Alchemical transformations can produce manifestations of molecular systems that may otherwise not be physically observable. Characterizing such manifestations, in concert with those that are structurally observable, provides novel insights into molecular complexes that can benefit computer-aided drug discovery. We apply a model of alchemical molecular binding, which is based on the probability distributions of the perturbation energy of two binding actors along an alchemical path, to statistically analyze solute systems that are subject to an alchemical hydration transformation. The statistical characterization of three systems of increasing complexity are complemented with structural analysis of molecular dynamics trajectories. Trained on numerical alchemical simulations, the analytical model reproduces the hydration free energy profiles and solute-solvent interaction energy distributions. Without prior knowledge of the system, the model can examine heterogenous molecular populations and capture thermodynamic features, particularly energetic transitions, that reflect conformational changes as a solute is progressively coupled to the solvent. This work offers a new route to not only classify molecular states based on their statistical properties rather than their structural features, but also to similarly characterize their <i>behaviors</i> under an alchemical transformation. More importantly, the analytical model serves as a stepping stone to the development of automated, statistical characterizations of protein-ligand complexes and to the advancement of binding free energy models.

Statistical characterization of alchemical hydration equilibria

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