Today, we are going to talk about malaria. As you may know, this disease of the Plasmodium parasite family threatens nearly half of the world’s population and led to over 400,000 deaths in 2019, predominantly among children in resource-limited areas in Africa, Asia and Central and South America. New therapies are desperately needed, in particular to cope with increased resistance against artemisinin-based combination therapies.
To help address this challenge, we have been involved in a public-private consortium that aims to deliver a tool to predict potential blood-stage malaria inhibitors and today we have a great announcement, which is the public release of MAIP!
MAIP is an acronym for MAlaria Inhibitor Prediction. With MAIP we have achieved what we believe has never been done before: a publicly-available malaria inhibition model built on more than 6 million compounds! Yes, 6 million! We believe this is one of the largest antimalarial datasets ever gathered.
Our project partners used their internal screening libraries, but rather than directly sharing their confidential compound structures and activity data, they each trained a QSAR model on their individual training set and shared the models with us.
Our role at ChEMBL was to develop the code to create and evaluate the models, to implement a consensus approach to combine the models and to develop the MAIP website. We worked hard to integrate all these information together and the result is a service that allows you to submit compounds to the consensus-based model.
There are many more things to say about this project, in particular regarding the technical aspects, but this would make a very large post. Instead, we suggest you wait for our upcoming paper. Meanwhile, you can also watch the record of the recent MAIP introduction webinar.
Please do try MAIP and let us know what you think. You can leave your comments on this thread or contact us at chembl-help@ebi.ac.uk
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