Andreas Krämer berichtet seinem Vortrag von seinen ersten Projekten als Postdoc am Laboratory of Computational Biology der National Institutes of Health (NIH) in Bethesda, MD, das in der Nähe von Washington D.C. angesiedelt ist.
Titel des Vortrags ist: "Membrane Permeability from Conventional MD Simulations: Counting Transitions vs. Bayesian Analysis"
The permeation of small molecules through membranes can presently be observed in conventional (i.e., non-enhanced) molecular dynamics simulations. This contribution focuses on three important aspects of such calculations. (1) The advantages and disadvantages of calculating permeability by direct counting of transition events versus Bayesian analysis based on the inhomogeneous solubility diffusion model. (2) A new Python/C++ tool that speeds up a previous implementation of the Bayesian analysis by two orders of magnitude and allows permeabilities to be extracted in a matter of seconds from a previously generated trajectory. (3) Simulated permeabilities of water, oxygen, and ethanol through various homogeneous bilayers. The results fall short of the experimental values, clearly demonstrating the requirement for accurate polarizable force fields.