Virtually screening antiviral compounds to model their interactions with the SARS-CoV-2 virus may enable scientists to more easily identify antiviral drugs that work against the virus while informing the search for viable vaccine candidates, according to a new study. By screening for interactions with certain structural domains and active sites on the virus, this structure-based approach may help scientists identify existing drugs that can be repurposed, including therapies developed to treat MERS-CoV, SARS-CoV, Ebola, and HIV. This approach may also assist with the development of new drugs and protein-based SARS-CoV-2 vaccines with fewer experiments and higher reliability than traditional methods. Information about SARS-CoV-2 reported from its recent genome sequencing has revealed key targets for drugs and vaccines, including the spike protein complex, which helps mediate viral entry into host cells, as well as the main protease, an enzyme that enables viral replication and transcription. To test how these elements of the virus' structure may be used to search virtually for prospective drugs, Pritam Kumar Panda and colleagues computationally screened 640 antiviral compounds from a database against the spike protein and main protease using AutoDock Vina, an open-source program for identifying the "best fit" orientation of a molecule that binds to a protein. The researchers then used two additional programs, UCSF Chimera and Discovery Studio Visualizer, to analyze these molecular orientations. The researchers found that an antiviral polymerase inhibitor PC786 targets several SARS-CoV-2 receptors with high affinity, making it a standout among the antiviral drugs they studied. Panda et al. also identified several additional antiviral drugs with strong binding affinities to the spike protein and main protease, revealing a number of drugs that may be candidates for further research in efforts to fight SARS-CoV-2.
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Journal
Science Advances