A Computational study to guide the development of new SARS-CoV-2 detection hyper-spectral platforms

A Computational study to guide the development of new SARS-CoV-2 detection hyper-spectral platforms is led by Dr Juan Torras from the Polytechnic University of Catalonia, Spain. This project focusses on the earliest and fastest detection of the coronavirus causing COVID-19 in patients as well as the understanding of its infection mechanisms. The team is convinced that the knowledge developed in this project will help to obtain novel and better SARS-CoV-2 therapeutics and diagnostics based on antibodies. At the moment PCR tests allow the detection of viral RNA and are the most widely used to diagnose COVID-19. However, according to the group, this type of tests fail in different situations. Simultaneously, antibody tests have a great advantage and they could complement PCR tests. The team proposes to study silica and gold substrates with different antibodies with classical molecular dynamics. The group will use a nanoparticle (NP) detector for comparative study among different antibodies, their orientation, and their interaction with silica and gold surfaces. In parallel, the group is working on interactions between antibodies virus spike of the HIV-1 to create novel immunosensor devices. The team is ready to use this experience, all tools, and algorithms in the new COVID-19 project to study the antibody interactions with SARS-CoV-2 spike glycoprotein. Of course, they will use molecular dynamics, quantum mechanics, and molecular mechanics. According to the scientists, combining the new knowledge and results will help to obtain novel and better SARS-CoV-2 therapeutics and diagnostics based on antibodies. PRACE awarded the project with 40 000 000 core hours on Joliot-Curie KNL, hosted by GENCI at CEA, France.