Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments.
Bottom Line: The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions poses the question of whether ENM approaches can be successfully extended to this class of biomolecules.This issue is tackled here by considering various families of elastic networks of increasing complexity applied to a representative set of RNAs.We find that simulations and experimental data are systematically best reproduced by either an all-atom or a three-beads-per-nucleotide representation (sugar-base-phosphate), with the latter arguably providing the best balance of accuracy and computational complexity.
Affiliation: Scuola Internazionale Superiore di Studi Avanzati, International School for Advanced Studies, 265, Via Bonomea I-34136 Trieste, Italy.Show MeSH
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Mentions: The consistency of ENM and MD simulations was assessed by computing the Pearson correlation coefficient (R) for the MSF profiles and the RWSIP for the essential dynamical spaces. To keep the comparison as simple and transparent as possible, each measure was computed separately for the S, B and P interaction centers. For multi-center ENMs this required the calculation of the effective interaction matrix (Equation (2)). Using as a reference the experimental structure in place of the MD centroid introduces only minor differences in the results, see Supplementary Figure S3. Each measure was then averaged over the four systems in Table 1 (see Supplementary Figure S4 for non-averaged values). The results, shown in Figure 3, are profiled as a function of the elastic network interaction cutoff distance, Rc. The smallest physically viable value for Rc, that is the abscissa of the left-most point of the curves, is the minimum value ensuring that the ENM zero-energy modes exclusively correspond to the six roto-translational modes.
Affiliation: Scuola Internazionale Superiore di Studi Avanzati, International School for Advanced Studies, 265, Via Bonomea I-34136 Trieste, Italy.