Identification of novel dihydroorotate dehydrogenase (DHODH) inhibitors for cancer: computational drug repurposing strategy

癌症新型二氢乳清酸脱氢酶 (DHODH) 抑制剂的鉴定:计算机辅助药物重定位策略

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Abstract

BACKGROUND: Dihydroorotate dehydrogenase (DHODH) is a crucial enzyme in de novo pyrimidine production, initially sought since its disruption is frequently observed in malignancies. DHODH inhibitors have been demonstrated in multiple trials to effectively destroy tumour cells. For instance, leflunomide, teriflunomide and brequinar are currently in practice for DHODH based therapeutics. However, their usage is hampered due to their less efficiency and toxicity issues. Adding together, no studies have reported drug repurposing efforts targeting DHODH. METHODS: To address these challenges, the present study aimed to identify novel and potent DHODH inhibitors through virtual screening, with a distinct focus on repurposing. Initially, 2619 FDA approved molecules were subjected to molecular docking using AutoDock Vina and Molsoft ICM-Pro. Consequently, binding free energy were performed using Uni-GBSA and PRODIGY. Toxicity and cancer cell line activity were assessed using high precision machine learning techniques. In the end, gold standard simulation studies executed to validate the hit compound inhibitory activity against DHODH protein. RESULTS: The results of our analysis identified two molecules, DB09026 and DB00503, as potent DHODH inhibitors. It is worth noting that the identified compound able to bind with key residues in the DHODH target protein. Moreover, scaffold analysis supports the existence of anti-cancer activity of the identified compounds. In essence, long 100ns molecular dynamic simulation results were also correlates well with the previous results. CONCLUSION: Collectively, we hypothesize that both ritonavir and Aliskiren exhibits minimal side effect, it could be of interesting choice for the management of cancer due to its improved potency. CLINICAL TRIAL NUMBER: Not applicable.

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