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Status: Done started: 2018-Feb-26 14:22:17 UTC
Project Namev3198
SequenceMMMASKDVVPTAASSENANNNSSIKSRLLARLKGSGGATSPPNSIKITNQDMALGLIGQVPAPKATSVDVPKQQRDRPPR TVAEVQQNLRWTERPQDQNVKTWDELDHTTKQQILDEHAEWFDAGGLGPSTLPTSHERYTHENDEGHQVKWSAREGVDLG ISGLTTVSGPEWNMCPLPPVDQRSTTPATEPTIGDMIEFYEGHIYHYAIYIGQGKTVGVHSPQAAFSITRITIQPISAWW RVCYVPQPKQRLTYDQLKELENEPWPYAAVTNNCFEFCCQVMCLEDTWLQRKLISSGRFYHPTQDWSRDTPEFQQDSKLE MVRDAVLAAINGLVSRPFKDLLGKLKPLNVLNLLSNCDWTFMGVVEMVVLLLELFGIFWNPPDVSNFIASLLPDFHLQ
Secondary structure

CCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHCCCCCCCCCCCCCEECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC CHHHHHHHHCCCCCCCCCCCCCCCCCCHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCEEEEEECCCCCCC CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCEEEEECCEEEEEEEEECCCEEEEECCCCCEEEEEEEEEEECCCCC EEEEECCCCCCCCHHHHHHHCCCCCCCCCCCCCHHHHHHHHCCCCHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCCH HHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHCCCCCHHHHHHHHHHHHHHHCCCCCCCCHHHHHHHHCCCCCCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2018-Feb-27 03:17 UTC

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

Cluster #1234567
Cluster density28.24.54.32.11.40.70.4
Cluster size139784145371010
Average cluster RMSD4.917.29.521.625.914.122.7

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.

#1234567
1 0.00 30.20 34.60 30.00 41.40 43.80 52.50
2 30.20 0.00 31.90 33.70 43.30 41.10 57.40
3 34.60 31.90 0.00 36.10 42.70 42.60 56.50
4 30.00 33.70 36.10 0.00 42.10 46.50 49.90
5 41.40 43.30 42.70 42.10 0.00 34.60 33.00
6 43.80 41.10 42.60 46.50 34.60 0.00 36.90
7 52.50 57.40 56.50 49.90 33.00 36.90 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.

#1234567
1 1.00 0.07 0.06 0.06 0.05 0.06 0.04
2 0.07 1.00 0.07 0.06 0.05 0.07 0.05
3 0.06 0.07 1.00 0.08 0.05 0.07 0.05
4 0.06 0.06 0.08 1.00 0.06 0.07 0.07
5 0.05 0.05 0.05 0.06 1.00 0.06 0.05
6 0.06 0.07 0.07 0.07 0.06 1.00 0.05
7 0.04 0.05 0.05 0.07 0.05 0.05 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