Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis

Lazea

et al. 2011

IJMS

Self Cite

The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom’s polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the “optimal molecular structural domains” and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.

Section: Application To Non-nucleoside Reverse Transcriptase Pyridmentioning

confidence: 99%

Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

Lazea

et al. 2011

IJMS

Self Cite

SAR and QSAR in Environmental Research

“…The statistical correlation of an experimental property with a set of descriptors results in a model which can be used to discover practical relationships and trends. Within the QSPR framework there are several factors that are crucial; among them, the most important are: (a) the composition of the training and test sets; (b) the choice of representative molecular descriptors with low collinearities between them; (c) the amount of descriptors included in the model; (d) the use of suitable modelling methods; and (e) the employment of validation techniques to verify the predictive performance of the developed models [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

QSPR study on refractive indices of solvents commonly used in polymer chemistry using flexible molecular descriptors

Fioressi

Bacelo

Cui

et al. 2015

A predictive Quantitative Structure-Property Relationship (QSPR) for the refractive indices of 370 solvents commonly used in the processing and analysis of polymers is presented, using as chemical information descriptors the simplified molecular input line entry system (SMILES). The model employs a flexible molecular descriptor and a conformation-independent approach. Various well-known techniques, such as the use of an external test set of compounds, the cross-validation method, and Y-randomization were used to test and validate the established equations. The predicted values were finally compared with published results from the literature. The simple model proposed correlates the refractive index values with good accuracy, and it is not dependent on 3D-molecular geometries.

“…On the other hand, interest in the calculation of electronic structures in excited states has been motivated by the increasing application of fluorescent molecules in a variety of research areas, including chemical biology, analytical chemistry, medicinal chemistry and molecular biology [ 21 , 22 ]. In recent years, calculations of electronic structures in the excited states have been a focus of interest because of the development of computations based on the time-dependent density functional theory (TDDFT) [ 23 , 24 , 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Experimental and Theoretical Study of O-Substituent Effect on the Fluorescence of 8-Hydroxyquinoline

Zayed

El‐Shishtawy

Elroby

et al. 2015

IJMS

The synthesis and characterization of different ether and ester derivatives of 8-hydroxyquinoline have been made. UV-visible and fluorescence spectra of these compounds have revealed spectral dependence on both solvent and O-substituent. The fluorescence intensity of ether derivatives revealed higher intensity for 8-octyloxyquinoline compared with 8-methoxyquinoline, whereas those of ester derivatives had less fluorescence than 8-hydroxyquinoline. Theoretical calculations based on Time-dependent density functional theory (TD-DFT) were carried out for the quinolin-8-yl benzoate(8-OateQ) compound to understand the effect of O-substituent on the electronic absorption of 8-hydroxyquinaline (8-HQ). The calculations revealed comparable results with those obtained from the experimental data. Optimized geometrical structure was calculated with DFT at B3LYP/6-311++G** level of theory. The results indicated that 8-OateQ is not a coplanar structure. The absorption spectra of the compound were computed in gas-phase and solvent using B3LYP and CAM-B3LYP methods with 6-311++G ** basis set. The agreement between calculated and experimental wavelengths was very good at CAM-B3LYP/6-311++G** level of theory.