Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction.
BACKGROUND
A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1.


RESULTS
The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases.


CONCLUSIONS
Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.
Doshi
Kishore J
KJ
The Institute for Cellular and Molecular Biology, The University of Texas at Austin, TX 78712-0159, USA. kjdoshi@mail.utexas.edu
Cannone
Jamie J
JJ
Cobaugh
Christian W
CW
Gutell
Robin R
RR
D001483:Base Sequence; D019295:Computational Biology / Q000379:methods / Q000592:standards; D019277:Entropy; D008957:Models, Genetic; D009690:Nucleic Acid Conformation; D010802:Phylogeny; D011237:Predictive Value of Tests; D012313:RNA / Q000737:chemistry*; D019642:RNA, Archaeal / Q000737:chemistry; D012329:RNA, Bacterial / Q000737:chemistry; D018747:RNA, Chloroplast / Q000737:chemistry; D000077278:RNA, Mitochondrial; D012336:RNA, Ribosomal, 16S / Q000737:chemistry; D012338:RNA, Ribosomal, 23S / Q000737:chemistry; D012341:RNA, Ribosomal, 5S / Q000737:chemistry; D013816:Thermodynamics
D019642:RNA, Archaeal; D012329:RNA, Bacterial; D018747:RNA, Chloroplast; D000077278:RNA, Mitochondrial; D012336:RNA, Ribosomal, 16S; D012338:RNA, Ribosomal, 23S; D012341:RNA, Ribosomal, 5S; D012313:RNA