Identification and characterisation of novel antiprostate cancer compound from Indian medicinal plants

Abstract

Artificial intelligence (AI) is revolutionising many aspects of various research areas including life science. NLP and NLU is part of the AI. In the present study we have utilised this tool to identify the prostate cancer target from available literatures as the target identification is very essential for the success and failure of the drug discovery process. newlineCytochrome P450 17A1 (CYP17A1) is important enzyme that catalyses a ratelimiting step in the steroidogenic pathway which is needed for androgen production. 5and#945;-Reductase (5AR) plays an important role in androgen metabolism which convert testosterone to more potent dihydrotestosterone which aggravate the cancer. Androgen receptor (AR) overexpression enables prostate cancer to progress to CRPC. Lysine-specific histone demethylase 1A (LSD1) is an epigenetic regulator which is recently been investigated as prostate cancer target. Recently, it has been reported that Delta-like protein 3 (DLL3) is overexpressed in most of the CRPC-NE and considered as a novel drug target for molecular imaging of neuroendocrine prostate cancer highly aggressive variant and shows minimal to no expression in localized prostate cancer and benign prostate hyperplasia (BPH). Prostate cancer targets identified by our NLP/NLU programs have critical role as mentioned above which reflects the effectiveness of the tool. newline5AR and DLL3 experimental structure was not available till date so we have used the computational tools to generate it. The generated model was thoroughly examined by various tools. MD simulation was employed to get near global state conformation which was taken further for virtual screening to identify its phytochemical inhibitor. newlineFor all the five recognised prostate cancer targets a multi-stage docking approach with increasing stringent criteria was used to identify the most potent phytochemical inhibitors against it.