Skip to main content

Malaria inhibitor prediction platform

By


What a time! For most of us, this is the first time that we have experienced a pandemic and its impact on our daily life. Although working from home has become our routine in the ChEMBL group, we are still working as hard as ever! Of course, COVID-19 data is taking up some of our attention,  (see ChEMBL_27) but we are also continuing our work relevant to other diseases that affect large populations around the world.

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

Comments

Post a Comment

Popular posts from this blog

Here's a nice Christmas gift - ChEMBL 35 is out!

By
Use your well-deserved Christmas holidays to spend time with your loved ones and explore the new release of ChEMBL 35!            This fresh release comes with a wealth of new data sets and some new data sources as well. Examples include a total of 14 datasets deposited by by the ASAP ( AI-driven Structure-enabled Antiviral Platform) project, a new NTD data se t by Aberystwyth University on anti-schistosome activity, nine new chemical probe data sets, and seven new data sets for the Chemogenomic library of the EUbOPEN project. We also inlcuded a few new fields that do impr ove the provenance and FAIRness of the data we host in ChEMBL:  1) A CONTACT field has been added to the DOCs table which should contain a contact profile of someone willing to be contacted about details of the dataset (ideally an ORCID ID; up to 3 contacts can be provided). 2) In an effort to provide more detailed information about the source of a deposited dat...
Post a Comment
Read more

Improvements in SureChEMBL's chemistry search and adoption of RDKit

By Eloy
    Dear SureChEMBL users, If you frequently rely on our "chemistry search" feature, today brings great news! We’ve recently implemented a major update that makes your search experience faster than ever. What's New? Last week, we upgraded our structure search engine by aligning it with the core code base used in ChEMBL . This update allows SureChEMBL to leverage our FPSim2 Python package , returning results in approximately one second. The similarity search relies on 256-bit RDKit -calculated ECFP4 fingerprints, and a single instance requires approximately 1 GB of RAM to run. SureChEMBL’s FPSim2 file is not currently available for download, but we are considering generating it periodicaly and have created it once for you to try in Google Colab ! For substructure searches, we now also use an RDKit -based solution via SubstructLibrary , which returns results several times faster than our previous implementation. Additionally, structure search results are now sorted by...
Post a Comment
Read more

ChEMBL 34 is out!

By
We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains:         2,431,025 compounds (of which 2,409,270 have mol files)         3,106,257 compound records (non-unique compounds)         20,772,701 activities         1,644,390 assays         15,598 targets         89,892 documents Data can be downloaded from the ChEMBL FTP site:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding ...
Post a Comment
Read more

Improved querying for SureChEMBL

By
    Dear SureChEMBL users, Earlier this year we ran a survey to identify what you, the users, would like to see next in SureChEMBL. Thank you for offering your feedback! This gave us the opportunity to have some interesting discussions both internally and externally. While we can't publicly reveal precisely our plans for the coming months (everything will be delivered at the right time), we can at least say that improving the compound structure extraction quality is a priority. Unfortunately, the change won't happen overnight as reprocessing 167 millions patents takes a while. However, the good news is that the new generation of optical chemical structure recognition shows good performance, even for patent images! We hope we can share our results with you soon. So in the meantime, what are we doing? You may have noticed a few changes on the SureChEMBL main page. No more "Beta" flag since we consider the system to be stable enough (it does not mean that you will never ...
Post a Comment
Read more

ChEMBL brings drug bioactivity data to the Protein Data Bank in Europe

By
In the quest to develop new drugs, understanding the 3D structure of molecules is crucial. Resources like the Protein Data Bank in Europe (PDBe) and the Cambridge Structural Database (CSD) provide these 3D blueprints for many biological molecules. However, researchers also need to know how these molecules interact with their biological target – their bioactivity. ChEMBL is a treasure trove of bioactivity data for countless drug-like molecules. It tells us how strongly a molecule binds to a target, how it affects a biological process, and even how it might be metabolized. But here's the catch: while ChEMBL provides extensive information on a molecule's activity and cross references to other data sources, it doesn't always tell us if a 3D structure is available for a specific drug-target complex. This can be a roadblock for researchers who need that structural information to design effective drugs. Therefore, connecting ChEMBL data with resources like PDBe and CSD is essen...
Post a Comment
Read more