Bosc2021 - MAIP: a web service for predicting blood‐stage malaria inhibitors

Prediction of the antimalarial potential of small molecules. This model is an ensemble of smaller QSAR models trained on proprietary data from various sources, up to a total of >7M compounds. The training sets belong to Evotec, Johns Hopkins, MRCT, MMV - St. Jude, AZ, GSK, and St. Jude Vendor Library. The code and training data are not released, using this model posts predictions to the MAIP online server. The Ersilia Model Hub also offers MAIP-surrogate as a downloadable package for IP-sensitive queries.

Model Type: Predictive machine learning model.
Model Relevance: Predicts antimalarial activity.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam

Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos4zfy