Identification and Evaluation of Bioactive Compounds from Azadirachta indica as Potential Inhibitors of DENV-2 Capsid Protein: An Integrative Study Utilizing Network Pharmacology, Molecular Docking, Molecular Dynamics Simulations, and Machine Learning Techniques.

印楝属 对接(动物) 计算生物学 鉴定(生物学) 生物信息学 分子动力学 化学 药理学 传统医学 生物化学 生物 医学 计算化学 植物 护理部 基因
作者
Md. Ahad Ali Khan,Md. Nazmul Hasan Zilani,Mahedi Hasan,Nahid Hasan
出处
期刊:Heliyon [Elsevier BV]
卷期号:11 (4): e42594-e42594
标识
DOI:10.1016/j.heliyon.2025.e42594
摘要

Dengue fever is a viral disease caused by the dengue flavivirus and transmitted through mosquito bites in humans. According to the World Health Organization, severe dengue causes approximately 40,000 deaths annually, and nearly 4 billion people are at risk of dengue infection. The urgent need for effective treatments against the dengue virus has led to extensive research on potential bioactive compounds. In this study, we utilized a network pharmacology approach to identify the DENV-2 capsid protein as an appropriate target for intervention. Subsequently, we selected a library of 537 phytochemicals derived from Azadirachta indica (Family: Meliaceae), known for their anti-dengue properties, to explore potential inhibitors of this protein. The compound library was subjected to molecular docking to the capsid protein to identify potent inhibitors with high binding affinity. We selected 81 hits based on a thorough analysis of their binding affinities, particularly those exhibiting higher binding energy than the established inhibitor ST-148. After evaluating their binding characteristics, we identified two top-scored compounds and subjected them to molecular dynamics simulations to assess their stability and binding properties. Additionally, we predicted ADMET properties using in silico methods. One of the inhibitors, [(5S,7R,8R,9R,10R,13R,17R)-17-[(2R)-2-hydroxy-5-oxo-2H-furan-4-yl]-4,4,8,10,13-pentamethyl-3-oxo-5,6,7,9,11,12,16,17-octahydrocyclopenta[a]phenanthren-7-yl] acetate (AI-59), showed the highest binding affinity at -10.4 kcal/mol. Another compound, epoxy-nimonol (AI-181), demonstrated the highest number of H-bonds with a binding affinity score of -9.5 kcal/mol. During molecular dynamics simulation studies, both compounds have exhibited noteworthy outcomes. Through molecular mechanics employing Generalized Born surface area (MM/GBSA) calculations, AI-59 and AI-181 displayed negative ΔG_bind scores of -74.99 and -83.91 kcal/mol, respectively. The hit compounds identified in the present investigation hold the potential for developing drugs targeting dengue virus infections. Furthermore, the knowledge gathered from this study serves as a foundation for the structure- or ligand-based exploration of anti-dengue compounds.
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