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Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods

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Abstract

In drug discovery, prediction of binding affinity ahead of synthesis to aid compound prioritization is still hampered by the low throughput of the more accurate methods and the lack of general pertinence of one method that fits all systems. Here we show the applicability of a method based on density functional theory using core fragments and a protein model with only the first shell residues surrounding the core, to predict relative binding affinity of a matched series of mineralocorticoid receptor (MR) antagonists. Antagonists of MR are used for treatment of chronic heart failure and hypertension. Marketed MR antagonists, spironolactone and eplerenone, are also believed to be highly efficacious in treatment of chronic kidney disease in diabetes patients, but is contra-indicated due to the increased risk for hyperkalemia. These findings and a significant unmet medical need among patients with chronic kidney disease continues to stimulate efforts in the discovery of new MR antagonist with maintained efficacy but low or no risk for hyperkalemia. Applied on a matched series of MR antagonists the quantum mechanical based method gave an R2 = 0.76 for the experimental lipophilic ligand efficiency versus relative predicted binding affinity calculated with the M06-2X functional in gas phase and an R2 = 0.64 for experimental binding affinity versus relative predicted binding affinity calculated with the M06-2X functional including an implicit solvation model. The quantum mechanical approach using core fragments was compared to free energy perturbation calculations using the full sized compound structures.

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Abbreviations

BACE-1:

β-Site APP cleaving enzyme

DFT:

Density functional theory

FEP:

Free energy perturbation

LBD:

Ligand binding domain

LBP:

Ligand binding pocket

LLE:

Lipophilic ligand efficiency

logD7.4 :

Logarithm of the distribution coefficient in octanol/water at pH 7.4

MDR:

Minimum discriminatory ratio

MR:

Mineralocorticoid receptor

QM:

Quantum mechanical

REST:

Replica exchange with solute tempering

SPA:

Scintillation proximity assay

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Acknowledgments

The authors thank DMPK for logD7.4 profiling of the compounds, Marianne Wedin and Ulla Karlsson for performing MR binding assay experiments. We also thank Mats Svensson for valuable discussions and scientific input.

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Authors and Affiliations

  1. RIA Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden

    Katarina Roos & Emma Evertsson

  2. CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden

    Anders Hogner, Kenneth L. Granberg & Anneli Nordqvist

  3. Discovery Sciences, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK

    Derek Ogg

  4. Oncology Medicinal Chemistry, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK

    Martin J. Packer

  5. Discovery Sciences, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden

    Eva Hansson

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  1. Katarina Roos
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  2. Anders Hogner
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  3. Derek Ogg
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Correspondence to Katarina Roos or Anneli Nordqvist.

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Roos, K., Hogner, A., Ogg, D. et al. Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods. J Comput Aided Mol Des 29, 1109–1122 (2015). https://doi.org/10.1007/s10822-015-9880-1

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