Mattia Bernetti, Elena Rosini, Luca Mollica, Matteo Masetti, Loredano Pollegioni, Maurizio Recanatini, Andrea Cavalli
Journal: Journal of chemical information and modeling 2019;58(11):2255-2265
PMID: 30339750
Traditionally, a drug potency is expressed in terms of thermodynamic quantities, mostly K and empirical IC values. Although binding affinity as an estimate of drug activity remains relevant, it is increasingly clear that it is also important to include (un)binding kinetic parameters in the characterization of potential drug-like molecules. Herein, we used standard in silico screening to identify a series of structurally related inhibitors of hDAAO, a flavoprotein involved in schizophrenia and neuropathic pain. We applied a novel methodology, based on scaled molecular dynamics, to rank them according to their residence times. Notably, we challenged the application in a prospective fashion for the first time. The good agreement between experimental residence times and the predicted residence times highlighted the procedure's reliability in both predictive and refinement scenarios. Additionally, through further inspection of the performed simulations, we substantiated a previous hypothesis on the involvement of a protein loop during ligand unbinding.
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