We use the concept of the statistical distance to develop a general theoretical framework for the design of molecular and coarse-grained models.1 The methodology is evaluated in comparison with other currently used techniques, such as force matching,2 relative entropy minimization,3 and Boltzmann inversion fitting4 to show that the newly proposed approach is more general and leads to more accurate and robust models. An efficient implementation of the force field optimization algorithm is achieved by using the thermodynamic perturbation relations.5,6 The resulting methodology can utilize a combination of experimental and quantum chemical data as a reference, and is capable of finding globally optimal model parameters with minimal computational expenses.
 L. Vlcek and A.A. Chialvo “Similarity between Statistical Mechanical Systems and Its Application in Molecular Model Development” in preparatioin.
 F. Ercolessi and J. B. Adams “Interatomic Potentials from 1st-Principles Calculations - the Force-Matching Method” Europhysics Letters 1994, 26, 583-588.
 M. S. Shell “Systematic Coarse-Graining of Potential Energy Landscapes and Dynamics in Liquids” J. Chem. Phys. 2012, 137, 13.
 D. Reith, M. Putz, and F. Muller-Plathe “Deriving Effective Mesoscale Potentials from Atomistic Simulations” J. Comput. Chem. 2003, 24, 1624-1636.
 A. A. Chialvo “Excess Properties of Liquid-Mixtures from Computer-Simulation - a Coupling-Parameter Approach to the Determination of Their Dependence on Molecular Asymmetry” Mol. Phys. 1991, 73, 127-140.
 L. Vlcek, A.A. Chialvo, and D.R. Cole “Optimized Unlike-Pair Interactions for Water-Carbon Dioxide Mixtures Described by the SPC/E and EPM2 Models” J. Phys. Chem. B 2011, 115, 8775-8784.