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Status: Done started: 2017-Feb-28 18:29:49 UTC
Project NameAR09
SequenceVKLAGNSSLCPVSGWAIYSKDNSIRIGSKGDVFVIREPFISCSPLECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMSCP IGEVPSPYNSRFESVAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKSWRNNILRTQESECACVNGSCFTVM TDGPSDGQASYKIFRIEKGKIVKSVEMNAPNYHYEECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIF GDNPRPNDKTGSCGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWDPNGWTGTDNNFSIKQDIVGINEWSGY SGSFVQHPELTGLDCIRPCFWVELIRGRPKENTIWTSGSSISFCGVNSDTVGWSWPDGAELPFTIDK
Secondary structure

CCCCCCCCCCCCCCEEEEECCCCEEECCCCCEEEEECCCEECCCCCEEEEEEECCCCCCCCCCCCCCCCCCCCCEEECCC CCCCCCCCCCCCCEEEECCCCCCCCCCEEEEEEECCCCCEEEEEEECCEEEHHHHHHHHCCCCCCCCEEEEECCCEEEEE CCCCCCCCCEEEEEEEECCEEEEEEECCCCCCCCCCCCCCCCCCCEEEEECCCCCCCCCCCEECCCCCCEEEEEEEECCC CCCCCCCCCCCCCCCCCCCCCCCCCEEEEEECCEEEEEEEECCCCCCCEEEEECCCCCCCCCCCCEEEECEEEEECCCCC CCCCCCCCCCCCCCCCCCEEEEEEEECCCCCCEEEECCCEEEEEECCCCCCCCCCCCCCCCCCEECC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2017-Mar-01 07:24 UTC

Provided templates.

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

Cluster #12345678
Cluster density332.6169.1166.499.991.073.873.557.3
Cluster size10264423940242326
Average cluster RMSD0.30.40.30.40.40.30.30.5

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 1.99 0.82 1.09 1.08 1.66 1.09 1.16
2 1.99 0.00 1.97 1.84 1.77 1.38 1.84 1.75
3 0.82 1.97 0.00 0.91 0.96 1.89 1.00 1.05
4 1.09 1.84 0.91 0.00 0.77 1.84 0.83 0.83
5 1.08 1.77 0.96 0.77 0.00 1.80 0.71 0.66
6 1.66 1.38 1.89 1.84 1.80 0.00 1.81 1.75
7 1.09 1.84 1.00 0.83 0.71 1.81 0.00 0.86
8 1.16 1.75 1.05 0.83 0.66 1.75 0.86 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 0.97 0.98 0.96 0.97 0.96 0.96 0.95
2 0.97 1.00 0.96 0.95 0.97 0.95 0.95 0.94
3 0.98 0.96 1.00 0.94 0.95 0.93 0.94 0.93
4 0.96 0.95 0.94 1.00 0.98 0.95 0.96 0.96
5 0.97 0.97 0.95 0.98 1.00 0.96 0.98 0.98
6 0.96 0.95 0.93 0.95 0.96 1.00 0.95 0.95
7 0.96 0.95 0.94 0.96 0.98 0.95 1.00 0.94
8 0.95 0.94 0.93 0.96 0.98 0.95 0.94 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