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Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

Misini Ignjatović, Majda ; Caldararu, Octav LU ; Dong, Geng LU ; Muñoz-Gutierrez, Camila ; Adasme-Carreño, Francisco and Ryde, Ulf LU orcid (2016) In Journal of Computer-Aided Molecular Design 30(9). p.707-730
Abstract

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then,... (More)

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970–1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bennett acceptance ratio, Big-QM, Blind-test competition, Continuum solvation, D3R grand challenge, Free-energy perturbation, Induced-fit docking, Ligand-binding affinity, MM/GBSA, QM/MM
in
Journal of Computer-Aided Molecular Design
volume
30
issue
9
pages
24 pages
publisher
Springer
external identifiers
  • scopus:84983775745
  • pmid:27565797
  • wos:000387088900005
ISSN
0920-654X
DOI
10.1007/s10822-016-9942-z
language
English
LU publication?
yes
id
a4a2291a-b48c-42af-9e70-008428b96c43
date added to LUP
2016-12-02 08:30:58
date last changed
2024-07-27 23:38:12
@article{a4a2291a-b48c-42af-9e70-008428b96c43,
  abstract     = {{<p>We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970–1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.</p>}},
  author       = {{Misini Ignjatović, Majda and Caldararu, Octav and Dong, Geng and Muñoz-Gutierrez, Camila and Adasme-Carreño, Francisco and Ryde, Ulf}},
  issn         = {{0920-654X}},
  keywords     = {{Bennett acceptance ratio; Big-QM; Blind-test competition; Continuum solvation; D3R grand challenge; Free-energy perturbation; Induced-fit docking; Ligand-binding affinity; MM/GBSA; QM/MM}},
  language     = {{eng}},
  month        = {{09}},
  number       = {{9}},
  pages        = {{707--730}},
  publisher    = {{Springer}},
  series       = {{Journal of Computer-Aided Molecular Design}},
  title        = {{Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations}},
  url          = {{https://lup.lub.lu.se/search/files/20966856/hsp90.pdf}},
  doi          = {{10.1007/s10822-016-9942-z}},
  volume       = {{30}},
  year         = {{2016}},
}