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Status: Done started: 2020-Jun-29 14:08:05 UTC
Project Nameprotein
SequenceGIINTLQKYYCRVRGGRCAVLSCLPKEEQIGKCSTRGRKCCRRKKEAAAKTEAIVCVELAAYMAILQQLAFAAYQQLAFA QALAAYLAFAQALNYAAYQALNYEHRFAAYQALNYEHRFAAYNPHLKETILAAYKETINVGLGPGPGIKTEAIVCVELTG PGPGSLETSLSIEAPWGPGPGIALSWSSVEHRGGPGPGETGMAILQQLAFGPGPGTGMAILQQLAFAGPGPGLQQLAFAQ ALNYGPGPGQQLAFAQALNYEGPGPGGMAILQQLAFAQ
Secondary structure

CHHHHHHHHHHHCCCCEEEEEECCCCCCCCCCCCCCCCHHHHHHHHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHHHHHCCHHHHHHHHHHCCCCCCCCCCCCHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCCC CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC CCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2020-Jun-30 04:03 UTC

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

Cluster #12345678910
Cluster density31.43.12.51.91.41.21.10.90.90.8
Cluster size136502927242323171615
Average cluster RMSD4.316.211.414.117.018.721.119.717.218.8

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 22.40 25.80 24.20 23.10 23.80 22.70 24.30 25.10 29.00
2 22.40 0.00 23.20 22.60 15.10 19.10 23.90 25.20 21.70 26.30
3 25.80 23.20 0.00 19.00 24.80 23.00 28.50 29.60 17.00 32.80
4 24.20 22.60 19.00 0.00 25.30 26.00 26.90 26.50 16.80 30.20
5 23.10 15.10 24.80 25.30 0.00 19.40 25.70 26.40 24.30 28.00
6 23.80 19.10 23.00 26.00 19.40 0.00 29.20 30.20 23.20 29.00
7 22.70 23.90 28.50 26.90 25.70 29.20 0.00 25.50 29.50 26.80
8 24.30 25.20 29.60 26.50 26.40 30.20 25.50 0.00 28.90 32.60
9 25.10 21.70 17.00 16.80 24.30 23.20 29.50 28.90 0.00 32.30
10 29.00 26.30 32.80 30.20 28.00 29.00 26.80 32.60 32.30 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.

#12345678910
1 1.00 0.10 0.17 0.14 0.10 0.09 0.11 0.10 0.15 0.09
2 0.10 1.00 0.16 0.11 0.17 0.11 0.09 0.11 0.14 0.08
3 0.17 0.16 1.00 0.20 0.16 0.13 0.10 0.14 0.19 0.09
4 0.14 0.11 0.20 1.00 0.14 0.13 0.09 0.13 0.20 0.09
5 0.10 0.17 0.16 0.14 1.00 0.16 0.11 0.15 0.15 0.09
6 0.09 0.11 0.13 0.13 0.16 1.00 0.12 0.12 0.14 0.10
7 0.11 0.09 0.10 0.09 0.11 0.12 1.00 0.08 0.10 0.14
8 0.10 0.11 0.14 0.13 0.15 0.12 0.08 1.00 0.12 0.08
9 0.15 0.14 0.19 0.20 0.15 0.14 0.10 0.12 1.00 0.09
10 0.09 0.08 0.09 0.09 0.09 0.10 0.14 0.08 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