Automated Adaptive Absolute Binding Free Energy Calculations

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 <i>t</i>-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).

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2024-09-10
DOI
https://doi.org/10.1021/acs.jctc.4c00806
Citations
15
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
7.34

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article

Automated Adaptive Absolute Binding Free Energy Calculations

Daniel J. Cole, Julien Michel, Graeme R. Robb, Finlay Clark
15 citations
Journal of Chemical Theory and Computation
Parallel Computing and Optimization Techniques
7.34
article

Automated Adaptive Absolute Binding Free Energy Calculations

Daniel J. Cole, Julien Michel, Graeme R. Robb, Finlay Clark
article en
15 citations

Abstract

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 <i>t</i>-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).

Journal of Chemical Theory and Computation
AstraZeneca (United Kingdom) (GB), Newcastle University (GB), University of Edinburgh (GB)
AstraZeneca, UK Research and Innovation, Engineering and Physical Sciences Research Council
Affordable and clean energy
Openalex Percentile: Top 2%
Parallel Computing and Optimization Techniques
7.34
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