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  Defining an essence of structure determining residue contacts in proteins

Sathyapriya, R., Duarte, J. M., Stehr, H., Filippis, I., & Lappe, M. (2009). Defining an essence of structure determining residue contacts in proteins. PLoS Computational Biology, 5(12), e1000584-e1000584. doi:10.1371/journal.pcbi.1000584.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7CB2-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7CB3-B
Genre: Journal Article
Alternative Title : PLoS Comput Biol

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 Creators:
Sathyapriya, R.1, Author              
Duarte, Jose M.1, Author              
Stehr, Henning1, Author              
Filippis, Ioannis2, Author
Lappe, Michael1, Author              
Affiliations:
1Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              
2Max Planck Society, ou_persistent13              

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 Abstract: The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this “structural essence” has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts—such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed “cone-peeling” that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 Å Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This “structural essence” opens new avenues in the fields of structure prediction, empirical potentials and docking.

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Language(s): eng - English
 Dates: 2009-12-04
 Publication Status: Published in print
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Title: PLoS Computational Biology
  Alternative Title : PLoS Comput Biol
Source Genre: Journal
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Pages: - Volume / Issue: 5 (12) Sequence Number: - Start / End Page: e1000584 - e1000584 Identifier: ISSN: 1553-734X