Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies
for screening
and optimizing potential drug molecules. A critical factor in this
process is the binding affinity between candidate molecules and targets,
quantified as binding free energy. Among various estimation methods,
alchemical transformation methods stand out for their theoretical
rigor. Despite challenges in force field accuracy and sampling efficiency,
advancements in algorithms, software, and hardware have increased
the application of free energy perturbation (FEP) calculations in
the pharmaceutical industry. Here, we review the practical applications
of FEP in drug discovery projects since 2018, covering both ligand-centric
and residue-centric transformations. We show that relative binding
free energy calculations have steadily achieved chemical accuracy
in real-world applications. In addition, we discuss alternative physics-based
simulation methods and the incorporation of deep learning into free
energy calculations.