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Status: Done started: 2014-Oct-17 10:39:48 UTC
Project Namesnap29
SequenceMSAYPKSYNPFDDDGEDEGARPAPWRDARDLPDGPDAPADRQQYLRQEVLRRAEATAASTSRSLALMYESEKVGVASSEE LARQRGVLERTEKMVDKMDQDLKISQKHINSIKSVFGGLVNYFKSKPVETPPEQNGTLTSQPNNRLKEAISTSKEQEAKY QASHPNLRKLDDTDPVPRGAGSAMSTDAYPKNPHLRAYHQKIDSNLDELSMGLGRLKDIALGMQTEIEEQDDILDRLTTK VDKLDVNIKSTERKVRQL
Secondary structure

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHH HHCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHCC

Simulation (CABS) temperature3.5 - 1.0
Estimated finish time2014-Oct-18 00:34 UTC

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

Cluster #12345678910
Cluster density20.26.73.52.42.01.81.61.51.40.3
Cluster size8769464231183218134
Average cluster RMSD4.310.413.117.315.510.119.912.19.315.6

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 19.00 23.60 25.40 36.10 27.70 22.60 25.60 35.90 33.80
2 19.00 0.00 24.30 16.20 31.00 17.30 22.90 15.80 32.50 28.70
3 23.60 24.30 0.00 24.40 32.80 26.00 20.70 22.00 33.70 31.80
4 25.40 16.20 24.40 0.00 29.70 18.40 21.10 12.50 31.00 26.30
5 36.10 31.00 32.80 29.70 0.00 29.30 31.70 30.40 20.10 15.40
6 27.70 17.30 26.00 18.40 29.30 0.00 25.90 19.10 33.20 27.30
7 22.60 22.90 20.70 21.10 31.70 25.90 0.00 22.30 30.10 31.80
8 25.60 15.80 22.00 12.50 30.40 19.10 22.30 0.00 32.40 26.40
9 35.90 32.50 33.70 31.00 20.10 33.20 30.10 32.40 0.00 23.80
10 33.80 28.70 31.80 26.30 15.40 27.30 31.80 26.40 23.80 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 0.21 0.28 0.18 0.14 0.23 0.18 0.19 0.18 0.17
2 0.21 1.00 0.20 0.31 0.17 0.25 0.17 0.40 0.20 0.17
3 0.28 0.20 1.00 0.21 0.18 0.19 0.24 0.20 0.21 0.19
4 0.18 0.31 0.21 1.00 0.18 0.26 0.18 0.34 0.18 0.17
5 0.14 0.17 0.18 0.18 1.00 0.15 0.15 0.17 0.19 0.20
6 0.23 0.25 0.19 0.26 0.15 1.00 0.15 0.26 0.19 0.17
7 0.18 0.17 0.24 0.18 0.15 0.15 1.00 0.17 0.16 0.16
8 0.19 0.40 0.20 0.34 0.17 0.26 0.17 1.00 0.21 0.18
9 0.18 0.20 0.21 0.18 0.19 0.19 0.16 0.21 1.00 0.18
10 0.17 0.17 0.19 0.17 0.20 0.17 0.16 0.18 0.18 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