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Status: Done started: 2020-Jan-25 00:02:28 UTC
Project Name2e5t_r9
SequenceIDVLRAKAAKERAERRLQSQQDDIDFKRAELALKRAMNRLSVAEMK
Secondary structure

CCHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2020-Jan-25 07:08 UTC

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

Cluster #123
Cluster density62.634.113.4
Cluster size17012763
Average cluster RMSD2.73.74.7

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.

#123
1 0.00 15.90 13.60
2 15.90 0.00 5.62
3 13.60 5.62 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.

#123
1 1.00 0.51 0.50
2 0.51 1.00 0.56
3 0.50 0.56 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