Find a candidate drug (ligand) with a high binding affinity with the 2019-COVID main protease. A few studies have shown that HIV antivirals offer promising results, but this is still an open field of discovery. Use machine learning to identify a potential candidate, then use docking software to get the binding affinity between it and the main protease. Write a report that describes your process and results in detail in the form of a jupyter notebook. Finding a new drug or validating an existing drug are both suitable approaches, we will be donating samples of the winning compound to the Wuhan Institute of Virology for further analysis.
Report your results in a Jupyter notebook. Ensure clear process details and documentation.
1st place: $1000 cash + $500 JetML cloud Credits + Youtube video collaboration with Siraj Raval
2nd place: $1000 JetML cloud credits
3rd place: $1000 JetML cloud credits
Feb 17 2020
March 2 2020
The competition is judged based on reproducibility, documentation quality, and the antiviral feasibility of your candidate molecule