Smith College

Virus-CKB (viral-associated disease-specific chemogenomics knowledgebase) is a bioinformatics platform developed to accelerate COVID-19 drug repurposing by predicting existing FDA-approved drugs that can undergo clinical trials. Traditional drug discovery can take up to 8 years, cost up to \$2 billion, and suffer from low approval rates. Virus-CKB streamlines this process by facilitating viral infection research and identifying candidate therapeutics efficiently.

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

- 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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