Quantitative structure-activity relationship (QSAR), for predicting estrogenic activity of persistent organic pollutants (POPS) activity of different compounds used as dataset. Density functional theory using B3LYP/6-31G* quantum chemical calculation method was used to find the optimized geometry of the studied chemical disruptor compounds. Fourteen types of molecular descriptors were used to find out the relation between POPS activity and structural properties. Relevant molecular descriptors were selected by genetic function algorithms. The best model obtained was given a distinct validated, good and robust statistical parameters which include; Square correlation coefficient R 2 value of (0.9289), Adjusted determination coefficient, R 2 adj value of (0.9284), leave one out cross validation determination coefficient Q 2 value of (0.9548) and external validation as predicted determination coefficient R value of R 2 (0.819335). Molecular docking analysis find out, the best lead-compound with the higher negative value score of (− 11.8 kcal/mol) were formed hydrophobic interaction and H-bonding with amino acid residue between the disruptor compounds with their 1 × 7j as receptor. The result obtained from the study is expected to be significant and predict estrogenic activities disruptors of the POPS.
In order to develop quantitative structure-activity relationship (QSAR), for predicting antiulcer activity of hydroxamic acid analogues use as dataset and their antiulcer activity were obtained from the literature. Density Functional Theory (DFT) using B3LYP/6-31G* quantum chemical calculation method was used to find the optimized geometry of the studied compounds. Eight types of molecular descriptors were used to find out the relation between antipeptic ulcer (APU) activity and structural properties. Relevant molecular descriptors were selected by Genetic Function Algorithms (GFA). The best model obtained was given a distinct validated, good and robust statistical parameters which include; square correlation coefficient R2 value of (0.9989), adjusted determination coefficient, R2adj value of (0.9984), Leave one out cross validation determination coefficient Q2 value of (0.9948) and external validation as predicted determination coefficient R2 value of(0.8409). Molecular docking analysis find out that, the best lead-compound with the higher negative value score of (-8.5 kcal/mol) were formed hydrophobic interaction and H-bonding with amino acid residue between the inhibitors compounds with their respective receptor.
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