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Status: Done started: 2017-Apr-14 02:21:34 UTC
Project NameQ2
SequenceMAGDEREKAHCLVVPAAAQGHFTPLLQFSKRLIPKRIRVTLALTRFIHSTMTVTAQSGIHIDTISDGFDHSGLILQDPEH YSQTFRRVGSETLTDLIRKQSESRHPVHCIIYDASMPWFLDVAKRFGIVGAAFLTQSCAVNAIYYHLREGTIKRPVVSDP AAGTLVIDGLPPLEVSDLPSFIWDDLHTEFLAAHLRQFSNDGADWVFCNTVYQLELEAVDWLTKQWLINFRTIGPTIPSF YLDKQIPDDKDYDISIFNPQNQTCMNWLQSKPDGSVVYVSFGSLARLSPQQTEELYFGLKNSNHYFLWVVRESEVAKLPK EEYLSGEKGLVVSWCSQLQVLASGKVGCFVTHCGWNSTLEALSLGVPMVAMPECGDQLTNAKFIKDVWKTGVRAEADDGK GIMWGMIKREVIERCIREVMEGEETRRNADKWGKIIKEAVVEGGSSDKNTEDFATSLINFAETFQFSC
Secondary structure

CCCCCCCCCEEEEECCCCCCCCCHHHHHHHHHCCCCCEEEEEECCCCCCCCCCCCCCCEEEEECCCCCCCCCCCCCCHHH HHHHHHHHHHHHHHHHHHHHHCCCCCCCEEECCCCCCCHHHHHHHCCCCEEHHHHHHHHHHHHHHHHHCCCCCCCCCCCC CCCCEECCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHCCCCCCEEEEECCHHHHHHHHHHHHCCCCCCCCCCCCCCCCC CCCCCCCCCCCCCCCCCCCCCCCHHHHHCCCCCCCEEEEECCCCCCCCHHHHHHHHHHHHHCCCCEEEEEECCCCCCCCC HHHCCCCCCEEECCCCHHHHHCCCCCEEECCCCCHHHHHHHHHHCCCEEECCCCCCCCCCHHHHHHHHCCCEEECCCCCC CCCCCEECHHHHHHHHHHHHCCHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHHHCCCCCCCCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2017-Apr-14 16:16 UTC

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

Cluster #1234567
Cluster density19.56.86.15.52.42.11.3
Cluster size13791324093120
Average cluster RMSD7.013.45.27.33.814.715.2

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 30.60 32.50 41.10 33.30 46.90 46.80
2 30.60 0.00 41.30 59.70 40.90 0.30 64.80
3 32.50 41.30 0.00 39.20 31.30 47.10 44.10
4 41.10 59.70 39.20 0.00 36.10 28.20 28.70
5 33.30 40.90 31.30 36.10 0.00 43.70 43.90
6 46.90 0.30 47.10 28.20 43.70 0.00 27.10
7 46.80 64.80 44.10 28.70 43.90 27.10 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 0.08 0.07 0.07 0.08 0.07
2 0.07 1.00 0.07 0.07 0.07 0.06 0.05
3 0.08 0.07 1.00 0.08 0.10 0.07 0.07
4 0.07 0.07 0.08 1.00 0.10 0.08 0.09
5 0.07 0.07 0.10 0.10 1.00 0.06 0.08
6 0.08 0.06 0.07 0.08 0.06 1.00 0.07
7 0.07 0.05 0.07 0.09 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