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Marcelo Lazzarotto

Publications and source records attributed to Marcelo Lazzarotto.

2 recordsLinked to original sources

Optimized modified topliss method: a tool for quantitative structure-activity relationship studies.

The structural variation of lead compounds often includes the variation of substituents at a particular site. A common difficulty, in quantitative structure-activity relationship (QSAR) studies, is to select the best substituents to obtain, with a minimum number of experiments, a major change in some impor. tant properties of the molecule. To improve a proposed modified Topliss method, 187 different substituted compounds belonging to 70 series were studied. A single linear regression was carried out between the experimental activity of each series of compounds and the molecular structure parameters pi, sigma, Es and MR, along with some combinations of them, in order to select the best substituents for constructing the "reduced" correlation. This selection considered the scaled smallest residue average of the substituent, the number of times that the substituent is inserted in the 70 series and its quadrant in the Craig graph. The results obtained in this study with this simple method showed a good predictive capacity when compared with the multiple regression analysis, using the Hansch method.

Algorithms↗

From the manual method of Topliss to a modified quantitative method.

The optimization of the properties of a lead compound is the first goal of most pre-clinical research projects. Optimization strategies may be applied to the synthesis of analogous compounds in order to minimize cost and time. One strategy of synthesis is the change of the substituents in the molecule. The manual method of Topliss was introduced for the prediction of the substituted compounds that will have the most potent activity in a series of aromatic substituted analogues. A modified Topliss method is proposed that consist of the quantitative correlation by a single regression equation of the activity of a series of 4 or 5 substituted aromatic compounds with the descriptor parameters: hydrophobic (pi), electronic (sigma) and sterics (Es and MR) and some combinations of them in order to predict future synthesis, or to obtain a training set of compounds to be used in the application of more advanced experimental design methods. These results when compared with those of multiple regression analysis applying the Hansch equation are very satisfactory.

Drug Design↗