AMR chemical collections
This page outlines our goal to create the reference database of purchasable compound collections with potential interest to the field of AMR
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This page outlines our goal to create the reference database of purchasable compound collections with potential interest to the field of AMR
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We have plans to develop the Ersilia AMR Chemical Collections (E-AMR-CC) web app, initially focused on Klebsiella pneumoniae. E-AMR-CC will consist of a catalog of bespoke chemical libraries with predicted anti-Klebsiella activity. The resource will be extensible to other species in the future.
Below is a table of the current code repositories available at Ersilia that will be key to develop the E-AMR-CC resource.
Main CLI tool from Ersilia, offering easy-to-use functionality to fetch and serve AI/ML models for drug discovery.
The Ersilia Model Hub contains general-purpose models for drug discovery, which will be used to annotate the compound libraries.
End-to-end modeling based on ensembles of descriptors and autoML tools.
For the supervised AI/ML models (phenotypic), this will be the main pipeline to build and distill models.
Generic data collection tool from ChEMBL, with a focus on AI/ML-readiness.
This tool will be used to fine-tune TabPFN models, used especially in the modellability assessment.
Workflow to collect antimicrobial data from ChEMBL, including data preparation with LLMs, and modellability assesment.
The workflow has been tested on A. baumannii. It will now be used on Klebsiella pneumoniae.
Screening of the Enamine REAL 1B Lead-like library against 30 A. baumannii models.
This is an example repository demonstrating that billion-scale screening is feasible for anti-Klebsiella activity prediction models.
GC-ADDA4TB project aimed at discovering pan-engaging warheads against essential tRNA synthetases.
Structure-based approach containing robust detection of binding pockets in ensembles of structures. A similar strategy will be applied to Klebsiella targets.