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通过模拟病毒融合动力学发现的广谱冠状病毒抑制剂。

Broad-spectrum coronavirus inhibitors discovered by modeling viral fusion dynamics.

作者信息

Reilly Charles B, Moore Joel, Lightbown Shanda, Paul Austin, Bernier Sylvie G, Carlson Kenneth E, Ingber Donald E

机构信息

Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, United States.

Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States.

出版信息

Front Mol Biosci. 2025 May 15;12:1575747. doi: 10.3389/fmolb.2025.1575747. eCollection 2025.

DOI:10.3389/fmolb.2025.1575747
PMID:40443526
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12119275/
Abstract

Development of oral, broad-spectrum therapeutics targeting SARS-CoV-2, its variants, and related coronaviruses could curb the spread of COVID-19 and avert future pandemics. We created a novel computational discovery pipeline that employed molecular dynamics simulation (MDS), artificial intelligence (AI)-based docking predictions, and medicinal chemistry to design viral entry inhibitors that target a conserved region in the SARS-CoV-2 spike (S) protein that mediates membrane fusion. DrugBank library screening identified the orally available, FDA-approved AXL kinase inhibitor bemcentinib as binding this site and we demonstrated that it inhibits viral entry in a kinase-independent manner. Novel analogs predicted to bind to the same region and disrupt S protein conformational changes were designed using MDS and medicinal chemistry. These compounds significantly suppressed SARS-CoV-2 infection and blocked the entry of S protein-bearing pseudotyped α,β,γ,δ, variants as well as SARS CoV and MERS-CoV in human ACE2-expressing or DPP4-expressing cells more effectively than bemcentinib. When administered orally, the optimized lead compound also significantly inhibited SARS-CoV2 infection in mice. This computational design strategy may accelerate drug discovery for a broad range of applications.

摘要

开发针对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)及其变体以及相关冠状病毒的口服广谱疗法,可能会遏制2019冠状病毒病(COVID-19)的传播,并避免未来的大流行。我们创建了一种新颖的计算发现流程,该流程采用分子动力学模拟(MDS)、基于人工智能(AI)的对接预测和药物化学来设计病毒进入抑制剂,这些抑制剂靶向SARS-CoV-2刺突(S)蛋白中介导膜融合的保守区域。药物银行库筛选确定了口服可用的、美国食品药品监督管理局(FDA)批准的AXL激酶抑制剂贝美替尼可结合该位点,并且我们证明它以激酶非依赖的方式抑制病毒进入。使用MDS和药物化学设计了预测可结合同一区域并破坏S蛋白构象变化的新型类似物。这些化合物在表达人血管紧张素转换酶2(ACE2)或表达二肽基肽酶4(DPP4)的细胞中,比贝美替尼更有效地显著抑制SARS-CoV-2感染,并阻断携带S蛋白的α、β、γ、δ变体假型以及严重急性呼吸综合征冠状病毒(SARS-CoV)和中东呼吸综合征冠状病毒(MERS-CoV)的进入。口服给药时,优化后的先导化合物在小鼠中也显著抑制SARS-CoV-2感染。这种计算设计策略可能会加速广泛应用的药物发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/08b350d9502d/fmolb-12-1575747-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/1e695176d3f8/fmolb-12-1575747-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/08b350d9502d/fmolb-12-1575747-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/1e695176d3f8/fmolb-12-1575747-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/9ca61d67c654/fmolb-12-1575747-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/130adc893206/fmolb-12-1575747-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/2f3109cc7194/fmolb-12-1575747-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f0c/12119275/08b350d9502d/fmolb-12-1575747-g006.jpg

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