Advancing Drug Discovery through Enhanced Free Energy Calculations.
By Robert Abel, Lingle Wang, Edward D Harder, B. Berne, Richard A. Friesner. Accounts of Chemical Research, 2017
304 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/2ded97fa91068add6c4b3bed22418aa546af0222
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Tatu Pantsar
- Rodrigo Vargas Honorato
- Jonathan Romero
- Alán Aspuru-Guzik
- Alexandre M. J. J. Bonvin
- Adrian E. Roitberg
- Yudong Cao
- José Miguel Hernández-Lobato
In Molecular Biology
- Tatu Pantsar
- Ross C. Walker
- Rodrigo Vargas Honorato
- David A. Case
- Robert Abel
- Jonathan Romero
- Alán Aspuru-Guzik
- Alexandre M. J. J. Bonvin
Citations in the corpus
- Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development (2020, methodology): “Applications include, for instance, estimation of affinities ∆bG (the standard Gibbs free energy of binding) of ligands for proteins using the so-called free energy perturbation (FEP) methods [40], the inclusion of charge fluctuations in constant pH AAMD [41], folding of small proteins [42], and the”
- GPU-accelerated molecular dynamics and free energy methods in Amber18: performance enhancements and new features (2018, methodology): “The Amber18 development roadmap will extend sampling capabilites for free energy simulations to facilitate advancement of drug discovery, 61 including implementation of the Gibbs sampling scheme 62 to improve the exchange rates in replica-exchange simulations, self-adjusted mixture sampling (SAMS)…”
- Potential of quantum computing for drug discovery (2018, background): “Another approach is the free-energy perturbation (FEP) technique, where the first ligand is mutated by small structural changes into a second ligand to mimic the thermodynamic ligand-interconversion cycle, with averages taken over many samples [73].”
- OPLS3e: Extending Force Field Coverage for Drug-Like Small Molecules. (2019, background): “…assessing the accuracy relative to QM for the other molecules; 4. identify the distinguishing chemical features that lead to a significant loss in accuracy; 5. revise the torsion type definitions to encapsulate the new chemical features; and 6. refit the model with the new basis of torsion types.”