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Status: Done started: 2017-Aug-28 21:38:40 UTC
Project NameR7a
SequenceMADKVQTTLLFLAVGEFSVGILGNAFIGLVNCMDWVKKRKIASIDLILTSLAISRICLLCVILLDCFILVLYPDVYATGK EMRIIDFFWTLTNHLSIWFATCLSIYYFFKIGNFFHPLFLWMKWRIDRVISWILLGCVVLSVFISLPATENLNADFRFCV KAKRKTNLTWSCRVNKTQHASTKLFLNLATLLPFCVCLMSFFLLILSLRRHIRRMQLSATGCRDPSTEAHVRALKAVISF LLLFIAYYLSFLIATSSYFMPETELAVIFGESIALIYPSSHSFILILGNNKLRHASLKVIWKVMSILKGRKFQQHKQI
Secondary structure

CCHHHHHHHHHHHHHHHHHHHHCCEEEEEEECCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCC HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHCCCHHHHHHHHHHHHHHHHHHHHHCCCCCCCHHHHH HCCCCCCCEEEECCCCCCHHHHHHHHHCCCCHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHCCCCCCCHHHHHHHHHHHHHCCCCCCHHHHCCCCHHHHHHHHHHHHCCCCCCCCCCCCCCCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2017-Aug-29 11:33 UTC

Provided templates.

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

Cluster #123456789
Cluster density212.591.273.271.645.642.430.227.715.8
Cluster size856035653022311814
Average cluster RMSD0.40.70.50.90.70.51.00.70.9

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.

#123456789
1 0.00 1.52 2.18 2.79 2.09 2.63 1.74 2.06 1.71
2 1.52 0.00 1.94 3.12 1.77 2.51 1.32 2.19 2.21
3 2.18 1.94 0.00 3.47 1.36 2.37 2.15 2.26 2.79
4 2.79 3.12 3.47 0.00 3.23 2.55 2.80 2.56 2.41
5 2.09 1.77 1.36 3.23 0.00 2.00 1.78 1.84 2.68
6 2.63 2.51 2.37 2.55 2.00 0.00 1.94 1.33 3.09
7 1.74 1.32 2.15 2.80 1.78 1.94 0.00 1.71 2.34
8 2.06 2.19 2.26 2.56 1.84 1.33 1.71 0.00 2.61
9 1.71 2.21 2.79 2.41 2.68 3.09 2.34 2.61 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.

#123456789
1 1.00 0.92 0.91 0.89 0.88 0.86 0.89 0.90 0.93
2 0.92 1.00 0.93 0.88 0.93 0.91 0.94 0.92 0.90
3 0.91 0.93 1.00 0.89 0.90 0.88 0.92 0.90 0.91
4 0.89 0.88 0.89 1.00 0.88 0.88 0.91 0.90 0.91
5 0.88 0.93 0.90 0.88 1.00 0.91 0.95 0.93 0.89
6 0.86 0.91 0.88 0.88 0.91 1.00 0.92 0.92 0.90
7 0.89 0.94 0.92 0.91 0.95 0.92 1.00 0.94 0.91
8 0.90 0.92 0.90 0.90 0.93 0.92 0.94 1.00 0.92
9 0.93 0.90 0.91 0.91 0.89 0.90 0.91 0.92 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