Assessing the accuracy of direct-coupling analysis for RNA contact prediction
| Autor: | Francesca Cuturello, Guido Tiana, Giovanni Bussi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Pseudolikelihood
Riboswitch Protein Conformation FOS: Physical sciences Biology Quantitative Biology - Quantitative Methods Article Settore FIS/03 - Fisica della Materia Evolution Molecular 03 medical and health sciences Physics - Biological Physics Molecular Biology DCA Condensed Matter - Statistical Mechanics Quantitative Methods (q-bio.QM) 030304 developmental biology 0303 health sciences Sequence Statistical Mechanics (cond-mat.stat-mech) 030302 biochemistry & molecular biology RNA coevolution Computational Biology Large numbers Mutual information Inverse problem Covariance Biological Physics (physics.bio-ph) FOS: Biological sciences Mutation Sequence Alignment Algorithm Algorithms Software |
| Zdroj: | RNA |
| Popis: | Many non-coding RNAs are known to play a role in the cell directly linked to their structure. Structure prediction based on the sole sequence is however a challenging task. On the other hand, thanks to the low cost of sequencing technologies, a very large number of homologous sequences are becoming available for many RNA families. In the protein community, it has emerged in the last decade the idea of exploiting the covariance of mutations within a family to predict the protein structure using the direct-coupling-analysis (DCA) method. The application of DCA to RNA systems has been limited so far. We here perform an assessment of the DCA method on 17 riboswitch families, comparing it with the commonly used mutual information analysis and with state-of-the-art R-scape covariance method. We also compare different flavors of DCA, including mean-field, pseudo-likelihood, and a proposed stochastic procedure (Boltzmann learning) for solving exactly the DCA inverse problem. Boltzmann learning outperforms the other methods in predicting contacts observed in high resolution crystal structures. Comment: Supporting information included in ancillary files |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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