The development and application of quantum mechanics (QM) methodologies in computer-
aided drug design have flourished in the last 10 years. Despite the natural advantage of QM methods
to predict binding affinities with a higher level of theory than those methods based on molecular
mechanics (MM), there are only a few examples where diverse sets of protein-ligand targets have
been evaluated simultaneously. In this work, we review recent advances in QM docking and scoring
for those cases in which a systematic analysis has been performed. In addition, we introduce and validate
a simplified QM/MM expression to compute protein-ligand binding energies. Overall, QMbased
scoring functions are generally better to predict ligand affinities than those based on classical
mechanics. However, the agreement between experimental activities and calculated binding energies
is highly dependent on the specific chemical series considered. The advantage of more accurate QM
methods is evident in cases where charge transfer and polarization effects are important, for example
when metals are involved in the binding process or when dispersion forces play a significant role as
in the case of hydrophobic or stacking interactions.
Keywords: Quantum mechanics, Hybrid QM/MM methodologies, QM-based protein-ligand binding energies, QM-based docking
calculations, QM/MM scoring functions, Systematic assessment of protein-ligand affinities.
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