Molecular modeling of mono- and bis-quaternary ammonium salts as ligands at the α4β2 nicotinic acetylcholine receptor subtype using nonlinear techniques

Ayers, Joshua T.; Clauset, Aaron; Schmitt, Jens; Dwoskin, Linda P.; Crooks, Peter A.

doi:10.1208/aapsj070368

Cited by 12 publications

(11 citation statements)

References 30 publications

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“…GFA has been used by other researchers as well to develop good QSAR models. 19,20) The goodness of the regression fits are estimated using parameters such as, r 2 (ϭ1ϪSSE/TSS), r 1Ϫr 2 )) and MSSE (ϭmean sum of square of errorϭSSE/n) where, TSSϭtotal sum of squares and SSEϭsum of squares, PRESSϭpredicted sum of squares based on leaveone-out method.…”

Section: Methodsmentioning

confidence: 99%

QSAR Studies on Chalcones and Flavonoids as Anti-tuberculosis Agents Using Genetic Function Approximation (GFA) Method

2007

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Tuberculosis is an infection caused by Mycobacterium tuberculosis, which commonly affects the respiratory tract, i.e. lungs.1) It is termed as "a global health emergency" by world health organization (WHO) in 1993 as it affects 1.7 billion people per year, that is equal to one-third of the entire world population. The first line of drugs used in the treatment of tuberculosis (TB) is a combination of isoniazid, rifampicin, pyrazinamide and ethambutol. The high concentration of lipids in the cell wall of M. tuberculosis has been attributed to its resistant to antibiotics. The lipid fraction of cell wall consists of three major components mycolic acids, cord factor and wax-D. Isoniazid is known to inhibit the synthesis of mycolic acid. Ethambutol is known to inhibit the incorporation of mycolic acid into the cell wall. Rifampicin acts by binding to DNA-dependent RNA polymerase and inhibits initiation of RNA synthesis. Pyrazinoic acid, the active form of pyrazinamide, is reported by Zhang Y., et al. to inhibit M. tuberculosis membrane transport function and disrupt membrane energetics.2) It is expected that the disease can be completely eliminated with the help of combination therapy, but these hopes were dashed with the advent of drug resistant strains. The development of drug resistant strains is due to point mutations in the bacterial chromosome, resulting in changes in the antibiotic target that renders the strain no longer susceptible to the drug.Thus the increasing clinical importance of tuberculosis has lent additional urgency to researchers to identify new and effective antimycobacterial compounds. Literature survey reveals that chalcones, flavones and flavanones possess antiinflammatory, 3) anticancer, 4) antileishmanial, 5) antimalarial, 6) antimicrobial and antioxidant 7) activities. It is reported that the chalcones and their derivatives are more effective against Gram-positive bacteria than against Gram-negative bacteria. 8)But it is interesting to note that they are also effective against this acid-fast bacillus which is neither Gram-positive nor negative. These compounds show very good activity against H37Rv strain. Understanding the effect of structural features on the activity would help the researchers to design new molecules that may exhibit higher activity. Quantitative structure activity relationship (QSAR) approach is better for designing new drugs when the target is not known or if there are multiple targets.QSAR studies on heterocyclic analogues of salicylanilides performed through the combination of Free-Wilson and Hansch approach explains the influences of electronic and hydrophobic properties.9) Gupta M. K., et al. have observed that topological descriptors are correlated with the antimycobacterial activity of nitro/acetamido alkenol and chloro/amino alkenol derivatives.10) 3D-QSAR uses three-dimensional properties of the molecules (particularly steric and electrostatic factors) and correlates these descriptors with the biological activity. 3D-QSAR studies carried out by Shagufta, et al. o...

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Section: Methodsmentioning

confidence: 99%

QSAR Studies on Chalcones and Flavonoids as Anti-tuberculosis Agents Using Genetic Function Approximation (GFA) Method

2007

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“…3D QSAR and QSAR studies on nAChR paralleled the efforts in the development of the pharmacophore models, [95,189,190,193,[195][196][197][198] supporting the rational design and synthesis of novel nicotinic ligands. [60,71,95] The pharmacophoric patterns of nAChR, both from SAR and computational techniques such as DISCO and Catalyst HipHop, were widely used in the conformer selection and in the alignment of the ligands involved in the development of the nicotinic 3D QSAR models, that is, in the construction of mathematical models aimed at uncovering relationships between chemical properties, the 3D molecular features of the compounds, and biological activity of the set of nicotinic ligands.…”

Section: Allosteric Modulatorsmentioning

confidence: 99%

Central Nicotinic Receptors: Structure, Function, Ligands, and Therapeutic Potential

et al. 2007

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The growing interest in nicotinic receptors, because of their wide expression in neuronal and non-neuronal tissues and their involvement in several important CNS pathologies, has stimulated the synthesis of a high number of ligands able to modulate their function. These membrane proteins appear to be highly heterogeneous, and still only incomplete information is available on their structure, subunit composition, and stoichiometry. This is due to the lack of selective ligands to study the role of nAChR under physiological or pathological conditions; so far, only compounds showing selectivity between alpha4beta2 and alpha7 receptors have been obtained. The nicotinic receptor ligands have been designed starting from lead compounds from natural sources such as nicotine, cytisine, or epibatidine, and, more recently, through the high-throughput screening of chemical libraries. This review focuses on the structure of the new agonists, antagonists, and allosteric ligands of nicotinic receptors, it highlights the current knowledge on the binding site models as a molecular modeling approach to design new compounds, and it discusses the nAChR modulators which have entered clinical trials.

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“…Two recent reviews that report on ligand-based models of neuronal nAChR agonists, involving either pharmacophore development or quantitative structure-affinity relationships, have been reported by Glennon et al and Nicolotti et al, respectively [29-30] More recently, QSAR studies in this area that focus on specific types of analogs, have also been reported [31-35]. With regard to quaternary ammonium nAChR antagonists, QSAR studies on a series of mono - and bis -quaternary ammonium salts have been reported by Ayers et al [36]. In this study, the Self Organizing Maps (SOM) approach was used to classify the compounds according to their structures and activities.…”

Section: Resultsmentioning

confidence: 99%

Computational neural network analysis of the affinity of N-n-alkylnicotinium salts for the α4β2* nicotinic acetylcholine receptor

Zheng

Deaciuc

et al. 2008

Journal of Enzyme Inhibition and Medicinal Chemistry

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Based on an 85 molecule database, linear regression with different size datasets and an artificial neural network approach have been used to build mathematical relationships to fit experimentally obtained affinity values (Ki) of a series of mono- and bis-quaternary ammonium salts from [3H]nicotine binding assays using rat striatal membrane preparations. The fitted results were then used to analyze the pattern among the experimental Ki values of a set of N-n-alkylnicotinium analogs with increasing n-alkyl chain length from 1 to 20 carbons. The affinity of these N-n-alkylnicotinium compounds was shown to parabolically vary with increasing numbers of carbon atoms in the n-alkyl chain, with a local minimum for the C4 (n-butyl) analogue. A decrease in Ki value between C12 and C13 was also observed. The statistical results for the best neural network fit of the 85 experimental Ki values are r2 = 0.84, rmsd = 0.39; normalrcv2=0.68, and loormsd = 0.56. The generated neural network model with the 85 molecule training set may also be of value for future predictions of Ki values for new virtual compounds, which can then be identified, subsequently synthesized, and tested experimentally.

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Molecular modeling of mono- and bis-quaternary ammonium salts as ligands at the α4β2 nicotinic acetylcholine receptor subtype using nonlinear techniques

Cited by 12 publications

References 30 publications

QSAR Studies on Chalcones and Flavonoids as Anti-tuberculosis Agents Using Genetic Function Approximation (GFA) Method

QSAR Studies on Chalcones and Flavonoids as Anti-tuberculosis Agents Using Genetic Function Approximation (GFA) Method

Central Nicotinic Receptors: Structure, Function, Ligands, and Therapeutic Potential

Computational neural network analysis of the affinity of N-n-alkylnicotinium salts for the α4β2* nicotinic acetylcholine receptor

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