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.     

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.     

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.     

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 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.     

Three-dimensional, quantitative-structure-property-relationship study of aqueous solubility for phenylsulfonyl carboxylates using comparative-molecular-field analysis and comparative-molecular-similarity-indices analysis.

With both the comparative-molecular-field analysis (CoMFA) and the comparative-molecular-similarity-indices analysis (CoMSIA), the paper describes two five-component, three-dimensional, quantitative-structure-property-relationship (3D-QSPR) models for the aqueous solubility logSw (Sw, mol x L(-1)) of 52 phenylsulfonyl carboxylates. Two models yield the leave-one-out cross-validated correlation coefficient q2 values 0.851 and 0.821, and the conventional correlation coefficient r2 values 0.963 and 0.929, respectively. The achievement of high q2 and r2 values of the CoMFA model indicates the significance of correlation of steric and electrostatic fields with the aqueous solubility. The key features in the CoMFA contour maps are critical to trace the important properties and gain insight to the solvation 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 may be faster than CoMFA in data processing.     

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.     

Fate and antibacterial potency of anticoccidial drugs and their main abiotic degradation products

The antibacterial potency of eight anticoccidial drugs was tested in a soil bacteria bioassay (pour plate method), EC₅₀-values between 2.4 and 19.6 μM were obtained; however, one compound, nicarbazin exhibited an EC₅₀-value above the maximum tested concentration (21 μM, 9.1 mg L⁻¹). The potency of mixtures of two of the compounds, narasin and nicarbazin, was synergistic (more than additive) with 10-fold greater antibacterial potency of the mixture than can be explained by their individual EC₅₀-values. The influence of pH, temperature, oxygen concentration and light on the transformation of robenidine and salinomycin was investigated. Robenidine was transformed by photolysis (DT₅₀ of 4.1 days) and was unstable at low pH (DT₅₀ of approximately 4 days); salinomycin was merely transformed at low pH, the latter into an unknown number of products. The antibacterial potency of the mixtures of transformation products of robenidine after photolysis and at low pH was comparable with that of the parent compound. Finally five photo-transformation products of robenidine were structural elucidated by accurate mass measurements, i-FIT values (isotopic pattern fit) and MS/MS fragmentation patterns.     

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.     

Insights into the structure of urea-like compounds as inhibitors of the juvenile hormone epoxide hydrolase (JHEH) of the tobacco hornworm Manduca sexta: analysis of the binding modes and structure-activity relationships of the inhibitors by docking and CoMFA calculations

Substituted urea compounds are well-known as potent inhibitors of juvenile hormone epoxide hydrolase (JHEH) of the tobacco hornworm Manduca sexta. Docking simulations of 47 derivatives inside JHEH were performed to gain insight into the structural characteristics of these complexes. The obtained orientations show a strong similitude with the observed in the known X-ray crystal structures of human soluble epoxide hydrolase (sEH) complexed with dialkylurea inhibitors. In addition, the predicted inhibitor concentration (IC₅₀) of the above-mentioned compounds as JHEH inhibitors were obtained by a quantitative structure-activity relationship (QSAR) method by using comparative molecular field analysis (CoMFA) applied to aligned dataset. The best models included steric and electrostatic fields and had adequate predictive abilities. In addition, these models were used to predict the activity of an external test set of compounds that was not used for building the model. Furthermore, plots of the CoMFA fields allowed conclusions to be drawn for the choice of suitable inhibitors.     

Application of a computational model for Michael addition reactivity in the prediction of toxicity to Tetrahymena pyriformis

A computational model to predict acute aquatic toxicity to the ciliate Tetrahymena pyriformis has been developed. A general prediction of toxicity can be based on three consecutive steps: 1. Identification of a potential reactive mechanism via structural alerts; 2. Confirmation and quantification of (bio)chemical reactivity; 3. Establishing a relationship between calculated reactivity and toxicity. The method described herein uses a combination of a reactive toxicity (RT) model, including computed kinetic rate constants for adduct formation (log k) via a Michael acceptor mechanism of action, and baseline toxicity (BT), modelled by hydrophobicity (octanol-water partition coefficient). The maximum of the RT and BT values defines acute toxicity for a particular compound. The reactive toxicity model is based on site-specific steric and quantum chemical ground state electronic properties. The performance of the model was examined in terms of predicting the toxicity of 106 potential Michael acceptor compounds covering several classes of compounds (aldehydes, ketones, esters, heterocycles). The advantages of the computational method are described. The method allows for a closer and more transparent mechanistic insight into the molecular initiating events of toxicological endpoints.     

Quantitative structure-toxicity relationships of organophosphorous pesticides to fish (Cyprinus carpio)

This study was conducted to determine the relationships between 1381 chemical and structural parameters of 43 organophosphorus pesticides (OPs) and their toxicity to fish, Cyprinus carpio, using ChemOffice 8.03 and Dragon 2.1. By multivariate linear regression and intervariable regression analyses, various equations have been derived to calculate the lethal toxicity value, LC(50), for 43 OPs found in fish with different levels of toxicity. Results show that for all selected OPs, especially those of low toxic OPs (LC(50)< 2.5 mM), the equation, LC(50) = 56.259 - 13.071 lg K(ow)+17.510 MATS8P-17.455 Mor24u - 0.085 MW + 1.706 (lg K(ow))(2) + 2.306 (Mor14e)(2) + 6.849 Mor20 m (n = 43, F = 36.815, r = 0.942, r(adj)(2) = 0.862, SE = 2.899, p < 10(-6)), could account for 86.2% of the variability of the toxic effect. The steric and electronic characteristics and the hydrophobicity of OPs, in particular, are among the most important parameters determining the toxicity of OPs to fish. For the OPs with high toxicity, different structural parameters were introduced into the following two equations: LC(50)=3.795-1.195 (H1p)(2)-0.037 U-2.225 MATS3v-19.593 Tcon (n = 16, F = 56.820, r = 0.977, r(adj)(2) = 0.937, SE = 0.143, p < 10(-6)), where LC(50) is less than 2.5 mM, and LC(50) = 0.341-0.561 (HOMA)(2) + 0.231 HOMA (n = 3,r(adj)(2) = 1), where LC(50) is less than 0.3 mM. These results suggest that chemical and structural parameters could be useful in modeling chemical reactivity within homologous series of OP compounds and elucidating possible mechanisms associated with different levels of toxicity to fish.     

Separation of the strength and selectivity of the microbiological effect of synthetic dyes by spectral mapping technique

The growth inhibitory effect of 30 synthetic dyes on 22 bacteria (test organisms) belonging to various taxonomic groups was determined. The strength (potency) and selectivity of the biological effect were separated by the spectral mapping technique, reducing the dimensionality of the selectivity maps to two by the nonlinear mapping technique. The relationship between biological effect and physicochemical parameters of dyes was elucidated by stepwise regression analysis. It has been established that the strength of the effect of anthracene and trityl derivatives was higher than that of azobenzene dyes and significantly depended on the hydrophobicity of the compound. The selectivity of the effect also depended on hydrophobicity and on the nonpolar unsaturated surface area of the dyes. Gram negative and Gram positive bacteria differed in the strength and selectivity of their response to dyes indicating the marked impact of the taxonomical position on the response. Contrary to other multivariate mathematical statistical methods biological activity may be divided by SPM into potency and selectivity values, therefore, application of the technique in future QSAR studies is highly recommended.     

Source contributions to the mutagenicity of urban particulate air pollution

Using organic compounds as tracers, a chemical mass balance model was employed to investigate the relationship between the mutagenicity of the urban organic aerosol sources and the mutagenicity of the atmospheric samples. The fine particle organic mass concentration present in the 1993 annual average Los Angeles-area composite sample was apportioned among eight emission source types. The largest source contributions to fine particulate organic compound mass concentration were identified as smoke from meat cooking, diesel-powered vehicle exhaust, wood smoke, and paved road dust. However, the largest source contributions to the mutagenicity of the atmospheric sample were natural gas combustion and diesel-powered vehicles. In both the human cell and bacterial assay systems, the combined mutagenicity of the composite of primary source effluents predicted to be present in the atmosphere was statistically indistinguishable from the mutagenicity of the actual atmospheric sample composite. Known primary emissions sources appear to be capable of emitting mutagenic organic matter to the urban atmosphere in amounts sufficient to account for the observed mutagenicity of the ambient samples. The error bounds on this analysis, however, are wide enough to admit to the possible importance of additional mutagenic organics that are formed by atmospheric reaction (e.g., 2-nitrofluoranthene has been identified as an important human cell mutagen in the atmospheric composite studied here, accounting for approximately 1% of the total sample mutagenic potency).     

QSAR trout toxicity models on aromatic pesticides

The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC₅₀ concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.     

QSAR trout toxicity models on aromatic pesticides

The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC50 concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.