Modeling complex RNA tertiary folds with Rosetta.
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.
Department of Biochemistry, Stanford University, Stanford, California, USA.
Clarence Yu
CY
Cheng
Department of Biochemistry, Stanford University, Stanford, California, USA.
Fang-Chieh
FC
Chou
Department of Biochemistry, Stanford University, Stanford, California, USA; Department of Physics, Stanford University, Stanford, California, USA. Electronic address: rhiju@stanford.edu.
Rhiju
R
Das
D016000:Cluster Analysis; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D012984:Software; D012985:Software Design; D057188:Workflow
D012313:RNA
Blind prediction; Chemical mapping; Fragment assembly; RNA tertiary structure; Structure mapping