First-order Molecular Connectivity Index Research Articles

Fluorescence Study of the Influence of the Structure and Hydrophobicity of Fluorescent Dyes and Cationic Surfactants on their Association in Aqueous Solutions

The statistical characteristics of the dependences of the fluorescence signal of analytical systems as a function of the integral parameters of the structure of fluorescent reagents and cationic surfactants on their association in aqueous solutions has been investigated. Molecular weight, surface area, and their first-order molecular connectivity index have been taken as parameters of the structure of the reagents and cationic surfactants. The influence of the hydrophobicity of the reagent and cationic surfactants, such as the octanol–water distribution constant and octanol–water partition coefficient, on the fluorescence signal of the reagent–cationic surfactant associates have also been investigated. It is shown that the associates of anionic reagents with cationic surfactant counter ions are characterised by high stability and a higher analytical signal compared with associates in which there is no electrostatic attraction between the reagent and the surfactant ion. The effect of hydrophobicity of the reagent and cationic surfactant in the absence of electrostatic attraction between the interacting particles is similar. The increase in the role of the influence of the structure of cationic reagents in their association with cationic surfactants, when the electrostatic attraction is absent and the stability of the associates is due mainly to hydrophobic interactions, is noticeable. The regularities of the influence of the colloid-chemical state on the analytical signal of associated cationic surfactants in solutions have been investigated. The study made it possible to formulate a rational basis for the search and design of analytical systems for the determination of large cations by the fluorescence method.

Synthesis, antimicrobial activities and QSAR studies of heterocyclic Schiff base ligands with organosilicon(IV) halides

A series of heterocyclic Schiff base ligands 4-hydroxy-3-[1-{(2-hydroxy-aryl) imino}-ethyl]-6-methyl-pyran-2-one; aryl = phenyl, 4-methylphenyl, 4-chlorophenyl or 4-nitrophenyl (1–4) and their organosilicon(IV) complexes R2Si(L) (R = Et, Bu or Ph) (5–16) were synthesized and characterized. The elemental analyses, molar conductance and spectral (IR, 1H, 13C and 29Si NMR) data suggested pentacoordinated environment around the silicon atom, where tridentate ligands coordinate through the azomethine nitrogen and oxygen of hydroxyl groups. The ligands and their organosilicon complexes were tested in vitro against pathogenic bacteria and fungi to assess their antimicrobial properties. The activity of the ligands improved against most of the strains of the tested microorganisms on complexation to the organosilicon groups. The antimicrobial activities were correlated with QSAR studies using the linear free energy relationship model which indicate the importance of topological parameters, third-order and valence first-order molecular connectivity indices (3 χ v and 1 χ v ), to explain the antibacterial and antifungal activities of all synthesized compounds.

Adsorption and Movement of Carbofuran in Four Different Soils Varying in Physical and Chemical Properties

Laboratory studies were conducted to determine the adsorption and movement of carbofuran on four divergent textured Indian soils at a fixed volume fraction (fs = 0.1) of methanol/water mixtures using batch equilibrium and soil thin layer chromatography (soil TLC) techniques. The measured equilibrium adsorption isotherms for silt loam (FSL and ASL) and loam (KL) soils were L-shaped and for sandy loam (BSL) soil S-shaped, all being well fitted by the Freundlich isotherm. A higher adsorption of carbofuran was observed on FSL followed by ASL, KL and BSL soils as anticipated by the values obtained for the Freundlich constant, KF and partition coefficient, KD. The Frontal Retardation factor (FRf) values obtained from soil TLC studies were inversely proportional to the KF and KD values. The affinity of carbofuran towards organic carbon, organic matter and clay content of the soils was evaluated by calculating the KOC, KOM and KC values. The negative magnitude of the Gibbs'free energy (ΔG0) indicated the spontaneity of the adsorption of carbofuran onto the soils studied. The leaching index (LI) of carbofuran calculated for the soils studied indicated its high potential to leach into shallow aquifers and ground water. Pearson's correlations calculated for KF and KD against the soil properties showed a highly significant correlation with the clay + silt content of the soils. Multiple regression of KF and KD against the soil properties indicated that the mineral content of the soils (clay and clay + silt) is the best predictor of carbofuran adsorption, followed by soil pH. Predicted log KOM values were also evaluated by using the aqueous solubility, the 1-octanol/ water partition coefficient (KOW), the adsorbability index (AI) and the first-order molecular connectivity index (1χ) of carbofuran. Use of the aqueous solubility, and the 1-octanol/water partition coefficient (KOW) to predict the extent of adsorption gave values which displayed a considerable error in comparison to those measured experimentally, whereas the use of the adsorbability index (AI) and the first-order molecular connectivity index (1χ) of carbofuran improved the predictions considerably.

Polyparameter Linear Free Energy Relationships for Estimating the Equilibrium Partition of Organic Compounds between Water and the Natural Organic Matter in Soils and Sediments

Values of the organic-carbon-based partition coefficient (Koc) have often been estimated using one-parameter linear free energy relationships (op-LFERs), which include both correlations between log Koc and log Kow, where Kow is the octanol-water partition coefficient, and op-LFERs that are based on first-order molecular connectivity indices. For chemicals with tendencies toward strong hydrogen-bonding or other specific interactions with the organic phase, however,these methods are notsufficientlyaccurate. Polyparameter LFERs (pp-LFERs) address these shortcomings by explicitly considering contributions toward free energy change from multiple kinds of molecular interactions with both water and bulk organic phases. This paper reviews pp-LFER theory and presents the development of a new pp-LFER for organic chemical partitioning with soil/sediment organic matter (SOM) using a data set of 356 carefully selected experimental values of log Koc for 75 chemicals, including apolar, monopolar, and bipolar compounds. The paradigm of representing SOM by a single pp-LFER is qualitatively supported by our results, and the set of coefficients for the regression log Koc= (1.10+/-0.10)E - (0.72+/-0.14)S + (0.15+/-0.15)A - (1.98+/-0.14)B + (2.28+/-0.14)V + (0.14+/-0.10) represents a proposed set of water-SOM-specific properties for estimating log Koc. The developed correlation outperformed other currently recommended approaches with the given Koc data set and also compared favorably against the use of new multiple class-specific op-LFER regressions. Overall, the pp-LFER approach is recommended over other current methods for the purpose of Koc estimation and especially for polar chemicals.

A nonlinear group contribution method for predicting the free energies of inclusion complexation of organic molecules with alpha- and beta-cyclodextrins.

A group-contribution method was developed for calculating the binding constants or the free energies of complexation between native alpha- or beta-cyclodextrin (CD) and organic guest molecules. The nonlinear models for binary (1:1 stoichiometry) complexes of alpha- and beta-CDs were derived with squared correlation coefficients (r(2)) of 0.868 and 0.917 based on a database consisting of 102 and 218 diverse guest molecules, respectively. The parameters used in the models are first-order molecular connectivity index as a measure of molecular bulk and atom/group counts in the guest molecules. The models allow accurate estimations for the wide range of guests containing C, H, N, O, S, and/or all halogens by summing the contribution values of each defined group present in the chemical structure of the guest along with guest's molecular size factors (linear and square terms) and then the summation to a constant coefficient value. The predictive performance of the models was tested by extra set of 27 compounds which were not included in the original data set. The predicted values by the models are in good agreement with the experimentally determined data.

Relationship of properties of polycyclic aromatic hydrocarbons to sequestration in soil

A study was conducted to determine whether the sequestration of 21 polycyclic aromatic hydrocarbons (PAHs) in soil was correlated with their properties. From 22 to 58% of the PAHs was not extracted with n-butanol after their addition to soil. After 28 days of aging, the percentage of the PAHs remaining in the soil increased to 47–77%; however, nearly all of each compound was recovered by Soxhlet extraction. Correlations were based on the amounts of aged compound extracted with butanol. Properties of compounds used in the correlations included K ow, molecular length and molecular-connectivity indices (MCIs). No one property, including log K ow, resulted in an R 2 value greater than 0.26. A chain MCI ( 6χ ν CH) together with log K ow or a first-order MCI ( 1χ) resulted in R 2 values of 0.49 and 0.54, respectively. The data suggest that the properties tested are not important to predicting the sequestration of PAHs in soil.

Effect of Cationic, Non-Ionic and Anionic Surfactants on the Adsorption of Carbofuran on Three Different Types of Indian Soil

The adsorption of carbofuran in aqueous surfactant-free and surfactant (cationic, non-ionic and anionic) solutions of different micellar concentration (½ × CMC, CMC and 2 × CMC) on three different types of Indian soil has been studied using the batch shaking technique. The measured equilibrium adsorption isotherms for the surfactant-free and surfactant/soil/water systems at different critical micellar concentrations were S-shaped and in close agreement to the Freundlich isotherms. Higher adsorption of carbofuran in both systems was observed on silt loam soil followed by loam and sandy soils, and was anticipated by the values obtained for the Freundlich constant, KF, and the partition coefficient, KD. The values of KF and KD obtained also confirmed that the adsorption of carbofuran in aqueous surfactant solutions followed the order cationic > nonionic > anionic at all the CMC values studied. The affinity of carbofuran towards organic matter and the clay content of the soils was evaluated by calculating the Kom and Kc values, when it was found that carbofuran adsorption was better correlated with the clay content than with the organic matter content. The predicted log Kom values were also obtained from the aqueous solubility, 1-octanol/water partition coefficient (Kow), adsorbability index (Al) and first-order molecular connectivity index (1χ) of carbofuran. Use of the aqueous solubility and the 1-octanol/water partition coefficient of carbofuran to predict the adsorption gave values with a considerable error in comparison with those measured experimentally, whereas the use of the absorbability index and first-order molecular connectivity index for carbofuran improved the predictions considerably. The results obtained are interesting in that they afford basic data relating to the possible use of surfactants for solving problems of soil contamination by carbofuran.

Studies on some 3(2H)-pyridazinone derivatives with antinociceptive activity.

Nineteen new [6-(4-methoxyphenyl)-3(2H)-pyridazinone-2-yl]-acetamide (1-10) and 3-[6-(4-methoxyphenyl)-3(2H)-pyridazin-one-2-yl]propanamide (11-19) derivatives have been synthesized in this study. The structures of the compounds have been elucidated by their IR and NMR spectral data and elemental analysis. Antinociceptive activity of the compounds has been investigated by modified Koster's Test in mice, using aspirin as a reference. All the compounds (at 100 mg/kg dose) except 1 and 9 have been found more potent than aspirin. Compound 6 in the group of acetamide derivatives and compound 15 in the group of propanamides exhibited the highest antinociceptive activity. In addition, the propanamides have generally been found more potent than acetamides. In addition to these studies, the quantitative relationships between some structural parameters (such as log P, parachor, molar refractivity, and molecular connectivity indices) and antinociceptive activity of the compounds have been investigated. Statistical regression analysis has shown a close relationship to exist between the first-order molecular connectivity index (1 chi) and the antinociceptive activity.

Quantitative Structure−Property Relationships for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network

Radial basis function (RBF) neural network models for the simultaneous estimation of flash point (Tf) and boiling point (Tb) based on 25 molecular functional groups and their first-order molecular connectivity index (1χ) have been developed. The success of the whole modeling process depended on a network optimization strategy based on biharmonic spline interpolation for the selection of an optimum number of RBF neurons (n) in the hidden layer and their associated spread parameter (σ). The RBF networks were trained by the Orthogonal Least Squares (OLS) learning algorithm. After dividing the total database of 400 compounds into training (134), validation (133), and testing (133), the average absolute errors obtained for the validation and testing sets ranges from 10 °C to 12 °C and 11 °C to14 °C for Tf and Tb, respectively, and are in agreement with the experimental value of about 10 °C. Results of a standard Partial Least Square (PLS) regression model for single output predictions range from 23 °C to 24 °C...

QSAR modelling of soil sorption. Improvements and systematics of log K OC vs. log K OW correlations

A systematic study was performed to evaluate the quality and reliability of the quantitative relationships between the soil sorption coefficients and the n-octanol/water partition coefficients (log K OC vs. log K OW). A system of QSAR models has been derived which is based on a reliable set of experimental log K OW data (LOGPSTAR data) or reliable estimates calculated with the latest version of the ClogP algorithm. Particular emphasis has been made to clearly define the boundaries for application of developed models as well as the quality of estimates. Thus, for each developed model the application domain is clearly defined through the chemical (structural) domain, substituents domain, and X-variable domain. Finally, the QSAR model with the first-order molecular connectivity indices has been incorporated in the derived system of QSAR models since the soil sorption estimates of the predominantly hydrophobic chemicals based on the log K OW data have large uncertainties, particularly in the log K OW data range from 4 to 7.5.

Molecular topology/fragment contribution method for predicting soil sorption coefficients

The first-order molecular connectivity index ( 1 χ) has been successfully used to predict soil sorption coefficients (K oc ) for nonpolar organics, but extension of the model to polar compounds has been problematic. To address this, we developed a new estimation method based on 1 χ and a series of statistically derived fragment contribution factors for polar compounds. After developing an extensive database of measured K oc values, we divided the dataset into a training set of 189 chemicals and an independent validation set of 205 chemical.

Quantitative modeling of soil sorption for xenobiotic chemicals.

Experimentally determining soil sorption behavior of xenobiotic chemicals during the last 10 years has been costly, time-consuming, and very tedious. Since an estimated 100,000 chemicals are currently in common use and new chemicals are registered at a rate of 1000 per year, it is obvious that our human and material resources are insufficient to experimentally obtain their soil sorption data. Much work is being done to find alternative methods that will enable us to accurately and rapidly estimate the soil sorption coefficients of pesticides and other classes of organic pollutants. Empirical models, based on water solubility and n-octanol/water partition coefficients, have been proposed as alternative, accurate methods to estimate soil sorption coefficients. An analysis of the models has shown (a) low precision of water solubility and n-octanol/water partition data, (b) varieties of quantitative models describing the relationship between the soil sorption and above-mentioned properties, and (c) violations of some basic statistical laws when these quantitative models were developed. During the last 5 years considerable efforts were made to develop nonempirical models that are free of errors imminent to all models based on empirical variables. Thus far molecular topology has been shown to be the most successful structural property for describing and predicting soil sorption coefficients. The first-order molecular connectivity index was demonstrated to correlate extremely well with the soil sorption coefficients of polycyclic aromatic hydrocarbons (PAHs), alkylbenzenes, chlorobenzenes, chlorinated alkanes and alkenes, heterocyclic and heterosubstituted PAHs, and halogenated phenols. The average difference between predicted and observed soil sorption coefficients is only 0.2 on the logarithmic scale (corresponding to a factor of 1.5). A comparison of the molecular connectivity model with the empirical models described earlier shows that the former is superior in accuracy, performance, and range of applicability. It is possible to extend this model, with the addition of a single, semiempirical variable, to take care of polar and ionic compounds and to accurately predict the soil sorption coefficients for almost 95% of all organic chemicals whose coefficients have been reported. No empirical or nonempirical models have ever predicted the soil sorption coefficients to such a high degree of accuracy on such a broad selection of structurally diverse compounds. An additional advantage of the molecular connectivity model is that it is sufficient to know the structural formulas to make predictions about soil sorption coefficients.(ABSTRACT TRUNCATED AT 400 WORDS)

Prediction of Soil Sorption Coefficients of Hydrophobic Organic Pollutants by Adsorbability Index

Abstract The adsorbability index proposed by Abe et al. to predict the activated carbon adsorption of organic compounds from aqueous solution was well correlated with the soil sorption coefficients of polycyclic aromatic hydrocarbons (PAHs), alkylbenzenes, chlorobenzenes, chlorinated alkanes and alkenes, heterocyclic and substituted PAHs, and halogenated phenols. The adsorbability index was also found to be well correlated with the first-order molecular connectivity index and the total molecular surface areas of these compounds.

A simulation model for the fate of pesticide residues in a field soil

The model employed for simulating the fate of pesticides in soil was based on the one dimensional convective-dispersive-reaction equation. The model assumed a constant pore-water velocity (v), linear equilibrium adsorption, and first-order degradation. The adsorption parameter (kd) was calculated from molecular structure with the help of a first-order molecular connectivity index. On the basis of the results of sensitivity analysis the model was made partially stochastic in order to account for horizontal heterogenity in a field soil. Concentration profiles were obtained by employing the mode, median and mean values of (v, D) while the values of kd and t1/2 were kept constants; where D and t1/2 were the apparent diffusion coefficient and the degradation half-life, respectively. The resulted extremes in concentration profiles were expected to be observed within a relatively small area of the heterogeneous filed soil. A random variable, namely the contaminated depth, ζ was defined so that the soil beneath it would be practically free of pesticide during its entire life-time. The values of (ξ1, ξ2, ξ3) under continuous leaching were (0.14, 0.56, 1.00 m), (0.29, 1.50, 2.62 m), and (0.65, 2.25, 4.00m) for DDT, toxaphene and lindane, respectively; where ξ1, ξ2 and ξ3 were values of ζ calculated by employing the mode, median, and mean values of (v, D), respectively. Within a relatively small area the first value would be frequently observed whereas the others would be less pronounced. The depth and shape of the resultant base of the contaminated zone were substantially more sensitive to changes in the surface rates of recharge than to changes in the values of the chemical parameters kd and t1/2. The implication of the results for the assesment of pesticide contamination of groundwaters were discussed.

Calculation of retention indices by molecular topology: chlorinated alkanes

This study was undertaken to test the ability of the molecular connectivity model to predict retention indices using both statistical correlation coefficients and correctly predicted elution sequences as criteria of fit. The test was performe don three groups of chloroalkanes. Regression analyses show that the molecular connectivity model successfully predicts the retention indices of chlorinated alkanes on polar and non-polar stationary phases. However, first-order molecular connectivity indices alone are not sufficientk, higher order indices are demonstrared to be necessary. The results also indicate that different structural features determine the retention index values of mono- and dichlorides. For monochlorides the major factor is the size of the alkly chain, while for dichlorides the major factor is the toplogical relation between the two chlorine atoms. The comaparison of the results obtained with the molecular connectivity model and the empirical additive scheme reveals several important advantages of the molecular connectivity approach.