Comparison of criteria used to access carcinogenicity in CPANN QSAR models versus the knowledge-based expert system Toxtree

The primary goal of this study was to describe and compare the criteria used to assess carcinogenic activity. The statistically-based predictive quantitative structure–activity relationship (QSAR) models based on the counter propagation artificial neural network (CPANN) algorithm, and knowledge-based expert systems based on a decision tree structural alert (SA) approach (Toxtree application), were considered. The integration of the QSAR (CPANN models) and SAR (Toxtree SA application) approach contributed to the mechanistic understanding of the QSAR model considered. The mapping technique inherent to CPANN Kohonen enables us to relate the similarities or dissimilarities within a congeneric set of chemicals with particular SAs for carcinogenicity. The focus of our investigations was the similarities and dissimilarities of the features used in the QSAR and SAR methods. Due to the complexity of the carcinogenic endpoint, the integration of different approaches allows the models to be improved and provides a valuable technique for evaluating the safety of chemicals.     

Prediction of spectral interference in inductively coupled plasma-atomic emission spectrometry by primary computer expert system

Spectra and spectral interferences in inductively coupled plasma-atomic emission spectrometry, ICP-AES, have been simulated and predicted by a primary expert system under contrasting conditions of local temperature equilibrium (LTE) and non-LTE. In this expert system a comprehensive computer model has been applied to provide expert knowledge on an non-LTE ICP discharge, analyte ionization and excitation, and spectral line shape. The system also includes several databases to supply the calculation with spectral and elemental parameters. Some typical examples are illustrated, with satisfactory outcomes. It is found that predictions under non-LTE conditions are much closer to the reality than those under LTE conditions.     

Prediction of carcinogenicity of polynuclear aromatic hydrocarbons on the basis of their chemical structures

The carcinogenicities of polynuclear aromatic hydrocarbons in particulates extracted from diesel engine exhaust are predicted on the basis of the combined bay-L region theory proposed earlier, in conjunction with pattern recognition techniques. The predicted carcinogenicities agree well with experimental data, thus showing the validity of the proposed model equations.     

Method development by an expert system advantages and limitations

Several approaches can be used for the prediction of the optimum eluent composition in RP-HPLC, but only a few are known that use the structure of the solute. The latest release of the computer program EluEx, version 3.0, was developed to help the chromatographer in practical work. The program is based on the prediction of the pK_a and log P (logarithm of 1-octanol-water partition coefficient) values of the solutes. The first eluent suggestion can be done without any preliminary practical work, based on the structural formulae of the solutes. In our experience, two or three experiments are usually sufficient to determine the optimized binary conditions. The surface heterogeneity and the diversity of RP columns, such as the effect of silanol interaction, can be handled by the program only to a limited extent. If the difference in hydrophobicity between two compounds is small, the elution order cannot be predicted properly in all instances. The same is true for some isomers, e.g., diastereomers. In this paper, the results of applying the program to some neutral, acidic and basic solutes are summarized.     

Prediction of acute toxicity of organophosphorus pesticides using topological indices

Topological indices were used in the prediction of the acute toxicity (intraperitoneal and oral LD₅₀) of organophosphorus pesticides on rats. Models with six variables for the prediction of LD₅₀-i.p. (r?=?0.849, Q ²?=?0.613) and eight variables for LD₅₀-oral (r?=?0.906, Q ²?=?0.701) were selected. External group and cross-validation by use of leave-n-out tests were also performed in order to assess the stability and the prediction performance of the selected topological models.     

Prediction of acute toxicity of organophosphorus pesticides using topological indices

Topological indices were used in the prediction of the acute toxicity (intraperitoneal and oral LD(50)) of organophosphorus pesticides on rats. Models with six variables for the prediction of LD(50)-i.p. (r = 0.849, Q(2) = 0.613) and eight variables for LD(50)-oral (r = 0.906, Q(2) = 0.701) were selected. External group and cross-validation by use of leave-n-out tests were also performed in order to assess the stability and the prediction performance of the selected topological models.     

Prediction of aqueous solubility of drugs and pesticides with COSMO-RS

The COSMO-RS method, originally developed for the prediction of liquid-liquid and liquid-vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO-RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug-like compounds. On these data an rms deviation of 0.66 log-units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log-units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO-RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO-RSol.     

Prediction of solvents extraction-the organochlorine pesticides in soil using solubility parameter

Prediction of the optimal extraction solvent based on the solubility parameter to extract the typical organochlorine pesticides from Jiangxi red soil was reported in this paper. Hildebrand solubility parameters, including dispersion coefficient (δ_d), polarity (δ_p) and hydrogen bonding (δ_h), of extraction solvents (including hexane, dichloromethane, hexane/methanol (4:1, v/v), hexane/acetone (1:1, v/v), hexane/dichloromethane (1:1, v/v) and organochlorine pesticides were calculated using group contribution method. The solvents, such as hexane/methanol (4:1, v/v) and hexane/acetone (1:1, v/v) were selected as ideal extraction solvents to extract o,p′-DDT o,p′-DDE and o,p′-DDD with high recoveries (>82%), furthermore, these solvents can be used to extract α-endosulfan, Endrin and HCB with the reliable recoveries (>75%). The estimated finding by solubility parameters was supported by the results of soxhlet extraction.     

ChemInform Abstract: Prediction of the Fundamental Vibrational Frequencies for C60 by Local Density Functional Theory

ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.     

Gas chromatographic system for the identification of halogenated pesticides by retention indices using n-alkanes as standards

A gas chromatographic system for the evaluation of linear temperature-programmed retention indices allowing n-alkanes to be adopted as the reference retention markers for any type of analyte, irrespective of the atoms present in their molecules, is described. It is based on the simultaneous use of two different detectors (a flame ionization detector and a specific detector suitable for the sample components), both connected (in parallel) to the same column outlet. The performance of this system has been tested by measuring the retention indices of fifteen chlorinated pesticides under conditions of linear programming temperature, by adopting an electron-capture detector as the specific detector. The reliability of the retention indices thus determined has been proven by verifying that they can be reproduced under different chromatographic conditions.     

Multidetermination of PCBs and pesticides by use of a dual GC column-dual detector system

Summary A new gas chromatographic method involving the use of two capillary columns, a switching valvue and electron capture-nitrogen-phosphorus detection, and allowing up to four retention characteristics per component to be obtained is reported.The proposed method was applied to the analysis for 123 compounds (13 PCBs and 110 pesticides), the determination limits and optimal measuring ranges of which are reported.The performance of the method was checked by analysis of certified standards and spiked samples, and was applied to the determination of the analytes in various water samples.     

An in silico expert system for the identification of eye irritants

This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient chemicals for eye irritancy potential, which is based upon exclusion rules of five physicochemical properties – molecular weight (MW), hydrophobicity (log P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA) and polarizability (Pol). These rules were developed using the ADMET Predictor software and a dataset of 917 eye irritant chemicals. The dataset was divided into 826 (90%) chemicals used for training set and 91 (10%) chemicals used for external validation set (every 10th chemical sorted by molecular weight). The sensitivity of these rules for the training and validation sets was 72.3% and 71.4%, respectively. These rules were also validated for their specificity using an external validation set of 2011 non-irritant chemicals to the eye. The specificity for this validation set was revealed as 77.3%. This method facilitates rapid screening and prioritization of data poor chemicals that are unlikely to be tested for eye irritancy in the Draize test.     

An expert system applied to the control of an industrial-scale bioreactor

Control of a fed-batch industrial-scale fermenter requires a large amount of “finger-tip feeling” on the part of operators, despite reasonably sophisticated instrumentation. The reason for this is that there are no applicable deterministic models giving aid to the control system in deciding the best operation strategies. This is a typical case of a heuristic experimental process, treating inexact knowledge that is excluded from deterministic and statistic modelling a priori. Essential parts of this problem can be solved by means of an expert system shell, capable of dealing with uncertain information, using the linguistic shell application. Knowledge was extracted from process records on fermentation batches producing baker's yeast on an industrial scale. A strategy for heuristically optimized yield and growth rate can be predicted using knowledge gained in previous runs and stored in the knowledge base of the expert system. The expert system, once built up, can also be used for experimental simulation of the effects of fundamental decision parameters: temperature, production rate, ethanol concentration and specific growth rate. The use of expert system consultations can be generally recommended as an efficient aid in fermentation control.     

Development of an expert system rulebase for the prospective identification of photoallergens

Relationships between the structure and properties of chemicals can be programmed into knowledge-based systems such as DEREK (an acronym for 'Deductive Estimation of Risk from Existing Knowledge'). The DEREK knowledge-based computer system contains a sub-set of over 50 rules describing chemical substructures (toxophores) responsible for skin sensitization. This rulebase, based originally on Unilever historical in-house guinea pig maximisation test data, is largely complete and is undergoing refinement as the next stage of its development. As part of an ongoing program of validation and testing, the predictive ability of the sensitization rule set was assessed by processing the structures of over 100 chemical substances in the list of contact allergens identified by the BgVV (German Federal Institute for Health Protection of Consumers). The exercise highlighted areas of chemistry where further development of the rulebase was required, either by extension of the scope of existing rules or by generation of new rules where a sound mechanistic rationale for the biological activity could be established. Several chemicals likely to be acting as photoallergens were identified and rules for photoallergenicity were written covering three classes of chemicals. This paper describes work to extend the DEREK rules for photoallergenicity as part of the European Phototox Project.