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Title:Distance-based configurational entropy of proteins from molecular dynamics simulations
Authors:ID Fogolari, Federico (Author)
ID Corazza, Alessandra (Author)
ID Fortuna, Sara (Author)
ID Soler, Miguel Angel (Author)
ID VanSchouwen, Bryan (Author)
ID Brancolini, Giorgia (Author)
ID Corni, Stefano (Author)
ID Melacini, Giuseppe (Author)
ID Esposito, Gennaro (Author)
Files:.pdf 10_Fogolari_Enropy.pdf (2,40 MB)
MD5: 6DF5E4A2373ACD4EC5AD39DBE8766276
Work type:Not categorized
Typology:1.01 - Original Scientific Article
Organization:UNG - University of Nova Gorica
Abstract:Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements; the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state; backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy); the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.
Keywords:entropy, protein, molecular dynamics, simulations, MD
Year of publishing:2015
Number of pages:26
Numbering:10, 7
PID:20.500.12556/RUNG-2690 New window
COBISS.SI-ID:4536315 New window
DOI:10.1371/journal.pone.0132356 New window
Publication date in RUNG:12.10.2016
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Record is a part of a journal

Title:PLoS ONE
Publisher:Public Library of Science
Year of publishing:2015


License:CC BY 4.0, Creative Commons Attribution 4.0 International
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:10.10.2016