Abstract:
:Reliable modeling of RNA tertiary structures is key to both understanding these structures' roles in complex biological machines and to eventually facilitating their design for molecular computing and robotics. In recent years, a concerted effort to improve computational prediction of RNA structure through the RNA-Puzzles blind prediction trials has accelerated advances in the field. Among other approaches, the versatile and expanding Rosetta molecular modeling software now permits modeling of RNAs in the 100-300 nucleotide size range at consistent subhelical (~1 nm) resolution. Our laboratory's current state-of-the-art methods for RNAs in this size range involve Fragment Assembly of RNA with Full-Atom Refinement (FARFAR), which optimizes RNA conformations in the context of a physically realistic energy function, as well as hybrid techniques that leverage experimental data to inform computational modeling. In this chapter, we give a practical guide to our current workflow for modeling RNA three-dimensional structures using FARFAR, including strategies for using data from multidimensional chemical mapping experiments to focus sampling and select accurate conformations.
journal_name
Methods Enzymoljournal_title
Methods in enzymologyauthors
Cheng CY,Chou FC,Das Rdoi
10.1016/bs.mie.2014.10.051subject
Has Abstractpub_date
2015-01-01 00:00:00pages
35-64eissn
0076-6879issn
1557-7988pii
S0076-6879(14)00052-4journal_volume
553pub_type
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