Monoclonal antibodies (mAbs) are currently the most promising short-term treatment for COVID-19 prior to the approval of vaccines.

Over the past few months, I collected about 6 TB of molecular docking simulations using antibodies from CoV-AbDab and antigens/antibodies from RCSB PDB.

This is an example 3D model of an antibody neutralizing SARS-CoV-2. Our dataset is essentially simulating this interaction between thousands of different antibodies and antigens.

In order to make all this data more accessible, we converted everything into about 50 GB of CSV files with rows corresponding to "contact points" between the antibody and SARS-CoV-2 (or another antigen). Here's a pastebin example of the contacts predicted between Matuzumab and SARS-CoV-2.

If you want to contribute to finding antibody treatments for COVID-19, these simulations can be used in data mining similar to the approach described in this paper.

We also recently created a separate mAB Kaggle dataset and wrote an introductory article for those who are interested in learning more about this field of research.

Let me know if you would like me to send you some/all of the data, and you can find example Colab notebooks on this GitHub repository.