Determination of the complete three-dimensional structure of the trypsin inhibitor from squash seeds in aqueous solution by nuclear magnetic resonance and a combination of distance geometry and dynamical simulated annealing.

Holak, T.A; Gondol, D; Otlewski, J; Wilusz, T.

139555 Biological Macromolecular Structures Enabling Breakthroughs in Research and Education

1CTI

DETERMINATION OF THE COMPLETE THREE-DIMENSIONAL STRUCTURE OF THE TRYPSIN INHIBITOR FROM SQUASH SEEDS IN AQUEOUS SOLUTION BY NUCLEAR MAGNETIC RESONANCE AND A COMBINATION OF DISTANCE GEOMETRY AND DYNAMICAL SIMULATED ANNEALING

Structural Similarities for the Entities in PDB 1CTI

The following structural similarities have been found using the jFATCAT-rigid algorithm [1,2].

To reduce the number of hits, a 40% sequence identity clustering has been applied and a representative chain taken from each cluster. If the representative chain consists of multiple domains, each domain is included in the search. If available, the SCOP 1.75 domain assignment [3] is used. Otherwise algorithmic domain assignments are computed using the ProteinDomainParser [4].

Currently viewing only significant results (P-value < 0.001). Show all available results.

Cluster data are up-to-date as of: Sep-27-2017

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A detailed description of the procedure for the all vs. all alignments is available.

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Entity #1 | Chains A

Description: TRYPSIN INHIBITOR protein | Length: 29

No structure alignment results are available for 1CTI.A explicitly.

It is represented by chain 1LU0.a which has more than 95% sequence identity.

Show structure comparison results for representative 1LU0.a

[1] Andreas Prlić; Spencer Bliven; Peter W. Rose; Wolfgang F. Bluhm; Chris Bizon; Adam Godzik; Philip E. Bourne (2010)
Pre-calculated protein structure alignments at the RCSB PDB website
Bioinformatics 26: 2983-2985
[2] The all vs. all comparisons are based on jFATCAT (a Java port of the original FATCAT algorithm Yuzhen Ye & Adam Godzik (2003))
Flexible structure alignment by chaining aligned fragment pairs allowing twists.
Bioinformatics vol.19 suppl. 2. ii246-ii255.

[3] Andreeva A., Howorth D., Chandonia J.-M., Brenner S.E., Hubbard T.J.P., Chothia C., Murzin A.G. (2008).
Data growth and its impact on the SCOP database: new developments.
Nucl. Acids Res. 2008 36: D419-D425
[4] Alexandrov N., Shindyalov I. (2003)
PDP: protein domain parser.
Bioinformatics 2003 Feb;19(3);429-30.

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