Is clay-polycation adsorbent future of the greener society? In silico modeling approach with comprehensive virtual...

Presence of organic pollutants in the wastewater and aquatic environment is one of the serious concerns worldwide. Superior adsorption of organic pollutants on modified clays with organocations is well approved nowadays. Among hybrid materials, clay-polyelectrolyte nanocomposites (CPN) are one of the specifically designed materials for the efficient adsorption of diverse organic pollutants. Due to higher surface area of the clay mineral coupled with a polymer coating, they have an explicit affinity for the organic pollutants. In this background, we have developed statistically significant and mechanistically interpretable quantitative structure-property relationship (QSPR) model for adsorption coefficient of diverse organic pollutants to the protonated montmorillonite-poly-4-vinylpyridine-co-styrene (Mt-HPVPcoS), a hybrid CPN. Further, the model was employed to predict the logk_d value of ∼0.9 million chemicals from five diverse databases spanning from existing and experimental pharmaceuticals, natural and synthetic chemicals and dyes with unknown logk_d value for the mentioned CPN. The reliability of predicted data is checked with two layers confidence screening i.e. the applicability domain study followed by prediction quality check by 'Prediction Reliability Indicator'. Thus, prediction of each compound can be used for data gap filling by environmental regulatory authorities as well as industries. Followed by, maximum common substructure-based (MCS) algorithm is employed for individual database to extract the important structural scaffold for higher logk_d to the mentioned CPN.