title: 2D-RNA-coupling numbers: a new computational chemistry approach to link secondary structure topology with biological function.
abstract: Methods for prediction of proteins, DNA, or RNA function and mapping it onto sequence often rely on bioinformatics alignment approach instead of chemical structure. Consequently, it is interesting to develop computational chemistry approaches based on molecular descriptors. In this sense, many researchers used sequence-coupling numbers and our group extended them to 2D proteins representations. However, no coupling numbers have been reported for 2D-RNA topology graphs, which are highly branched and contain useful information. Here, we use a computational chemistry scheme: (a) transforming sequences into RNA secondary structures, (b) defining and calculating new 2D-RNA-coupling numbers, (c) seek a structure-function model, and (d) map biological function onto the folded RNA. We studied as example 1-aminocyclopropane-1-carboxylic acid (ACC) oxidases known as ACO, which control fruit ripening having importance for biotechnology industry. First, we calculated tau(k)(2D-RNA) values to a set of 90-folded RNAs, including 28 transcripts of ACO and control sequences. Afterwards, we compared the classification performance of 10 different classifiers implemented in the software WEKA. In particular, the logistic equation ACO = 23.8 . tau(1)(2D-RNA) + 41.4 predicts ACOs with 98.9%, 98.0%, and 97.8% of accuracy in training, leave-one-out and 10-fold cross-validation, respectively. Afterwards, with this equation we predict ACO function to a sequence isolated in this work from Coffea arabica (GenBank accession DQ218452). The tau(1)(2D-RNA) also favorably compare with other descriptors. This equation allows us to map the codification of ACO activity on different mRNA topology features. The present computational-chemistry approach is general and could be extended to connect RNA secondary structure topology to other functions.
authors.affiliation: Department of Organic Chemistry, University of Santiago de Compostela, Santiago de Compostela 15782, Spain. gonzalezdiazh@yahoo.es
authors.forename: Humberto
authors.initials: H
authors.lastname: González-Díaz
authors.forename: Guillermín
authors.initials: G
authors.lastname: Agüero-Chapin
authors.forename: Javier
authors.initials: J
authors.lastname: Varona
authors.forename: Reinaldo
authors.initials: R
authors.lastname: Molina
authors.forename: Giovanna
authors.initials: G
authors.lastname: Delogu
authors.forename: Lourdes
authors.initials: L
authors.lastname: Santana
authors.forename: Eugenio
authors.initials: E
authors.lastname: Uriarte
authors.forename: Gianni
authors.initials: G
authors.lastname: Podda
mesh_terms: D000465:Algorithms; D000594:Amino Acid Oxidoreductases / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D001185:Artificial Intelligence; D001483:Base Sequence; D040503:Coffea / Q000201:enzymology / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D019277:Entropy; D016015:Logistic Models; D008390:Markov Chains; D009690:Nucleic Acid Conformation; D010940:Plant Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D012313:RNA / Q000737:chemistry* / Q000235:genetics; D055672:Static Electricity
chemical_list: D010940:Plant Proteins; D012313:RNA; D000594:Amino Acid Oxidoreductases; C059460:1-aminocyclopropane-1-carboxylic acid oxidase