Development of Novel QSPR Strategy and Models for the Solubility Prediction and In Silico Bioavailability Study of Paclitaxel Prodrugs

Abstract

Cancer is one of the most deadly diseases prevailing now-a-days. One of the common characteristic that all cancer cells share is the abnormal growth of cells. Chemotherapy is a universal way for treating cancer. Taxol having the encouraging anti-cancer activity but there is delay in the development of this drug because of its low aqueous solubility and hypersensitivity posed by its formulation in Cremophor EL. To avoid this hypersensitivity and obtain better clinical use of Paclitaxel, developing a new co-solvent and improving the formulation for Paclitaxel delivery systems has become important. In addition to developing better formulation for Paclitaxel, there were ways to achieve more efficient modified Paclitaxel that is prodrug formation. Theoretical models such as quantitative structure property-relationship (QSPR) can provide a set of predictors for any molecular property using the structure of the molecule. Delving into the cost- and time-effective computational strategies for the solubility prediction of prodrugs was performed. A novel QSPR strategy (QSPR-sPL) has been developed for the solubility prediction of small datasets as from pharmaceutical perspective small datasets are important for the solubility prediction. Also, dataset of Paclitaxel prodrug was and the substituent groups were taken for the solubility prediction implementing the pipeline developed. Also to increase the bioavailability, study with human metabolic enzymes for the metabolic study of phosphate Paclitaxel prodrugs was performed in-silico to inspect their oral bioavailability and found the highly soluble Isotaxel to be more bioavailable that could be given orally also. newline