dc.contributor |
Agència de Gestió d'Ajuts Universitaris i de Recerca |
dc.contributor |
Universitat Pompeu Fabra. Computational Biophysics Laboratory |
dc.contributor.author |
Giorgino, Toni |
dc.date.accessioned |
2013-06-18T10:35:31Z |
dc.date.available |
2013-06-18T10:35:31Z |
dc.date.created |
2013-05-20 |
dc.date.issued |
2013-06-18 |
dc.identifier.uri |
http://hdl.handle.net/2072/212327 |
dc.format.extent |
15 p. |
dc.language.iso |
eng |
dc.relation.ispartofseries |
Els ajuts de l'AGAUR;2009BP_B00109 |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.source |
RECERCAT (Dipòsit de la Recerca de Catalunya) |
dc.subject.other |
Molecular dynamics |
dc.subject.other |
Kintetics |
dc.subject.other |
Unstructured |
dc.subject.other |
Graphical processing unit |
dc.subject.other |
High-performance computing |
dc.title |
Distributed all-atom simulations of intrinsically unstructured proteins |
dc.type |
info:eu-repo/semantics/report |
dc.embargo.terms |
cap |
dc.description.abstract |
The Computational Biophysics Group at the Universitat Pompeu Fabra (GRIB-UPF) hosts two unique computational resources dedicated to the execution of large scale molecular dynamics (MD) simulations: (a) the ACMD molecular-dynamics software, used on standard personal computers with graphical processing units (GPUs); and (b) the GPUGRID. net computing network, supported by users distributed worldwide that volunteer GPUs for biomedical research. We leveraged these resources and developed studies, protocols and open-source software to elucidate energetics and pathways of a number of biomolecular systems, with a special focus on flexible proteins with many degrees of freedom. First, we characterized ion permeation through the bactericidal model protein Gramicidin A conducting one of the largest studies to date with the steered MD biasing methodology. Next, we addressed an open problem in structural biology, the determination of drug-protein association kinetics; we reconstructed the binding free energy, association, and dissaciociation rates of a drug like model system through a spatial decomposition and a Makov-chain analysis. The work was published in the Proceedings of the National Academy of Sciences and become one of the few landmark papers elucidating a ligand-binding pathway. Furthermore, we investigated the unstructured Kinase Inducible Domain (KID), a 28-peptide central to signalling and transcriptional response; the kinetics of this challenging system was modelled with a Markovian approach in collaboration with Frank Noe’s group at the Freie University of Berlin. The impact of the funding includes three peer-reviewed publication on high-impact journals; three more papers under review; four MD analysis components, released as open-source software; MD protocols; didactic material, and code for the hosting group. |