Quantum-Mechanics Methodologies in Drug Discovery: Applications of Docking and Scoring in Lead Optimization
2017
The development and application of quantum mechanics (QM) methodologies in computeraided
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 selected 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, QM-based 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:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
26
Citations
NaN
KQI