Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of >13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer.Communicated by Ramaswamy H. Sarma.
Keywords: Delta‐like ligand 3; homology modelling; molecular docking; molecular dynamics simulations; neuroendocrine prostate cancer; phytochemicals.