English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  In silico FRET from simulated dye dynamics.

Hoefling, M., & Grubmüller, H. (2013). In silico FRET from simulated dye dynamics. Computer physics communications, 184(3), 841-852. doi:10.1016/j.cpc.2012.10.018.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-BAEE-0 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-C799-9
Genre: Journal Article

Files

show Files
hide Files
:
1684289.pdf (Publisher version), 2MB
Name:
1684289.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Creators

show
hide
 Creators:
Hoefling, M.1, Author              
Grubmüller, H.1, Author              
Affiliations:
1Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society, ou_578631              

Content

show
hide
Free keywords: -
 Abstract: Single molecule fluorescence resonance energy transfer (smFRET) experiments probe molecular distances on the nanometer scale. In such experiments, distances are recorded from FRET transfer efficiencies via the Förster formula, E = 1/(1 + (R/R0)6). The energy transfer however also depends on the mutual orientation of the two dyes used as distance reporter. Since this information is typically inaccessible in FRET experiments, one has to rely on approximations, which reduce the accuracy of these distance measurements. A common approximation is an isotropic and uncorrelated dye orientation distribution. To assess the impact of such approximations, we present the algorithms and implementation of a computational toolkit for the simulation of smFRET on the basis of molecular dynamics (MD) trajectory ensembles. In this study, the dye orientation dynamics, which are used to determine dynamic FRET efficiencies, are extracted from MD simulations. In a subsequent step, photons and bursts are generated using a Monte Carlo algorithm. The application of the developed toolkit on a poly-proline system demonstrated good agreement between smFRET simulations and experimental results and therefore confirms our computational method. Furthermore, it enabled the identification of the structural basis of measured heterogeneity. The presented computational toolkit is written in Python, available as open-source, applicable to arbitrary systems and can easily be extended and adapted to further problems.

Details

show
hide
Language(s): eng - English
 Dates: 2013
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.cpc.2012.10.018
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Computer physics communications
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 184 (3) Sequence Number: - Start / End Page: 841 - 852 Identifier: -