Three-dimensional quantitative structure-activity relationship study for phenylsulfonyl carboxylates using CoMFA and CoMSIA

From both the comparative molecular field analysis (CoMFA) and the comparative molecular similarity indices analysis (CoMSIA), the paper describes two three-dimensional quantitative structure-activity relationship (3D-QSAR) models for the acute toxicity logEC50 (15 min-EC50 in micromoll(-1)) of 56 phenylsulfonyl carboxylates on Photobacterium phosphoreum. Two models yield the leave-one-out cross-validated correlation coefficient q2 values of 0.823 and 0.713, and the conventional correlation coefficient r2 values of 0.958 and 0.933, respectively. The achievement of higher q2 and r2 values of CoMFA model indicates the significance of correlation of steric and electrostatic fields with biological activities. The key features in the CoMFA contour maps are critical to trace the important properties and gain insight into the toxic mechanism of tested compounds. The quality of CoMSIA model is slightly lower than that of CoMFA in terms of q2 and r2 values. Not requiring molecular superposition, CoMSIA is faster than CoMFA in data processing.     

3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA

In the present study we have performed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA and CoMSIA models have given q(2) value of more than 0.5 and r(2) value of more than 0.84. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive r(2) values. Best predictions were obtained with CoMFA model of combined modified training set (q(2) = 0.631, r(2) = 0.900), giving predictive residual value = 0.02 log unit for the test compound. Addition of CoMSIA study has elucidated the role of hydrophobicity and hydrogen bonding along with the effect of steric and electrostatic properties revealed by CoMFA. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands.     

Three-dimensional quantitative structure activity relationship (3D-QSAR) analysis for in vitro toxicity of chlorophenols to HepG2 cells

In the present paper, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to investigate two 3D-QSAR models for the cytotoxicity of chlorophenols. These models have evaluated the intensity of chlorophenols' toxicity on HepG2 cells in vitro. The CoMFA model has both high consistency and predictability. The contribution of the electrostatic field to biological activity is greater than that of the steric field. The CoMSIA model used in this study includes two fields, one is hydrophobic field, and the other is electrostatic field. The relative contribution of them is 0.789:0.211. Consisted with the CoMFA model, the CoMSIA electrostatic filed also plays a dominant role. The CoMFA and CoMSIA contour maps significantly elucidated that the electrostatic field is more important than the other fields and might be one of the reasons resulting in potential reactive mechanism involved in cell proliferation inhibition.     

3D-QSAR of fungal quorum-sensing inhibiting analogs of farnesol

Thirty-four analogs with variable antifungal activity were selected to develop models for establishing three-dimensional quantitative structure-activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA) and comparative similarity indices analyses (CoMSIA) were conducted on the group of analogs to determine the structural requirements for selectivity and potency in inhibiting biofilm formation and fungal growth. The best CoMFA model predicted a q(2) = 0.5 and an r(2) = 0.991, and revealed that electrostatic properties play a significant role in potency and selectivity. The best CoMSIA model combined electrostatics, hydrogen bond acceptor and donor, and hydrophobic fields with a q(2) = 0.664 r(2) = 0.952, S = 0.099, and F = 139.892. The analyses of the contour maps from both models provide significant insight into the structural necessities for a potent compound. Therefore, manipulating various chemical properties of the substituted groups on the farnesol chain can be used to enhance the fungicidal properties of the target compound.     

Three-dimensional quantitative structure activity relationships of quorum-sensing and biofilm inhibitors in gram-negative bacteria

Thirty N-acyl homoserine lactone (AHL) analogs with variable antibacterial activity and displaying inhibition of biofilm formation were selected to develop models for establishing three-dimensional quantitative structure-activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) were carried out to determine the optimum structural requirements for selectivity and potency of quorum-sensing and bacterial biofilm inhibition. The best CoMFA model predicted a q2 value of 0.519 and an r2 value of 0.984 and revealed that electrostatic and steric properties play a significant role in potency and selectivity. The CoMSIA model predicted a q2 value of 0.411 and an r2 value of 0.938 based on a combination of steric, electrostatic, and hydrophobic effects. The analysis of the contour maps from each model provide insight into the structural requirements for increasing the activity of a compound. Consequently, manipulating the chemical and physical properties of substituted acyl groups on the homoserine lactone moiety can provide important information toward enhancing the antibacterial properties of the target chemical compound.     

Studies of 3D-quantitative structure-activity relationships on a set of nitroaromatic compounds: CoMFA,advanced CoMFA and CoMSIA

By using comparative molecular field analysis (CoMFA), advanced CoMFA and comparative molecular similarity index analysis (CoMSIA) methods, the 3D relationships between the structures of 35 nitroaromatic compounds and their toxicities have been investigated to yield statistically reliable models of considerable predictive power. In contrast to CoMFA, CoMSIA produces better results for the correlation. Moreover, the obtained CoMSIA contour maps that interpret the correlations in terms of field contributions allow physicochemical properties relevant for binding to be easily mapped back onto molecular structures, and thus elucidate structural features among ligands that are responsible for toxicities. Besides, most of the highlighted regions in CoMSIA and CoMFA contour maps are mirrored by features in the surrounding environment. Thereby, CoMFA and CoMSIA both help to give explanations of the toxic mechanism of tested compounds.     

3D-QSAR of fungal quorum-sensing inhibiting analogs of farnesol

Thirty-four analogs with variable antifungal activity were selected to develop models for establishing three-dimensional quantitative structure-activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA) and comparative similarity indices analyses (CoMSIA) were conducted on the group of analogs to determine the structural requirements for selectivity and potency in inhibiting biofilm formation and fungal growth. The best CoMFA model predicted a q² = 0.5 and an r² = 0.991, and revealed that electrostatic properties play a significant role in potency and selectivity. The best CoMSIA model combined electrostatics, hydrogen bond acceptor and donor, and hydrophobic fields with a q² = 0.664 r² = 0.952, S = 0.099, and F = 139.892. The analyses of the contour maps from both models provide significant insight into the structural necessities for a potent compound. Therefore, manipulating various chemical properties of the substituted groups on the farnesol chain can be used to enhance the fungicidal properties of the target compound.     

Three-dimensional quantitative structure activity relationships of quorum-sensing and biofilm inhibitors in gram-negative bacteria

Thirty N-acyl homoserine lactone (AHL) analogs with variable antibacterial activity and displaying inhibition of biofilm formation were selected to develop models for establishing three-dimensional quantitative structure-activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) were carried out to determine the optimum structural requirements for selectivity and potency of quorum-sensing and bacterial biofilm inhibition. The best CoMFA model predicted a q² value of 0.519 and an r² value of 0.984 and revealed that electrostatic and steric properties play a significant role in potency and selectivity. The CoMSIA model predicted a q² value of 0.411 and an r² value of 0.938 based on a combination of steric, electrostatic, and hydrophobic effects. The analysis of the contour maps from each model provide insight into the structural requirements for increasing the activity of a compound. Consequently, manipulating the chemical and physical properties of substituted acyl groups on the homoserine lactone moiety can provide important information toward enhancing the antibacterial properties of the target chemical compound.     

Investigation of structural requirements for inhibitory activity at the rat and housefly picrotoxinin binding sites in ionotropic GABA receptors using DISCOtech and CoMFA

A number of widely diverse compounds that show inhibitory activities at the picrotoxinin binding sites in housefly and rat GABA receptors were investigated by using the distance comparison technique (DISCOtech) and comparative molecular field analysis (CoMFA) methods to explore the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds. These compounds consist of three diverse types of noncompetitive GABA receptor antagonists, i.e., trioxabicyclooctanes and their derivatives, picrodendrins and related terpenoids, and fipronil and its analogs. For investigation of the structural requirements for inhibitory activity at the picrotoxinin binding site of GABA receptor, DISCOtech pharmacophore models containing one center of hydrophobic ring and two hydrogen bond acceptor atoms for both housefly-head and rat-brain GABA receptors were constructed, respectively. In particular, the interacting areas in housefly receptors appear to be wider than that in rat receptors, the differences between rat and housefly receptor models implicate the selectivity of noncompetitive GABA receptor antagonists. In addition, corresponding CoMFA models with good statistical indices (r(2)>0.9 and q(2)>0.5) were also obtained. These models can be used as guidance for the development of new compounds with high activities and selectivities.     

Modification of UNIFAC parameter table Revision 5 for representation of aqueous solubility and 1-octanol/water partition coefficient for POPs

In order to represent aqueous solubility and 1-octanol/water partition coefficient for POPs (persistent organic pollutants) by the UNIFAC model, two pairs of group interaction parameters in Revision 5 of the UNIFAC parameter table were modified. First, the pair of interaction parameters between the aromatic carbon-chloride (ACCl) and water (H2O) groups were corrected by minimizing the deviation between the experimental and calculated values of these properties for chlorinated benzenes, polychlorinated biphenyls, and polychlorinated dibenzo-p-dioxins and dibenzofurans. The corrected interaction parameters provided a better representation of both properties than the calculation results obtained in early works using the UNIFAC model. Second, the unknown pair of interaction parameters between the chloroalkene (Cl(C=C)) and H2O groups, which are required for calculating those properties of the other five POPs (aldrin, chlordane, endrin, dieldrin, and heptachlor), were newly determined from the experimental data on their properties. Finally, this study shows that Revision 5 could also predict solubility of POPs in some organic solvents. The modified parameter table is first suggested as the UNIFAC parameter table applicable to various phase equilibria including aqueous or nonaqueous solubility and partition coefficient of POPs.     

Artificial neural network (ANN) modeling of adsorption of methylene blue by NaOH-modified rice husk in a fixed-bed column system

In this study, rice husk was modified with NaOH and used as adsorbent for dynamic adsorption of methylene blue (MB) from aqueous solutions. Continuous removal of MB from aqueous solutions was studied in a laboratory scale fixed-bed column packed with NaOH-modified rice husk (NMRH). Effect of different flow rates and bed heights on the column breakthrough performance was investigated. In order to determine the most suitable model for describing the adsorption kinetics of MB in the fixed-bed column system, the bed depth service time (BDST) model as well as the Thomas model was fitted to the experimental data. An artificial neural network (ANN)-based model was also developed for describing the dynamic dye adsorption process. An extensive error analysis was carried out between experimental data and data predicted by the models by using the following error functions: correlation coefficient (R ²), average relative error, sum of the absolute error and Chi-square statistic test (χ ²). Results show that with increasing bed height and decreasing flow rate, the breakthrough time was delayed. All the error functions yielded minimum values for the ANN model than the traditional models (BDST and Thomas), suggesting that the ANN model is the most suitable model to describe the fixed-bed adsorption of MB by NMRH. It is also more rational and reliable to interpret dynamic dye adsorption data through a process of ANN architecture.     

农药正辛醇／水分配系数的测定方法及其与其他环境参数的相关性

对已报道的农药正辛醇／水分配系数的６种测定方法进行了简述和比较，对农药Ｋｏｗ值与其他环境参数Ｓｗ，Ｋｏｃ，ＢＣＦ１的相关性进行了综述。     

Sorption of acidic organic solute onto kaolinitic soils from methanol-water mixtures

The fate of the acidic organic solute from the soil-water-solvent system is not well-understood. In this study, the effect of the acidic functional group of organic solute in the sorption from cosolvent system was evaluated. The sorption of naphthalene (NAP) and 1-naphthoic acid (1-NAPA) by three kaolinitic soils and two model sorbents (kaolinite and humic acid) were measured as functions of the methanol volume fractions (f (c) ≤ 0.4) and ionic compositions (CaCl(2) and KCl). The solubility of 1-NAPA was also measured in various ionic compositions. The sorption data were interpreted using the cosolvency-induced sorption model. The K (m) values (= the linear sorption coefficient) of NAP with kaolinitic soil for both ionic compositions was log linearly decreased with f (c). However, the K (m) values of 1-NAPA with both ionic compositions remained relatively constant over the f (c) range. For the model sorbent, the K (m) values of 1-NAPA with kaolinite for the KCl system and with humic acid for both ionic compositions decreased with f (c), while the sorption of 1-NAPA with kaolinite for the CaCl(2) system was increased with f (c). From the solubility data of 1-NAPA with f (c), no significant difference was observed with the different ionic compositions, indicating an insignificant change in the aqueous activity of the liquid phase. In conclusion, the enhanced 1-NAPA sorption, greater than that predicted from the cosolvency-induced model, was due to an untraceable interaction between the carboxylate and hydrophilic soil domain in the methanol-water system. Therefore, in order to accurately predict the environmental fate of acidic pesticides and organic solutes, an effort to quantitatively incorporate the enhanced hydrophilic sorption into the current cosolvency-induced sorption model is required.     

Correlation relationships between physico-chemical properties and gas chromatographic retention index of polychlorinated-dibenzofurans

Correlation relationships between physico-chemical properties including vapor pressures (P), water solubilities (S), Henry's law constants (H(c)), n-octanol-water partition coefficients (K(ow)), sediment-water partition coefficient (K(pw)) and biotic lipid-water partition coefficient (K(bw), bioconcentration factor) of polychlorinated-dibenzofurans (PCDFs) and their gas chromatographic retention indices (GC-RIs) were established. A model equation between GC-RIs (= RI) and these physico-chemical properties (K) of PCDFs was in a form of log K = aRI2 + bRI + c with correlation coefficients (R2) greater than 0.94, except H(c). These equations were derived from six experimental data (five experimental data for log K(bw)) in each physico-chemical properties of PCDFs reported previously. The values of log P, log S, log H(c), log K(ow), log K(pw) and log K(bw) of PCDFs predicted by these equations based on their GC-RIs in the present study derviated from those calculated by the solubility parameters for fate analysis method in a previous study by 0.49, 0.32, 0.11, 0.34, 0.14 and 0.22 log units, respectively.