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Status: Done started: 2015-Nov-12 16:49:51 UTC
Project Namesbicolor
SequenceMAAQEEKTATAVTTEEPAPAAEPQPKPAAAARRAGPSASANPFDFSTMMNLLNDPSIKEMAEQIAKDPAFTEMAEQLQKT VVSPRQRQQQQAASAAAAAQLDPQKYVATMQQLMQNPQFVAMAERLGSALMQDPAVSTMLGGLTNPAHKEQLEARVARMK DDPDLKPILDEIESGGPAAMMKYWNDPEALQKFGRAMGVGGGPSGEAGGAEHAEAEDDAGEEGEYEDESIVHHTASIGDV EGLKKALEDGADKDEEDSEGRRGLHFACGYGELQCAQALLEAGAAVDAVDKNKNTALHYAAGYGRKDCVALLLESGAAVT LQNLDGKTPIDVAKLNNQDDVLKLLEKHAFV
Secondary structure

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHCCCCCHHHHHHHHHCCCCHHHHHHHHHHH HCCCHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHCCHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHHHH CCCCCHHHHHHHHHCCCHHHHHHCCCHHHHHHHHHHHCCCCCCCCCCCCHHHHHCCCCCCCCCCCCCCCHHHHHHHCCCH HHHHHHHHCCCCCCCCCCCCCHHHHHHHHCCCHHHHHHHHHCCCCCCCCCCCCCHHHHHHHHCCCHHHHHHHHHCCCCCC CCCCCCCHHHHHHHHCCCHHHHHHHHHCCCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2015-Nov-13 05:44 UTC

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

Cluster #12345678910
Cluster density14.63.63.22.42.11.61.51.31.00.4
Cluster size8542573438341924216
Average cluster RMSD5.811.517.714.018.221.213.119.020.216.9

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 25.10 24.10 30.90 28.60 23.10 27.40 29.60 31.70 34.80
2 25.10 0.00 27.20 27.30 13.20 32.10 32.10 25.50 34.00 36.60
3 24.10 27.20 0.00 30.20 27.40 26.90 29.20 32.50 33.30 30.50
4 30.90 27.30 30.20 0.00 25.90 31.90 26.80 24.70 29.50 33.70
5 28.60 13.20 27.40 25.90 0.00 31.80 29.90 25.50 31.10 35.80
6 23.10 32.10 26.90 31.90 31.80 0.00 26.90 34.30 31.70 34.40
7 27.40 32.10 29.20 26.80 29.90 26.90 0.00 25.80 28.20 27.50
8 29.60 25.50 32.50 24.70 25.50 34.30 25.80 0.00 30.00 33.20
9 31.70 34.00 33.30 29.50 31.10 31.70 28.20 30.00 0.00 36.30
10 34.80 36.60 30.50 33.70 35.80 34.40 27.50 33.20 36.30 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 0.11 0.10 0.09 0.10 0.10 0.09 0.10 0.06 0.07
2 0.11 1.00 0.09 0.09 0.33 0.09 0.08 0.08 0.06 0.07
3 0.10 0.09 1.00 0.07 0.08 0.08 0.09 0.10 0.07 0.09
4 0.09 0.09 0.07 1.00 0.10 0.07 0.08 0.08 0.08 0.07
5 0.10 0.33 0.08 0.10 1.00 0.09 0.09 0.10 0.07 0.07
6 0.10 0.09 0.08 0.07 0.09 1.00 0.08 0.09 0.05 0.09
7 0.09 0.08 0.09 0.08 0.09 0.08 1.00 0.09 0.05 0.08
8 0.10 0.08 0.10 0.08 0.10 0.09 0.09 1.00 0.06 0.08
9 0.06 0.06 0.07 0.08 0.07 0.05 0.05 0.06 1.00 0.07
10 0.07 0.07 0.09 0.07 0.07 0.09 0.08 0.08 0.07 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