<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Cavalli, Andrea</dc:creator>
  <dc:creator>Camilloni, Carlo</dc:creator>
  <dc:creator>Vendruscolo, Michele</dc:creator>
  <dc:date>2013-03-07</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">In order to characterise the dynamics of proteins, a well-established method is to incorporate experimental parameters as  replica-averaged structural restraints into molecular dynamics simulations. Here, we justify this approach in the case of  interproton distance information provided by nuclear Overhauser effects by showing that it generates ensembles of  conformations according to the maximum entropy principle. These results indicate that the use of replica-averaged structural  restraints in molecular dynamics simulations, given a force field and a set of experimental data, can provide an accurate  approximation of the unknown Boltzmann distribution of a system.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://n2t.net/ark:/12658/srd1318872</dc:identifier>
  <dc:identifier>https://susi.usi.ch/global/documents/318872</dc:identifier>
  <dc:identifier>https://susi.usi.ch/documents/318872/files/Cavalli_JCP_2013.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1063/1.4793625</dc:relation>
  <dc:relation>info:eu-repo/semantics/altIdentifier/ark/12658/srd1318872</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:source>The journal of chemical physics. - 2013, vol. 138, no. 9, p. 094112</dc:source>
  <dc:subject>info:eu-repo/classification/udc/61</dc:subject>
  <dc:title xmlns:ns1="xml" ns1:lang="en">Molecular dynamics simulations with replica-averaged structural restraints generate structural ensembles according to the maximum entropy principle</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
