A generalized-Yvon-Born-Green method for coarse-grained modeling: advances, challenges, and insight

The Yvon-Born-Green (YBG) integral equation is a basic result of liquid state theory that relates the pair potential of a simple fluid to the resulting equilibrium two- and three-body correlation functions. Quite recently, we derived a more general form that can be applied to complex molecular systems. This generalized-YBG (g-YBG) theory provides not only an exact relation between a given potential and the resulting equilibrium correlation functions, but also a remarkably powerful framework for directly solving the statistical mechanics inverse problem of determining potentials from equilibrium structure ensembles. In the context of coarse-grained (CG) modeling, the g-YBG theory determines a variationally optimal approximation to the many-body potential of mean force directly (i.e., noniteratively) from structural correlation functions and, in particular, allows “force-matching” without forces. While our initial efforts numerically validated the g-YBG theory with relatively simple systems, our more recent efforts have considered increasingly complex systems, such as peptides and polymers. This minireview summarizes this progress and the resulting insight, as well as discusses the outstanding challenges and future directions for the g-YBG theory.

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