Ersilia Model Hub Identifier: eos8d8a
6.3K
Estimates the probability that a small molecule crosses the Mycobacterium tuberculosis cell envelope, a waxy barrier that blunts otherwise potent inhibitors. Merget and colleagues built the original MycPermCheck by treating 3815 compounds that inhibited mycobacterial growth by 90% at 10 uM and weighed under 500 Da as permeable, against randomly drawn drug-like ZINC molecules as negatives. What is served here is not that tool but an Ersilia replication, a LazyQSAR binary classifier trained with decoys from Ersilias own sampler. Permeability alone does not imply antitubercular activity.
This model was incorporated on 2021-10-14.Last packaged on 2026-10-28.
eos8d8amycpermcheckAnnotationActivity predictionTuberculosisMycobacterium tuberculosisPermeability, ADME, Antimicrobial activityCompound11FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| mycpermcheck | float | high | Probability of permeability in Mtb |
LocalReplicatedAMD64, ARM644218571993.07Computational Performance (seconds):
35.6731.6675.45Peer reviewed2013This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a MIT license.
Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.
To use this model locally, you need to have the Ersilia CLI installed. The model can be fetched using the following command:
# fetch model from the Ersilia Model Hub
ersilia fetch eos8d8a
Then, you can serve, run and close the model as follows:
# serve the model
ersilia serve eos8d8a
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close
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Content type
Image
Digest
sha256:d474cccc5…
Size
713.9 MB
Last updated
5 days ago
docker pull ersiliaos/eos8d8aPulls:
43
Oct 19 to Oct 25