Testing and Usage of an Automated Multi-bead Iterative Boltzmann Inversion (IBI) Code

Iterative Boltzmann Inversion (IBI) is a systematic coarse-graining (CG) method in which tabular CG potentials are derived that reproduce target distributions generated from atomistic reference simulations. We report here on a software code which automates the development of multi-bead coarse-grained potentials using IBI. Two major problems make automation difficult: 1) noisy distributions derived from sampling; 2) low sampling regions which introduces discontinuities in the sampling. Both of these make differentiation to calculate energy and forces difficult and error prone. Our code addresses these problems using an approach which combines data smoothing, fitting to functional expansions, and extrapolation schemes to handle low sampling regions without discontinuity or data distortion. A number of code features will be discussed aimed at providing guidance on usage. In particular, we discuss the importance of proper sampling and equilibration in the reference simulations and how this leads accurate target distributions in low sampling regions (as well as the suppression of erroneous features) which is a key to potential convergence. Finally, we discuss associated tools that enable robust input including automated conversion of molecular systems from all-atom (AA) to CG models.