Accurate Physics-Based Prediction of Binding Affinities of RNA- and DNA-Targeting Ligands

Accurate
prediction of the affinity of ligand binding to nucleic
acids represents a formidable challenge for current computational
approaches. This limitation has hindered the use of computational
methods to develop small-molecule drugs that modulate the activity
of nucleic acids, including those associated with anticancer, antiviral,
and antibacterial effects. In recent years, significant scientific
and technological advances as well as easier access to compute resources
have contributed to free-energy perturbation (FEP) becoming one of
the most consistently reliable approaches for predicting relative
binding affinities of ligands to proteins. Nevertheless, FEP’s
applicability to nucleic-acid targeting ligands has remained largely
undetermined. In this work, we present a systematic assessment of
the accuracy of FEP, as implemented in FEP+ software and facilitated
by the OPLS4 force field, in predicting relative binding free energies
of congeneric series of ligands interacting with a variety of DNA/RNA
systems. The study encompassed more than 100 ligands exhibiting diverse
binding modes, some partially exposed and others deeply buried. Using
a consistent simulation protocol, more than half of the predictions
are within 1 kcal/mol of the experimentally measured values. Across
the data set, we report a combined average pairwise root-mean-square-error
of <1.4 kcal/mol, which falls within one log unit of the experimentally
measured dissociation constants. These results suggest that FEP+ has
sufficient accuracy to guide the optimization of lead series in drug
discovery programs targeting RNA and DNA.