Mostrar el registro sencillo del ítem
dc.contributor.author
Monzón, Alexander
dc.contributor.author
Zea, Diego Javier
dc.contributor.author
Fornasari, Maria Silvina
dc.contributor.author
Saldaño, Tadeo Enrique
dc.contributor.author
Fernández Alberti, Sebastián
dc.contributor.author
Tosatto, Silvio C. E.
dc.contributor.author
Parisi, Gustavo Daniel
dc.date.available
2017-09-27T15:51:32Z
dc.date.issued
2017-02
dc.identifier.citation
Monzón, Alexander; Zea, Diego Javier; Fornasari, Maria Silvina; Saldaño, Tadeo Enrique; Fernández Alberti, Sebastián; et al.; Conformational diversity analysis reveals three functional mechanisms in proteins; Public Library of Science; Plos Computational Biology; 13; 2; 2-2017; 1-18; e1005398
dc.identifier.issn
1553-734X
dc.identifier.uri
http://hdl.handle.net/11336/25220
dc.description.abstract
Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call "rigid" (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Public Library of Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Protein Evolution
dc.subject.classification
Bioquímica y Biología Molecular
dc.subject.classification
Ciencias Biológicas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Conformational diversity analysis reveals three functional mechanisms in proteins
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-09-08T20:19:00Z
dc.identifier.eissn
1553-7358
dc.journal.volume
13
dc.journal.number
2
dc.journal.pagination
1-18; e1005398
dc.journal.pais
Estados Unidos
dc.journal.ciudad
San Francisco
dc.description.fil
Fil: Monzón, Alexander. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Zea, Diego Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina
dc.description.fil
Fil: Fornasari, Maria Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
dc.description.fil
Fil: Saldaño, Tadeo Enrique. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Fernández Alberti, Sebastián. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Tosatto, Silvio C. E.. Università di Padova; Italia
dc.description.fil
Fil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.journal.title
Plos Computational Biology
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005398
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1371/journal.pcbi.1005398
Archivos asociados