Computational Assessment of Plant-Derived Alkaloids for Anti-SARS-CoV-2 Properties - Maniyeri, Abhinav; Krishnamoorthy, Karthika (Sciences of Phytochemistry, 2026)
The demand for efficient antiviral treatments that go beyond traditional treatment, whose effectiveness may be compromised by viral changes and documented adverse effects following immunization, has increased due to the quick and ongoing introduction of SARS-CoV-2 variations. In this regard, a potential class of natural chemicals for SARS-CoV-2 medication development is plant-derived alkaloids, which are known for their broad-spectrum antiviral qualities. This research employs network pharmacology, gene ontology, and molecular docking to find effective alkaloid candidates that can target conserved viral proteins across SARS-CoV-2 variations. 5 bioactive alkaloids were screened against three key coronavirus proteins—2AJF (spike RBD–ACE2 complex), 2DD8 (spike RBD-neutralizing antibody complex), and 2J98 (replication-associated nsp9 protein). Binding affinities ranged from -6.0 to -11.3 kcal/mol, with Manzamine A emerging as the strongest inhibitor across all targets (2AJF: -11.3, 2DD8: -10.0, 2J98: -9.1 kcal/mol). Its stable hydrogen-bonding network and interactions with key amino acids suggest strong potential to disrupt viral entry, immune evasion mechanisms, and replication processes. Network pharmacology revealed 5,272 SARS-CoV-2 associated genes, of which 51 overlapped with alkaloid-related targets. Venn analysis identified 6 shared genes, and protein-protein interaction (PPI) network construction highlighted critical hub regulators like MTOR, AKT1, STAT3, SYK, CASP3, and JAK2 implicated in immune modulation, apoptosis, inflammation, and viral pathogenicity. The combined computational approach identifies Manzamine A as a promising natural scaffold for anti-SARS-CoV-2 drug development. Experimental validation through in vitro, in vivo, MD simulation and pharmacokinetic research is still necessary to show clinical application, even though the results provide insightful information for future therapeutic design.