Smith College

Virus-CKB or the viral-associated disease-specific chemogenomics knowledgebase is a platform created to quickly predict existing FDA-approved drugs which can be repurposed and progress to clinical trials to be used to treat COVID-19. New and effective anti-COVID-19 drugs are in urgent need, but discovering new drugs can take up to 8 years, can cost up to $2 billion and have low approval ratings, hence why re-purposing drugs could be useful. Essentially, the database was created to make viral infection research easier.


The Virus-CKB Platform

Zhiwei Feng, Maozi Chen, Tianjian Liang, Mingzhe Shen, Hui Chen, Xiang-Qun Xie, Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research, Briefings in Bioinformatics, , bbaa155, https://doi.org/10.1093/bib/bbaa155

Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research

Link to the Virus-CKB Platform

- HTDocking
-  TargetHunter
- Blood Brain Barrier Predictor
- Spider Plot
- Other third party software

Virus-CKB Established Tools and Algorithms (Outputs)

First, the user enters up to five compounds to the Virus-CKB platform. A task is assigned for each compound and the input format of the compounds are converted to PDB (Protein Data Bank) and PDBQT (similar to PDB) formats. 
  
Next, the Blood-Brain Barrier predictor, HTDocking and the TargetHunter are applied to the compounds simultaneously. The BBB predictor predicts the ability of compounds to penetrate the BBB. Docking scores are generated by putting the compounds into previously defined binding pockets in “different conformations of a target protein.” The TargetHunter calculates the similarity score of molecules against the known active compound dataset. 


Then, using docking scores and the similarity score, a target classification is performed and these results are passed through Spider Plot for visualization.


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