 0.09 0.09 0.08 0.08 0.08
2 0.35 1.00 0.10 0.09 0.09 0.09 0.10 0.08 0.08 0.08
3 0.10 0.10 1.00 0.11 0.08 0.08 0.10 0.08 0.08 0.08
4 0.10 0.09 0.11 1.00 0.10 0.09 0.09 0.09 0.07 0.07
5 0.09 0.09 0.08 0.10 1.00 0.09 0.07 0.07 0.07 0.07
6 0.09 0.09 0.08 0.09 0.09 1.00 0.08 0.07 0.07 0.08
7 0.09 0.10 0.10 0.09 0.07 0.08 1.00 0.08 0.07 0.08
8 0.08 0.08 0.08 0.09 0.07 0.07 0.08 1.00 0.07 0.08
9 0.08 0.08 0.08 0.07 0.07 0.07 0.07 0.07 1.00 0.07
10 0.08 0.08 0.08 0.07 0.07 0.08 0.08 0.08 0.07 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