CABS-flex: server for fast simulation of protein structure fluctuations

Download models Download C^α trajectory

Status: Done started: 2018-Nov-29 08:28:56 UTC

Project Name
Sequence	MQLKPMEINP EMLNKVLSRL GVAGQWRFVD VLGLEEESLG SVPAPACALL LLFPLTAQHE NFRKKQIEEL KGQEVSPKVY FMKQTIGNSC GTIGLIHAVA NNQDKLGFED GSVLKQFLSE TEKMSPEDRA KCFEKNEAIQ AAHDAVAQEG QCRVDDKVNF HFILFNNVDG HLYELDGRMP FPVNHGASSE DTLLKDAAKV CREFTEREQG EVRFSAVALC KAA
Secondary structure	CCCCCCCCCH HHHHHHHHHC CCCCCEEEEE CCCCCCCCCC CCCCCEEEEE EEEECCHHHH HHHHHHHHHH CCCCCCCCCC CCCCCCCCCH HHHHHHHHHH CCCCCCCCCC CCHHHHHHHH CCCCCHHHHH HHHHHCHHHH HHHHHHHHHC CCCCCCCCCE EEEEEEEECC EEEEECCCCC CCEEEEECCC CCHHHHHHHH HHHHHHHCCC CCCCEEEEEE ECC
Movie from predicted structures	To download the movie, right click on the desired file format:
Estimated finish time	2018-Nov-29 12:17 UTC

Project Name

Multimodel

Multimodel [PDB] Multimodel with superimposed input structure [PDB] Fluctuation data [TXT] Fluctuation plot [EPS]

Model 001

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 002

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 003

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 004

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 005

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 006

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 007

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 008

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 009

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 010

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 011

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Model 012

Model [PDB] Model with superimposed input structure [PDB] RMSD data [TXT] RMSD plot [EPS]

Project Name

Clustering data

Cluster #	1	2	3	4	5	6	7	8	9	10	11	12
Cluster density	231.4	206.7	157.5	151.8	144.7	142.3	122.2	119.2	96.6	96.1	81.3	66.5
Cluster size	284	263	206	174	162	174	167	139	131	118	100	82
Average cluster RMSD	1.2	1.3	1.3	1.1	1.1	1.2	1.4	1.2	1.4	1.2	1.2	1.2

Read about clustering method.

C^α RMSD & GDT_TS to the input structure

#	1	2	3	4	5	6	7	8	9	10	11	12
RMSD	2.60	2.73	2.72	2.49	2.55	2.60	2.50	2.73	2.51	2.49	2.38	2.51
GDT_TS	0.68	0.68	0.66	0.68	0.70	0.67	0.68	0.65	0.70	0.69	0.72	0.68

The table contains RMSD and GDT_TS values (calculated on the Cα atoms) between the predicted models and the input structure. Note that GDT_TS metric is intended as a more accurate measurement than the more common RMSD.
Read more about the root-mean-square deviation (RMSD) measure
Read more about the global distance test (GDT, also written as GDT_TS to represent "total score") measure.

C^α RMSD between predicted models

#	1	2	3	4	5	6	7	8	9	10	11	12
1	0.00	1.90	2.11	2.11	2.02	1.97	2.30	1.91	2.10	2.40	1.95	2.20
2	1.90	0.00	1.83	2.27	2.07	2.11	2.20	1.78	2.04	2.27	2.22	2.17
3	2.11	1.83	0.00	2.54	2.33	2.38	2.68	2.07	2.26	2.35	2.20	2.39
4	2.11	2.27	2.54	0.00	1.76	1.59	2.34	2.22	1.96	2.14	1.95	1.69
5	2.02	2.07	2.33	1.76	0.00	1.84	2.35	2.22	2.23	1.77	1.79	1.95
6	1.97	2.11	2.38	1.59	1.84	0.00	2.19	2.04	2.00	2.05	1.84	1.86
7	2.30	2.20	2.68	2.34	2.35	2.19	0.00	2.46	2.28	2.42	2.47	2.49
8	1.91	1.78	2.07	2.22	2.22	2.04	2.46	0.00	1.97	2.33	1.98	2.06
9	2.10	2.04	2.26	1.96	2.23	2.00	2.28	1.97	0.00	2.15	2.02	1.96
10	2.40	2.27	2.35	2.14	1.77	2.05	2.42	2.33	2.15	0.00	1.83	2.11
11	1.95	2.22	2.20	1.95	1.79	1.84	2.47	1.98	2.02	1.83	0.00	1.74
12	2.20	2.17	2.39	1.69	1.95	1.86	2.49	2.06	1.96	2.11	1.74	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.

C^α GDT_TS between predicted models

#	1	2	3	4	5	6	7	8	9	10	11	12
1	1.00	0.77	0.73	0.72	0.73	0.73	0.70	0.78	0.73	0.70	0.78	0.72
2	0.77	1.00	0.77	0.70	0.73	0.72	0.70	0.77	0.73	0.72	0.72	0.73
3	0.73	0.77	1.00	0.66	0.69	0.66	0.65	0.74	0.70	0.67	0.71	0.69
4	0.72	0.70	0.66	1.00	0.78	0.81	0.70	0.71	0.75	0.73	0.75	0.80
5	0.73	0.73	0.69	0.78	1.00	0.77	0.70	0.71	0.72	0.80	0.81	0.76
6	0.73	0.72	0.66	0.81	0.77	1.00	0.73	0.72	0.74	0.74	0.77	0.76
7	0.70	0.70	0.65	0.70	0.70	0.73	1.00	0.67	0.70	0.69	0.69	0.70
8	0.78	0.77	0.74	0.71	0.71	0.72	0.67	1.00	0.72	0.69	0.74	0.71
9	0.73	0.73	0.70	0.75	0.72	0.74	0.70	0.72	1.00	0.73	0.73	0.76
10	0.70	0.72	0.67	0.73	0.80	0.74	0.69	0.69	0.73	1.00	0.77	0.73
11	0.78	0.72	0.71	0.75	0.81	0.77	0.69	0.74	0.73	0.77	1.00	0.79
12	0.72	0.73	0.69	0.80	0.76	0.76	0.70	0.71	0.76	0.73	0.79	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, Faculty of Chemistry, University of Warsaw 2013