RNA is a fundamental class of biomolecules that mediate a large variety of molecular processes within the cell. Computational algorithms can be of great help in the understanding of RNA structure-function relationship. One of the main challenges in this field is the development of structure-prediction algorithms, which aim at the prediction of the three-dimensional (3D) native fold from the sole knowledge of the sequence. In a recent paper, we have introduced a scoring function for RNA structure prediction. Here, we analyze in detail the performance of the method, we underline strengths and shortcomings, and we discuss the results with respect to state-of-the-art techniques. These observations provide a starting point for improving current methodologies, thus paving the way to the advances of more accurate approaches for RNA 3D structure prediction.
|Titolo:||Towards de novo RNA 3D Structure Prediction|
|Autori:||Bottaro S; Di Palma F; Bussi G|
|Rivista:||RNA & DISEASE|
|Data di pubblicazione:||2015|
|Digital Object Identifier (DOI):||10.14800/rd.544|
|Fulltext via DOI:||10.14800/rd.544|
|Appare nelle tipologie:||1.1 Journal article|