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Issue No. 05 - September/October (2011 vol. 8)
ISSN: 1545-5963
pp: 1247-1257
Samuel Coulbourn Flores , Stanford University, Stanford
Michael A. Sherman , Stanford University, Stanford
Christopher M. Bruns , Stanford University, Stanford
Peter Eastman , Stanford University, Stanford
Russ Biagio Altman , Stanford University, Stanford
Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.
Internal coordinate mechanics, molecular, structure, dynamics, RNA, modeling, prediction, linear, scaling.

S. C. Flores, P. Eastman, M. A. Sherman, R. B. Altman and C. M. Bruns, "Fast Flexible Modeling of RNA Structure Using Internal Coordinates," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. , pp. 1247-1257, 2010.
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