In silico evaluation of the pharmacological potential of a series of 5- arylidene derivatives of 3-(benzo[d]thiazol-2-ylamino)-2-thioxothiazolidin-4-one

Abstract

to develop new ligands capable of specifically targeting a biological target, researchers need knowledge about potential targets. Over the past decades, the rapid development of cheminformatics has contributed to the acceleration of this process, which led to the emergence of appropriate software. In silico tools, based on the chemical structure of a molecule, can predict the possible affinity of a ligand to a specific biomolecular target with high accuracy. The broad spectrum of biological activity of rhodanine and benzothiazole has long been known. Considering the pharmacological potential of these heterocycles, we decided to investigate the influence of an arylidene moiety introduced into the 5th position of the basic heterocyclic scaffold on the biological activity of benzothiazole-substituted rhodanines. Using one of the freely available web servers, we conducted a targeted search for therapeutic targets for 5-arylidene-substituted rhodanine derivatives with a benzothiazole moiety in the 3rd position of the basic heterocycle. Through the freely available SuperPred 3.0 program, we studied the potential pharmacological activity of a series of 5-arylidene derivatives of 3-(benzo[d]thiazol-2-ylamino)-2-thioxothiazolidin-4-one. According to prediction results, all molecules are promising. The derivatives in this series, based on their chemical structure, are similar to drugs from various ATC classes and are characterized by a high probability of interaction with multiple biological targets. Based on the results of SAR analysis, it can be concluded that different aryl substituents have varying impacts on the inhibitory activity of compounds against therapeutic targets. The studied molecules demonstrated potential antitumor activity. The common predicted targets for our compounds with the highest binding scores and high model accuracy are Aldose reductase, Cathepsin D and Transcription intermediary factor 1-alpha. The highest potential inhibitory indicators for these biomolecular targets were observed for compounds 3 (97.49% for interaction with Transcription intermediary factor 1-alpha), 5 (98.42% for interaction with Aldose reductase), and 9 (98.39% for interaction with Cathepsin D). The accuracy of the prediction models is sufficiently high, amounting to 95.56%, 92.38%, and 98.95%, respectively. According to the obtained results, the predominant biological effect of the derivatives of this series is antitumor. The molecular structure of compound 7 is most similar to existing antitumor agents, while the highest binding levels to the specified targets (>90%) were observed for compounds 8, 10, and 2, with prediction model accuracy ranging from 92.38% to 98.95%. When attempting to identify certain structure–activity relationships, it was determined that the 5-arylidene moiety of the basic rhodanine scaffold plays a crucial role in revealing pharmacological effects by ensuring affinity to potential targets. The impact of 5-arylidene derivatives on relevant protein molecules is higher than predicted for the core compound; however, the obtained data require further experimental validation.