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
Background: 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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025009740 |
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| Summary: | Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusion: 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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| ISSN: | 2405-8440 |