Standard Binding Free Energies from Computer Simulations: What Is the Best Strategy?
Open accessAbstract
Accurate prediction of standard binding free energies describing protein–ligand association remains a daunting computational endeavor. This challenge is rooted to a large extent in the considerable changes in conformational, translational, and rotational entropies underlying the binding process that atomistic simulations cannot easily sample. In spite of significant methodological advances, reflected in a continuously improving agreement with experiment, a characterization of alternate strategies aimed at measuring binding affinities, notably their respective advantages and drawbacks, is somewhat lacking. Here, two distinct avenues to determine the standard binding free energy are compared in the case of a short, proline-rich peptide associating to the Src homology domain 3 of tyrosine kinase Abl. These avenues, one relying upon alchemical transformations and the other on potentials of mean force (PMFs), invoke a series of geometrical restraints acting on collective variables designed to alleviate sampling limitations inherent to classical molecular dynamics simulations. The experimental binding free energy of Δ G bind = −7.99 kcal/mol is well reproduced by the two strategies developed herein, with Δ G bind = −7.7 for the alchemical route and Δ G bind = −7.8 kcal/mol for the alternate PMF-based route. In detailing the underpinnings of these numerical strategies devised for the accurate determination of standard binding free energies, many practical elements of the proposed rigorous, conceptual framework are clarified, thereby paving way to tackle virtually any recognition and association phenomenon.
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While the path-based PMF approach appears more tractable, it is still difficult to obtain converged free energy estimates for large biomolecules with complex geometries.
“While the path-based PMF approach appears more tractable, it is still difficult to obtain converged free energy estimates for large biomolecules with complex geometries.53,62−68”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [64]
The Results section (‘Calculation of S* and I* in the PMF-based approach’; page unavailable) says slow molecular motions can severely hamper convergence of the separation PMF, and the Discussion reports convergence problems for PMF restraint terms. The Discussion also presents PMF as a viable route for protein–protein association, but it does not establish that PMF is generally more tractable or specifically assess converged estimates for large biomolecules with complex geometries. (LLM, conf=0.82)
Experimental — accuracy not yet measuredMore precise free energy changes can be obtained through the application of restraints which ensure that the relative orientation and position of the ligand with respect to the receptor is preserved and therefore the available phase space to be sampled during the simulations is reduced.
“More precise free energy changes can be obtained through the application of restraints which ensure that the relative orientation and position of the ligand with respect to the receptor is preserved and therefore the available phase space to be sampled during the simulations is reduced.54,63−65”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [64]
In principle, the binding free energy should be independent of the type of restraints, the atom centers selected for the construction of the restraints, or the values of the force constants, provided stable restraints that have been appropriately selected.
“In principle, the binding free energy should be independent of the type of restraints, the atom centers selected for the construction of the restraints, or the values of the force constants,64,77,86 provided stable restraints that have been appropriately selected.87”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [64]
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- Authors
- Gumbart, J. C., Roux, B., & Chipot, C.
- Affiliations
- Argonne National Laboratory (US)
- Biosciences Division, Argonne National Laboratory, Argonne, Illinois 60439, United States
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Chipot, Christophe
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-11-16
- Volume
- 9
- Issue
- 1
- Pages
- 794-802
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- PMC
- PMC3685508
- OpenAlex
- W2072256473
- Cited by
- 343
- References
- 76
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 18 · 2023: 29 · 2022: 31 · 2021: 20 · 2020: 36 · 2019: 22 · 2018: 26 · 2017: 34 · 2016: 35 · 2015: 22 · 2014: 23 · 2013: 17
- FWCI
- 21.34
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Chemical Theory and Computation (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (R01CA093577)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Keywords
- protein-ligand binding, alchemical free energy calculations, potential of mean force, SH2 domain, Abl tyrosine kinase, proline-rich peptides, collective variables, sampling limitations, entropic contribution, binding affinity prediction
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