Derivation of a pharmacophore model for anandamide using constrained conformational searching and comparative molecular field analysis

Weida Tong, Elizabeth R. Collantes, William J. Welsh, Barbara A. Berglund, Allyn C. Hewlett

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61 Scopus citations

Abstract

Constrained molecular dynamics simulations on anandamide, together with a systematic distance comparison search, have revealed a specific low-energy conformer whose spatial disposition of the pharmacophoric elements closely matches that of HHC; This conformer enables near superposition of the following: (1) the oxygen of the carboxyamide and the phenolic hydroxyl group of HHC, (2) the hydroxyl group of the ethanol and the cyclohexyl hydroxyl group of HHC, (3) the alkyl tail and the lipophilic side chain of HHC, and (4) the polyolefin loop and the tricyclic ring structure of HHC. The close matching of common pharmacophoric elements of anandamide with HHC offers persuasive evidence of the biological relevance of this conformer. The proposed pharmacophore model was capable of discriminating between structurally related compounds exhibiting different pharmacological potency for the CB1 cannabinoid receptor, i.e., anandamide and N-(2- hydroxyethyl)prostaglandinamide. Furthermore, a 3D-QSAR model was derived using CoMFA for a training set of 29 classical and nonclassical analogues which rationalized the binding affinity in terms of steric and electrostatic properties and, more importantly, which predicted the potency of anandamide in excellent agreement with experimental data. The ABC tricyclic HU-210/HU- 211 and ACD tricyclic CP55,243/CP55,244 enantiomeric pairs were employed as test compounds to validate the present CoMFA mode]. For each enantiomeric pair, the CoMFA-predicted log K(i) values correctly identified that enantiomer exhibiting the higher affinity for the receptor.

Original languageEnglish (US)
Pages (from-to)4207-4215
Number of pages9
JournalJournal of medicinal chemistry
Volume41
Issue number22
DOIs
StatePublished - Oct 23 1998
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Drug Discovery

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