{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T05:35:12Z","timestamp":1792128912162,"version":"4.4.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T00:00:00Z","timestamp":1765843200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The coronavirus disease 2019 (COVID-19) pandemic underscored the urgent need for broad-spectrum antiviral agents capable of targeting both viral proteins and host factors to mitigate disease severity. Apigenin has antiviral and anti-inflammatory properties. However, the potential of apigenin against SARS-CoV-2 remains insufficiently explored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this study, the potential role of apigenin in the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the underlying mechanism were explored using matrix factorization, deep learning, multiscale molecular modeling and network pharmacology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The graph-based integrated Gaussian kernel similarity (GiGs) model predicted that apigenin might be a drug against SARS-CoV-2. The prediction of drug-target affinity using a convolution model with self-attention (CSatDTA) model revealed the potential binding affinity of apigenin with glucose-regulated protein 78 (GRP78) and heparan sulfate proteoglycan (HSPG). Molecular docking further validated strong binding to GRP78 (\u20138.198 kcal\/mol) and moderate binding to HSPG (\u20135.6 kcal\/mol), mediated by van der Waals forces and hydrogen bonds. Multiscale molecular modeling revealed that apigenin could bind to Non-structural protein 15 (Nsp15). Further, the network pharmacology analysis implied that apigenin might modulate the host inflammatory responses by potentially regulating the PI3K-Akt and HIF-1 signaling pathways and binding directly to protein kinase B (AKT1) and prostaglandin endoperoxide synthase 2 (PTGS2).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Computational profiling suggests apigenin exerts a multi-target mechanism against SARS-CoV-2, potentially disrupting viral entry, replication, and host inflammatory responses. The findings of this research outline a promising strategy and provide a rationale for developing novel natural product-based treatment methods for SARS-CoV-2.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmicb.2025.1708660","type":"journal-article","created":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T06:26:34Z","timestamp":1765866394000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Nature\u2019s cryptographic codebreaker: in silico decoding of apigenin\u2019s triple defense against SARS-CoV-2"],"prefix":"10.3389","volume":"16","author":[{"given":"Juanjuan","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yabo","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongya","family":"Guan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoukui","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"D437","DOI":"10.1093\/nar\/gkaa1038","article-title":"RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences.","volume":"49","author":"Burley","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1926","DOI":"10.3390\/vaccines10111926","article-title":"The delta and omicron variants of SARS-CoV-2: What we know so far.","volume":"10","author":"Chavda","year":"2022","journal-title":"Vaccines"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1458","DOI":"10.3390\/v14071458","article-title":"Commercially Available Flavonols Are Better SARS-CoV-2 inhibitors than isoflavone and flavones.","volume":"14","author":"Chaves","year":"2022","journal-title":"Viruses"},{"key":"B4","doi-asserted-by":"publisher","first-page":"153603","DOI":"10.1016\/j.phymed.2021.153603","article-title":"Apigenin inhibits the growth of colorectal cancer through down-regulation of E2F1\/3 by miRNA-215-5p.","volume":"89","author":"Cheng","year":"2021","journal-title":"Phytomedicine"},{"key":"B5","doi-asserted-by":"publisher","first-page":"107945","DOI":"10.1016\/j.asoc.2021.107945","article-title":"A deep learning ensemble approach to prioritize antiviral drugs against novel coronavirus SARS-CoV-2 for COVID-19 drug repurposing.","volume":"113","author":"Deepthi","year":"2021","journal-title":"Appl. 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