  The partitioning of small molecules in cell membranes---a key parameter for
pharmaceutical applications---typically relies on experimentally-available bulk
partitioning coefficients. Computer simulations provide a structural resolution
of the insertion thermodynamics via the potential of mean force, but require
significant sampling at the atomistic level. Here, we introduce high-throughput
coarse-grained molecular dynamics simulations to screen thermodynamic
properties. This application of physics based models in a large-scale study of
small molecules establishes linear relationships between partitioning
coefficients and key features of the potential of mean force. This allows us to
predict the structure of the insertion from bulk experimental measurements for
more than 400,000 compounds. The potential of mean force hereby becomes an
easily accessible quantity---already recognized for its high predictability of
certain properties, e.g., passive permeation. Further, we demonstrate how
coarse graining helps reduce the size of chemical space, enabling a
hierarchical approach to screening small molecules.
