Download models Download trajectory View trajectory
Status: Done started: 2017-Sep-14 01:25:46 UTC
Project Nameproteinac
SequenceMDFLPTQVFYGRRWRPRMPPRPWRPRMPTMQRPDQQARQMQQLIAAVSTLALRQNAAAPQRGKKKQPRRKKPKPQPEKPK KQEQKPKQKKAPKRKPGRRERMCMKIEHDCIFEVKHEGKVTGYACLVGDKVMKPAHVPGVIDNADLARLSYKKSSKYDLE CAQIPVAMKSDASKYTHEKPEGHYNWHYGAVQYTGGRFTVPTGVGKPGDSGRPIFDNKGPVVAIVLGGANEGTRTALSVV TWNKDMVTKITPEGTVEW
Secondary structure

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCCCCCC CCCCCCCCCCCCCCCCCCCCCCEEEECCCEEEEEEECCEEEEEEEEECCEECCCCCCCCCCCCHHHHHHHCCCCCCCCCC CCCCCCCCCCCCCCCCCCCCCCCCCCCCCEEEEECCEEEEECCCCCCCCCCCCCCCCCCCEEEEEECCCCCCCEEEEEEE EECCCCEEEECCCCCCCC

Simulation (CABS) temperature2.0 - 1.0
Estimated finish time2017-Sep-14 15:20 UTC

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

Cluster #12345678910
Cluster density48.421.911.45.84.72.51.81.00.70.3
Cluster size947056463815181472
Average cluster RMSD1.93.24.98.08.05.910.214.39.46.2

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.

#12345678910
1 0.00 21.30 22.20 21.80 22.40 23.40 26.60 23.60 24.60 26.70
2 21.30 0.00 23.00 22.80 23.10 23.60 24.20 23.80 23.80 27.00
3 22.20 23.00 0.00 6.57 9.52 26.10 24.60 24.20 27.20 29.60
4 21.80 22.80 6.57 0.00 9.79 25.60 25.10 23.90 28.40 29.90
5 22.40 23.10 9.52 9.79 0.00 25.10 25.40 24.80 26.80 27.40
6 23.40 23.60 26.10 25.60 25.10 0.00 22.40 26.80 24.50 27.30
7 26.60 24.20 24.60 25.10 25.40 22.40 0.00 25.30 24.10 29.80
8 23.60 23.80 24.20 23.90 24.80 26.80 25.30 0.00 25.20 31.80
9 24.60 23.80 27.20 28.40 26.80 24.50 24.10 25.20 0.00 26.50
10 26.70 27.00 29.60 29.90 27.40 27.30 29.80 31.80 26.50 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 0.14 0.12 0.11 0.12 0.13 0.10 0.07 0.09 0.08
2 0.14 1.00 0.15 0.17 0.14 0.11 0.10 0.07 0.10 0.10
3 0.12 0.15 1.00 0.52 0.41 0.12 0.10 0.08 0.08 0.09
4 0.11 0.17 0.52 1.00 0.47 0.11 0.10 0.06 0.08 0.08
5 0.12 0.14 0.41 0.47 1.00 0.11 0.10 0.06 0.08 0.09
6 0.13 0.11 0.12 0.11 0.11 1.00 0.11 0.07 0.08 0.09
7 0.10 0.10 0.10 0.10 0.10 0.11 1.00 0.07 0.07 0.07
8 0.07 0.07 0.08 0.06 0.06 0.07 0.07 1.00 0.07 0.06
9 0.09 0.10 0.08 0.08 0.08 0.08 0.07 0.07 1.00 0.09
10 0.08 0.10 0.09 0.08 0.09 0.09 0.07 0.06 0.09 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