QSAR study of 4-phenylpiperidine derivatives as μ opioid agonists by neural network method

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

Addiction is a complex behavioral phenomenon in which naturally occurring or synthetic chemicals modulate the response of the reward system through their binding to a variety of neuroreceptors, resulting in compulsive substance-seeking and use despite harmful consequences to the individual. Among these, the opioid receptor (OR) family and more specifically, the mu-opioid receptor (MOR) subtype plays a critical role in the addiction to powerful prescription and illicit drugs such as hydrocodone, oxycodone, fentanyl, cocaine, and methamphetamine (Contet et al. in Curr Opin Neurobiol 14(3):370-378, 2004). Conversely, agonists binding to kappa (KOR) and antagonists binding to delta opioid receptors (DOR) have been reported to induce negative reinforcing effects. As more than 700 new psychoactive substances were illegally sold between 2009 and 2016 (DEA-DCT-DIR-032-18), most of them lacking basic toxicological and pharmacological profiles, molecular modeling approaches that could quickly and reliably fill the gaps in our knowledge would be highly desirable tools for determining the effects of these synthetics. Here, we report accurate 3D-spectrometric data-activity relationship classification models for large and diverse datasets of MOR, KOR and DOR binders with areas under the receiver operating characteristic curve for the "blind" prediction sets exceeding 0.88. Structural features associated with (selective) binding to MOR, KOR and/or DOR were identified. These models could assist regulatory agencies in evaluating the health risks associated with the use of unprofiled substances as well as to help the pharmaceutical industry in its search for new drugs to combat addiction.

Design, synthesis, characterization, and computational studies on benzamide substituted Mannich bases as novel, potential antibacterial agents

A series of benzamide substituted Mannich bases (1–7) were synthesized. The synthesized derivatives were authenticated by TLC, UV-Visible, FTIR, NMR, and mass spectroscopic techniques and further screened for in vitro antibacterial activity by test tube dilution method using amoxicillin and cefixime as standard drugs. The compounds 5, 6, and 7 were found to be the most active antibacterial agents among all the synthesized compounds. The physicochemical similarity of the compounds with standard drugs was assessed by calculating various physicochemical properties using software programs. The percent similarity of synthesized compounds was found to be good and compound 1 was found to have higher percentage of similarity. The compounds were subjected to QSAR by multilinear regression using Analyze it version 3.0 software, and four statistically sound models were developed with R² (0.963–0.997), R_adj² (0.529–0.982), and Q² (0.998–0.999) with good F (2.35–65.56) values.

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

Despite being studied for over 30 years, a consensus structure-activity relationship (SAR) that encompasses the full range peptidic and nonpeptidic μ-opioid receptor ligands is still not available. To achieve a consensus SAR the Conformationally Sampled Pharmacophore (CSP) method was applied to develop a predictive model of the efficacy of μ-opioid receptor ligands. Emphasis was placed on predicting the efficacy of a wide range of agonists, partial agonists, and antagonists as well as understanding their mode of interaction with the receptor. Inclusion of all accessible conformations of each ligand, a central feature of the CSP method, enabled structural features between diverse μ-opioid receptor ligands that dictate efficacy to be identified. The models were validated against a diverse collection of peptidic and nonpeptidic ligands, including benzomorphans, fentanyl (4-anilinopiperidine), methadone (3,3-diphenylpropylamines), etonitazene (benzimidazole derivatives), funaltrexamine (C6-substituted 4,5-epoxymorphinan), and herkinorin. The model predicts (1) that interactions of ligands with the B site, as with the 19-alkyl substituents of oripavines, modulate the extent of agonism; (2) that agonists with long N-substituents, as with fentanyl and N-phenethylnormorphine, can bind in an orientation such that the N substitutent interacts with the B site that also allows the basic N-receptor Asp interaction essential for agonism; and (3) that the μ agonist herkinorin, that lacks a basic nitrogen, binds to the receptor in a manner similar to the traditional opioids via interactions mediated by water or a ion. Importantly, the proposed CSP model can be reconciled with previously published SAR models for the μ receptor.

QSAR models to predict mutagenicity of acrylates, methacrylates and alpha,beta-unsaturated carbonyl compounds

OBJECTIVE

The purpose of this study is to develop a quantitative structure-activity relationship (QSAR) model that can distinguish mutagenic from non-mutagenic species with alpha,beta-unsaturated carbonyl moiety using two endpoints for this activity - Ames test and mammalian cell gene mutation test - and also to gather information about the molecular features that most contribute to eliminate the mutagenic effects of these chemicals.

METHODS

Two data sets were used for modeling the two mutagenicity endpoints: (1) Ames test and (2) mammalian cells mutagenesis. The first one comprised 220 molecules, while the second one 48 substances, ranging from acrylates, methacrylates to alpha,beta-unsaturated carbonyl compounds. The QSAR models were developed by applying linear discriminant analysis (LDA) along with different sets of descriptors computed using the DRAGON software.

RESULTS

For both endpoints, there was a concordance of 89% in the prediction and 97% confidentiality by combining the three models for the Ames test mutagenicity. We have also identified several structural alerts to assist the design of new monomers.

SIGNIFICANCE

These individual models and especially their combination are attractive from the point of view of molecular modeling and could be used for the prediction and design of new monomers that do not pose a human health risk.

What makes a molecule an anaesthetic? Studies on the mechanisms of anaesthesia using a physicochemical approach

Recent studies of mechanisms of anaesthesia have been mainly 'target orientated', investigating the activity of both volatile and i.v. agents at putative sites of action. An alternative approach is one that is 'ligand orientated', focusing on the properties of molecules that define their immobilizing ability and secondly define their potency. The use of conventional descriptors (such as non-polar solubility or the octanol-water partition coefficient [Log P]) are limited in their utility as predictors of potency as they represent three-dimensional molecular properties as a one-dimensional parameter. Using different computer-based molecular modelling methods (molecular similarity studies and comparative molecular field analysis [CoMFA]), we have identified the molecular bases of the activity of structurally diverse anaesthetics, such that they can be described as a single model based on the spatial distribution of molecular bulk and electrostatic potential. The same approach can also be used to model other properties of anaesthetic agents, such as cardiovascular depression. The present data suggest that, for the i.v. agents, it may be difficult to separate immobilizing (anaesthetic) activity and cardiovascular depression within a single molecule.

Endogenous opiates and behavior: 2006

This paper is the 29th consecutive installment of the annual review of research concerning the endogenous opioid system, now spanning 30 years of research. It summarizes papers published during 2006 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior (Section 2), and the roles of these opioid peptides and receptors in pain and analgesia (Section 3); stress and social status (Section 4); tolerance and dependence (Section 5); learning and memory (Section 6); eating and drinking (Section 7); alcohol and drugs of abuse (Section 8); sexual activity and hormones, pregnancy, development and endocrinology (Section 9); mental illness and mood (Section 10); seizures and neurological disorders (Section 11); electrical-related activity and neurophysiology (Section 12); general activity and locomotion (Section 13); gastrointestinal, renal and hepatic functions (Section 14); cardiovascular responses (Section 15); respiration and thermoregulation (Section 16); and immunological responses (Section 17).

Novel 1-oxyl-2-substitutedphenyl-4,4,5,5-tetramethylimidazolines: Synthesis, selectively analgesic action, and QSAR analysis

Based on the knowledge that imidazoline can result in analgesic action due to its selective binding with the prostacyclin receptor, 20 1-oxyl-2-substitutedphenyl-4,4,5,5-tetramethylimidazolines (3a-t) were prepared in moderate yields. At 0.13 mmol/kg dose, their in vivo analgesic activities were evaluated after the mice were administered at 30, 60, 90, and 150 min. Compared with the pain threshold (12.27+/-9.56-17.71+/-7.00%) of normal saline (NS) receiving mice, the pain threshold (23.42+/-8.14% to 102.58+/-10.66%) of 3a-t receiving mice increases significantly. Considering a prostacyclin receptor targeting analgesic agent usually had bleeding action and to appraise the bleeding risk, the in vivo tail bleeding time of 1.30 mmol/kg 3a-t receiving mice was found to be ranged from 116.3+/-8.2s to 120.3+/-9.2s, which was substantially equal to that (117.8+/-8.4s to 119.0+/-8.6s) of NS receiving mice. Based on the possibility of imidazoline acting as vasodilator, the in vitro vasorelaxations of 3a-t were tested using the rat aortic strip model. When the aortic strip contracted by noradrenaline (NE, final concentration 10(-7)mol/l) was treated with 3a-t (final concentration 5 x 10(-4)mol/l), only lower percentage inhibitions (6.55+/-5.70-37.40+/-4.07%) were recorded, implying that the vasorelaxation of 3a-t was neglectable. By selecting appropriate molecular descriptors generated from e-dragon server, the QSAR model of the analgesic activities of 3a-t was constructed using the multiple linear regression method. The established QSAR model showed reasonable accuracy and thus it is promising to be used for screening new 1-oxyl-2-substitutedphenyl-4,4,5,5-tetramethylimidazoline derivatives as analgesic agents.