Bernard Denzil, Coop Andrew, MacKerell Alexander D
Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, Maryland 21201, USA.
J Med Chem. 2007 Apr 19;50(8):1799-809. doi: 10.1021/jm0612463. Epub 2007 Mar 17.
Recent studies have indicated several therapeutic applications for delta opioid agonists and antagonists. To exploit the therapeutic potential of delta opioids developing a structural basis for the activity of ligands at the delta opioid receptor is essential. The conformationally sampled pharmacophore (CSP) method (Bernard et al. J. Am. Chem. Soc. 2003, 125, 3103-3107) is extended here to obtain quantitative models of delta opioid ligand efficacy and affinity. Quantification is performed via overlap integrals of the conformational space sampled by ligands with respect to a reference compound. Iterative refinement of the CSP model identified hydrophobic groups other than the traditional phenylalanine residues as important for efficacy and affinity in DSLET and ICI 174 864. The obtained models for a structurally diverse set of peptidic and nonpeptidic delta opioid ligands offer good predictions with R2 values>0.9, and the predicted efficacy for a set of test compounds was consistent with the experimental values.
最近的研究表明δ阿片受体激动剂和拮抗剂有多种治疗应用。为了开发δ阿片类药物的治疗潜力,建立δ阿片受体配体活性的结构基础至关重要。在此扩展了构象采样药效团(CSP)方法(Bernard等人,《美国化学会志》,2003年,125卷,3103 - 3107页)以获得δ阿片受体配体效力和亲和力的定量模型。通过配体相对于参考化合物采样的构象空间的重叠积分进行定量。CSP模型的迭代优化确定了除传统苯丙氨酸残基之外的疏水基团对DSLET和ICI 174 864的效力和亲和力很重要。针对一组结构多样的肽类和非肽类δ阿片受体配体获得的模型具有良好的预测能力,R2值>0.9,并且一组测试化合物的预测效力与实验值一致。