Abstract
The ever increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a recently developed RNA structure prediction method based on the virtual bond-based coarse-grained folding model (Vfold). The main emphasis in the Vfold method is placed on the loop entropy calculations, the treatment of noncanonical (mismatch) interactions and the 3D structure assembly from motif-based template library. As case studies, we use the glycine riboswitch and the G310-U376 domain of MLV RNA to illustrate the Vfold-based prediction of RNA 3D structures from the sequences.
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Acknowledgment
This research was supported by NIH grant GM063732 and NSF grant MCB0920411.
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Xu, X., Chen, SJ. (2015). A Method to Predict the 3D Structure of an RNA Scaffold. In: Ponchon, L. (eds) RNA Scaffolds. Methods in Molecular Biology, vol 1316. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2730-2_1
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DOI: https://doi.org/10.1007/978-1-4939-2730-2_1
Publisher Name: Humana Press, New York, NY
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