Predicting Absolute Ligand Binding Free Energies to a Simple Model Site
Open accessAbstract
A central challenge in structure-based ligand design is the accurate prediction of binding free energies. Here we apply alchemical free energy calculations in explicit solvent to predict ligand binding in a model cavity in T4 lysozyme. Even in this simple site, there are challenges. We made systematic improvements, beginning with single poses from docking, then including multiple poses, additional protein conformational changes, and using an improved charge model. Computed absolute binding free energies had an RMS error of 1.9 kcal/mol relative to previously determined experimental values. In blind prospective tests, the methods correctly discriminated between several true ligands and decoys in a set of putative binders identified by docking. In these prospective tests, the RMS error in predicted binding free energies relative to those subsequently determined experimentally was only 0.6 kcal/mol. X-ray crystal structures of the new ligands bound in the cavity corresponded closely to predictions from the free energy calculations, but sometimes differed from those predicted by docking. Finally, we examined the impact of holding the protein rigid, as in docking, with a view to learning how approximations made in docking affect accuracy and how they may be improved.
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More rigorous free energy methods such as alchemical binding free energy calculations have become established for the computation of binding free energies of small molecules to proteins with MD.
“More rigorous free energy methods such as alchemical binding free energy calculations have become established for the computation of binding free energies of small molecules to proteins with MD.55−60”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [55]
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Alibay, I., Magarkar, A., Seeliger, D., & Biggin, P. (2022) · Communications Chemistry · doi:10.1038/s42004-022-00721-4 · Cited by 61 · see citing works
“4, the helicity of this loop region changes between the initial models used for ligands 3 – 20, 28 and 31 (PDB IDs: 2XDL and 2XAB) to the ones used for ligands 21 – 27, 29 – 30 (PDB ID: 2XHT and 2XHX).”
BackgroundMethodConformational Transitions and Convergence of Absolute Binding Free Energy Calculations
Lapelosa, M., Gallicchio, E., & Levy, R. (2012) · Journal of Chemical Theory and Computation · doi:10.1021/ct200684b · Cited by 60 · see citing works
Drug Design: Free-energy calculations in structure-based drug design
Shirts, M., Mobley, D., & Brown, S. P. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511730412.007 · Cited by 60 · see citing works
Self-citationSuitability of MMGBSA for the selection of correct ligand binding modes from docking results
Ahinko, M., Niinivehmas, S. P., Jokinen, E. M., & Pentikäinen, O. (2018) · Chemical Biology and Drug Design · doi:10.1111/cbdd.13446 · Cited by 59 · see citing works
“Especially in cases of multiple possible binding modes, this inability may cause a substantial decrease in the precision of the free energy calculation [24,25].”
BackgroundJo, S., & Jiang, W. (2015) · Computer Physics Communications · doi:10.1016/j.cpc.2015.08.030 · Cited by 70 · see citing works
Blind Prediction of Charged Ligand Binding Affinities in a Model Binding Site
Rocklin, G. J., Boyce, S. E., Fischer, M. M., Fish, I., Mobley, D. L., Shoichet, B. K., & Dill, K. A. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.07.030 · Cited by 58 · see citing works
“Previous blind predictive studies using this force field have suggested that free-energy calculations can predict binding affinities for hydrophobic and polar compounds if the proper ligand pose is sampled and calculations converge [6,10].”
InfluentialSelf-citationEffect of Input Differences on the Results of Docking Calculations
Feher, M., & Williams, C. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci9000629 · Cited by 59 · see citing works
Challenges encountered applying equilibrium and non-equilibrium binding free energy calculationsPreprint
Baumann, H., Gapsys, V., de Groot, B. L., & Mobley, D. (2020) · Journal of Physical Chemistry B · doi:10.26434/chemrxiv.13225181.v1 · Cited by 56 · see citing works
Self-citationWang, E., Liu, H., Wang, J.-M., Weng, G.-Q., Sun, H.-Y., Wang, Z., Kang, Y., & Hou, T.-J. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00024 · Cited by 56 · see citing works
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Copernicus: A new paradigm for parallel adaptive molecular dynamics
Pronk, S., Bowman, G., Hess, B., Larsson, P., Haque, I., Pande, V., Pouya, I., Beauchamp, K., Kasson, P., & Lindahl, E. (2011) · 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1145/2063384.2063465 · Cited by 54 · see citing works
“Computer simulations of biomolecules, in particular proteins, have yielded fundamental insights into how these building blocks of life work [1], fold into functional form [15] and interact [14].”
BackgroundGao, C., Park, M.-S., & Stern, H. A. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2009.11.018 · Cited by 54 · see citing works
- Authors
- Mobley, D. L., Graves, A. P., Chodera, J. D., McReynolds, A. C., Shoichet, B. K., & Dill, K. A.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Shoichet, Brian K.
- Dill, Ken A.
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 2007-08
- Volume
- 371
- Issue
- 4
- Pages
- 1118-1134
- ISSN
- 0022-2836 (ISSN-L)
- PMC
- PMC2104542
- OpenAlex
- W2128494768
- Cited by
- 310
- References
- 0
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 19 · 2023: 8 · 2022: 21 · 2021: 11 · 2020: 14 · 2019: 10 · 2018: 20 · 2017: 12 · 2016: 21 · 2015: 12 · 2014: 12 · 2013: 19 · 2012: 24
- FWCI
- 23.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (GM63592)
- U.S. Air Force
- University of California, San Francisco
- National Institute of General Medical Sciences (R01GM063592, R56GM063592, R01GM034993, GM59957, R01GM059957, GM63592)
- 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 › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Keywords
- absolute binding free energy, alchemical free energy calculations, T4 lysozyme, structure-based ligand design, explicit solvent, protein conformational change, charge model, docking, decoy discrimination, protein-ligand binding
- MeSH terms
- Binding Sites, Computer Simulation, Ligands, Models, Molecular, Protein Binding, Proteins, Temperature, Titrimetry, Protein Structure, Tertiary, Crystallography, X-Ray, Hydrophobic and Hydrophilic Interactions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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