Nolatrexed Dihydrochloride

Cytochrome P450 enzymes (CYPs) play a crucial role in the metabolism and synthesis of various compound classes. While drug-metabolizing CYP enzymes are frequently investigated as anti-targets, the inhibition of CYP enzymes involved in adrenal steroidogenesis is not well studied. The steroidogenic enzyme CYP17A1 is a dual-function enzyme catalyzing hydroxylase and lyase reactions relevant for the biosynthesis of adrenal glucocorticoids and androgens. Inhibition of CYP17A1-hydroxylase leads to pseudohyperaldosteronism with subsequent excessive mineralocorticoid receptor activation, hypertension and hypokalemia. In contrast, specific inhibition of the lyase function might be beneficial for the treatment of prostate cancer by decreasing adrenal androgen levels. This study combined in silico and in vitro methods to identify drugs inhibiting CYP17A1. The most potent CYP17A1 inhibitors identified are serdemetan, mocetinostat, nolatrexed, liarozole, and talarozole. While some of these drugs are currently under investigation for the treatment of various cancers, their potential for the treatment of prostate cancer is yet to be explored. The DrugBank database was screened for CYP17A1 inhibitors, to increase the awareness for the risk of drug-induced pseudohyperaldosteronism and to highlight drugs so far unknown for their potential to cause side effects resulting from CYP17A1 inhibition.

Oral Cancer is one of the major killers in India and of global concern.An attempt has been made here to identify small mol. inhibitors of Bcl-2 (B-cell lymphoma 2) protein through docking studies in search of new oral cancer drugs from a curated set of 276 known anti-neoplastic agents obtained from PubChem.The Bcl-2 protein (PDB id:6QGH), being complexed with ligand ABT-263, has been detached from the complex.The ligand-free protein and 276 compounds have been prepared for docking studies using corresponding tools available in Discovery Studio (DS), ver.4.1.The 276 compounds have been docked on the first site of the protein using LibDock docking program available in DS.By considering Methotrexate as the reference compound (LibDock score: 114.76), we have identified 25 compounds as the most potential oral cancer drugs having LibDock scores greater than 100.Another set of 114 compounds with LibDock scores between 80 and 100 have also been identified as the next set of potential drug candidates and some of them show anti-apoptosis properties.Two other compounds with LibDock scores below 80 have been identified for comparative analyses with some high-scoring compoundsThe docking results have been given in tables and pictures (screenshots) of the docked poses of selected compounds have been shown to illustrate the findings.Finally, the most suitable potential compounds have been identified by applying Lipinski′s Rule of 5.The present approach using known anti-neoplastic agents is believed to help discover potential anti-oral cancer drug candidates.