Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data

and Computer Simulations

Poster Abstracts

61-POS

Board 21

Molecular Breakdown of DEER Data from Self-learning Atomistic Simulations

Fabrizio Marinelli

, Giacomo Fiorin, José Faraldo-Gómez.

n/a, Bethesda, USA.

Double Electron-Electron Resonance (DEER) has become a landmark technique to investigate

bio-molecular structure and dynamics. DEER allows obtaining the distance distributions between

spin-labels attached to a biomolecule and in contrast to X-ray crystallography and NMR

spectroscopy, DEER is neither limited by the need of crystallization nor by the size of the

biomolecule. This notwithstanding, it is often not straightforward to interpret DEER data as it

reflects a plethora of molecular conformations and rotameric states of the spin-labels. Several

strategies to disentangle this variability have been put forward recently, either based on

approximate structural models or on atomistic simulations. Both kinds of approaches however

rely on probability distributions that are inferred from the actual measured data and do not take

into account the experimental noise. Building upon the maximum entropy principle, we present

an adaptive simulation framework to minimally bias an atomistic simulation to sample a

conformational ensemble that reproduces the DEER data within the experimental uncertainty.

Our approach has been formulated either to target directly the DEER time signal within the

experimental noise or to reproduce DEER distributions within the confidence intervals. We first

test the performance of this approach for the spin-labeled T4 lysozyme. Then, we apply it to

investigate the conformational dynamics of the apo VcSiaP binding protein, that undergoes an

open to close conformational change upon substrate binding. The results indicate a wider

opening of the VcSiaP apo state compared to both the X-ray structure and standard MD

simulations, underlying that the proposed technique is a powerful tool to structurally characterize

DEER experiments and to investigate the dynamics of biomolecules.