Free energy differences underly a variety of biologically relevant processes, and as such, their computation can provide valuable insight into solvation, association, and conformational equilibria. Rigorous, physics based alchemical free energy calculations have become a powerful computational tool to study these processes and perform molecular design. Traditional methods, such as free energy perturbation theory or thermodynamic integration (TI), have been widely developed and employed for these purposes, but generally suffer from an inherent scalability limitation and an additive expense of running stratified simulations at discrete physical or alchemical states of a biochemical system. In contrast, by utilizing a continuous alchemical coupling parameter, λ-dynamics can successfully overcome these disadvantages. Multisite λ-dynamics (MSλD) can investigate many different substituent modifications at one or multiple sites around the common core of a molecule simultaneously within a single molecular dynamics simulation. Thus, tens to hundreds of relative free energy differences can be readily computed and significant resource cost savings are achieved. This work will demonstrate the power of MSλD to explore combinatorial chemical spaces within the context of a pharmaceutical design problem addressing β-secretase 1 (BACE1), a prominent Alzheimer’s disease target. For a ligand series involving challenging substituent modifications and a change in the size of a ring, i.e. a scaffold modification, no loss of statistical precision is observed in computed free energies of binding with MSλD compared to conventional TI and multistate Bennett acceptance ratio (TI/MBAR) calculations; yet MSλD is at least 7 times more efficient. Excellent agreement with experimental <i>IC<sub>50</sub></i>s is also observed, with a mean unsigned error of 0.5 kcal/mol. The combination of a high degree of accuracy and precision in computed free energy differences with the ability to explore large chemical spaces makes MSλD an attractive alternative to conventional free energy methods for a variety of applications, especially computer-aided drug design.

Exploring large combinatorial chemical spaces to accelerate drug discovery with multisite λ-dynamics

2019 Fall National Meeting

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