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Technology Topics Modeling

Modeling RNA structures

PSI-SGKB [doi:10.1038/th_psisgkb.2010.19]
Technical Highlight - May 2010
Short description: The number of three-dimensional RNA structures is rapidly increasing, but are we getting close to being able to accurately predict new native structures?

A two-dimensional annotation and three-dimensional representation of a bulged-G motif from the sarcin-ricin loop from the Escherichia coli SRP domain IV RNA.

RNA is attracting a lot of attention and many groups have solved high-resolution three-dimensional structures of these molecules, although there are nowhere near the number of structures of RNA that there are of proteins. It would be very useful if we could reliably predict the structure of RNAs from their sequence — but how close are we to that point?

A recent paper by Rhiju Das and colleagues in Nature Methods presents a very promising approach to RNA modeling, based on the successful Rosetta method used for protein structures. It works, like the protein version, by assuming that the native structures have the lowest global energy.

The big improvements in this method over their earlier attempts are thanks to the addition of extensive new energy terms within the 'force fields'. Called fragment assembly of RNA with full-atom refinement (FARFAR), the new method defines terms for hydrogen bonding between bases and backbone oxygen atoms, and, importantly includes information about bonds between hydrogen and the hydroxyl O2' group (which is the difference between RNA and DNA). It also includes an energy term for C-H...O contacts, which contribute to the conformational preferences of the nucleotides and participate in the formation of some non-Watson–Crick base pairs.

FARFAR accurately modeled 50% of the 32 RNA motifs tested to a 1–2 Å resolution. This is no mean feat considering that the group focused on modeling conformations of non-canonical regions. The results are particularly encouraging because they correctly modeled non-Watson–Crick base pairs, which are used to form loops or junctions between helices and to connect RNA regions. These have been extremely difficult to model accurately up until now.

Atomic-resolution de novo prediction of RNA structures will enable the design and engineering of specific RNAs for nanotechnology or synthetic biology.

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Maria Hodges


  1. R. Das, J. Karanicolas & D. Baker Atomic accuracy in predicting and designing noncanonical RNA structure.
    Nature Methods 7, 291-294 (2010). doi:10.1038/nmeth.1433

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