title: Predicting the relative binding affinity of mineralocorticoid receptor antagonists by density functional methods.
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 R(2) = 0.76 for the experimental lipophilic ligand efficiency versus relative predicted binding affinity calculated with the M06-2X functional in gas phase and an R(2) = 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.
authors.affiliation: RIA Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden. katarina.roos@gmail.com.
authors.forename: Katarina
authors.initials: K
authors.lastname: Roos
authors.affiliation: CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Hogner
authors.affiliation: Discovery Sciences, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK.
authors.forename: Derek
authors.initials: D
authors.lastname: Ogg
authors.affiliation: Oncology Medicinal Chemistry, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK.
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Packer
authors.affiliation: Discovery Sciences, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
authors.forename: Eva
authors.initials: E
authors.lastname: Hansson
authors.affiliation: CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
authors.forename: Kenneth L
authors.initials: KL
authors.lastname: Granberg
authors.affiliation: RIA Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden.
authors.forename: Emma
authors.initials: E
authors.lastname: Evertsson
authors.affiliation: CVMD Medicinal Chemistry, AstraZeneca, Pepparedsleden 1, 431 83, Mölndal, Sweden. anneli.nordqvist@astrazeneca.com.
authors.forename: Anneli
authors.initials: A
authors.lastname: Nordqvist
mesh_terms: D018360:Crystallography, X-Ray; D006801:Humans; D006860:Hydrogen Bonding; D000451:Mineralocorticoid Receptor Antagonists / Q000737:chemistry* / Q000494:pharmacology*; D062105:Molecular Docking Simulation; D011485:Protein Binding; D011789:Quantum Theory; D018161:Receptors, Mineralocorticoid / Q000737:chemistry / Q000378:metabolism*
chemical_list: D000451:Mineralocorticoid Receptor Antagonists; D018161:Receptors, Mineralocorticoid
keywords: DFT; FEP; Nuclear hormone receptor; QM