QSAR studies on benzene sulfonamide carbonic anhydrase inhibitors: need of hydrophobic parameter for topological modeling of binding constants of sulfonamides to human CA-II.

The binding constants (logK) of benzene sulfonamides to human CA-II have been modeled using a large series of distance-based topological indices. The need or otherwise of the hydrophobic parameter (logP) for such topological modeling of logK has been examined critically. In both the cases excellent results have been obtained. In multiparametric models involving indicator parameters we observed that introduction of hydrophobic parameter (logP) yields much improved statistics. The results are discussed on the basis of statistical parameters and also by using cross-validation method.

Novel use of chemical shift in NMR as molecular descriptor: a first report on modeling carbonic anhydrase inhibitory activity and related parameters.

A novel use of NMR chemical shift of the SO(2)NH(2) protons (in dioxane as solvent) as a molecular descriptor is described for modeling the inhibition constant for benzene sulfonamides against the zinc enzyme carbonic anhydrase (CA, EC 4.2.1.1). The methodology is extended to model diuretic activity and lipophilicity of benzene sulfonamide derivatives. The regression analysis of the data has shown that the NMR chemical shift is incapable of modeling lipophilicity. However, it is quite useful for modeling the diuretic activity of these derivatives. The results are compared with those obtained using distance-based topological indices: Wiener (W)-, Szeged (Sz)-, and PI (Padmakar-Ivan) indices.

Use of the PI index in predicting toxicity of nitrobenzene derivatives.

The PI Index is a Szeged-like topological index developed very recently. It has useful applications in chemistry which are yet to be investigated thoroughly. Herein, we report quantitative structure-toxicity relationship (QSTR) study using the PI Index. We have used 41 monosubstituted nitrobenzene for this purpose. The results have shown that the PI Index alone is not an appropriate index for modelling toxicity of nitrobenzene derivatives. Combinations of the PI Index with other distance-based topological indices resulted into statistically significant models and excellent results are obtained in pentaparametric models. The predictive potential of the models is discussed on the basis of cross-validation method, as well as by estimating root-mean-square error (RMS).

Prediction of lipophilicity of polyacenes using quantitative structure-activity relationships.

Predictive models for the lipophilicity (logP) of first 25 derivatives of polyacenes are reported. The models are derived from distance-based numerical descriptors which encode information about topology of each compounds in the data set. A new PI-type index called Sadhna index and abbreviated as Sd is introduced for the first time, and its relative correlation potential is established using the results obtained from Wiener (W), Szeged (Sz), first-order Randic connectivity (chi), and Padmakar-Ivan indices. The data show that lipophilicity (logP) is best modelled in bi-parametric model containing PI and Sd indices. The effect due to size, shape, branching, steric and polarity effects on the exhibition of lipophilicity is critically discussed. The predictive ability of the models is discussed on the basis of cross-validation parameters.