QSAR treatment of electronic substituent effects using frontier orbital theory and topological parameters

A methodology for the estimation of Hammett substituent constants from comp utational-based descriptors utilizing quantitative structure activity/prope rty relationships (QSAR/QSPR) formalism is presented. Electronic descriptor s derived from quantum chemical calculations and molecular topology were us ed to generate computational-based analogues of empirical Hammett substitue nt;constants from statistical analysis. Global quantum chemical reaction in ;tices were drawn from frontier orbital theory and density functional theor y and formulated from AM1-based calculations. A localized index based on th e electrotopological State index was used to encode information on individu al group properties. From a training set consisting of 150 meta and para-su bstituted benzoic acids, statistical analysis of computational-based descri ptors as a function of empirical substituent constants yielded a five-param eter QSAR/QSPR model which generates computational-based constants exhibiti ng a strong correlation with empirical values (r(2) = 0.958). Both internal (PRESS) and external (independent testing set of benzoic acids) Validation procedures suggest that the electronic effects QSAR/QSPR model derived in this work from computational-based parameters is a, statistically viable pa radigm. Both predicted and empirical constants were used in Hammett-type va lidation analyses as functions of chemical, biological, and spectroscopic d ata for thirty structurally diverse meta and para-substituted aromatic test ing sets. Statistical measures of ensuing correlations were examined and co mpared, : and the empirical and predicted results were of similar quality. Validation results reveal that a large number of computational-based substi tuent constants can be accurately estimated from semiempirical AM1 frontier orbital energies and electronic structure information obtained directly fr om substituted benzoic acids without the aid of empirical parametrization.