Prediction of interaction energies of substituted hydrogen-bonded Watson-Crick cytosine:guanine(8X) base pairs.

We investigated the variation in the interaction energy between the Watson-Crick hydrogen-bonded DNA base pairs guanine and cytosine (G(8X):C), where guanine is substituted in the C8 position by 37 different functional groups. Base pairs were optimized at the B3LYP/6-311+G(2d,p) level. A base pair complex containing a more strongly electron-withdrawing group remarkably forms a more stable base pair with C. Multivariate linear regression provided a quantitative relationship between the interaction energies and descriptors generated by the quantum chemical topology (QCT) approach. The descriptors were sampled from the monomers only, not the supermolecular base pair complexes. A model with r2 = 0.96 and a root-mean-square (rms) value of 0.6 kJ/mol was obtained for a training set of 28 base pair complexes. The model was tested by an external test set of 9 complexes, yielding r2 = 0.99 and an rms value of 0.2 kJ/mol. The results indicated that the bonds C6=O6 and N2-H2 at the hydrogen-bonded frontier of the guanine derivatives play an important role in transmitting the substituent effects. A linear correlation between substitution energies and Hammett constants (sigma(m)) was also obtained for all 37 substituents, yielding r2 = 0.82 and an rms value of 1.2 kJ/mol. The model based on QCT descriptors can therefore be used for the prediction of the interaction energy of the base pair G(8x):C, strictly based on data for the G(8x) monomers only.

Electrochemical studies of the interaction of clarithromycin with bovine serum albumin.

The interaction of clarithromycin (CAM) with bovine serum albumin (BSA) was investigated in pH 4.5-8.0 phosphate buffer solutions in which three irreversible reduction waves P(1), P(2) and P(3) of CAM appeared on linear-sweep voltammetry on a static dropping mercury working electrode. In the acidic media, with the addition of BSA into the CAM solution, a new electrochemically active complex was formed and there was interaction between the carbonyl group C=O in the C-9 position of CAM and BSA. It was found that electrostatic and hydrophobic forces played an important role in the binding reaction. However, new electrochemically non-active complexes were formed at physiological pH condition. The study showed that the formation constant and formation ratio of the interaction between CAM and BSA were 1.51 x 10(12) and 3:1 for P(2) wave, and 4.53 x 10(5) and 1:1 for P(3) wave, respectively. The ion strength enhanced the hydrophobic interaction between CAM and BSA.

Computational study of substituent effects on the interaction energies of hydrogen-bonded Watson-Crick cytosine: guanine base pairs.

The substituent effects on interaction energies of hydrogen-bonded DNA Watson-Crick base pairs in the gas phase were captured in a model using ab initio descriptors (at the B3LYP/6-311+G(2d,p) level). While forming a noncovalently bonded complex with unsubstituted guanine (G), cytosine (C) carried 42 possible substituents both at the C6 position (C6X:G) and at the C5 position (C5X:G). We rationalize why complexes possessing a more strongly electron-withdrawing group in CX form less stable base pairs. Multivariate linear regression constructed the quantitative relationships between the interaction energies of the complexes and the descriptors, which were drawn from quantum chemical topology (QCT). For the C6X dataset, the best model yielded r2 = 0.93 and a root-mean-square (rms) energy of 0.53 kJ/mol for the 28 complexes in the training set. This model was evaluated by an external test set (14 complexes), yielding an r2 value of 0.96 and an rms error of 0.42 kJ/mol. For the C5X dataset, the QCT descriptors generated a linear model, with r2 values of 0.92 and 0.97 and rms values of 1.69 and 1.24 kJ/mol for the training set (31 compounds) and the external test set (11 compounds), respectively. The models built here could therefore be useful for the assessment of the interaction energy of C6X:G and C5X:G purely from monomeric data.

Mutagenic probability estimation of chemical compounds by a novel molecular electrophilicity vector and support vector machine.

MOTIVATION: Mutagenicity is among the toxicological end points that pose the highest concern. The accelerated pace of drug discovery has heightened the need for efficient prediction methods. Currently, most available tools fall short of the desired degree of accuracy, and can only provide a binary classification. It is of significance to develop a discriminative and informative model for the mutagenicity prediction. RESULTS: Here we developed a mutagenic probability prediction model addressing the problem, based on datasets covering a large chemical space. A novel molecular electrophilicity vector (MEV) is first devised to represent the structure profile of chemical compounds. An extended support vector machine (SVM) method is then used to derive the posterior probabilistic estimation of mutagenicity from the MEVs of the training set. The results show that our model gives a better performance than TOPKAT (http://www.accelrys.com) and other previously published methods. In addition, a confidence level related to the prediction can be provided, which may help people make more flexible decisions on chemical ordering or synthesis. AVAILABILITY: The binary program (ZGTOX_1.1) based on our model and samples of input datasets on Windows PC are available at http://dddc.ac.cn/adme upon request from the authors.

Classification study of skin sensitizers based on support vector machine and linear discriminant analysis.

The support vector machine (SVM), recently developed from machine learning community, was used to develop a nonlinear binary classification model of skin sensitization for a diverse set of 131 organic compounds. Six descriptors were selected by stepwise forward discriminant analysis (LDA) from a diverse set of molecular descriptors calculated from molecular structures alone. These six descriptors could reflect the mechanic relevance to skin sensitization and were used as inputs of the SVM model. The nonlinear model developed from SVM algorithm outperformed LDA, which indicated that SVM model was more reliable in the recognition of skin sensitizers. The proposed method is very useful for the classification of skin sensitizers, and can also be extended in other QSAR investigation.

[The effects of kuijiekang capsule on ulcerative colitis induced by TNBS in rats].

OBJECTIVE: To evaluate the effects of Kuijiekang Capsule (KJK) on rats colitis induced by TNBS. METHODS: Rats with TNBS/ethanol-induced colitis were used and treated with KJK. The experimental animals were divided into 6 groups: control group, model group, SASP group (0.50 g/kg), KJK group (0.64, 0.32, 0.16 g/kg). The animals were administrated 0. 5% carboxymethyl cellulose, SASP and KJK respectively (from the 6th d after the establishment of ulcerative colitis model to the end of the experiment, 18 d totally). At the end of the experiment, the colon mucosal damage index (CMDI), the activity of myelperoxidase (MPO) and the occult blood test (OB) in feces were observed, the mucosa pathohistology was measured and thymus and spleen of rats were weighed respectively. Meanwhile, the content of malondiadehyde (MDA) , superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) of colonic tissue were detected. RESULTS: The remarkable effects of KJK at dosage of 0.64, 0.32 g/kg on TNBS-induced colitis were observed, the extent of CMDI and OB were decreased, MPO activeity of colonic tissue was reduced. The extent of atrophy of thymus gland and intumesce of spleen of rat were ameliorated. Meanwhile, the content of MDA was reduced, and the activities of SOD and GSH-Px were increased. Pathological histology results showed that KJK could alleviate the pathohistological lesion of the colon of rat. CONCLUSION: Treatment with KJK shows beneficial effects on the mucosal damage of rats colitis induced by TNBS/ethanol. The mechanism of the actions of KJK may relate to anti-inflammatory effect, immunoloregulation and anti-oxidation.

Development of migration models for acids in capillary electrophoresis using heuristic and radial basis function neural network methods.

A quantitative structure-mobility relationship (QSMR) was developed for the absolute mobilities of a diverse set of 277 organic and inorganic acids in capillary electrophoresis based on the descriptors calculated from the structure alone. The heuristic method (HM) and the radial basis function neural networks (RBFNN) were utilized to construct the linear and nonlinear prediction models, respectively. The prediction results were in agreement with the experimental values. The HM model gave a root-mean-square (RMS) error of 3.66 electrophoretic mobility units for the training set, 4.67 for the test set, and 3.88 for the whole data set, while the RBFNN gave an RMS error of 2.49, 3.19, and 2.65, respectively. The heuristic linear model could give some insights into the factors that are likely to govern the mobilities of the compounds, however, the prediction results of the RBFNN model seem to be better than that of the HM.

Effect of Chinese medicine alpinetin on the structure of human serum albumin.

Alpinetin (7-hydroxy-5-methoxyflavanone), one of the main constituents from the seeds of Alpinia katsumadai Hayata, belongs to flavonoids with its usefulness as antibacterial, anti-inflammatory and other important therapeutic activities of significant potency and low systemic toxicity. In this paper, the interaction of alpinetin to human serum albumin (HSA) has been studied for the first time by spectroscopic method including Fourier transform infrared (FT-IR) spectroscopy, circular dichroism (CD), and UV-absorption spectroscopy in combination with fluorescence quenching study under physiological conditions with drug concentrations of 3.3 x 10(-6)-2.0 x 10(-5)mol/L. The results of spectroscopic measurements and the thermodynamic parameters obtained (the enthalpy change DeltaH(0) and the entropy change DeltaS(0) were calculated to be -10.20 kJ/mol and 53.97 J/molK(-1) according to the Van't Hoff equation) suggest that hydrophobic interaction is the predominant intermolecular forces stabilizing the complex, which is also good agreement with the results of molecule modeling study. The alterations of protein secondary structure in the presence of alpinetin in aqueous solution were quantitatively estimated by the evidences from FT-IR and CD spectroscopy with reductions of alpha-helices about 24%, decreases of beta-sheet structure about 2%, and increases of beta-turn structure about 21%. The quenching mechanism and the number of binding site (n approximately 1) were obtained by fluorescence titration data. Fluorescent displacement measurements confirmed that alpinetin bind HSA on site III. In addition, the effects of common ions on the constants of alpinetin-HSA complex were also discussed.

QSPR prediction of GC retention indices for nitrogen-containing polycyclic aromatic compounds from heuristically computed molecular descriptors.

Gas chromatographic retention indices of nitrogen-containing polycyclic aromatic compounds (N-PACs) have been predicted by quantitative structure-property relationship (QSPR) analysis based on heuristic method (HM) implemented in CODESSA. In order to indicate the influence of different molecular descriptors on retention indices and well understand the important structural factors affecting the experimental values, three multivariable linear models derived from three groups of different molecular descriptors were built. Moreover, each molecular descriptor in these models was discussed to well understand the relationship between molecular structures and their retention indices. The proposed models gave the following results: the square of correlation coefficient, R(2), for the models with one, two and three molecular descriptors was 0.9571, 0.9776 and 0.9846, respectively.

Study of quantitative structure-mobility relationship of carboxylic and sulphonic acids in capillary electrophoresis.

A quantitative structure-mobility relationship (QSMR) was developed for the absolute mobilities of 115 carboxylic and sulphonic acids in capillary electrophoresis based on the descriptors calculated from the structure alone. The heuristic method (HM) and radial basis function neural networks (RBFNN) were utilized to construct the linear and nonlinear prediction models, respectively. The prediction results were in agreement with the experimental values. The HM model gave an root-mean-square (RMS) error of 3.76 electrophoretic mobility units for the training set, 5.59 for the test set, and 4.19 for the whole data set, while the RBFNN gave an RMS error of 1.78, 2.04, and 1.83, respectively. The heuristic linear model could give some insights into the factors that are likely to govern the mobilities of the compounds, however, the prediction results of the RBFNN model seem to be better than that of the heuristic method.

Simultaneous determination of some active ingredients in anti-viral preparations of traditional Chinese medicine by micellar electrokinetic chromatography.

A simple and rapid micellar electrokinetic chromatography method was developed for the simultaneous determination of quercetin, gentiopicrin, forsythin, chlorogenic acid and caffeic acid in anti-viral preparations of traditional Chinese medicine (apTCM). In this method, the effects of buffer pH, concentration of the borax and SDS, organic modifiers, applied voltage and temperature on the separation were tested and discussed. The results showed that the fi ve analytes could be well separated within 11 min under conditions of 40 mM borax (pH 9.65) containing 20 mM SDS, 20 kV, at 25 degrees C. In the tested concentration range, regression equations revealed good linear relationships (correlation coefficients 0.9920-0.9991) between the peak areas and corresponding concentrations. In addition, a multiple linear regression QSPR model was constructed to predict the migration times of the analytes and the results were satisfactory. The method was validated by analysis of the five compounds in three representative apTCM samples with recoveries ranging from 89.2 to 106.6%.

Study on the quantitative relationship between the structures and electrophoretic mobilities of flavonoids in micellar electrokinetic capillary chromatography.

Quantitative structure-mobility relationship (QSMR) models were developed between the structures of flavonoids and their eletrophoretic mobilities in micellar electrokinetic capillary chromatography. Molecular descriptors calculated from structure alone are used to represent molecular structures, moreover, Nt was defined by ourselves. Multiple linear regression and radial basis function neural networks (RBFNNs) are utilized to construct the linear and nonlinear prediction model, respectively. The optimal QSMR model developed was based on a 3-10-1 RBFNNs architecture. The root mean square errors in mobilities predictions for the data set was 0.1083 mobility unit (10(-4) cm2 V(-1) s(-1)). The prediction results were in good agreement with the experimental values.