A biocomputational multireporter platform for the identification of coronavirus protease inhibitors
There remains an urgent need for the development of specfic antiviral therapeutics and vaccines against SARS-CoV-2. One of the best characterized drug targets among coronaviruses is the main protease (Mpro, 3CLpro), which is thought to be essential for viral replication and, therefore, is regarded as promising target for antiviral pharmacotherapy. Therefore, we propose the establishment of a multi-reporter platform for the cell-based validation of drug inhibitors against the SARS-Cov-2 protease Mpro. The core of this platform will be a fluorescence-activatable reporter of protease activity to enable the quantitative live imaging of protease inhibition by candidate drugs, based on our previous work on flaviviruses. To establish this, we will first model the molecular interactions of putative candidate reporter molecules designed as a broad-spectrum coronavirus reporters for the study of current and future coronaviruses. The molecular construct will be inserted into a lentiviral vector to establish a stable human cell line together with a sequence for the full Mpro protease, implying that the viable virus is not required and no BSL3 lab will be needed. In this setup, the co-expressed protease will continuously cleave the reporter providing the 100% fluorescent cellular signal and a decay in cell fluorescence would correlate with the activity of a protease inhibitor. In addition, we will also include reporters for chromatin condensation, mitochondrial morphology and cell death to create a very sensitive multi-reporter system to sense off-target effects of the inhibitors and their potential cytotoxicity. To demonstrate the usefulness of these approach, we will perform molecular docking of several compound libraries supported by high-performance computing to identify several potential candidate inhibitors that will be tested on our multi-reporter platform. The transdisciplinary nature of this project is essential for the successful completion of our objectives.
The project is registered internationally at the World Pandemic Research Network (WPRN), with the aim of being part of a platform for research communities. It is a network maintained by researchers, showing who is doing what and where. The link to the project is https://wprn.org/item/486252
Protein Sensor
Drug Computational Simulation
Experimental validation
The principle of inhibiting the action of the virus is simple: prevent the protease from dividing the polyproteins into parts, because if it does so, it would be able to start the virus replication process. In this way, the work carried out by doctors Rodrigo Mora and Francisco Siles is to identify which inhibitors exist and it would be useful to test, for which they access the so-called compound libraries, which have chemical substances. Faced with the economic impossibility of buying and bringing them all to test them, a biocomputational platform orders them and in turn recommends those that «fit» (compound with protease) and therefore would work to experiment. All of the above summarizes one of the first stages of the work, but there are more phases and in turn greater complexity. This is one more project of the University of Costa Rica to face the pandemic.
