Membrane/Toxin Interaction Energetics via Serial Multiscale Molecular Dynamics Simulations.
Wee CL., Ulmschneider MB., Sansom MSP.
Computing free energies of complex biomolecular systems via atomistic (AT) molecular dynamics (MD) simulations remains a challenge due to the need for adequate sampling and convergence. Recent coarse-grained (CG) methodology allows simulations of significantly larger systems (∼10(6) to 10(8) atoms) over longer (μs/ms) time scales. Such CG models appear to be capable of making semiquantitative predictions. However, their ability to reproduce accurate thermodynamic quantities remains uncertain. We have recently used CG MD simulations to compute the potential of mean force (PMF) or free energy profile of a small peptide toxin interacting with a lipid bilayer along a 1D reaction coordinate. The toxin studied was VSTx1 (Voltage Sensor Toxin 1) from spider venom which inhibits the archeabacterial voltage-gated potassium (Kv) channel KvAP by binding to the voltage-sensor (VS) domains. Here, we re-estimate this PMF profile using (i) AT MD simulations with explicit membrane and solvent and (ii) an implicit membrane and solvent (generalized Born; GBIM) model where only the peptide was explicit. We used the CG MD free energy simulations to guide the setup of the corresponding AT MD simulations. The aim was to avoid local minima in the AT simulations which would be difficult over shorter AT time scales. A cross-comparison of the PMF profiles revealed a conserved topology, although there were differences in the magnitude of the free energies. The CG and AT simulations predicted a membrane/water interface free energy well of -27 and -23 kcal/mol, respectively (with respect to water). The GBIM model, however, gave a reduced interfacial free energy well (-12 kcal/mol). In addition, the CG and GBIM models predicted a free energy barrier of +61 and +96 kcal/mol, respectively, for positioning the toxin at the center of the bilayer, which was considerably smaller in the AT simulations (+26 kcal/mol). Thus, we present a framework for serially combining CG and AT simulations to estimate the free energy of peptide/membrane interactions. Such approaches for combining simulations at different levels of granularity will become increasingly important in future studies of complex membrane/protein systems.