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Status: Done started: 2020-Mar-30 04:17:54 UTC
Project NameAVP0394
SequenceKKKKVVAETYVLV
Secondary structure

CCEEEEEEEEEEC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2020-Mar-30 08:45 UTC

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

Cluster #1234
Cluster density69.956.436.130.8
Cluster size1141097265
Average cluster RMSD1.61.92.02.1

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.

#1234
1 0.00 2.15 9.72 2.86
2 2.15 0.00 8.89 2.15
3 9.72 8.89 0.00 8.56
4 2.86 2.15 8.56 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.

#1234
1 1.00 0.73 0.56 0.73
2 0.73 1.00 0.52 0.77
3 0.56 0.52 1.00 0.50
4 0.73 0.77 0.50 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.


 

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