<b>Combinatorial Design of Imidazole/Triazole Linked Aryl-Substituted Derivatives as CYP17 Inhibitors Exploring Hansch and Molecular Docking Approach</b>

Prostate cancer is an age-related most common cancer characterized by uncontrolled cell growth that develops in the walnut-sized prostate gland in men that potentially forms tumors and metastases to other parts of the body that are untreated. It is widely recognized that 80% of the prostate cancers are androgen-dependent. Thus, inhibition of CYP17 hydroxylase and lyase will stop the androgen synthesis and testosterone over production and ultimately help in treating prostate cancer. Heterocyclic scaffolds (especially imidazole and triazole) have great affinity and potency against the CYP17 hydroxylase and lyase. In this study, we developed a statistically robust and reliable predictive model using Hansch and topological parameters with a series of phenyl alkyl imidazole-based 17α-hydroxylase/17-20-lyase inhibitors. The promising scaffolds were optimized based on the mechanistic interpretations of substitutions, fragments, and branching, and a total of 3645 novel compounds were designed and screened over topological models to identify drug-like potential inhibitors. Molecular docking analysis depicted binding patterns, interaction energies, and a possible mechanism of inhibition of potential molecules. Finally, six potential hydroxylase and nine lyase inhibitors were reported based on the docking score and binding free energy. The novel 369 and 318 are the most promising designed candidates for prostate cancer treatment, while the compound 625 is a potential selective lyase inhibitor with 375-fold activity over the hydroxylase. The ADMET study states the compounds are drug-like and non-toxic. The findings of this study will definitely help the experimental researchers with a prior basis for the potential of novel, promising CYP-17 inhibitors of this class. Received: 23 August 2024 | Revised: 19 December 2024 | Accepted: 15 January 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. Author Contribution Statement Balaji Wamanrao Matore: Data curation, Writing – original draft, Visualization. Anjali Murmu: Writing – review & editing. Jagadish Singh: Formal analysis, Investigation. Partha Pratim Roy: Conceptualization, Methodology, Software, Validation, Resources, Supervision, Project administration.