Computational modeling, ligand-based drug design, drug-likeness and ADMET properties studies of series of chromen-2-ones analogues as anti-cancer agents

Abstract

Four QSAR models were developed from the training set data using genetic function algorithm (GFA) coupled with multi linear regression (MLR), and their expressions are presented below:Model 1 Y = 0.342327907 * apol + 0.002006877 * ATSC8m + 0.021947183 * ATSC7s − 2.110146447 * SM1_Dzm − 0.027702443 * SpAbs_Dzs + 0.122940438 * ZMIC4 − 9.882891756.

Model 2 Y = 0.333966562 * apol + 0.001909583 * ATSC8m + 0.019049122 * ATSC7s − 2.079324191 * SM1_DzZ − 0.027112784 * SpAbs_Dzs + 0.119956742 * ZMIC4 − 9.456381109.

Model 3 Y = 0.342932868 * apol + 0.002004154 * ATSC8m + 0.021734174 * ATSC7s − 2.067273713 * SM1_Dzm − 0.027821824 * SpAD_Dzs + 0.122642435 * ZMIC4 − 9.889860694.

Model 4 Y = 0.334437304 * apol + 0.001906343 * ATSC8m + 0.018877487 * ATSC7s − 2.033875692 * SM1_DzZ − 0.027216796 * SpAD_Dzs + 0.119277728 * ZMIC4 − − 9.454115852.