Identification of apigenin as a multi-target inhibitor against SARS-CoV-2 by computational exploration

Multi-target strategy can serve as a valid treatment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but existing drugs most focus on a single target. Thus, multi-target drugs that bind multiple sites simultaneously need to be urgently studied. Apigenin has antiviral and anti-inflammatory properties. Here, we comprehensively explored the potential effect and mechanism of apigenin in SARS-CoV-2 treatment by a network algorithm, deep learning, molecular docking, molecular dynamics (MD) simulation, and normal mode analysis (NMA). KATZ-based VDA prediction method (VDA-KATZ) indicated that apigenin may provide a latent drug therapy for SARS-CoV-2. Prediction of DTA using convolution model with self-attention (CSatDTA) showed potential binding affinity of apigenin with multiple targets of virus entry, assembly, and cytokine storms including cathepsin L (CTSL), membrane (M), envelope (E), Toll-like receptor 4 (TLR4), nuclear factor-kappa B (NF-κB), NOD-like receptor pyrin domain-containing protein 3 (NLRP3), apoptosis-associated speck-like protein (ASC), and cysteinyl aspartate-specific proteinase-1 (Caspase-1). Molecular docking indicated that apigenin could effectively bind these targets, and its stability was confirmed using MD simulation and NMA. Overall, apigenin is a multi-target inhibitor for the entry, assembly, and cytokine storms of SARS-CoV-2.