Welcome to QSAR DataBase
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
- 22 Jun 2021
- Garcia-Sosa, A. T.; Maran, U. Combined Naïve Bayesian, chemical fingerprints, and molecular docking classifiers to model and predict androgen receptor binding activity data for environmentally- and health-sensitive substances. Int. J. Mol. Sci. 2021, 22, 6695.
- 25 Nov 2020
- Zukić, S.; Maran, U. Modelling of antiproliferative activity measured in HeLa cervical cancer cells in a series of xanthene derivatives. SAR QSAR Environ. Res. 2020, 31, 905-921.
- 26 Oct 2020
- Drgan, V.; Župerl, Š.; Vračko, M.; Como, F.; Novič, M. Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm. SAR QSAR Environ. Res. 2016, 27, 501–519.
- 16 Jul 2020
- Piir, G.; Sild, S.; Maran, U. Binary and multi-class classification for androgen receptor agonists, antagonists and binders. Chemosphere 2021, 262, 128313.
Recent blog posts
On our mind
- 26 Oct 2020 | New community from Slovenia (NIC)
The last quarter of 2020 brought a new community from Slovenia. Laboratory for Cheminformatics at National Institute of Chemistry (NIC). NIC has a long history for providing in silico tools for mechanistic and empirical modelling applicable for drug design, assessment of toxicity, and materials optimization.
- 17 Sep 2020 | QsarDB predictor service supports DRAGON descriptors
Each model in QsarDB can be used for prediction if the user calculates or determines experimentally the descriptors in the model and enters them in the “QDB Predictor” application [1] or via the REST service [2]. For some models, the prediction service also works directly from the structure. In this case, the QsarDB repository calculates the required molecular descriptors on the fly. Currently, QsarDB supports this functionality for a limited number of models, and they use open source software (Chemistry Development Kit, PaDEL-Descriptor and XlogP3) to calculate molecular descriptors.
- 03 Jun 2020 | New community from Italy (JRC)
In 2020, the QsarDB team celebrated Europe Day (May 9) in a modest but professional way. Namely, on that day, a new community was opened for the European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), which is a part of the European Commission's Joint Research Center (JRC) in Ispra, Italy.
- 03 Feb 2020 | Representing QSARs in era of Big Data
The topic of Big Data has strongly entered into predictive and computational toxicology, and is here in order to stay. However, not only the data is big, large are also computational models (the so-called QSAR models) derived from these data. Therefore, the management of computational models in the context of Big Data needs more attention and efforts, so that the models remain transparent and independently verifiable.