All-atom knowledge-based potential for RNA structure prediction and assessment

Simple item page
dc.catalogadoraba
dc.contributor.authorCapriotti, E.
dc.contributor.authorNorambuena, T.
dc.contributor.authorMarti Renom, M. A.
dc.contributor.authorMelo Ledermann, Francisco Javier
dc.date.accessioned2025-02-06T18:59:42Z
dc.date.available2025-02-06T18:59:42Z
dc.date.issued2011
dc.description.abstractMotivation: Over the recent years, the vision that RNA simply serves as information transfer molecule has dramatically changed. The study of the sequence/structure/function relationships in RNA is becoming more important. As a direct consequence, the total number of experimentally solved RNA structures has dramatically increased and new computer tools for predicting RNA structure from sequence are rapidly emerging. Therefore, new and accurate methods for assessing the accuracy of RNA structure models are clearly needed. Results: Here, we introduce an all-atom knowledge-based potential for the assessment of RNA three-dimensional (3D) structures. We have benchmarked our new potential, called Ribonucleic Acids Statistical Potential (RASP), with two different decoy datasets composed of near-native RNA structures. In one of the benchmark sets, RASP was able to rank the closest model to the X-ray structure as the best and within the top 10 models for ∼93 and ∼95% of decoys, respectively. The average correlation coefficient between model accuracy, calculated as the root mean square deviation and global distance test-total score (GDT-TS) measures of C3′ atoms, and the RASP score was 0.85 and 0.89, respectively. Based on a recently released benchmark dataset that contains hundreds of 3D models for 32 RNA motifs with non-canonical base pairs, RASP scoring function compared favorably to ROSETTA FARFAR force field in the selection of accurate models. Finally, using the self-splicing group I intron and the stem-loop IIIc from hepatitis C virus internal ribosome entry site as test cases, we show that RASP is able to discriminate between known structure-destabilizing mutations and compensatory mutations. Availability: RASP can be readily applied to assess all-atom or coarse-grained RNA structures and thus should be of interest to both developers and end-users of RNA structure prediction methods. The computer software and knowledge-based potentials are freely available at http://melolab.org/supmat.html.
dc.format.extent8 páginas
dc.fuente.origenSIPA
dc.identifier.doi10.1093/bioinformatics/btr093
dc.identifier.eissn1367-4811
dc.identifier.issn1367-4803
dc.identifier.scopusid2-s2.0-79954460627
dc.identifier.urihttps://doi.org/10.1093/bioinformatics/btr093
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/102171
dc.identifier.wosidWOS:000289301600006
dc.information.autorucFacultad de Ciencias Biológicas; Melo Ledermann, Francisco Javier; 0000-0002-0424-5991; 82342
dc.issue.numero8
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final1093
dc.pagina.inicio1086
dc.revistaBioinformatics (Oxford, England)
dc.rightsacceso restringido
dc.subject.ddc570
dc.subject.deweyBiología
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAll-atom knowledge-based potential for RNA structure prediction and assessment
dc.typeartículo
dc.volumen27
sipa.codpersvinculados82342
Files
Collections
Artículos de revistas