Automated 3D structure composition for large RNAs
نویسندگان
چکیده
Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues.
منابع مشابه
RNAComposer: automated high-resolution structure prediction for large RNAs
In contrast to the protein field, a much smaller number of RNA tertiary structures has been assessed by X-ray crystallography, NMR spectroscopy and cryo-EM, and deposited in structural data banks. In view of the rapidly growing access to RNA secondary structures their 3D structure prediction is in great demand in the RNA community. Only a few programs and web-accessible tools have been proposed...
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