Knowledge-based instantiation of full atomic detail into coarse-grain RNA 3D structural models

Abstract

Motivation: The recent development of methods for modeling RNA 3D structures using coarse-grain approaches creates a need to bridge low- and high-resolution modeling methods. Although they contain topological information, coarse-grain models lack atomic detail, which limits their utility for some applications.Results: We have developed a method for adding full atomic detail to coarse-grain models of RNA 3D structures. Our method [Coarse to Atomic (C2A)] uses geometries observed in known RNA crystal structures. Our method rebuilds full atomic detail from ideal coarse-grain backbones taken from crystal structures to within 1.87–3.31 Å RMSD of the full atomic crystal structure. When starting from coarse-grain models generated by the modeling tool NAST, our method builds full atomic structures that are within 1.00 Å RMSD of the starting structure. The resulting full atomic structures can be used as starting points for higher resolution modeling, thus bridging high- and low-resolution approaches to modeling RNA 3D structure.Availability: Code for the C2A method, as well as the examples discussed in this article, are freely available at www.simtk.org/home/c2a.Contact: russ.altman@stanford.edu

RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

“…As a consequence, exciting developments in the field of de novo structure prediction have occurred in the last few years: computer-assisted modeling tools (Martinez et al 2008;Jossinet et al 2010); conformational space search (Parisien and Major 2008); discrete molecular dynamics (Ding et al 2008a); knowledge-based, coarse-grained refinement (Jonikas et al 2009); template-based Rother et al 2011b); and force-field-based approaches (Das et al 2010) inspired by proven proteinfolding techniques adapted to the RNA field (for review, see Rother et al 2011a). All these new approaches are pushing the limits of automatic RNA structure prediction from short sequences of a few nucleotides to medium-sized molecules with several dozens.…”

Automated 3D RNA Structure Prediction Using the RNAComposer Method for Riboswitches1

“…Considerable differences are also visible in terms of prediction quality, which depends on the RNA strand length and topology, processor time needed, and degree of automation. Physics-based automated methods use the coarse-grained and atomic-level molecular dynamics (Cao & Chen, 2011;Jonikas, Radmer, & Altman, 2009;Jonikas, Radmer, Laederach, et al, 2009;Sharma, Ding, & Dokholyan, 2008;Xu, Zhao, & Chen, 2014), internal coordinate space dynamics (Flores & Altman, 2010;Flores, Sherman, Bruns, Eastman, & Altman, 2011), and fragment assembly (Das, Karanicolas, & Baker, 2010;Parisien & Major, 2008). Full-atomic structure predictions based on dynamics and fragment assembly are powerful tools for modeling relatively complex but small RNAs.…”

“…Full-atomic structure predictions based on dynamics and fragment assembly are powerful tools for modeling relatively complex but small RNAs. Despite the computational cost, the coarse-grained molecular dynamics can access larger RNAs but requires demanding and not fully resolved addition of atomic details to coarse-grain models ( Jonikas, Radmer, & Altman, 2009;Jonikas, Radmer, Laederach, et al, 2009). Knowledge-based comparative modeling (Rother, Rother, Puton, & Bujnicki, 2011) depends on the access to 3D structural templates and unequivocal sequence alignment.…”

RNA Folding: Structure Prediction, Folding Kinetics and Ion Electrostatics

“…NAST has been tested by building the structural models for two RNA molecules-the yeast tRNA Phe (76-nt) and the P4-P6 domain of the Tetrahymena thermophila group I intron (158-nt), with the averaged RMSD 8.0 ± 0.3 and 16.3 ± 1.0 Å, respectively. Recently, the authors also developed a fully automated frament-and knowledge-based method, called C2A (Coarse to Atomic) [19], to add full atomic details to coarse-grained models.…”