000032791 001__ 32791
000032791 005__ 20171130135647.0
000032791 0247_ $$2doi$$a10.1371/journal.pcbi.1003835
000032791 0248_ $$2sideral$$a89224
000032791 037__ $$aART-2014-89224
000032791 041__ $$aeng
000032791 100__ $$0(orcid)0000-0001-5072-0645$$aTapia-Rojo, R.$$uUniversidad de Zaragoza
000032791 245__ $$aMesoscopic Model and Free Energy Landscape for Protein-DNA Binding Sites: Analysis of Cyanobacterial Promoters
000032791 260__ $$c2014
000032791 5060_ $$aAccess copy available to the general public$$fUnrestricted
000032791 5203_ $$aThe identification of protein binding sites in promoter sequences is a key problem to understand and control regulation in biochemistry and biotechnological processes. We use a computational method to analyze promoters from a given genome. Our approach is based on a physical model at the mesoscopic level of protein-DNA interaction based on the influence of DNA local conformation on the dynamics of a general particle along the chain. Following the proposed model, the joined dynamics of the protein particle and the DNA portion of interest, only characterized by its base pair sequence, is simulated. The simulation output is analyzed by generating and analyzing the Free Energy Landscape of the system. In order to prove the capacity of prediction of our computational method we have analyzed nine promoters of Anabaena PCC 7120. We are able to identify the transcription starting site of each of the promoters as the most populated macrostate in the dynamics. The developed procedure allows also to characterize promoter macrostates in terms of thermo-statistical magnitudes (free energy and entropy), with valuable biological implications. Our results agree with independent previous experimental results. Thus, our methods appear as a powerful complementary tool for identifying protein binding sites in promoter sequences.
000032791 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/FIS2011-25167$$9info:eu-repo/grantAgreement/ES/MINECO/BFU2012-31458$$9info:eu-repo/grantAgreement/ES/MICINN/BFU2009-07424$$9info:eu-repo/grantAgreement/ES/DGA/E19$$9info:eu-repo/grantAgreement/ES/DGA/B18
000032791 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000032791 590__ $$a4.62$$b2014
000032791 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b4 / 57 = 0.07$$c2014$$dQ1$$eT1
000032791 591__ $$aBIOCHEMICAL RESEARCH METHODS$$b11 / 79 = 0.139$$c2014$$dQ1$$eT1
000032791 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000032791 700__ $$0(orcid)0000-0003-0698-6555$$aMazo, J.J.$$uUniversidad de Zaragoza
000032791 700__ $$aHernández, J.Á.
000032791 700__ $$0(orcid)0000-0002-2742-3711$$aPeleato, M.L.$$uUniversidad de Zaragoza
000032791 700__ $$0(orcid)0000-0001-8644-4574$$aFillat, M.F.$$uUniversidad de Zaragoza
000032791 700__ $$0(orcid)0000-0002-9551-624X$$aFalo, F.$$uUniversidad de Zaragoza
000032791 7102_ $$12003$$2395$$aUniversidad de Zaragoza$$bDepartamento de Física de la Materia Condensada$$cFísica de la Materia Condensada
000032791 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDepartamento de Bioquímica y Biología Molecular y Celular$$cBioquímica y Biología Molecular
000032791 7102_ $$11002$$2412$$aUniversidad de Zaragoza$$bDepartamento de Bioquímica y Biología Molecular y Celular$$cFisiología Vegetal
000032791 773__ $$g10, 10 (2014), e100383 [10 p.]$$pPLoS Comput. Biol.$$tPLoS Computational Biology$$x1553-734X
000032791 8564_ $$s2003825$$uhttps://zaguan.unizar.es/record/32791/files/texto_completo.pdf$$yVersión publicada
000032791 8564_ $$s118923$$uhttps://zaguan.unizar.es/record/32791/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000032791 909CO $$ooai:zaguan.unizar.es:32791$$particulos$$pdriver
000032791 951__ $$a2017-11-30-13:53:35
000032791 980__ $$aARTICLE