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The HIV-1 reverse transcriptase (RT) is a major target for drug development. Inhibition of this enzyme has been one of the primary therapeutic strategies in suppressing the replication of HIV-1. A series of 2-amino-6-arylsulfonylbenzonitrile derivatives were subjected to quantitative structure-activity relationship (QSAR) analysis. Very recently, we proposed the use of substituent electronic descriptors (SED) instead of the electronic descriptors of whole molecules as new and expedite source of electronic descriptors. In this study, we used SED parameters in QSAR modeling of anti HIV-1 activity of 6-arylsulfonylbenzonitrile derivatives. In SED methodology produces a vector of electronic descriptors for each substituent and thus a matrix of SED is generated for each molecule. Consequently, a three-dimensional array is obtained by staking the data matrices of different molecules beside each other. As a novel multiway data analysis method, molecular maps of atom-level properties (MOLMAP) approach was also used to transfer a three-dimensional array of SED descriptors into new two-dimensional parameters using Kohonen network, following by genetic algorithm-based partial least square(GA-PLS) to connect a quantitative relationship between the Kohonen scores and biological activity.In unfolding data, HOMO1, HOMOB1, SOFB1 and EPHA4 represent the most important indices on QSAR equation derived by PLS analysis. Accurate QSAR models were obtained by both approaches. The resulted GA-PLS model of MOLMAP approach possessed high statistical quality r2= 0.83 and q2=0.70. It could explain and predict about 70% of variances in the anti-HIV1 inhibitory activity of the studied molecules. However, the superiority of three-way analysis of SED parameters based on MOLMAP approach with respect to simple unfolding was obtained.