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Analyzing the flexibility of RNA structures by constraint counting
Authors:Fulle Simone  Gohlke Holger
Institution:Department of Biological Sciences, Molecular Bioinformatics Group, J. W. Goethe-University, Frankfurt, Germany
Abstract:RNA requires conformational dynamics to undergo its diverse functional roles. Here, a new topological network representation of RNA structures is presented that allows analyzing RNA flexibility/rigidity based on constraint counting. The method extends the FIRST approach, which identifies flexible and rigid regions in atomic detail in a single, static, three-dimensional molecular framework. Initially, the network rigidity of a canonical A-form RNA is analyzed by counting on constraints of network elements of increasing size. These considerations demonstrate that it is the inclusion of hydrophobic contacts into the RNA topological network that is crucial for an accurate flexibility prediction. The counting also explains why a protein-based parameterization results in overly rigid RNA structures. The new network representation is then validated on a tRNAASP structure and all NMR-derived ensembles of RNA structures currently available in the Protein Data Bank (with chain length ≥40). The flexibility predictions demonstrate good agreement with experimental mobility data, and the results are superior compared to predictions based on two previously used network representations. Encouragingly, this holds for flexibility predictions as well as mobility predictions obtained by constrained geometric simulations on these networks. Potential applications of the approach to analyzing the flexibility of DNA and RNA/protein complexes are discussed.
Keywords:MD  molecular dynamics  FIRST  floppy inclusion and rigid substructure topography  3D  three-dimensional  FRODA  framework rigidity optimized dynamics algorithm  DOF  degree(s) of freedom  dof  independent internal degree(s) of freedom  PDB  Protein Data Bank  GNM  Gaussian Network Model  NOE  nuclear Overhauser enhancement  RMSD  root mean-square deviation
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