Molecular Dynamics Conformation Of Opioid Peptides

摘要：分子建模方法（分子动力学，构象搜索，蒙特卡罗）使用牛视紫红质的结晶结构数据（不包括细胞内和细胞外结构域），这是迄今为止唯一结晶的哺乳动物7-跨膜受体，为了用硅方法建立delta-阿片受体的模型；即，通过交换特定的氨基酸，计算机定向诱变以确保视紫红质格式的序列与δ -阿片受体的序列一致。多种基于Dmt-Tic药效团的受体激动剂和拮抗剂通过x射线衍射分析得到，这些药物来自三种具有不同特异性的选择性化合物（δ -和μ -阿片受体选择性和非选择性），以及与δ -阿片受体具有非常低亲和力的特异性μ -阿片受体激动剂，被停靠在提出的结合囊中。配体结合结构域最初是根据从文献中获得的定点诱变数据确定的。通过1-H NMR （COSY， NOESY， HOHAHA， ROESY， DQF-COSY实验）和CD在不同溶剂和温度条件下初步检测了这些配体的最小分子模型，反映了它们已知的生物活性和受体亲和性，以及肽的构象变化。就配体而言，芳香环距离可能是区分δ -阿片受体拮抗剂和激动剂的一个非常重要的特征，尽管肽具有固有的灵活性，但它提供了一种假定的“受体结合构象”。正如预期的那样，mu-阿片受体激动剂在δ受体口袋区表现出较差的契合性，证实了该方法的应用。用Dmt-Tic药效团观察到的地形特征将其与所有其他肽区分开来，并与受体口袋中选择的侧链相互作用。数据表明，肽配体和受体的假定受体结合构象涉及芳香环和氢键之间的堆叠，并且μ -阿片激动剂与δ配体特异性残基的相互作用很差。此外，似乎有两个区域的激动剂和拮抗剂相互作用，其中只有一个是由这两种类型的化合物共享。因此，三角洲阿片受体拮抗剂的环内距离可能预示着其在受体内的适合性而存在生物学差异。具有双受体结合特性或选择性的肽类似物同样有助于以预测模式应用分子建模。因此，δ受体模型和我们的δ和μ阿片样物质拮抗剂和激动剂药效团将作为设计新的有效配体的支架。

Summary: Molecular modeling methodologies (molecular dynamics, conformational searching, Monte Carlo) used data from the crystallized structure of bovine rhodopsin (excluding the intracellular and extracellular domains), which is the only mammalian 7-transmembrane receptor crystallized to date, in order to develop a model of the delta-opioid receptor by in silico methods; i.e., computer-directed mutagenesis to ensure that the sequence of the rhodopsin format coincided with that of the delta-opioid receptor by exchanging specific amino acids. A variety of delta agonists and antagonists based on the Dmt-Tic pharmacophore derived from X-ray diffraction analyses of three selective compounds with different specificities (delta- and mu-opioid receptor selective, and non-selective), as well as specific mu-opioid receptor agonists, which should have very low affinity with the delta-opioid receptor, were docked into the proposed binding pocket. The ligand-binding domain was initially determined from data on site-directed mutagenesis obtained from the literature. The minimized molecular models of the ligands reflected their known biological activities and receptor affinities and conformational changes in the peptides were initially examined by 1-H NMR (COSY, NOESY, HOHAHA, ROESY, DQF-COSY experiments), CD under varying solvent and temperature conditions. In terms of the ligands, the aromatic ring distance may be a singularly important characteristic which distinguishes delta-opioid receptor antagonists and agonists for both mu- and delta-opioid receptors providing a presumptive "receptor-bound conformation" in spite of the inherent flexibility of the peptide. As anticipated, mu-opioid receptor agonists exhibited a poor fit in the delta receptor pocket region, confirming the application of this methodology. The topographical features observed with the Dmt-Tic pharmacophore differentiate it from all other peptides and its interaction with select side-chains in the receptor pocket. The data suggest that the presumed receptor-bound conformation of the peptide ligand and receptor involves stacking between aromatic rings and hydrogen bonding and that mu-opioid agonists poorly interacted with those residues specific for delta ligands. Furthermore, there appeared to be two regions in which agonists and antagonists interact, only one of which is shared by these two types of compounds. Thus, intra-ring distance of delta-opioid receptor antagonists may portend biological differences due to its fit within its receptor. Peptide analogues with dual receptor binding characteristics or selectivity for the mu-opioid receptor equally assisted in the application of molecular modeling in a predictive mode. Thus, model of the delta receptor and our delta- and mu-opioid antagonist and agonist pharmacophores will serve as scaffolds in the design of new potent ligands. Based on pharmacophores developed by delta-opioid receptor analogues containing Dmt-Tic and several low energy modles of Dmt-Tic-Bid derivatives, pharmacophores were generated for virtual screening using LigandScout software. Furthermore, pharmacophores were obtained for morphine (mu agonist), Nalt44 and SNC-80 (delta agonists) to validate the pharmacophore screening procedure. The morphine pharmacophore produced more than 1,100 hits, whereas Nalt44 and SNC-80 each generated a single hit in a screen of the Derwent World Drug Index (WDI). Virtual screens of the Dmt-Tic pharmacophores identified 7 hits from WDI: while 4 of these retrieved up to 100 hits and identified seeral Dmt-Tic derivatives in our opioid database, 3 produced hits with features absent but required for opioid binding. Similarly, the same 4 pharmacophores were screened using the ChemDiverse database (ChemDiv) resulting in 3-900 hit, but most lacked "opioid-like" features. However, with modifications, some hits could serve as leads for opioid drug candidates. These methods offer an alternative approach to identify revelant pharmacophores for virtual screening when bioactive ligand conformations and the receptor binding site are unknown.