Evidence map›Paper›PMID 31984465›Full record

ArticleJournal of computer-aided molecular design2020

The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.

Andrea Rizzi, Travis Jensen, David R Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M Henriksen, Bert L de Groot and 7 more

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Potential distribution theory of alchemical transfer.The Journal of chemical physics · 2025
    Article
  7. Article
  8. Automated Adaptive Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Alchemical Free Energy Calculations on Membrane-Associated Proteins.Journal of chemical theory and computation · 2023
    Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Andrea RizziComputational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA. andrea.rizzi@choderalab.org.ORCID 0000-0001-7693-2013
Travis JensenDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, 80309, USA.
David R SlochowerSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, 92093, USA.ORCID 0000-0003-3928-5050
Matteo AldeghiMax Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany.ORCID 0000-0003-0019-8806
Vytautas GapsysMax Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany.ORCID 0000-0002-6761-7780
Dimitris NtekoumesBiomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527, Athens, Greece.
Stefano BosisioEaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh, EH9 3FJ, UK.
Michail PapadourakisEaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh, EH9 3FJ, UK.
Niel M HenriksenSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, 92093, USA.ORCID 0000-0002-7916-0757
Bert L de GrootMax Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany.ORCID 0000-0003-3570-3534
Zoe CourniaBiomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527, Athens, Greece.ORCID 0000-0001-9287-364X
Alex DicksonDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA.ORCID 0000-0002-9640-1380
Julien MichelEaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh, EH9 3FJ, UK.ORCID 0000-0003-0360-1760
Michael K GilsonSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, 92093, USA.ORCID 0000-0002-3375-1738
Michael R ShirtsDepartment of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, 80309, USA.ORCID 0000-0003-3249-1097
David L MobleyDepartment of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, California, 92697, USA. dmobley@uci.edu.ORCID 0000-0002-1083-5533
John D ChoderaComputational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA. john.chodera@choderalab.org.ORCID 0000-0003-0542-119X

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
THEORY AND MODELING OF NONCOVALENT BINDINGR01GM061300 · NIGMS · UNIVERSITY OF MD BIOTECHNOLOGY INSTITUTE · PI GILSON, MICHAEL K. · 2000 to 2021
$7.2M
Predoctoral Training Molecular BiophysicsT32GM065103 · NIGMS · UNIVERSITY OF COLORADO AT BOULDER · PI FALKE, JOSEPH J · 2002 to 2021
$4.3M
Revealing the Ligand Binding Landscape with Advanced Molecular Simulation MethodsR01GM130794 · NIGMS · MICHIGAN STATE UNIVERSITY · PI DICKSON, ALEXANDER · 2018 to 2025
$2.8M
Computational alchemy for molecular design and optimizationR01GM108889 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI MOBLEY, DAVID LOWELL · 2014 to 2022
$2.5M
Advancing predictive physical modeling through focused development of model systems to drive new modeling innovationsR01GM124270 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI MOBLEY, DAVID LOWELL · 2018 to 2021
$1.5M
NCI NIH HHS P30 CA008748NIGMS NIH HHS R01 GM061300NIGMS NIH HHS R01 GM108889NIGMS NIH HHS R01 GM124270NIGMS NIH HHS R01 GM130794NIGMS NIH HHS T32 GM065103
6 · The paper itself

Abstract

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange-while displaying very small variance-can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

Indexed as

ThermodynamicsBridged-Ring CompoundsEntropyImidazolesLigandsMacrocyclic CompoundsPhysical PhenomenaProtein BindingProteinsQuantum TheorySolventsBridged-Ring CompoundsImidazolesLigandsMacrocyclic CompoundsProteinsSolventsBinding affinityCucurbit[8]urilFree energy calculationsHost–guestOcta-acidSAMPL6Sampling

Identifiers

PMID31984465
PMCPMC7282318

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.