Guidelines for the analysis of free energy calculations

By Pavel V. Klimovich, Michael R. Shirts, David L. Mobley. Journal of Computer-Aided Molecular Design, 2015

477 citations recorded by the source corpus.

Free energy calculations based on molecular dynamics simulations show considerable promise for applications ranging from drug discovery to prediction of physical properties and structure-function studies. But these calculations are still difficult and tedious to analyze, and best practices for analysis are not well defined or propagated. Essentially, each group analyzing these calculations needs to decide how to conduct the analysis and, usually, develop its own analysis tools. Here, we review and recommend best practices for analysis yielding reliable free energies from molecular simulations. Additionally, we provide a Python tool, alchemical-analysis.py, freely available on GitHub as part of the pymbar package (located at http://github.com/choderalab/pymbar), that implements the analysis practices reviewed here for several reference simulation packages, which can be adapted to handle data from other packages. Both this review and the tool covers analysis of alchemical calculations generally, including free energy estimates via both thermodynamic integration and free energy perturbation-based estimators. Our Python tool also handles output from multiple types of free energy calculations, including expanded ensemble and Hamiltonian replica exchange, as well as standard fixed ensemble calculations. We also survey a range of statistical and graphical ways of assessing the quality of the data and free energy estimates, and provide prototypes of these in our tool. We hope this tool and discussion will serve as a foundation for more standardization of and agreement on best practices for analysis of free energy calculations.

Subfields: Atomic and Molecular Physics, and Optics, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e61a47661e0d648d6a58cbdec57c6e6052ca7c9f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery (2020, unknown): “83,202 5.7.”
Best practices for constructing, preparing, and evaluating protein-ligand binding aﬃnity benchmarks [Article v0.2] (2021, background): “This can for example be done by looking at the oﬀ-diagonals of an overlap matrix [120, 121].”
Best Practices for Constructing, Preparing, and Evaluating Protein-Ligand Binding Affinity Benchmarks [Article v1.0] (2021, background): “This can for example be done by looking at the oﬀ-diagonals of an overlap matrix [120, 121].”
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning (2019, background): “For example, the development of enhanced simulation protocolsforthebindingofsmalldrug molecules to proteinshasbecomea researcharea in itsown right ( 10 ).”