NEWLY DEVELOPED STATISTICALLY INTENSIVE QSAR MODELS FOR BIOLOGICAL ACTIVITY OF ISATIN DERIVATIVES

Abstract

The present study introduces a new approach for the quantitative structure-activity relationship (QSAR) issue, which can be called a statistically intensive or condensed QSAR model. This idea was successfully applied to the published data of 32 biologically active molecules derived from 4-(1-aryl-2-oxo-1,2-dihydro-indol-3-ylideneamino)-N-substituted benzene sulfonamides for mixed bacteria and specific bacteria like B.subtilis, E.coli, and S.aureus. The suggested four statistically intensive QSAR (SIQSAR) models possess only two descriptors with excellent statistical parameters, as their values of the square regression coefficient (r²) and cross-validation (q²) are lying within the range of 0.967-0.997 and 0.961-0.996, respectively. A zero-one correction term (ZO) reflects the effect of substituents, which was proposed as a second descriptor for two sets of biologically active compounds. In general, the results showed that the biological activity is depended majorly on the topographical properties, and predominated by the field-effect in contrast to an electronic one. The interesting feature of SIQSAR models is their closeness to mathematical methods such as simultaneous linear equation method by eliminating the common inaccuracy and unrealistic statistical treatments. The obtained SIQSAR models were employed for predicting new and efficient biologically active molecules derived from isatin.