Y. Zenmei Ohkubo, Taras V. Pogorelov, Mark J. Arcario, Geoff A. Christensen,
and Emad Tajkhorshid.
Accelerating membrane insertion of peripheral proteins with a novel
membrane mimetic model.
Biophysical Journal, 102:2130-2139, 2012.
OHKU2012-ET
Characterizing atomic details of membrane binding of peripheral membrane proteins by
molecular dynamics (MD) has been significantly hindered by the slow dynamics of
membrane reorganization associated with the phenomena. To expedite lateral diffusion of
lipid molecules without sacrificing the atomic details of such interactions, we have
developed a novel membrane representation, to our knowledge, termed the highly mobile
membrane-mimetic (HMMM) model to study binding and insertion of various molecular
species into the membrane. The HMMM model takes advantage of an organic solvent layer
to represent the hydrophobic core of the membrane and short-tailed phospholipids for the
headgroup region. We demonstrate that using these components, bilayer structures are
formed spontaneously and rapidly, regardless of the initial position and orientation of the
lipids. In the HMMM membrane, lipid molecules exhibit one to two orders of magnitude
enhancement in lateral diffusion. At the same time, the membrane atomic density profile of
the headgroup region produced by the HMMM model is essentially identical to those
obtained for full-membrane models, indicating the faithful representation of the
membrane surface by the model. We demonstrate the efficiency of the model in capturing
spontaneous binding and insertion of peripheral proteins by using the membrane anchor
(-carboxyglutamic-acid-rich domain; GLA domain) of human coagulation factor
VII as a test model. Achieving full insertion of the GLA domain consistently in 10
independent unbiased simulations within short simulation times clearly indicates the
robustness of the HMMM model in capturing membrane association of peripheral proteins
very efficiently and reproducibly. The HMMM model will provide significant improvements
to the current all-atom models by accelerating lipid dynamics to examine protein-
membrane interactions more efficiently
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