{"title":"Statistical mechanical modeling of RNA folding: from free energy landscape to tertiary structural prediction.","authors":"Song Cao, Shi-Jie Chen","doi":"10.1007/978-3-642-25740-7_10","DOIUrl":"https://doi.org/10.1007/978-3-642-25740-7_10","url":null,"abstract":"<p><p>In spite of the success of computational methods for predicting RNA secondary structure, the problem of predicting RNA tertiary structure folding remains. Low-resolution structural models show promise as they allow for rigorous statistical mechanical computation for the conformational entropies, free energies, and the coarse-grained structures of tertiary folds. Molecular dynamics refinement of coarse-grained structures leads to all-atom 3D structures. Modeling based on statistical mechanics principles also has the unique advantage of predicting the full free energy landscape, including local minima and the global free energy minimum. The energy landscapes combined with the 3D structures form the basis for quantitative predictions of RNA functions. In this chapter, we present an overview of statistical mechanical models for RNA folding and then focus on a recently developed RNA statistical mechanical model -- the <b>Vfold</b> model. The main emphasis is placed on the physics underpinning the models, the computational strategies, and the connections to RNA biology.</p>","PeriodicalId":91585,"journal":{"name":"Nucleic acids and molecular biology","volume":"27 ","pages":"185-212"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-642-25740-7_10","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34571704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}