QSAR, molecular docking approach on the estrogenic activities of persistent organic pollutants using quantum chemical disruptors

Abstract

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.