PAINS filtering
In silico check and filtering for potential Pan-assay interference compounds.
SEEK ID: https://fairdomhub.org/assays/1335
Modelling analysis
Projects: NMTrypI - New Medicines for Trypanosomatidic Infections
Investigation: Pteridines as anti-kinetoplastid folate-pathway protein inhibitors
Study: In silico property and correlation analysis
Assay position:
Biological problem addressed: Model Analysis Type
Organisms: No organisms
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Creators and Submitter
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Created: 22nd Aug 2020 at 09:12
Last updated: 30th Sep 2020 at 10:03
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Projects: Kinetics on the move - Workshop 2016, COVID-19 Disease Map, NMTrypI - New Medicines for Trypanosomatidic Infections, CoVIDD - Coronavirus interactions in drug discovery - optimization and implementation
Institutions: Kinetics on the move Workshop at HITS, Heidelberg Institute for Theoretical Studies (HITS gGmbH), University of Eastern Finland (UEF)
https://orcid.org/0000-0002-2801-8902
Group Leader, Molecular and Cellular Modeling Group, EML Research, Heidelberg
Projects: NMTrypI - New Medicines for Trypanosomatidic Infections
Web page: https://cordis.europa.eu/programme/id/FP7_HEALTH.2013.2.3.4-2
The New Medicines for Trypanosomatidic Infections - NMTrypI project aimed at obtaining new candidate drugs against Trypanosomatidic infections with appropriate efficiency from the lead phase to the final preclinical phase that are more accessible to patients.
Programme: Drug development for neglected parasitic diseases
Public web page: https://fp7-nmtrypi.eu/
Start date: 1st Feb 2014
End date: 31st Jan 2017
Multidisciplinary development of selective anti-parasitic multi-target inhibitors of PTR1/DHFR based on a pteridine scaffold.
Submitter: Ina Poehner
Studies: Docking to PTR1 and DHFR targets and off-targets, In silico property and correlation analysis
Assays: Compound library preparation, Correlation analysis between PTR1 and DHFR activities and anti-parasitic..., Correlation analysis between predicted ADMET properties and anti-parasit..., Docking receptor preparation, In silico ADMET data prediction, Induced-fit docking studies, PAINS filtering, Rigid-body docking studies
Computational prediction of physicochemical and advanced descriptors related to ADME-Tox and PAINS assessment. Potential correlations of the computed descriptors with experimentally determined anti-parasitic activities and correlations between experimentally determined levels of target protein inhibition (PTR1, DHFR) with the anti-parasitic activity were also studied.
Pteridines checked for Pan-assay interference compounds with the FAF-Drugs4 webserver (https://fafdrugs4.rpbs.univ-paris-diderot.fr/, last checked August 2020 and Lagorce et al. (2015) Nucleic Acids Res. 43, W200–207). Archive of PAINS filtering and ADME-Tox prediction results from FAF-Drugs4 run performed April 2019 with compound SMILES as input: applied_filters.txt: list of filters used; compound.sdf, accepted.sdf, intermediate.sdf, rejected.sdf, covalent_inhibitors.sdf and pains.sdf: compound ...
