QSAR Study (qsar + study)

Distribution by Scientific Domains

Selected Abstracts

Probing Small-Molecule Binding to the Liver-X Receptor: A Mixed-Model QSAR Study

Morena Spreafico
Abstract The LXR model has been added in the VirtualToxLab, a fully automated technology that allows for the identification of the endocrine-disrupting potential of drugs, chemicals and natural products. This protocol has then been applied to screen a series of 161 natural compounds probing their binding to the LXR. The results of the simulation were compared with experimental data (where available) and suggest that the LXR model can be applied to predict the binding affinity of existing or hypothetical compounds for screening purposes. The binding of 52 ligands towards the liver X receptors (LXRs) was identified trough docking to the three-dimensional protein structure and quantified by multidimensional QSAR (mQSAR), an approach referred to as ,mixed-model QSAR'. The model was validated by the prediction of 17 external compounds (oxysterols) present neither in the training nor in the test set. The robustness of the model was verified by consensus scoring using a conceptually different methodology, and chance correlation was ruled out by a series of scramble tests. [source]

A 3-D QSAR Study of Catechol- O -Methyltransferase Inhibitors Using CoMFA and CoMSIA

Chunzhi Ai
Abstract Inhibitors of Catechol- O -Methyltransferase (COMT) play an important role in the treatment of Parkinson's Disease (PD). A new Three-Dimensional Quantitative Structure,Activity Relationship (3-D QSAR) analysis was performed on 36 previously reported COMT inhibitors employing Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methodologies to correlate the molecular fields and percent inhibition values and three predictive models were derived. The CoMFA and CoMSIA models with steric and electrostatic field yielded cross-validated rs of 0.585 and 0.528, respectively whereas the conventional rs were 0.979 and 0.891, respectively. The CoMSIA model with hydrophobic field exhibited a r of 0.544 and a r of 0.930. The individual inspection of 3-D contours generated from these models helps in understanding the possible region for structural modification of molecules to improve the inhibitory bioactivity. These 3-D QSAR models are also useful for designing and predicting novel COMT inhibitors. [source]

QSAR Study of 2,3-Benzodiazepin-4(thi)one- and 1,2-Phthalazine-Related Negative Allosteric Modulators of the AMPA Receptor: A Structural Descriptors-Based Reassessment

Peter Buchwald
Abstract In an attempt to establish statistically more rigorous and chemically more meaningful quantitative structure-activity relationship (QSAR) equations, a reassessment of a recent study of in vivo anticonvulsant activity for a set of 2,3-benzodiazepin-4(thi)one- and 1,2-phthalazine-related allosteric AMPA antagonists (n=61) is presented. Contrary to the original, relatively nonspecific descriptor set, which included, for example, a number of topological descriptors, specific structural descriptors that are much easier to interpret from a medicinal chemical point of view are used in this multiple linear regression-based approach. Only statistically significant descriptors have been retained in the final equation, and whereas they give about the same correlation as those of the original paper on the training set (r2 of 0.79 vs. 0.76, n=49), they perform much better on the test set (predictive r of 0.73 vs. 0.05; r2 of 0.78 vs. 0.08, n=12). Descriptors found to be relevant are clearly related to substitutions at known pharmacophore positions, such as those corresponding to the 2,3-, 7,8- and 4,-positions of the benzodiazepine skeleton. Therefore, by a more careful selection of the descriptor set, both an improved prediction and a more intuitive quantitative interpretation could be achieved for this set of allosteric AMPA antagonists. [source]

Molecular Structure and QSAR Study on Antispasmodic Activity of some Xanthoxyline Derivatives

Rodrigo dos Santos
Abstract Semi-empirical molecular orbital calculations at AM1 level were done with the aim to investigate the structure-activity relationships of antispasmodic activities of ten 2-(X-benzyloxy)-4,6-dimethoxyacetophenones with X = H, 4,-F, 4,-NO2, 4,-CH3, 4,-Cl, 3,,4,-(CH3)2, 4,-OCH3, 4,-Br, 4,-OCH2C6H5, and 4,-C(CH3)3, against acetylcholine-induced contraction of the guinea pig ileum. The most significant quantum chemical descriptors for this series of compounds were the net atomic charges, nucleophilic and electrophilic frontier electron density, HOMO and LUMO orbitals, and reactivity indices. While no significant correlations were found employing molecular parameters such as heat of formation, dipole moment, molecular polarizability, and so on, good correlations were obtained using the reactivity indices of HOMO and LUMO orbitals at specific atoms of the molecules. These results indicate that the spatial distribution of HOMO and LUMO orbitals over these specific atoms play an important role for an increase of biological activity. [source]

New Route to Synthesis and QSAR Study of 1,2,4-Aryl Substituted Triazoles.

CHEMINFORM, Issue 49 2004
M. B. Deshmukh
Abstract For Abstract see ChemInform Abstract in Full Text. [source]

Hantzsch 1,4-dihydropyridines containing a nitrooxyalkyl ester moiety to study calcium channel antagonist structure,activity relationships and nitric oxide release

Jeffrey-Tri Nguyen
Abstract A group of 3-nitrooxyalkyl 5-alkyl 1,4-dihydro-2,6-dimethyl-4-(pyridyl)-3,5-pyridinedicarboxylates were prepared using a modified Hantzsch reaction that involved the condensation of a nitrooxyalkyl acetoacetate with an alkyl 3-aminocrotonate and a pyridinecarboxaldehyde. 1H NMR nuclear Overhauser enhancement (nOe) studies for 3-(3-nitrooxypropyl) 5-isopropyl 1,4-dihydro-2,6-dimethyl-4-(2-pyridyl)-3,5-pyridinedicarboxylate (17) indicates a predominant rotamer exists in solution where the pyridyl nitrogen atom is orientated above the 1,4-DHP ring system, and the pyridyl nitrogen atom is antiperiplanar to the 1,4-DHP ring H-4 proton. Variable temperature 1H NMR studies (,30 to +60°C) showed the 1,4-DHP NH proton in 17 is H-bonded in CHCl3 solution. This interaction is believed to be due to intermolecular H-bonding between the pyridyl nitrogen free electron pair and the 1,4-DHP NH proton. In vitro calcium channel antagonist (CCA) activities were determined using a muscarinic-receptor-mediated Ca+2 -dependent contraction of guinea pig ileal longitudinal smooth muscle assay. This class of compounds exhibited lower CCA activity (IC50 = 5.3 × 10,6 to 3.5 × 10,8 M range) than the reference drug nifedipine (IC50 = 1.4 × 10,8 M). For compounds having C-3 ,CH2CH2ONO2 and C-4 pyridyl substituents, the C-5 alkyl was a determinant of CCA (i -Pr > the approximately equipotent i -Bu, t -Bu, and Et analogs). The point of attachment of the isomeric C-4 pyridyl substituent was a determinant of CCA when C-3 ,CH2CH2ONO2 and C-5 i -Pr substituents were present providing the potency profile 2-pyridyl , 3-pyridyl > 4-pyridyl. CCA with respect to the C-3 nitrooxyalkyl substituent was inversely dependent on the length of the alkyl spacer. The percent nitric oxide (·NO) released in vitro by this group of compounds (range of 0.03,0.43%/ONO2 group), quantified as nitrite by reaction with the Griess reagent, was lower than that for the reference drug glycerol trinitrate (3.81%/ONO2 group). Nitric oxide release studies showed that the %·NO released was dependent on the number of ONO2 groups/molecule. A QSAR study for this group of compounds showed a correlation between the specific polarizability descriptor (SpPol) and %·NO release. Drug Dev. Res. 51:233,243, 2000. © 2001 Wiley-Liss, Inc. [source]

QSAR study of ,-lactam antibiotic efflux by the bacterial multidrug resistance pump AcrB,

Márcia M. C. Ferreira
Abstract AcrAB-TolC is the most important efflux pump system of Gram-negative bacteria, responsible for their resistance to lipophilic and amphilic drugs. In this work, HCA,PCA studies were performed to investigate the relationship between efflux activities (negative logarithm of minial inhibitor concentration, pMIC) of three strains of S. thypimurium with respect to ,-lactams, and to analyze the relationship between lipophilicity parameters calculated by different methods. The analyses demonstrate that pMICs strongly depend on properties of both bacterial strains and drug molecules, and that lipophilicity parameters do not necessarily contain the same information about the drugs. QSAR studies have shown that the calculated lipophilicities, in some cases, are non linearly related to the pMICs originated by active AcrAB-TolC bacterial pumps, due to the existence of ,-lactams with nitrogen- and sulfur-rich substituents. Among the most important ,-lactam molecular properties quantitatively related to pMICs are lipophilicity and electronic and hydrogen,bonding properties. Parameters describing these properties were included in the QSAR study to obtain parsimonius regression models for MICs. ,-Lactams were classified as good, moderately good and poor AcrAB-TolC substrates. Their stereoelectronic molecular properties, especially the Y-component of the molecular dipole moment and hydrogen binding properties, reflected this classification. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Omeprazole and analogue compounds: a QSAR study of activity against Helicobacter pylori using theoretical descriptors,

Aline Thais Bruni
Abstract Omeprazole and analogues were studied with respect to their activity as inhibitors of urease Helicobacter pylori. Conformational analysis was performed according to the method proposed by Bruni et al. Theoretical descriptors were calculated by an ab initio method (6,31G** basis set). Since several minimum energy structures were obtained for each compound, and the calculated descriptors proved to be sensitive to the structural conformation, different criteria were proposed for conformation selection. Three data sets were generated wherein conformations were grouped according to minimum heat of formation, minimum electronic energy and structural similarity. For these three sets, experimental per cent of control was used to develop quantitative structure,activity models by PLS. Their cross-validation and correlation coefficients were very good (Q2,=,0.97 and R2,=,0.99 on average) and the standard error of validation was much smaller in comparison with results from the literature. Copyright © 2002 John Wiley & Sons, Ltd. [source]

A self-adaptive genetic algorithm-artificial neural network algorithm with leave-one-out cross validation for descriptor selection in QSAR study

Jingheng Wu
Abstract Based on the quantitative structure-activity relationships (QSARs) models developed by artificial neural networks (ANNs), genetic algorithm (GA) was used in the variable-selection approach with molecule descriptors and helped to improve the back-propagation training algorithm as well. The cross validation techniques of leave-one-out investigated the validity of the generated ANN model and preferable variable combinations derived in the GAs. A self-adaptive GA-ANN model was successfully established by using a new estimate function for avoiding over-fitting phenomenon in ANN training. Compared with the variables selected in two recent QSAR studies that were based on stepwise multiple linear regression (MLR) models, the variables selected in self-adaptive GA-ANN model are superior in constructing ANN model, as they revealed a higher cross validation (CV) coefficient (Q2) and a lower root mean square deviation both in the established model and biological activity prediction. The introduced methods for validation, including leave-multiple-out, Y-randomization, and external validation, proved the superiority of the established GA-ANN models over MLR models in both stability and predictive power. Self-adaptive GA-ANN showed us a prospect of improving QSAR model. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010 [source]

Development of a general quantum-chemical descriptor for steric effects: Density functional theory based QSAR study of herbicidal sulfonylurea analogues

Zhen Xi
Abstract Quantitative structure-activity relationship (QSAR) analysis has become one of the most effective approaches for optimizing lead compounds and designing new drugs. Although large number of quantum-chemical descriptors were defined and applied successfully, it is still a big challenge to develop a general quantum-chemical descriptor describing the bulk effects more directly and effectively. In this article, we defined a general quantum-chemical descriptor by characterizing the volume of electron cloud for specific substituent using the method of density functional theory. The application of our defined steric descriptors in the QSAR analysis of sulfonylurea analogues resulted in four QSAR models with high quality (the best model: q2 = 0.881, r2 = 0.901, n = 35, s = 0.401, F = 68.44), which indicated that this descriptor may provide an effective way for solving the problem how to directly describe steric effect in quantum chemistry-based QSAR studies. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1571,1576, 2006 [source]

Antitumour activity and specificity as a function of substitutions in the lipophilic sector of helical lactoferrin-derived peptide

Nannan Yang
Abstract A peptide L5 (PAWRKAFRWAWRMLKKAA), derived from the N -terminal ,-helical region of bovine lactoferrin (LFB 14,31), that is highly active against several tumour cell lines was reported earlier. In this study, a number of L5 analogues were designed in order to investigate how subsequent replacements of the aromatic amino acids in L5 with three amino acids representing different structural parameters influenced antitumour activity and tumour cell specificity relative to normal human cells. The Trp residues were substituted by Lys, Ile or Ala, while the Phe residue was substituted with Ala. The resulting peptides were investigated for their activity against prokaryotic cells, four tumour cell lines, human lung fibroblasts and human erythrocytes. Most of the peptides were highly active against both E. coli and S. aureus. The peptides were more active against the tumour cell lines than against normal eukaryotic cells but the activity against normal fibroblasts varied more among the peptides than did their antitumour activities. The results revealed that aromatic residues located opposite the cationic sector in L5 were more critical for antitumour activity than were aromatic residues located adjacent to the cationic sector. The biological responses for the peptides against tumour cell lines, fibroblasts, S. aureus (but not E. coli), were highly correlated with the amino acid descriptors used in our QSAR model. The result obtained from the QSAR study identified specific structural features that were important for lytic activity and membrane specificity. Certain structural properties in positions 3, 9 and 11 were shown to be important for antitumour activity, while additional structural properties in position 7 were found to be important with respect to tumour cell specificity. This information may offer a possibility for de novo design of an antitumour peptide with an improved therapeutic index. Copyright © 2003 European Peptide Society and John Wiley & Sons, Ltd. [source]

Classical QSAR Modeling of Anti-HIV 2,3-Diaryl-1,3-thiazolidin-4-ones

Kunal Roy
Abstract Cytoprotection and cytotoxicity data of anti-HIV 2,3-diaryl-1,3-thiazolidin-4-ones were subjected to QSAR study using Fujita-Ban type analysis and a mixed approach based on Hansch and Fujita-Ban analyses. Apart from appropriate indicator and integer variables encoding different group contributions, different physicochemical variables like hydrophobicity (,) and steric (molar refractivity) parameters of aryl ring substituents of the compounds were used as predictor variables. Furthermore, Wang-Ford charges of the common atoms of the compounds calculated from molecular electrostatic potential surface of AM1 optimized geometries of the compounds and various topological parameters were used as additional descriptors. The variables for the multiple regression analyses were selected based on principal component factor analysis, and generated equations were statistically validated using leave-one-out technique and predicting the activity data of test set compounds. The statistical qualities of the equations for cytoprotection data (explained variance ranging 64.5,80.3%, leave-one-out predicted variance ranging 44.3,59.4%) are better than those for cytotoxicity data (explained variance ranging 59.7,60.6%, leave-one-out predicted variance ranging 52.4,54.4%). The analysis explores the structural and physicochemical requirements of the compounds for cytoprotection and cytotoxicity. [source]

Classical QSAR Modeling of CCR5 Receptor Binding Affinity of Substituted Benzylpyrazoles

Thomas Leonard
Abstract CCR5 receptor binding affinity of a series of substituted benzylpyrazole derivatives was subjected to QSAR study using Fujita-Ban type analysis and a mixed approach based on Hansch and Fujita-Ban analyses. Apart from appropriate indicator variables encoding different group contributions, different physicochemical variables like hydrophobicity (,), electronic (Hammett ,) and steric (molar refractivity, STERIMOL values) parameters of phenyl ring substituents of the benzyl moiety of the compounds were used as predictor variables. Additionally, Wang-Ford charges of the common atoms of the compounds calculated from molecular electrostatic potential surface of AM1 optimized geometries of the compounds and various topological parameters were used as additional descriptors. The variables for the multiple regression analyses were selected based on principal component factor analysis and generated equations were statistically validated using leave-one-out technique and predicting the binding affinities of test set compounds. The analysis explores the substitutional requirements of the phenyl nucleus of the benzylpyrazole moiety of the compounds for effective binding with CCR5 receptor. [source]

CODES/Neural Network Model: a Useful Tool for in Silico Prediction of Oral Absorption and Blood-Brain Barrier Permeability of Structurally Diverse Drugs

Isabel Dorronsoro
Abstract Two different neural network models able to predict both oral absorption (OA) and blood-brain barrier (BBB) permeability of structurally diverse drugs in use clinically are presented here. Using the descriptors generated by CODES, a program which codifies molecules from a topological point of view, we avoid the uncertain choice of molecular conformation and physicochemical parameters. In this work, a method called Reduction of Dimensions, designed for compressing data, is applied for the first time in order to minimize the bias factor added to a QSAR study when the selection of descriptors are performed. [source]