CoviPredX is a web-based application that predicts pIC50 values (a measure of bioactivity) for small molecules against coronavirus using an advanced XGBoost regression model. It helps researchers evaluate potential bioactivity for drug discovery efforts.
CoviPredX uses XGBoost, a powerful machine learning algorithm, to predict pIC50 values based on molecular fingerprints provided by the user. The model has been trained on extensive datasets to offer reliable predictions for bioactivity.
CoviPredX accepts molecular structures in Canonical SMILES format. The input data should be in a CSV file with the SMILES format for each compound, along with an optional unique identifier.
Molecular fingerprints are representations of molecules that encode structural information. CoviPredX uses these fingerprints as input features to predict the bioactivity (pIC50), making it possible to evaluate the potential effectiveness of compounds.
Go to the CoviPredX tool page, upload a CSV file containing Canonical SMILES and IDs, and click "Predict" to get the predicted pIC50 values for the molecules in your file.
Yes! CoviPredX is available as a web-based tool, and it also supports deployment on Linux and Windows platforms.
CoviPredX uses XGBoost, one of the most accurate machine learning models available. The tool has been tested extensively, and its predictions are highly reliable based on the molecular features provided.
No. CoviPredX is designed with a user-friendly interface. As long as you can provide the required molecular structure data (SMILES format), the tool will do the rest for you.
Yes, CoviPredX can handle large datasets, although processing times will vary depending on the size of the input file.
If you face any issues or have questions, feel free to contact our support team via the "Contact Us" section on the website or email us at rajeshdsr@bicpu.edu.in.