In order to choose the proper promotor for the XylE-transporter the membrane integrity is evaluated for Membrane-Transporter Systems. XylE Transporters are consecutively added to the system and membrane density and thickness is compared to literature references. The aim is to provide an educated guess in silico for transporter promotor selection to preserve membrane integrity and maximize transporter quantitiy simultaneously.

Molecular Dynamics (MD) simulations is one of the most common tools in computational biology. They are used to predict the mechanical behavior of a protein. At first a 3D Model of the protein is needed. This model gets transferred into a 3D enviroment. A force field is chosen which simulates all occuring forces during the simulation. In MD Simulations, a force field is a collection of mathematical functions and parameters which describe the potential energy of particles (atoms and molecules) and link them to a specific system nomenclature. For illustration the potential derived from the Assisted Model Building with Energy Refinement (AMBER) can be divided in four terms:

These terms are the core components of a force field. Thus the sum of all these terms approximates the total energy of a given system. Since we have an approximation of the potential and trajectories in phase space, the force acting on the particles can be computed as the derivative of this potential with respect to the particle position.

The first equation represents the non bonded interactions within a system. It can be divided into the Lennard-Jones potential, which approximates the interaction between a pair of neutral atoms or molecules. It is a empirically derived potential for van der Waals interactions. The second part is a Coulomb potential. It approximates the electrostatics between a pair of atoms i and j with partial charges by Edwald summation. The next term describes the oszillation of a chemical bonds as an harmonic spring. The last term describes the binding angels as well as the dihedral angels which are also approximated by harmonic springs. Force field parameters are derived by quantum mechanical calculations and fitted to available experimental datasets. The quality of MD simulations is largely depending on the applied force field.

Large moleculeassemblies, such as biomembranes, require tremendous computational time to compute significant time scales. To circumvent this obstacle a coarse-graining protocol can be implemented in the simulation routine. Coarse graining speaks for itself: the system is scaled into a coarser environment, using pseudocoordinates and pseudoatoms. That leads to a smoother potential and accelerates optimization. Additionally, 2 or more atoms are mapped into one pseudoatoms, which decreases the particle quantity and therefore coordinates and forces to compute. Martini uses a 4 to 1 atom:pseudoatom mapping, resulting in acceleration of a magnitude of four or more. Considering dynamics an elastic-network (e.g. ElNeDyn) can be applied to improve the physical accurancy of the simulation. Even though force-fields are fitted to experimental and theoretical data, as martini to the Gibbs-Energy of the Octanol-Water Partition Coefficient considering thermodynamics, every simulation needs its experimental interface to retain validity of the analysis and has to be choosen corresponding to the problem.

Membrane transport of the substrat Xylose could be a limiting factor in monomerproduction.

To maximize xylose-influx it is obvious, that the amount of membrane transporter proteins has to be maximized aswell. In this context it seems advisable to choose a highly active promoter for BioBrick construction. In order to consider membrane integrity coarse-grained MD simulations of different system containing an increasing amount of membrane transporters were run. The important membrane properties density and thickness were derived and compared to literature references to provide an educated guess for promotor selection in membrane transporter BioBrick construction.

General workflow

1. The membrane compisiton of the inner E.Coli membrane was estimated according to reference 1 and the available martini lipids resulting in an equimolar distribution of the lipids DPPC, DOPE, POPE and POPG.
2. A coarse-grained membrane patch was generated using the Insane script, consisting of 132 molecules per lipidtype.
3. The system was neutralized, solvated in water and 150mM NaCl and equibrilated to 323K and 1 bar to match native conditions.
4. The xylE coordinates from 4GC0.pdb were coarse-grained according to the Martini forcefield and combined with the elastic network model ElNeDyn.
5. The protein model was energy minimized and equibrilated to 323K and 1 bar to match native conditions.
6. The membrane proteins were oriented to the membrane according to the OPM-entry using VMD.
7. The membrane proteins were embedded using high lateral pressure of 1000 bar.
8. After embedding the membrane proteins a 2us NPT-simulation was made to relax membrane and evaluate membrane integrity.
9. Membrane density and thickness were derived from the simulated system and compared to literature references.