We have developed a statistical mechanics theory and an analytical model of alchemical molecular binding that describe the progression of the probability distributions of the perturbation energy along the thermodynamic pathway connecting, in an alchemical sense, the bound and unbound states of a molecular complex. The model has been successfully employed to optimize alchemical perturbation functions and simulation settings to enhance the efficiency of binding free energy calculations. Our simulation protocol consists of optimizing, using a maximum-likelihood approach, the analytical model's parameters against the distributions of perturbation energies extracted from alchemical molecular dynamics calculations. In this talk, we will review the analytical model's main features, and we will discuss the applicability of its physical parameters towards the analysis of the thermodynamic and structural characteristics of protein-ligand complexes. Some of the parameters are extensions of interaction energy estimators commonly used in the Linear Interaction Energy (LIE) models. However, our model is more general. We will illustrate, for example, how the model can detect and characterize conformational transitions triggered by ligand binding. We envision that this work will contribute to the development of physics-based automatic classification schemes of protein-ligand complexes.

Classification of protein complexes based on an analytical model of alchemical molecular binding

ACS Fall 2021

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