We present what we believe to be a novel statistical contact potential based on solved structures of transmembrane (TM) alpha-helical bundles, and we use this contact potential to investigate the amino acid likelihood of stabilizing helix-helix interfaces. To increase statistical significance, we have reduced the full contact energy matrix to a four-flavor alphabet of amino acids, automatically determined by our methodology, in which we find that polarity is a more dominant factor of group identity than is size, with charged or polar groups most often occupying the same face, whereas polar/apolar residue pairs tend to occupy opposite faces. We found that the most polar residues strongly influence interhelical contact formation, although they occur rarely in TM helical bundles. Two-body contact energies in the reduced letter code are capable of determining native structure from a large decoy set for a majority of test TM proteins, at the same time illustrating that certain higher-order sequence correlations are necessary for more accurate structure predictions.

We develop a coarse-grained parametrization strategy for lipid membranes that we illustrate for a dipalmitoylphosphatidylcholine bilayer. Our coarse-graining approach eliminates the high cost of explicit solvent but maintains more lipid interaction sites. We use a broad attractive tail-tail potential and extract realistic bonded potentials of mean force from all-atom simulations, resulting in a model with a sharp gel to fluid transition, a correct bending modulus, and overall very reasonable dynamics when compared with experiment. We also determine a quantitative stress profile and correct breakdown of contributions from lipid components when compared with detailed all-atom simulation benchmarks, which has been difficult to achieve for implicit membrane models. Such a coarse-grained lipid model will be necessary for efficiently simulating complex constructs of the membrane, such as protein assembly and lipid raft formation, within these nonaqueous chemical environments.