In silico modelling of thiazolidine derivatives with antioxidant potency: Models quantify the degree of contribution of molecular fragments towards the free radical scavenging ability

Saturated Five-Membered Thiazolidines and Their Derivatives: From Synthesis to Biological Applications

In past decades, interdisciplinary research has been of great interest for scholars. Thiazolidine motifs behave as a bridge between organic synthesis and medicinal chemistry and compel researchers to explore new drug candidates. Thiazolidine motifs are very intriguing heterocyclic five-membered moieties present in diverse natural and bioactive compounds having sulfur at the first position and nitrogen at the third position. The presence of sulfur enhances their pharmacological properties, and, therefore, they are used as vehicles in the synthesis of valuable organic combinations. They show varied biological properties viz. anticancer, anticonvulsant, antimicrobial, anti-inflammatory, neuroprotective, antioxidant activity and so on. This diversity in the biological response makes it a highly prized moiety. Based on literature studies, various synthetic approaches like multicomponent reaction, click reaction, nano-catalysis and green chemistry have been employed to improve their selectivity, purity, product yield and pharmacokinetic activity. In this review article, we have summarized systematic approaches for the synthesis of thiazolidine and its derivatives, along with their pharmacological activity, including advantages of green synthesis, atom economy, cleaner reaction profile and catalyst recovery which will help scientists to probe and stimulate the study of these scaffolds.

Development of predictive models for silicone rubber-water partition coefficients of hydrophobic organic contaminants

The silicone rubber passive sampling technique is extensively applied to monitor the aqueous freely dissolved concentration of hydrophobic organic compounds (HOCs). The silicone rubber-water partition coefficient (Ksrw) is an important parameter to accurately measure the concentrations of chemicals using passive sampling devices. In this study, two theoretical linear solvation energy relationship (TLSER) models and a quantitative structure-property relationship (QSPR) model were developed for predicting the Ksrw of HOCs. The 119 model compounds studied here included 31 personal care products, such as musks, UV-filters, and organophosphate flame retardants, as well as "conventional" pollutants, such as polycyclic aromatic hydrocarbons and polychlorinated biphenyls. The statistical parameters indicated that the final QSPR model with seven descriptors for all 119 chemicals had a satisfactory goodness-of-fit (Radj2 = 0.898), robustness (QLOO2 = 0.881) and predictive ability (Qext-F1,2,32 = 0.897-0.926). In comparison, the results of one TLSER model with four descriptors for 113 chemicals (Radj2 = 0.826, QLOO2 = 0.790, Qext-F1,2,32 = 0.805-0.837) and another TLSER model with one descriptor for 5 chemicals (Radj2 = 0.747, QLOO2 = 0.647) were also acceptable. The applicability domains of the obtained models covered chemicals containing hydroxyl, imino groups, carbonyl groups, ether bonds, halogen atoms, sulfur atoms, phosphorus atoms, nitro groups, and cyano groups. In addition, the structural features governing the partition behavior of chemicals between silicone rubber and water were explored through interpretation of appropriate mechanisms.