Molecular entities search and optimization with potential application in the treatment of SARS-CoV-2 infections
based on evolutionary information of relevant viral targets.
Through evolutionary and structural approaches, this project proposes to integrate different bioinformatics techniques to elucidate key proteins responsible for the coronavirus's general mechanisms of pathogenicity and search for possible molecules that reduce the infection or alleviate the symptoms caused by such a virus. Given the increasing number of data available in public databases, as a result of the current SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) pandemic, a search will be carried out for structures of viral proteins in these databases and through computational analysis of these structures, infer relevant proteins that act in general mechanisms of viral replication and infection. From this, viral proteins' key regions that allow low molecular weight molecule binding and interaction. With this, we intend to elucidate possible molecules that act by inhibiting pathogenicity mechanisms of viruses of the coronaviridae family. The project presents a general approach in which the expected results are applicable not only to apply to current SARS-CoV-2 pandemic but also to future virus infections promoted by other coronaviridae family viruses.