Computer-Aided Drug Design Identifies Amentoflavone as Novel RAB10 Inhibitor: Unlocking New Horizons in Hepatocellular Carcinoma Therapy

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is often associated with a poor prognosis, contributing significantly to cancer-related mortalities. It has been established that RAB10, a member of the RAS family, is overexpressed in HCC and plays an oncogenic role in the emergence of HCC, and developing medications that target it may offer a fresh approach to the disease's management. Therefore, a computational approach was employed to identify potential novel RAB10 inhibitors, and 2569 natural compounds were looked into for this. Initially, 10 compounds were identified by virtual screening and molecular docking to have the highest binding affinities (−9.6 to −10.1 kcal/mol) to the active site of RAB10, where 8 were deemed to meet the necessary criteria for becoming a drug-like substance. Following ADMET analysis, Amentoflavone, among the 8 substances, showed a considerable pharmacokinetics index without any associated toxicity. Amentoflavone was found to form both covalent and non-covalent interactions with the active residues of RAB10, essential for inhibiting its activity. LYS154, ALA153, and LYS22 amino acids of RAB10 were found to interact with the Amentoflavone via the generation of three intermolecular H-bonds. The drug-protein combination, which supports maintaining its structural stability and stiffness, demonstrates structural compactness and minimal conformational fluctuation, according to molecular dynamics simulation. Molecular Mechanics Poisson-Boltzmann Surface Area analysis further confirmed the stable binding of Amentoflavone inside the binding pocket of RAB10. These findings hypothesize that Amentoflavone might be a potential RAB10 inhibitor, which would increase HCC's therapeutic prospects. Received: 18 October 2024 | Revised: 28 March 2025 | Accepted: 20 May 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this study. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. The final outputs of all the analyses are documented in the main manuscript. Author Contribution Statement Md. Anayet Ullah: Methodology, Software, Formal analysis, Writing – original draft, Visualization. Priya Paul: Software, Formal analysis, Writing – original draft, Visualization. Sadia Afrin Runa: Formal analysis, Writing – original draft. Fatema Tuz Johura: Formal analysis, Writing – original draft. Mahafujul Islam Quadery Tonmoy: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing – review & editing, Visualization. Md. Shahriar Kabir Shakil: Resources, Writing – review & editing. Rumana Rashid: Writing – review & editing. Md. Mizanur Rahaman: Resources, Writing – review & editing. Newaz Mohammed Bahadur: Conceptualization, Validation, Investigation, Resources, Writing – review & editing, Supervision.