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Status: Done started: 2017-Sep-07 12:40:41 UTC
Project NameCYP71D443
SequenceMEFTYYFSLFLLFLLSCFVFVLIFSKTKQNLPPGPRKLPIIGHLHHLAGTAPPHHTLRHLADKHGPLMHLQLGECGYVIA SSTEIATHFFKTHDALFASRPSILASEIGAYNNTDISFAPYGKFWRQLRRICSVELLSAKRVKSFQPVREEEATELCKWI AQREGSAINLGEKVQQMNYHIMGRAVLGKKTGEQAAFIALVKEGLDLMSGLDIVDLYPSYRILRLFSRLKRRIEKHHHAM DRIAHNIIEDRKRSDNGEHRDHDLLDVLLGLQDDKSLEIPLTTDNIKAVLGDLFGAGVETSSTTVEWAMAEMLKHPKVLK KAQDEVRMVFDAKNGVVDECYFDELKYLKLIVKESLRLHPPGPLLLPRVSSERCEINGYEIPAKTRLLVNVYAIARDPKC WEDGESFKPERFLEKSVDFMGSSIELIPFGAGRRICPGITFGVATVEIALAMLLYYFDWVLPEGMKAEDLDMTDWPGIAA RKKDNLWAVPLVRRTLPA
Secondary structure

CCCHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCHHHHCCCCCCCHHHHHHHHHHCCCCCCCCCCCCEEEE CCHHHHHHHHHHCCCCCCCCCCHHHHHHCCCCCCCEEECCCCHHHHHHHHHHHHHHCCCCCCCCCCHHHHHHHHHHHHHH HCCCCCCCCHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHCCCCCCCCCCCHHHHHHHHCHHHHHHHHHHHH HHHHHHHHHHHHHCCCCCCCCCCHHHHHHCCCCCCCCCCCCCCCCHHHHHHHHHCCCCCCHHHHHHHHHHHHHHCCHHHH HHHHHHHHHHCCCCCCCCCCCCCCCCCCHHHHHHHCCCCCCCCCCCCCCCCCCCEECCEECCCCCEEEEEEEEECCCCCC CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCEE ECCCCEEEEEECCCCCCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2017-Sep-08 02:35 UTC

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

Cluster #12345678
Cluster density37.75.14.23.02.10.60.40.2
Cluster size160674242261373
Average cluster RMSD4.213.210.014.012.422.219.718.7

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.

#12345678
1 0.00 27.60 23.80 17.40 44.50 60.30 34.40 47.50
2 27.60 0.00 32.00 29.70 43.30 56.80 34.60 42.10
3 23.80 32.00 0.00 30.90 44.80 58.60 39.60 47.50
4 17.40 29.70 30.90 0.00 41.60 60.00 31.20 46.40
5 44.50 43.30 44.80 41.60 0.00 35.30 33.50 39.70
6 60.30 56.80 58.60 60.00 35.30 0.00 45.10 39.90
7 34.40 34.60 39.60 31.20 33.50 45.10 0.00 33.30
8 47.50 42.10 47.50 46.40 39.70 39.90 33.30 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.

#12345678
1 1.00 0.08 0.09 0.14 0.07 0.07 0.07 0.06
2 0.08 1.00 0.08 0.07 0.06 0.07 0.07 0.06
3 0.09 0.08 1.00 0.09 0.07 0.07 0.07 0.07
4 0.14 0.07 0.09 1.00 0.08 0.07 0.07 0.07
5 0.07 0.06 0.07 0.08 1.00 0.07 0.10 0.06
6 0.07 0.07 0.07 0.07 0.07 1.00 0.07 0.07
7 0.07 0.07 0.07 0.07 0.10 0.07 1.00 0.06
8 0.06 0.06 0.07 0.07 0.06 0.07 0.06 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