PLASMOpred

The AMA-1/RON2 interaction facilitates the tight junction formation, which is essential for the invasion of red blood cells by the Plasmodium parasite, a critical step in malaria infection.

PLASMOpred is a web-based application for predicting putative compounds against the AMA-1 RON2 invasion complex.

The maximum number of compounds you can predict using batch prediction is 1000 compounds.

PLASMOpred uses advanced machine learning models, trained on extensive datasets, to provide reliable and accurate predictions for malaria-related research.

AD for a machine learning model defines an area of chemical space within the training data for which the developed model gives steady and reliable predictions.

Confidence score ranges from 0 to 100%. Scores closer to 100% means high confidence whilst scores closer to 0 are low. A predicted active compound requires experimental validation as confirmation.

Yes, the results can be downloaded as a CSV file.