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Rigidity analysis of protein biological assemblies and periodic crystal structures.

Authors :
Jagodzinski F
Clark P
Grant J
Liu T
Monastra S
Streinu I
Source :
BMC bioinformatics [BMC Bioinformatics] 2013; Vol. 14 Suppl 18, pp. S2. Date of Electronic Publication: 2013 Nov 05.
Publication Year :
2013

Abstract

Background: We initiate in silico rigidity-theoretical studies of biological assemblies and small crystals for protein structures. The goal is to determine if, and how, the interactions among neighboring cells and subchains affect the flexibility of a molecule in its crystallized state. We use experimental X-ray crystallography data from the Protein Data Bank (PDB). The analysis relies on an effcient graph-based algorithm. Computational experiments were performed using new protein rigidity analysis tools available in the new release of our KINARI-Web server http://kinari.cs.umass.edu.<br />Results: We provide two types of results: on biological assemblies and on crystals. We found that when only isolated subchains are considered, structural and functional information may be missed. Indeed, the rigidity of biological assemblies is sometimes dependent on the count and placement of hydrogen bonds and other interactions among the individual subchains of the biological unit. Similarly, the rigidity of small crystals may be affected by the interactions between atoms belonging to different unit cells.<br />Conclusion: The rigidity analysis of a single asymmetric unit may not accurately reflect the protein's behavior in the tightly packed crystal environment. Using our KINARI software, we demonstrated that additional functional and rigidity information can be gained by analyzing a protein's biological assembly and/or crystal structure. However, performing a larger scale study would be computationally expensive (due to the size of the molecules involved). Overcoming this limitation will require novel mathematical and computational extensions to our software.

Details

Language :
English
ISSN :
1471-2105
Volume :
14 Suppl 18
Database :
MEDLINE
Journal :
BMC bioinformatics
Publication Type :
Academic Journal
Accession number :
24564201
Full Text :
https://doi.org/10.1186/1471-2105-14-S18-S2