Experimental and Computational Study of Novel Pyrazole Azo Dyes as Colored Materials for Light Color Paints.

This paper presents the synthesis of eight new pyrazole azo dyes using ethyl 5-amino-3-methyl-1H-pyrazole-4-carboxylate as the diazotization component and various active methylene derivatives as coupling components. These new azo dyes were characterized by spectroscopic (FT-IR, UV-VIS), and spectrometric (1H NMR, 13C NMR, MS) analyses. The dye structures were modeled by the MMFF94s force field and quantum chemical density functional theory (DFT) calculations using the B3LYP functional and the 6-311G(d,p) basis set, in the gas phase. Weak electrostatic hydrogen bonds for the azo and hydrazo dye tautomers were found in the ground state. The CIS, TD (using the B3LYP and M06-2X functionals), and ZINDO methods were used to estimate the dye UV-VIS spectra in ethanol, which were compared with the experimental ones. The anti-configuration arrangement of the π-bonds and the presence of the prevalent hydrazo dye tautomer were supported by the computed 1H NMR and 13C NMR spectra. A good accordance between the experimental and predicted absorption maxima and chemical shifts was observed. Color investigations using the CIEL*a*b* space were conducted for all dyes in powder and for their mixtures in water-based acrylic resins. The results confirm the newly synthesized dyes' color properties and that they might be used for light color paints in the varnishes industry.

Homology Modeling and Molecular Docking Approaches for the Proposal of Novel Insecticides against the African Malaria Mosquito (Anopheles gambiae).

Vector-borne infectious diseases are responsible for the deaths of over 700,000 people annually, than 400,000 of them resulting from malaria. The mosquito Anopheles gambiae is one of the dominant vector species of human malaria transmission. A significant issue of the conventional insecticides which target the arthropod borne infectious diseases is their induced resistance. To overcome this inconvenience, insecticides with new modes of action are required. One of the most promising targets for the development of new potential insecticides as evidenced by current studies is the D1-like dopamine receptor (DAR). To get a deeper understanding of the structural information of this receptor, the 3D homology model was built. The possible sites within the protein were identified and the most probable binding site was highlighted. The homology model along with a series of DAR antagonists with known activity against Anopheles gambiae larvae were used in docking experiments to gain insight into their intermolecular interactions. Furthermore, virtual screening of the natural compounds from the SPECS database led to the prediction of toxicity and environmental hazards for one potential new insecticide against the Anopheles gambiae mosquito.

Application of Molecular Docking, Homology Modeling, and Chemometric Approaches to Neonicotinoid Toxicity against Aphis craccivora.

Neonicotinoids are known as effective pesticides against various insect species. They can harm useful insects including honeybees, with a relatively low threat to nontarget organisms and the environment. This paper presents combined methods to explore the insecticidal activity of neonicotinoids with diverse scaffolds, active against Aphis craccivora. Pharmacophore, molecular docking into the active site of nicotinic acetylcholine receptor homology model, and linear and non-linear regression approaches were used to find new insecticide candidates. The potential toxic effects against honeybees were evaluated using the molecular docking in the active site of the new Aphis mellifera homology model. Four new untested compounds were assigned as insecticide candidates, active against Aphis craccivora with less potential toxic effects for honeybees. This approach may be an effective strategy to design environmentally friendly insecticides against the cowpea aphid.

Neonicotinoid insecticide design: molecular docking, multiple chemometric approaches, and toxicity relationship with Cowpea aphids.

Neonicotinoids are the fastest-growing class of insecticides successfully applied in plant protection, human and animal health care. The significant resistance increases led to the urgent need for alternative new neonicotinoids, with improved insecticidal activity. We performed molecular docking to describe a common binding mode of neonicotinoids into the nicotinic acetylcholine receptor, and to select the appropriate conformations to derive models. These were further used in a QSAR study employing both linear and nonlinear approaches to model the inhibitory activity against the Cowpea aphids. Linear modeling was performed by multiple linear regression and partial least squares and nonlinear modeling by artificial neural networks and support vector machine methods. The OECD principles were considered for QSAR models validation. Robust models with predictive power were found for neonicotinoid diverse structures. Based on our QSAR and docking outcomes, five new insecticides were predicted, according to the model applicability domain, the ligand efficiencies, and the binding mode. Therefore, the developed models can be confidently used for the prediction of the insecticidal activity of new chemicals, saving a substantial amount of time and money and, also, contributing to the chemical risk assessment.

An Approach to Identify New Insecticides Against Myzus Persicae. In silico Study Based on Linear and Non-linear Regression Techniques.

Neonicotinoids are known to have high insecticidal potency, low mammalian toxicity and relatively tough activity for the development of resistance against aphids. A series of guadipyr insecticides, active against Myzus persicae was engaged in silico studies, based on Multiple Linear Regression (MLR), Partial Least Squares regression (PLS), Artificial Neural Networks (ANN), Support Vector Machine (SVM) and Pharmacophore modeling. Robust and predictive models were built using correlations between the insecticidal profile, expressed by experimental pLC50 values, and molecular descriptors, calculated from the energy optimized structures. Four new potential insecticides active against Myzus persicae and their predicted pLC50 toxicity values were reported for the first time. The models presented here can be used as an approach in the screening and prioritization of chemicals in a scientific and regulatory frame and for toxicity prediction.

Combined molecular docking and QSAR study of fused heterocyclic herbicide inhibitors of D1 protein in photosystem II of plants.

Cinnoline, pyridine, pyrimidine, and triazine herbicides were found be inhibitors of the D1 protein in photosystem II (D1 PSII) electron transport of plants. The photosystem II inhibitory activity of these herbicides, expressed by experimental [Formula: see text] values, was modeled by a docking and quantitative structure-activity relationships study. A conformer ensemble for each of the herbicide structure was generated using the MMFF94s force field. These conformers were further employed in a docking approach, which provided new information about the rational "active conformations" and various interaction patterns of the herbicide derivatives with D1 PSII. The most "active conformers" from the docking study were used to calculate structural descriptors, which were further related to the inhibitory experimental [Formula: see text] values by multiple linear regression (MLR). The dataset was divided into training and test sets according to the partition around medoids approach, taking 27% of the compounds from the entire series for the test set. Variable selection was performed using the genetic algorithm, and several criteria were checked for model performance. WHIM and GETAWAY geometrical descriptors (position of substituents and moieties in the molecular space) were found to contribute to the herbicidal activity. The derived MLR model is statistically significant, shows very good stability and was used to predict the herbicidal activity of new derivatives having cinnoline, indeno[1.2-c]cinnoline-ll-one, triazolo[1,5-a] pyridine, imidazo[1,2-a]pyridine, triazine and triazolo[1,5-a] pyrimidine scaffolds whose experimental inhibitory activity against D1 PSII had not been determined up to now.

Quantitative estimation of pesticide-likeness for agrochemical discovery.

BACKGROUND: The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP). In the assessment of these definitions, we relied on the concept of desirability functions. RESULTS: We found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides. CONCLUSIONS: The hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery. Graphical AbstractQuantitative models for pesticide-likeness were derived using the concept of desirability functions parameterized for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings.

The Hydractinia echinata test-system. III: Structure-toxicity relationship study of some azo-, azo-anilide, and diazonium salt derivatives.

Structure-toxicity relationships for a series of 75 azo and azo-anilide dyes and five diazonium salts were developed using Hydractinia echinata (H. echinata) as model species. In addition, based on these relationships, predictions for 58 other azo-dyes were made. The experimental results showed that the measured effectiveness Mlog(1/MRC50) does not depend on the number of azo groups or the ones corresponding to metobolites, but it is influenced by the number of anilide groups, as well as by the substituents' positions within molecules. The conformational analysis pointed out the intramolecular hydrogen bonds, especially the simple tautomerization of quinoidic (STOH) or aminoidic (STNH2) type. The effectiveness is strongly influenced by the "push-pull" electronic effect, specific to two hydroxy or amino groups separated by an azo moiety (double alternate tautomery, (DAT), to the -COOH or -SO3H groups which are located in ortho or para position with respect to the azo group. The levels of the lipophylic/hydrophilic, electronic and steric equilibriums, pointed out by the Mlog(1/MRC50) values, enabled the calculation of their average values Clog(1/MRC50) ("Köln model"), characteristic to one derivative class (class isotoxicity). The azo group reduction and the hydrolysis of the amido/peptidic group are two concurrent enzymatic reactions, which occur with different reaction rates and mechanisms. The products of the partial biodegradation are aromatic amines. No additive or synergic effects are noticed among them.

Modeling of 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one derivatives by several conformational searching tools and molecular docking.

Neutrophil elastase, a serine proteinase from the chymotrypsin family, has been the object of comprehensive experimental and theoretical studies to develop efficient human neutrophil elastase inhibitors. The serine protease has been linked to the pathology of a variety of inflammatory diseases, making it an attractive target for the development of anti-inflammatory compounds. In this work, we have built a common binding model of the 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one derivatives into the human neutrophil elastase binding site. This was accomplished through a comparative conformational analysis (using OMEGA, HYPERCHEM, and MOPAC software) of 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one inhibitors followed by rigid and flexible molecular docking (by the FRED and GLIDE programs) into the target protein. We conclude that OMEGA software generates the most representative conformers to model the protein-ligand interactions.

Hydractinia echinata test system. II. SAR toxicity study of some anilide derivatives of Naphthol-AS type.

In this paper, a toxicity study for a series of anilides of Naphthol-AS type is presented. The toxicity of the model compounds was determined by using the Hydractinia echinata (Hydrozoa) test system. Conformational analysis of Naphthol-AS derivatives was performed to elucidate the possible enzymatic hydrolysis mechanism of these compounds. This mechanism occurs with different rates and always leads to a stoichiometric mixture of reaction products, consisting in the substituted amine and the corresponding α-hydroxy-carboxylic acid. With one exception, the toxicities of the reaction products are subadditive. Quite similar measured toxicity values, log(1/MRC50), led to their average calculated values, and thus to the establishment of class isotoxicity. This method represents a practical alternative useful for the reduction of experimental tests on animals to the lowest possible level, in accordance to the '3Rs' (reduction, refinement and replacement) concept.

A tentative quantitative structure-toxicity relationship study of benzodiazepine drugs.

Benzodiazepines belong to a large family of drugs, being used as hypnotics, anxiolytics, tranquillizers, anticonvulsants, in pre-medication and intravenous sedation. Several quantitative structure-toxicity (lethal oral dose for mouse) relationship (QSTR) models for 54 benzodiazepine derivatives have been developed. The molecular structure of these compounds was energetically optimized by molecular mechanics calculations. To the lowest energy conformations thus obtained, quantum chemical calculations (RM1 approach) were applied to finally optimize the structures. Several structural descriptors, volumes, molecular surface area, hydrophobicities and quantum chemical descriptors were calculated from the minimized structures. Multiple linear regression (MLR) combined with genetic algorithm for variable selection, artificial neural networks (ANNs), support vector machines (SVMs) and partial least squares (PLS) have been employed. Few satisfactory MLR models with predictive power were obtained. Nonlinear modelling methods of ANNs and SVMs gave somewhat better models than those obtained by MLR using same set of descriptors. Additional information on the factors which influence the benzodiazepine toxicity was given by PLS. The obtained models can be used for a rough evaluation of benzodiazepine toxicity.

Multilinear regression and comparative molecular field analysis (CoMFA) of azo dye-fiber affinities. 2. Inclusion of solution-phase molecular orbital descriptors.

For a data set with 30 direct azo dyes taken from literature, quantitative structure-activity relationship (QSAR) analyses have been performed to model the affinity of the dye molecules for the cellulose fiber. The electronic structure of the compounds was characterized using quantum chemical gas-phase (AM1) and continuum-solvation molecular orbital parameters. As regards the solution phase, COSMO appears to be better suited than SM2 in quantifying relative trends of the aqueous solvation energy. For the dye-fiber affinity, the leave-one-out prediction capability of multilinear regression equations is superior to CoMFA, with predictive squared correlation coefficients ranging from 0.63 (pure CoMFA) to 0.89. At the same time, solution-phase CoMFA is superior to previously derived AM1-based CoMFA models. As a general trend, the dye-fiber affinity increases with increasing electron donor capacity that corresponds to an increasing hydrogen bond acceptor strength of the azo dyes. The discussion includes the consideration of structural features that are likely to be involved in dye-fiber and dye-dye hydrogen bonding interactions, and possible links between CoMFA electrostatic results and the atomic charge distribution of the compounds.

Quantitative structure-activity relationships for the enantioselectivity of oxirane ring-opening catalyzed by epoxide hydrolases.

The enantioselective ring-opening catalyzed by epoxide hydrolases originating from seven different sources of a series of 2,2-disubstituted oxiranes containing alkyl chains of different lengths, unsaturated (alkenyl, alkinyl) and aromatic groups as well as electronegative heteroatoms at various positions within the side chain was analyzed by quantitative structure-activity relationships. Models for the enantioselectivity were derived with the aid of multiple linear regression analysis (MLR) using several steric and electronic (quantum chemical) descriptors. On the basis of the models derived by MLR nonlinear modeling with artificial neural networks (ANN) was also done. Good predictive performance was observed for both modeling approaches. The models also indicate that different steric and/or electronic features account for the enantioselectivities observed for the individual epoxide hydrolases.

Comparative molecular field analysis (CoMFA) of anionic azo dye-fiber affinities I: gas-phase molecular orbital descriptors.

This paper presents quantitative structure-activity relationship (QSAR) models for a series of 30 anionic azo dyes applied to cellulose fiber by comparative molecular field analysis. Two forms of the dye molecules (neutral and anionic) are compared. Neutral structures give better statistical results than the anionic species. The electronic and structural properties of these dyes were calculated by the semiempirical AM1 method. The results indicate the predominance of electrostatic interactions in dye-cellulose binding. The dominant contribution of the HOMO orbital molecular energy, used as descriptor, can be explained by the donor ability of the dye molecules in the dye adsorption on cellulose.