Cited by 59Protein Structure and DynamicsComputational Drug Discovery MethodsEnzyme Structure and Function

Evaluation of Predicted Protein–Protein Complexes by Binding Free Energy Simulations

Siebenmorgen, Till, Zacharias, Martin·2019·Journal of Chemical Theory and Computation

Abstract

The accurate prediction of protein-protein complex geometries is of major importance to ultimately model the complete interactome of interacting proteins in a cell. A major bottleneck is the realistic free energy evaluation of predicted docked structures. Typically, simple scoring functions applied to single-complex structures are employed that neglect conformational entropy and often solvent effects completely. The binding free energy of a predicted protein-protein complex can, however, be calculated using umbrella sampling (US) along a predefined dissociation/association coordinate of a complex. We employed atomistic US-molecular dynamics simulations including appropriate conformational and axial restraints and an implicit generalized Born solvent model to calculate binding free energies of a large set of docked decoys for 20 different complexes. Free energies associated with the restraints were calculated separately. In principle, the approach includes all energetic and entropic contributions to the binding process. The evaluation of docked complexes based on binding free energy calculation was in better agreement with experiment compared to a simple scoring based on energy minimization or MD refinement using exactly the same force field description. Even calculated absolute binding free energies of structures close to the native binding geometry showed a reasonable correlation to experiment. However, still for a number of complexes docked decoys of lower free energy than near-native geometries were found indicating inaccuracies in the force field or the implicit solvent model. Although time consuming the approach may open up a new route for realistic ranking of predicted geometries based on calculated free energy of binding.

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Crossref · 10.1021/acs.jctc.8b01022

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  • When applied to protein assemblies, MM-PBSA and MM-GBSA frequently produce binding free estimates with large statistical errors and make approximations, such as neglecting or partially accounting for the effects of changes in internal energy and entropy on protein association free energies, resulting in limited accuracy.

    “However, when applied to protein assemblies, these methods frequently produce binding free estimates with large statistical errors53 and make a number of approximations, such as neglecting or partially accounting for the effects of changes in internal energy and entropy on protein association free energies, resulting in limited accuracy.54”
  • 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”

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Authors
Siebenmorgen, T., & Zacharias, M.
Affiliations
Technical University of Munich (DE)
Corresponding author
Zacharias, Martin
Venue
Journal of Chemical Theory and Computation
Published
2019-01-30
Volume
15
Issue
3
Pages
2071-2086
ISSN
  • 1549-9618 (ISSN-L)
  • 1549-9626
OpenAlex
W2913931455
Cited by
59
References
3
Citations by year
2026: 6 · 2025: 2 · 2024: 8 · 2023: 11 · 2022: 8 · 2021: 11 · 2020: 7 · 2019: 6
FWCI
2.65
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Chemical Theory and Computation (publishedVersion)
  • PubMed (publishedVersion)
Funders
Deutsche Forschungsgemeinschaft (SFB 863/A10)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
Keywords
protein-protein complex, binding free energy, umbrella sampling, molecular dynamics, conformational entropy, solvent effects, force field accuracy, protein-protein interaction, docking scoring functions
MeSH terms
Animals, Humans, Protein Binding, Protein Conformation, Proteins, Thermodynamics, Protein Interaction Mapping, Databases, Protein, Molecular Dynamics Simulation, Protein Interaction Maps, Molecular Docking Simulation

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