Automated Adaptive Absolute Binding Free Energy Calculations.
Finlay ClarkGraeme R RobbDaniel J ColeJulien MichelPublished in: Journal of chemical theory and computation (2024)
Alchemical absolute binding free energy (ABFE) calculations have substantial potential in drug discovery, but are often prohibitively computationally expensive. To unlock their potential, efficient automated ABFE workflows are required to reduce both computational cost and human intervention. We present a fully automated ABFE workflow based on the automated selection of λ windows, the ensemble-based detection of equilibration, and the adaptive allocation of sampling time based on inter-replicate statistics. We find that the automated selection of intermediate states with consistent overlap is rapid, robust, and simple to implement. Robust detection of equilibration is achieved with a paired t -test between the free energy estimates at initial and final portions of a an ensemble of runs. We determine reasonable default parameters for all algorithms and show that the full workflow produces equivalent results to a nonadaptive scheme over a variety of test systems, while often accelerating equilibration. Our complete workflow is implemented in the open-source package A3FE (https://github.com/michellab/a3fe).
Keyphrases
- machine learning
- deep learning
- high throughput
- drug discovery
- loop mediated isothermal amplification
- randomized controlled trial
- density functional theory
- molecular dynamics
- molecular dynamics simulations
- electronic health record
- endothelial cells
- risk assessment
- real time pcr
- label free
- sensitive detection
- monte carlo
- pluripotent stem cells