Predicting Residence Time and Drug Unbinding Pathway through Scaled Molecular Dynamics
- Author(s)
- Doris A. Schuetz, Mattia Bernetti, Martina Bertazzo, Djordje Musil, Hans Michael Eggenweiler, Maurizio Recanatini, Matteo Masetti, Gerhard F. Ecker, Andrea Cavalli
- Abstract
Computational approaches currently assist medicinal chemistry through the entire drug discovery pipeline. However, while several computational tools and strategies are available to predict binding affinity, predicting the drug-target binding kinetics is still a matter of ongoing research. Here, we challenge scaled molecular dynamics simulations to assess the off-rates for a series of structurally diverse inhibitors of the heat shock protein 90 (Hsp90) covering 3 orders of magnitude in their experimental residence times. The derived computational predictions are in overall good agreement with experimental data. Aside from the estimation of exit times, unbinding pathways were assessed through dimensionality reduction techniques. The data analysis framework proposed in this work could lead to better understanding of the mechanistic aspects related to the observed kinetic behavior.
- Organisation(s)
- External organisation(s)
- University of Bologna, Italian Institute of Technology, Merck KGaA
- Journal
- Journal of Chemical Information and Modeling
- Volume
- 59
- Pages
- 535-549
- No. of pages
- 15
- ISSN
- 1549-9596
- DOI
- https://doi.org/10.1021/acs.jcim.8b00614
- Publication date
- 01-2019
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 301207 Pharmaceutical chemistry
- ASJC Scopus subject areas
- Chemistry(all), Chemical Engineering(all), Computer Science Applications, Library and Information Sciences
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/predicting-residence-time-and-drug-unbinding-pathway-through-scaled-molecular-dynamics(1a10f3b5-2e00-4419-bce6-d8522ef725ea).html