LAUSR

The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in the body. In this work, a three dimensional-quantitative structure activity relationship (3D-QSAR) pharmacophore model is developed on a diverse set of non-steroidal inhibitors of CYP17A1 enzyme. Highly active compounds are selected to define a six-point pharmacophore hypothesis with a unique geometrical arrangement fitting the following description: two hydrogen bond acceptors (A), two hydrogen bond donors (D) and two aromatic rings (R). The QSAR model showed adequate predictive statistics. The 3D-QSAR model is further used for database virtual screening of potential inhibitory hit structures. Density functional theory (DFT) optimization provides the electronic properties explaining the reactivity of the hits. Docking simulations discovers hydrogen bonding and hydrophobic interactions as responsible for the binding affinities of hits to the CYP17A1 Protein Data Bank structure. 13 hits from the database search (including five derivatives) are then synthesized in the laboratory as different scaffolds. Ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in vitro experiments reveals three new chemical entities (NCEs) with half maximal inhibitory concentration (IC50) values against the lyase route at mid-micromolar range with favorable selectivity to the lyase over the hydroxylase route (one of them with null hydroxylase inhibition). Thus, prospective computational design has enabled the design of potential lead lyase-selective inhibitors for further studies.