Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes.These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components.Simulations of the system are then used to compute thermodynamic information, such as binding affinities.Because of their growing promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery.However, many challenges remain to make them a robust and reliable tool. Here, we highlight key challenges facing these calculations, describe known examples of these challenges, and call for the designation of standard community benchmark test systems that will help the research community generate and evaluate progress.In our view, progress will require careful assessment and evaluation of new methods, force fields, and modeling innovations on well-characterized benchmark systems, and we lay out our vision for how this can be achieved.
This repository relates to the perpetual review (definition) paper called "Predicting binding free energies: Frontiers and benchmarks" by David L. Mobley, Germano Heinzelmann and Michael K. Gilson. Its focus is benchmark sets for binding free energy calculations, including the perpetual review paper, but also all things relating to benchmark sets for free energy calculations. This includes discussion, datasets, and standards for datasets and data deposition.
This work is posted with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews. Only the Annual Reviews version of the work is peer reviewed; versions posted here are effectively preprints updated at the authors' discretion. The right to create derivative works (exercised here) is also exercised with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews, http://www.annualreviews.org/
Updated versions of this work are maintained at github.com/mobleylab/benchmarksets and this eScholarship archive serves to archive release versions of the work.