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dc.contributor.authorAndrabi, Munazah-
dc.contributor.authorHutchins, Andrew Paul-
dc.contributor.authorMiranda-Saavedra, Diego-
dc.contributor.authorKono, Hidetoshi-
dc.contributor.authorNussinov, Ruth-
dc.contributor.authorMizuguchi, Kenji-
dc.contributor.authorAhmad, Shandar-
dc.date.accessioned2018-06-15T08:12:09Z-
dc.date.available2018-06-15T08:12:09Z-
dc.date.issued2017-06-22-
dc.identifierdoi: 10.1038/s41598-017-03199-6-
dc.identifierissn: 2045-2322-
dc.identifier.citationScientific Reports 7 (2017)-
dc.identifier.urihttp://hdl.handle.net/10261/166370-
dc.description.abstractDNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.-
dc.description.sponsorshipMinistry of Education, Culture, Sports, Science and Technology (MEXT) of Japan [JP25116003 and JP26330339 to H.K.] and Platform for Drug Discovery, Informatics, and Structural Life Science from Japan Agency for Medical Research and Development (AMED) to H.K. This study was in part supported by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology (Grant Numbers 25430186 and 25293079) and from the Ministry of Health, Labor, and Welfare to K.M. This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract number HHSN261200800001E-
dc.publisherNature Publishing Group-
dc.relation.isversionofPublisher's version-
dc.rightsopenAccess-
dc.titlePredicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences-
dc.typeartículo-
dc.identifier.doihttp://dx.doi.org/10.1038/s41598-017-03199-6-
dc.date.updated2018-06-15T08:12:09Z-
dc.description.versionPeer Reviewed-
dc.language.rfc3066eng-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc/4.0/-
dc.contributor.funderMinistry of Education, Culture, Sports, Science and Technology (Japan)-
dc.contributor.funderNational Institutes of Health (US)-
dc.contributor.funderNational Cancer Institute (US)-
dc.contributor.funderJapan Agency for Medical Research and Development-
dc.contributor.funderMinistry of Health, Labour and Welfare (Japan)-
dc.relation.csic-
dc.identifier.funderhttp://dx.doi.org/10.13039/501100001700es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/100000002es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003478es_ES
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