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Multivariate image analysis quantitative structure-activity relationship (MIA-QSAR) study aims to obtain information from a descriptor set, which are image pixels of two-dimensional molecule structures. In the QSAR study of protein P38 mitogen-activated protein (MAP) kinase compounds, the genetic algorithm application for pixel selection and image processing is investigated. There is a quantitative relationship between the structure and the pIC50 based on the information obtained. (The pIC50 is the negative logarithm of the half-maximal inhibitory concentration (IC50), so pIC50 = -log IC50.) Protein P38 MAP kinase inhibitors are used in the treatment of malignant tumors. The development of a model to predict the pIC50 of these compounds was performed in this study. To accomplish this, the molecules were first plotted and fixed in the same coordinates in ChemSketch. Then, the images were processed in the MATLAB program. Partial least squares (PLS) model, orthogonal signal correction partial least squares (OSC-PLS) model, and genetic algorithm partial least squares (GA-PLS) model methods are used to generate quantitative models, and pIC50 prediction is performed. The GA-PLS model has the highest predictive power for a series of statistical parameters such as root mean square error of prediction (RMSEP) and relative standard errors of prediction (RSEP). Finally, the molecular junction (docking) was done for predicted molecules in quantitative structure activity relationship (QSAR) with an appropriate receptor and acceptable results were obtained. These results are good and proper for the prediction of compounds with better properties. [ABSTRACT FROM AUTHOR]

Nowadays, Pyrazolone and its derivatives have gained a lot of attention due to their biological and medicinal applications. These compounds have antimicrobial, antifungal and anticancer properties. Therefore, using simple methods to prepare these compounds is important. Pyrazolone is one of the inhibitors of kinase domain containing receptor KDR or VEGFR-2. In this study, Quantitative Structure-Activity Relationship (QSAR) analysis was used to predict the inhibitory activity of new pyrazolone derivatives. Also, Bi-dimensional images were used to calculate pixels for QSAR modeling. Furthermore, the partial least squares (PLS) was used to establish a relationship between IC50-dependent variables and independent variables, i.e., pixels or hidden variables. In addition, Genetic Algorithm (GA) was used in PLS method (GA-PLS) to select the descriptors. In this method, the variables which selected to form the calibration model had negligible errors with acceptable characteristics. Pre-processing methods such as Orthogonal Signal Correction (OSC) were used to provide a suitable input for modeling as well as to improve the results of the GA (OSC-GA-PLS). Furthermore, Root Mean Squared Error of Prediction (RMSEP) was used to assess the performance of the models to predict the pIC50 of the studied compounds, the value of which was obtained equal to 0.30, 0.22, and 0.19 for PLS, GA-PLS and OSC-GA-PLS models, respectively. Finally, the proposed QSAR model was developed with the OSC-GA-PLS method to predict the inhibitory activity of the new compounds. [ABSTRACT FROM AUTHOR]

5a -reductase 2 is an interesting pharmaceutical target for the treatment of several diseases, including prostate cancer, benign prostatic hyperplasia, male pattern baldness and hirsutism. Quantitative structure-activity relationship (QSAR) analysis has been carried out for the prediction of inhibitory activity of a set of 4-X-17-Y-4-Azaandrost-3-ones as 5a -reductase 2 inhibitors. Bi-dimensional images were applied to calculate some pixels and partial least squares (PLS) algorithm was applied to QSAR modelling of 5a -reductase inhibitors. In this paper, we surveyed the effect of variable selection by application of genetic algorithms (GAs) for the PLS model. The GAs is very helpful in the variable selection in modeling and selecting the subset of pixels with the low prediction error. Pre-processing methods such as orthogonal pixel correction (OPC) were also used to provide the suitable input for modeling. These models were applied to the prediction of the molecules inhibition, which were not in the modeling procedure. The resulted model showed a high predictive ability with the root mean square error of prediction (RMSEP) of 0.52, 0.35 and 0.94 for PLS, GA-PLS and OPC-GA-PLS models respectively. Furthermore, the proposed QSAR model with the OPC-GA-PLS method was developed to predict the inhibitory activity of the new compounds. [ABSTRACT FROM AUTHOR]

Thirty-one Cephalosporin compounds were modeled using the multivariate image analysis and applied to the quantitative structure activity relationship (MIA-QSAR) approach. The acid dissociation constants (pKa) of cephalosporins play a fundamental role in the mechanism of activity of cephalosporins. The antimicrobial activity of cephalosporins was related to their first pKa by different models. Bidimensional molecular structures (images) were used to calculate some pixel descriptors. The selection of pixels by successive projections algorithm (SPA) was done to achieve simple MIA-QSAR models; based on a small subset of pixels. In the present study, the performance of pixel selection technique using SPA for partial least squares (PLS) model was evaluated. The obtained model showed nice prediction ability with root mean square error of prediction (RMSEP) values of 0.402, 0.315, and 0.160 for principal component regression (PCR), PLS and SPA-PLS models respectively. Among the three methods, SPA-PLS was potentially useful in predicting the pKa of cephalosporins. The study showed the maximum structural efficacy is on pKa in a, b and c regions. [ABSTRACT FROM AUTHOR]

A quantitative structure-activity relationship (QSAR) modeling was carried out for the prediction of inhibitory activity of dihydropyridine (DHP) derivatives known as calcium channel blocker (CCB) drugs. Partial least squares (PLS) algorithm was used for prediction of inhibitory activity of calcium channel antagonists as a function of the bidimensional images. In the present study, it is investigated that the effect of pixel selection by application of genetic algorithms (GAs) for PLS model, because of the GAs is very useful in the variable selection in modeling. Pre-processing methods such as wavelet transform (WT) were also used to enhance the predictive power of multivariate calibration methods. The subset of pixels, which resulted in the low prediction error, was selected by GA. To evaluate the models applied in this study (PLS, GA-PLS and WT-GA-PLS), the inhibitory activities of several compounds, not included in the modeling procedure, were predicted. The results of models showed high prediction ability with root mean square error of prediction (RMSEP) of 0.51, 0.39 and 0.17 for PLS, GA-PLS and WT-GA-PLS, respectively. The WT-GA-PLS method was employed to predict the inhibitory activity of the new antagonists. [ABSTRACT FROM PUBLISHER]

Abstract: Cloud point extraction has been used for the preconcentration of m-nitroaniline, o-nitroaniline and p-nitroaniline and later simultaneous spectrophotometric determination using polyethylene glycol tert-octylphenyl ether (Triton X-100) as surfactant. The resolution of a ternary mixture of the nitroaniline isomers (after extraction by cloud point) by the application of least-squares support vector machines (LS-SVM) was performed. The chemical parameters affecting the separation phase and detection process were studied and optimized. Under the optimum experimental conditions (i.e. pH 7.0, Triton X-100=0.6%, equilibrium time 20min and cloud point 75°C), calibration graphs were linear in the range of 0.2–20.0, 0.1–15.0 and 0.1–17.0μgml−1 with detection limits of 0.08, 0.05 and 0.06μgml−1 for m-nitroaniline, o-nitroaniline and p-nitroaniline, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graphs concentrations of nitroaniline isomers. The root mean square error of prediction (RMSEP) for m-nitroaniline, o-nitroaniline and p-nitroaniline were 0.0146, 0.0308 and 0.0304, respectively. This procedure allows the simultaneous determination of nitroaniline isomers in synthetic and real matrix samples good reliability of the determination was proved. [Copyright &y& Elsevier]

A simple, novel and sensitive spectrophotometric method was described for simultaneous determination of nitrophenol isomers mixtures. All factors affecting on the sensitivity were optimized and the linear dynamic range for determination of nitrophenol isomers were found. The simultaneous determination of nitrophenol mixtures by using spectrophotometric methods is a difficult problem, due to the spectral interferences. The partial least squares modeling was used for the multivariate calibration of the spectrophotometric data. The orthogonal signal correction was used for preprocessing of data matrices and the prediction results of model, with and without using orthogonal signal correction, were statistically compared. The experimental calibration matrix was designed by measuring the absorbance over the range 300–520nm for 21 samples of 1–20, 1–20 and 1–10μgml−1 of m-nitrophenol, o-nitrophenol and p-nitrophenol, respectively. The RMSEP for m-nitrophenol, o-nitrophenol and p-nitrophenol with and without OSC were 0.3682, 0.5965, 0.3408 and 0.7351, 0.9962, 1.0055, respectively. The proposed method was successfully applied for the determination of m-nitrophenol, o-nitrophenol and p-nitrophenol in synthetic and real matrix samples such as water. [Copyright &y& Elsevier]

A quantitative structure-property relationship study is suggested for the prediction of the acidity constants of some thiazolidine-4-carboxylic acid derivatives in aqueous solution. Ab initio theory was used to calculate some quantum chemical descriptors, including electrostatic potentials and local charges at each atom, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, etc. Modeling of the acidity constant of thiazolidine-4-carboxylic acid derivatives as a function of molecular structures was established by means of the partial least squares algorithm. The subset of descriptors, which resulted in a low prediction error, was selected by genetic algorithm. This model was applied for the prediction of the acidity constant of some thiazolidine-4-carboxylic acid derivatives, which were not in the modeling procedure. Relative errors of prediction lower than 1.5% were obtained by using the genetic algorithm-partial least squares (GA-PLS) method. The developed model has good prediction ability with a root mean square error of prediction of 0.0419 and 0.1013 for PLS and GA-PLS models, respectively. [ABSTRACT FROM AUTHOR]

Partial least squares modeling is a powerful multivariate statistical tool applied to extraction-spectrophotometric simultaneous determination of mixtures of barium and strontium. The method is based on the formation of the ternary complexes with 18C6 and rose bengal with barium and strontium. The 18C6-Ba-RB and 18C6-Sr-RB ternary complexes are quantitatively extracted into dichloromethane and the resolution of the mixtures is accomplished by partial least squares (PLS). In this study, the calibration model is based on absorption spectra in the 500-600 nm range for 25 different mixtures of barium and strontium. Calibration matrice's ranges were 0.05-5.50 and 0.03-4.50 m g mL-1 and detection limits were 0.036 and 0.017 m g mL-1 for barium and strontium, respectively. A series of synthetic solutions containing different concentrations of barium and strontium was used to check the prediction ability of the PLS model. The RMSEP for barium and strontium was 0.1323 and 0.0327 respectively. The method was successfully applied to the analysis of spiked water (natural, tap and waste waters) samples. [ABSTRACT FROM AUTHOR]

Abstract: The simultaneous determination of nitroaniline isomer mixtures by using spectrophotometric methods is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used for removes the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 200–500nm range for 21 different mixtures of nitroaniline isomers. Calibration matrices were containing 1–21, 1–15 and 1–18μgml−1 of m-nitroaniline, o-nitroaniline and p-nitroaniline, respectively. The RMSEP for m-nitroaniline, o-nitroaniline and p-nitroaniline with OSC and without OSC were 0.6567, 0.2692, and 0.3134, and 1.3818, 1.2181, and 0.3953, respectively. This procedure allows the simultaneous determination of nitroaniline isomers in real matrix samples and good reliability of the determination was proved. [Copyright &y& Elsevier]

Genetic algorithm (GA) is a suitable method for selecting wavelengths for PLS (partial least squares) calibration of mixtures with almost identical spectra without loss of prediction capacity using spectrophotometric method. The method is based on the development of the reaction between the analytes and Zincon at pH 9. A series of synthetic solution containing different concentrations of copper and zinc were used to check the prediction ability of the GA–PLS models. The RMSD for copper and zinc with GA and without GA were 0.0407 and 0.0865, 0.2147 and 0.3005, respectively. Calibration matrices were 0.05–1.8 and 0.05–1.5 μg ml−1 for copper and zinc, respectively. This procedure allows the simultaneous determination of cited ions in natural, tap and waste waters good reliability of the determination was proved. [Copyright &y& Elsevier]

The partial least squares calibration method was applied for the kinetic simultaneous determination of the divalent ions of cobalt, nickel and copper based on their catalytic effect on the reaction between resazurine and sulfide. The experimental calibration matrix was designed with 21 samples. The concentrations were varied between 0.1-1.1, 0.1-2.8 and 0.1-1.1 7mu;g ml[SUP-1] for cobalt, nickel and copper, respectively. The cross-validation method was used to select the number of factors. The RMSD for cobalt, nickel and copper were 0.0122, 0.0195 and 0.0179, respectively. Application of the method to artificial samples and several mixtures of standard solutions are performed which gave acceptable results. [ABSTRACT FROM AUTHOR]