Name
Title | ||
|---|---|---|
Binding residence time through scaled molecular dynamics: a prospective application to hDAAO inhibitors. |
Abstract | ||
|---|---|---|
Traditionally, a drug potency is expressed in terms of Prediction thermodynamic quantities, mostly K-d, and empirical IC50 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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1021/acs.jcim.8b00518 | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
DocType | Volume | Issue |
Journal | 58 | 11 |
ISSN | Citations | PageRank |
1549-9596 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mattia Bernetti | 1 | 0 | 1.35 |
| Elena Rosini | 2 | 0 | 0.68 |
| Luca Mollica | 3 | 0 | 0.68 |
| Matteo Masetti | 4 | 2 | 3.45 |
| Loredano Pollegioni | 5 | 0 | 0.68 |
| Maurizio Recanatini | 6 | 18 | 6.57 |
| Andrea Cavalli | 7 | 2 | 4.12 |