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Status: Done started: 2014-Mar-29 12:38:42 UTC
Project Nameconver_min
SequenceMCERAARLCRAGAHRLLREPPQQGRALGGLLRWVGARMGEPRESLAPAAPADPGPASPRGGTAVILDIFRRADKNDDGKL SLEEFQLFFADGVLNEKELEDLFHTIDSDNTNHVDTKELCDYFVDHMGDYEDVLASLETLNHSVLKAMGYTKKVYEGGSN VDQFVTRFLLKETANQIQSLLSSVESAVEAIEEQTSQLRQNHIKPSHSAAQTWCGSPTPASAPNHKLMAMEQGKTLPSAT EDAKEEGLEAQISRLAELIGRLESKAL
Secondary structure

CHHHHHHHHHHHHHHHCCCCCCCCCCCHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHCCCCCCCCC CHHHHHHHHHCCCCCHHHHHHHHHHHCCCCCCCCCHHHHHHHHHHHCCCHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCC CCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC CCCCHHCHHHHHHHHHHHHHHHHHCCC

Simulation (CABS) temperature2.5 - 1.0
Estimated finish time2014-Mar-30 01:33 UTC

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

Cluster #12345678
Cluster density48.747.646.036.134.630.319.87.5
Cluster size7168405253362911
Average cluster RMSD1.51.40.91.41.51.21.51.5

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 6.66 2.78 2.53 6.31 6.62 2.65 5.07
2 6.66 0.00 6.52 6.90 4.77 4.49 6.41 7.79
3 2.78 6.52 0.00 2.14 6.47 6.78 1.83 4.23
4 2.53 6.90 2.14 0.00 6.54 6.91 2.10 4.80
5 6.31 4.77 6.47 6.54 0.00 2.35 6.29 7.41
6 6.62 4.49 6.78 6.91 2.35 0.00 6.64 7.45
7 2.65 6.41 1.83 2.10 6.29 6.64 0.00 4.53
8 5.07 7.79 4.23 4.80 7.41 7.45 4.53 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 0.73 0.83 0.86 0.73 0.74 0.84 0.76
2 0.73 1.00 0.75 0.73 0.78 0.78 0.75 0.73
3 0.83 0.75 1.00 0.85 0.76 0.76 0.88 0.77
4 0.86 0.73 0.85 1.00 0.76 0.77 0.87 0.78
5 0.73 0.78 0.76 0.76 1.00 0.87 0.77 0.73
6 0.74 0.78 0.76 0.77 0.87 1.00 0.77 0.75
7 0.84 0.75 0.88 0.87 0.77 0.77 1.00 0.79
8 0.76 0.73 0.77 0.78 0.73 0.75 0.79 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