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Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR

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Abstract

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

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Abbreviations

FRET:

Fluorescence resonance energy transfer

M2H:

Mammalian-2-hybrid assay

MD:

Molecular dynamics

MMPBSA:

Molecular mechanics poisson boltzmann surface area calculations

NR:

Nuclear receptor

RMSD:

Root-mean-square deviation

SASA:

Solvent-accessible surface area

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Acknowledgements

Y.W., S.R.-C. and X. B. thank Servier for financial support.

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Authors and Affiliations

  1. Facultat de Farmàcia & Institut de Biomedicina de la Universitat de Barcelona (IBUB), Av. Joan XXIII, s/n, 08028, Barcelona, Spain

    Yvonne Westermaier, Sergio Ruiz-Carmona & Xavier Barril

  2. Catalan Institution for Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010, Barcelona, Spain

    Xavier Barril

  3. PEX Biotechnologie, Chimie & Biologie, Institut de Recherches Servier, 125 chemin de Ronde, 78290, Croissy-sur-Seine, France

    Yvonne Westermaier, Isabelle Theret, Françoise Perron-Sierra, Guillaume Poissonnet, Jean A. Boutin & Pierre Ducrot

  4. Pôle d’Innovation Thérapeutique Métabolisme, Institut de Recherches Servier, 3 rue de la République, 92150, Suresnes, France

    Catherine Dacquet

Authors
  1. Yvonne Westermaier
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  2. Sergio Ruiz-Carmona
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  3. Isabelle Theret
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  4. Françoise Perron-Sierra
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  5. Guillaume Poissonnet
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  6. Catherine Dacquet
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  7. Jean A. Boutin
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  8. Pierre Ducrot
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  9. Xavier Barril
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Corresponding author

Correspondence to Pierre Ducrot.

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Westermaier, Y., Ruiz-Carmona, S., Theret, I. et al. Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR. J Comput Aided Mol Des 31, 755–775 (2017). https://doi.org/10.1007/s10822-017-0040-7

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  • DOI: https://doi.org/10.1007/s10822-017-0040-7

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