Download models Download trajectory View trajectory
Status: Done started: 2014-Dec-22 18:41:36 UTC
Project Nameseq16
SequenceADSQVVDFYQNLGFEADPEGIKGMFWYPK
Secondary structure

CCCHHHHHHHHCCCEECCCCCEEEEEECC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2014-Dec-23 00:08 UTC

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

Cluster #12345678910
Cluster density27.313.711.410.79.78.04.44.31.71.5
Cluster size934253394834201777
Average cluster RMSD3.43.14.63.64.94.24.64.04.04.7

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 4.14 5.95 7.17 7.55 6.19 8.10 6.71 11.10 11.30
2 4.14 0.00 5.21 5.71 7.92 4.38 7.55 5.50 10.70 10.70
3 5.95 5.21 0.00 4.25 7.31 5.59 4.29 6.92 12.20 11.30
4 7.17 5.71 4.25 0.00 6.44 4.94 5.55 6.75 12.70 11.30
5 7.55 7.92 7.31 6.44 0.00 5.85 7.60 7.99 12.80 11.10
6 6.19 4.38 5.59 4.94 5.85 0.00 6.97 5.74 11.20 9.95
7 8.10 7.55 4.29 5.55 7.60 6.97 0.00 6.78 10.80 9.22
8 6.71 5.50 6.92 6.75 7.99 5.74 6.78 0.00 7.24 7.46
9 11.10 10.70 12.20 12.70 12.80 11.20 10.80 7.24 0.00 5.16
10 11.30 10.70 11.30 11.30 11.10 9.95 9.22 7.46 5.16 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 0.67 0.49 0.47 0.44 0.49 0.46 0.47 0.43 0.46
2 0.67 1.00 0.55 0.53 0.47 0.58 0.47 0.53 0.49 0.46
3 0.49 0.55 1.00 0.64 0.51 0.52 0.64 0.48 0.44 0.47
4 0.47 0.53 0.64 1.00 0.47 0.57 0.55 0.52 0.47 0.48
5 0.44 0.47 0.51 0.47 1.00 0.48 0.47 0.47 0.43 0.49
6 0.49 0.58 0.52 0.57 0.48 1.00 0.49 0.56 0.55 0.55
7 0.46 0.47 0.64 0.55 0.47 0.49 1.00 0.47 0.47 0.45
8 0.47 0.53 0.48 0.52 0.47 0.56 0.47 1.00 0.53 0.58
9 0.43 0.49 0.44 0.47 0.43 0.55 0.47 0.53 1.00 0.55
10 0.46 0.46 0.47 0.48 0.49 0.55 0.45 0.58 0.55 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