Automated de novo prediction of native-like RNA tertiary structures

@article{citeulike:1610926, abstract = {Edited by Ignacio Tinoco, Jr., University of California, Berkeley, CA, and approved July 10, 2007 (received for review April 25, 2007)RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of {approx}30 nt, the new method reproduces better than 90\% of WatsonCrick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 A rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-WatsonCrick base pairs seen in the native structures. Tandem stacks of "sheared" base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains. 10.1073/pnas.0703836104}, author = {Das, Rhiju and Baker, David }, citeulike-article-id = {1610926}, doi = {10.1073/pnas.0703836104}, journal = {PNAS}, keywords = {ab-initio, rna, structure\_prediction}, month = {August}, pages = {0703836104+}, posted-at = {2007-09-01 10:46:02}, priority = {2}, title = {Automated de novo prediction of native-like RNA tertiary structures}, url = {http://dx.doi.org/10.1073/pnas.0703836104}, year = {2007} }

TY - JOUR ID - citeulike:1610926 L3 - citeulike-article-id:1610926 TI - Automated de novo prediction of native-like RNA tertiary structures JF - PNAS SP - 0703836104 N2 - Edited by Ignacio Tinoco, Jr., University of California, Berkeley, CA, and approved July 10, 2007 (received for review April 25, 2007)RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of {approx}30 nt, the new method reproduces better than 90% of WatsonCrick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 A rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-WatsonCrick base pairs seen in the native structures. Tandem stacks of "sheared" base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains. 10.1073/pnas.0703836104 KW - ab-initio KW - rna KW - structure_prediction AU - Das, Rhiju AU - Baker, David PY - 2007/08/28/ UR - http://dx.doi.org/10.1073/pnas.0703836104 ER -