Fragment-based discovery of novel Baicalein derivatives as triple-target 3CLpro/PLpro/RdRp inhibitors against SARS-CoV-2.

Abstract

The rapid evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the emergence of drug resistance necessitate the development of multi-target antiviral therapeutics. This study aimed to computationally design a novel triple-target inhibitor derived from the natural flavonoid Baicalein, targeting the essential SARS-CoV-2 enzymes 3CLpro, PLpro, and RdRp to combat viral resistance. An integrated computational approach was employed, including virtual screening of compound libraries, molecular docking using Molecular Operating Environment software, fragment-based drug design to optimize Baicalein, and molecular dynamics simulations over 200 ns with AMBER 18 to assess binding stability. Binding free energies were calculated via MM/GBSA methods, and pharmacokinetic properties were evaluated using ADME/T predictions. Retrosynthetic analysis was performed to confirm synthetic feasibility. The novel compound BD02 demonstrated stable binding to all three targets, with significantly improved binding free energies compared to Baicalein: 3CLpro (-50.68 kcal/mol), PLpro (-59.05 kcal/mol), and RdRp (-51.98 kcal/mol). Molecular dynamics simulations showed low root mean square deviation values, indicating high structural stability. ADME/T predictions revealed favorable drug-like properties, including good absorption and low toxicity risks. BD02 is a computationally promising synthetic lead scaffold for broad-spectrum anti-coronavirus design. This multi-target design theoretically helps mitigate viral resistance and provides structural design references.