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Quantitative structure-property relationship study on the determination of binding constant by fluorescence quenching

100%

Liu H., Wen Y., Luan F., Gao Y., Guo Y., Xie Z., Hu Z.

Models to predict binding constant (logK) to bovine serum albumin (BSA) should be very useful in the pharmaceutical industry to help speed up the design of new compounds, especially as far as pharmacokinetics is concerned. We present here an extensive list of logK binding constants for thirty-five compounds to BSA determined by florescence quenching from the literature. These data have allowed us the derivation of a quantitative structure-property relationship (QSPR) model to predict binding constants to BSA of compounds on the basis of their structure. A stepwise multiple linear regression (MLR) was performed to build the model. The statistical parameter provided by the MLR model (R = 0.9200, RMS = 0.3305) indicated satisfactory stability and predictive ability for the model. Using florescence quenching spectroscopy, we also experimentally determined the binding constants to BSA for two bioactive components in traditional Chinese medicines. Using the proposed model it was possible to predict the binding constants for each, which were in good agreement with the experimental results. This QSPR approach can contribute to a better understanding of structural factors of the compounds responsible for drug-protein interactions, and be useful in predicting the binding constants of other compounds. [...]

Chemometric estimation of the RP TLC retention behaviour of some estrane derivatives by using multivariate regression methods

88%

Kovačević S., Jevrić L., Podunavac Kuzmanović S., Lončar E.

Open Chemistry

2013

vol. 11

issue 12

2031-2039

Quantitative structure-retention relationship (QSRR) was developed for a series of estrane derivatives, on the basis of their retention data, obtained in reversed-phase thin-layer chromatography (RP TLC), and in silico molecular descriptors. Physicochemical and topological descriptors, as well as molecular bulkiness descriptors, were calculated from the optimized molecular structures. Full geometry optimization was achieved by using Austin Model 1 (AM1) semi-empirical molecular orbital method. In the present study, QSRR analysis was based on principal component analysis (PCA), multiple linear regression (MLR) and partial least squares (PLS) method. PCA was applied in order to reveal similarities or dissimilarities between analytes, and MLR and PLS regression methods were carried out in order to identify the most important in silico molecular descriptors and quantify their influence on the retention behaviour of studied compounds. Physically meaningful and statistically significant structure-retention relationships were established. [...]

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2 Open Chemistry

1 2013

1 2009

1 Gao Y.

1 Guo Y.

1 Hu Z.

1 Jevrić L.

1 Kovačević S.

1 Liu H.

1 Lončar E.

1 Luan F.

1 Podunavac Kuzmanović S.

1 Wen Y.

1 Xie Z.

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Quantitative structure-property relationship study on the determination of binding constant by fluorescence quenching

Chemometric estimation of the RP TLC retention behaviour of some estrane derivatives by using multivariate regression methods