Welcome to QSAR DataBank
QsarDB is a smart repository for (Q)SAR/QSPR models and datasets, ready for discovery, exploring, citing and predicting.
Transparent QSAR data
Create and upload QDB archive
The QsarDB repository requires your model and associated data to be organized. A small effort will make your research transparent and usable.
Explore chemicals
Search from 40000 structures in QDB archives
Exact chemical search, similarity and substructure searches find QDB archives containing the query compound.
Recent submissions
Show your study on this list
- 23 Jan 2020
- Gajewicz, A.; Schaeublin, N.; Rasulev, B.; Hussain, S.; Leszczynska, D.; Puzyn, T.; Leszczynski, J. Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: Hints from nano-QSAR studies. Nanotoxicology 2014, 9, 313–325.
- 10 Jan 2020
- Saliner, A. G.; Netzeva, T. I.; Worth, A. P. Prediction of estrogenicity: validation of a classification model. SAR QSAR Environ. Res. 2006, 17, 195–223.
- 06 Nov 2019
- Käärik, M.; Arulepp, M.; Käärik, M.; Maran, U.; Leis, J. Characterization and prediction of double-layer capacitance of nanoporous carbon materials using the Quantitative nano-Structure-Property Relationship approach based on experimentally determined porosity descriptors. Carbon 2019.
- 27 Sep 2019
- Prana, V.; Fayet, G.; Rotureau, P.; Adamo, C. Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds. J. Hazard. Mater. 2012, 235-236, 169–177.
Recent blog posts
On our mind
- 23 Jan 2020 | New communities from France and England
The last quarter of 2019 brought two new communities to the QsarDB, namely, Ineris (France) and Chemoinformatics Research Group from Liverpool John Moores University (England).
- 09 Dec 2019 | QSAR2020 is approaching fast
19th International Workshop on (Quantitative) Structure-Activity Relationships in Environmental and Health Sciences will be in Durham, NC, June 8-11, 2020.
- 18 Oct 2019 | QsarDB archive parser in Python
Lisa Bang has developed a simple QsarDB archive parser for the Python programming language. This parser can be useful to someone interested in reproducing the QSAR provided in the QsarDB archive format.
- 30 Sep 2019 | QsarDB website got redesign
This summer, QsarDB’s main website underwent a major upgrade. The visual side was redesigned to have a modern look, but it was only a small part of the effort. Most of the work went into improving the documentation and its results are available in the new section, GUIDELINES.