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Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

ABSTRACT: Computational approaches for drug discovery, such as quantitative structure-activity relationship, rely on structural similarities of small molecules to infer biological activity but are often limited to identifying new drug candidates in the chemical spaces close to known ligands. Here we report a biological activity-based modeling (BABM) approach, in which compound activity profiles established across multiple assays are used as signatures to predict compound activity in other assays or against a new target. This approach was validated by identifying candidate antivirals for Zika and Ebola viruses based on high-throughput screening data. BABM models were then applied to predict 311 compounds with potential activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of the predicted compounds, 32% had antiviral activity in a cell culture live virus assay, the most potent compounds showing a half-maximal inhibitory concentration in the nanomolar range. Most of the confirmed anti-SARS-CoV-2 compounds were found to be viral entry inhibitors and/or autophagy modulators. The confirmed compounds have the potential to be further developed into anti-SARS-CoV-2 therapies.

SUBMITTER: Huang R

PROVIDER: S-EPMC9843700 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

Huang Ruili R Xu Miao M Zhu Hu H Chen Catherine Z CZ Zhu Wei W Lee Emily M EM He Shihua S Zhang Li L Zhao Jinghua J Shamim Khalida K Bougie Danielle D Huang Wenwei W Xia Menghang M Hall Mathew D MD Lo Donald D Simeonov Anton A Austin Christopher P CP Qiu Xiangguo X Tang Hengli H Zheng Wei W

Nature biotechnology 20210223 6

Computational approaches for drug discovery, such as quantitative structure-activity relationship, rely on structural similarities of small molecules to infer biological activity but are often limited to identifying new drug candidates in the chemical spaces close to known ligands. Here we report a biological activity-based modeling (BABM) approach, in which compound activity profiles established across multiple assays are used as signatures to predict compound activity in other assays or agains ...[more]

PMID: 33623157

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Project description:The highly contagious SARS-CoV-2 virus is primarily transmitted through respiratory droplets, aerosols, and contaminated surfaces. In addition to antiviral drugs, the decontamination of surfaces and personal protective equipment (PPE) is crucial to mitigate the spread of infection. Conventional approaches, including ultraviolet radiation, vaporized hydrogen peroxide, heat and liquid chemicals, can damage materials or lack comprehensive, effective disinfection. Consequently, alternative material-compatible and sustainable methods, such as nanomaterial coatings, are needed. Therefore, the antiviral activity of two novel zinc-oxide nanoparticles (ZnO-NP) against SARS-CoV-2 was investigated in vitro. Each nanoparticle was produced by applying highly efficient "green" synthesis techniques, which are free of fossil derivatives and use nitrate, chlorate and sulfonate salts as starting materials and whey as chelating agents. The two "green" nanomaterials differ in size distribution, with ZnO-NP-45 consisting of particles ranging from 30 nm to 60 nm and ZnO-NP-76 from 60 nm to 92 nm. Human lung epithelial cells (Calu-3) were infected with SARS-CoV-2, pre-treated in suspensions with increasing ZnO-NP concentrations up to 20 mg/mL. Both "green" materials were compared to commercially available ZnO-NP as a reference. While all three materials were active against both virus variants at concentrations of 10-20 mg/mL, ZnO-NP-45 was found to be more active than ZnO-NP-76 and the reference material, resulting in the inactivation of the Delta and Omicron SARS-CoV-2 variants by a factor of more than 106. This effect could be due to its greater total reactive surface, as evidenced by transmission electron microscopy and dynamic light scattering. Higher variations in virus inactivation were found for the latter two nanomaterials, ZnO-NP-76 and ZnO-NP-ref, which putatively may be due to secondary infections upon incomplete inactivation inside infected cells caused by insufficient NP loading of the virions. Taken together, inactivation with 20 mg/mL ZnO-NP-45 seems to have the greatest effect on both SARS-CoV-2 variants tested. Prospective ZnO-NP applications include an antiviral coating of filters or PPE to enhance user protection.

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Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

Publications

Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

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