Literature DB >> 15743203

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

Youyi Peng1, Susan M Keenan, Qiang Zhang, Vladyslav Kholodovych, William J Welsh.   

Abstract

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.

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Year:  2005        PMID: 15743203     DOI: 10.1021/jm049117e

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  7 in total

1.  Discovery of novel triazole-based opioid receptor antagonists.

Authors:  Qiang Zhang; Susan M Keenan; Youyi Peng; Anil C Nair; Seong Jae Yu; Richard D Howells; William J Welsh
Journal:  J Med Chem       Date:  2006-07-13       Impact factor: 7.446

2.  Quantitative conformationally sampled pharmacophore for delta opioid ligands: reevaluation of hydrophobic moieties essential for biological activity.

Authors:  Denzil Bernard; Andrew Coop; Alexander D MacKerell
Journal:  J Med Chem       Date:  2007-03-17       Impact factor: 7.446

3.  Consensus 3D model of μ-opioid receptor ligand efficacy based on a quantitative Conformationally Sampled Pharmacophore.

Authors:  Jihyun Shim; Andrew Coop; Alexander D MacKerell
Journal:  J Phys Chem B       Date:  2011-05-12       Impact factor: 2.991

4.  A 3D-QSAR model based screen for dihydropyridine-like compound library to identify inhibitors of amyloid beta (Aβ) production.

Authors:  Venkatarajan S Mathura; Nikunj Patel; Corbin Bachmeier; Michael Mullan; Daniel Paris
Journal:  Bioinformation       Date:  2010-09-20

5.  Determination of structural factors affecting binding to mu, kappa and delta opioid receptors.

Authors:  Svetoslav Slavov; William Mattes; Richard D Beger
Journal:  Arch Toxicol       Date:  2020-02-27       Impact factor: 5.153

6.  Discovery of Novel Delta Opioid Receptor (DOR) Inverse Agonist and Irreversible (Non-Competitive) Antagonists.

Authors:  Parthasaradhireddy Tanguturi; Vibha Pathak; Sixue Zhang; Omar Moukha-Chafiq; Corinne E Augelli-Szafran; John M Streicher
Journal:  Molecules       Date:  2021-11-05       Impact factor: 4.927

7.  Toward a Universal μ-Agonist Template for Template-Based Alignment Modeling of Opioid Ligands.

Authors:  Zhijun Wu; Victor J Hruby
Journal:  ACS Omega       Date:  2019-10-09
  7 in total

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