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计算和实验方法确定β受体阻滞剂为潜在的SARS-CoV-2刺突蛋白抑制剂。

Computational and Experimental Approaches Identify Beta-Blockers as Potential SARS-CoV-2 Spike Inhibitors.

作者信息

Puhl Ana C, Mottin Melina, Sacramento Carolina Q, Tavella Tatyana Almeida, Dias Gabriel Gonçalves, Fintelman-Rodrigues Natalia, Temerozo Jairo R, Dias Suelen S G, Ramos Paulo Ricardo Pimenta da Silva, Merten Eric M, Pearce Kenneth H, Costa Fabio Trindade Maranhão, Premkumar Lakshmanane, Souza Thiago Moreno L, Andrade Carolina Horta, Ekins Sean

机构信息

Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States.

LabMol - Laboratory of Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goiás, Goiânia 74605-170, GO, Brazil.

出版信息

ACS Omega. 2022 Aug 8;7(32):27950-27958. doi: 10.1021/acsomega.2c01707. eCollection 2022 Aug 16.

Abstract

Finding antivirals for SARS-CoV-2 is still a major challenge, and many computational and experimental approaches have been employed to find a solution to this problem. While the global vaccination campaigns are the primary driver of controlling the current pandemic, orally bioavailable small-molecule drugs and biologics are critical to overcome this global issue. Improved therapeutics and prophylactics are required to treat people with circulating and emerging new variants, addressing severe infection, and people with underlying or immunocompromised conditions. The SARS-CoV-2 envelope spike is a challenging target for viral entry inhibitors. Pindolol presented a good docking score in a previous virtual screening using computational docking calculations after screening a Food and Drug Administration (FDA)-approved drug library of 2400 molecules as potential candidates to block the SARS-CoV-2 spike protein interaction with the angiotensin-converting enzyme 2 (ACE-2). Here, we expanded the computational evaluation to identify five beta-blockers against SARS-CoV-2 using several techniques, such as microscale thermophoresis, NanoDSF, and assays in different cell lines. These data identified carvedilol with a of 364 ± 22 nM for the SARS-CoV-2 spike and activity (EC of 7.57 μM, CC of 18.07 μM) against SARS-CoV-2 in Calu-3 cells. We have shown how we can apply multiple computational and experimental approaches to find molecules that can be further optimized to improve anti-SARS-CoV-2 activity.

摘要

寻找针对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的抗病毒药物仍然是一项重大挑战,人们已经采用了许多计算和实验方法来解决这一问题。虽然全球疫苗接种运动是控制当前疫情的主要驱动力,但口服生物可利用的小分子药物和生物制剂对于解决这一全球问题至关重要。需要改进治疗方法和预防措施来治疗感染正在传播和新出现的变种病毒的人群、应对严重感染以及治疗有基础疾病或免疫功能低下的人群。SARS-CoV-2包膜刺突蛋白是病毒进入抑制剂的一个具有挑战性的靶点。在之前的虚拟筛选中,使用计算对接计算方法,在筛选了一个包含2400种分子的美国食品药品监督管理局(FDA)批准的药物库作为潜在候选药物,以阻断SARS-CoV-2刺突蛋白与血管紧张素转换酶2(ACE-2)的相互作用后,吲哚洛尔呈现出良好的对接分数。在此,我们扩展了计算评估,使用多种技术,如微量热泳动、纳米差示扫描荧光法以及在不同细胞系中的检测,来鉴定五种针对SARS-CoV-2的β受体阻滞剂。这些数据确定卡维地洛对SARS-CoV-2刺突蛋白的亲和力为364±22 nM,并且在Calu-3细胞中对SARS-CoV-2具有活性(半数有效浓度[EC]为7.57 μM,半数细胞毒性浓度[CC]为18.07 μM)。我们展示了如何应用多种计算和实验方法来寻找可以进一步优化以提高抗SARS-CoV-2活性的分子。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81ee/9386719/d4bef39e3cc1/ao2c01707_0002.jpg

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