QsarDB: QSAR and QSPR model repository

• Käärik, M.; Arulepp, M.; Maran, U.; Leis, J. Machine learning-assisted QnSPR study of structurally diverse nanoporous carbon materials and their capacitive behavior in dilute ionic liquid electrolyte. J. Mater. Sci. 2026, Published. 

  Published: Uko Maran, Maike Käärik, Mati Arulepp, Jaan Leis (2026-07-07)

  Abstract: The growing global demand for efficient energy storage has highlighted the need to discover and establish relationships and rules that link the electric double-layer (EDL) capacitance to the structural properties of the materials used in electrodes. Among these materials, nanoporous carbon stands out for its high microporosity and precisely adjustable pore ...

  Regression
• Piir, G.; Sild, S.; Spilioti, E.; Nikolopoulou, D.; Katsanou, E.; Langezaal, I.; Maran, U. Classification of Thyroid Peroxidase (TPO) Inhibitors Using Transfer Learning with SMILES Embeddings. Chemical Research in Toxicology 2026. 

  Published: Geven Piir, Sulev Sild, Eliana Spilioti, Dimitra Nikolopoulou, Effrosyni Katsanou, Ingrid Langezaal, Uko Maran (2026-05-27)

  Abstract: Thyroid hormones (THs) regulate many processes in mammals and, therefore, affect every organ in the body. Thyroid peroxidase (TPO) is an essential enzyme for the successful biosynthesis of THs. Although TPO inhibition is a well-documented molecular initiating event (MIE) in thyroid hormone system disruption adverse outcome pathways (AOPs), experimental methods ...

  HumanHealth Classification PredictFromStructure
• Beljkas, M.; Zukic, S.; Mirjacic Martinovic, K.; Djuric, A.; Vuletic, A.; Corinne, J.; Hölzel, J.; Böttger, E.; Gajić, M.; Santibanez F, J.; Stark, H.; Živković, A.; Srdic-Rajic, T.; Arimondo, P.; Maran, U.; Nikolic, K.; Petkovic, M.; Oljacic, S. Molecular Docking, Machine Learning-Guided Design, Synthesis, and Biological Evaluation of Novel Multitarget HDAC/ROCK Inhibitors. ChemRxiv 2025. 

  Published: Selma Zukic, Milan Beljkas (2025-05-13)

  Abstract: Histone deacetylases (HDACs) and Rho-associated coiled-coil containing protein kinases (ROCKs) are critical regulators of tumor development, progression and immunomodulation, particularly in aggressive cancers such as pancreatic ductal adenocarcinoma (PDAC) and triple negative breast cancer (TNBC). Previous in silico and in vitro studies have demonstrated the ...

  Regression
• Akinola, L. K.; Uzairu, A.; Shallangwa, G. A.; Abechi, S. E. Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists. SAR and QSAR in Environmental Research 2023, 34, 267–284. 

  Published: Geven Piir (2025-05-07)

  Abstract: Some adverse effects of hydroxylated polychlorinated biphenyls (OH-PCBs) in humans are presumed to be initiated via thyroid hormone receptor (TR) binding. Due to the trial-and-error approach adopted for OH-PCB selection in previous studies, experiments designed to test the TR binding hypothesis mostly utilized inactive OH-PCBs, leading to considerable waste ...

  HumanHealth Regression
• Toots, K. M.; Sild, S.; Leis, J.; Acree, W. E.; Maran, U. A multicomponent QSPR approach to describe and predict gas-ionic liquid distribution of organic solutes using machine learning. J. Mol. Liq. 2025, 436, 128184. 

  Published: Karl Marti Toots, Sild, Sulev, Leis, Jaan, Acree, William E., Maran, Uko (2025-03-17)

  Abstract: Ionic liquids are known as green solvents, which makes accurate prediction of gas–ionic liquid partition coefficients (log K) important from the perspective of various industrial applications. A gas–ionic liquid is a multicomponent system, but is usually modelled by the structural properties of one component, the solute. The integration of structural descriptors ...

  Regression
• Käärik, M.; Krjukova, N.; Maran, U.; Oja, M.; Piir, G.; Leis, J. Nanomaterial texture-based machine learning of ciprofloxacin adsorption on nanoporous carbon. Int. J. Mol. Sci. 2024, 25, 11696. 

  Published: Maike Käärik, Nadežda Krjukova, Uko Maran, Mara Oja, Geven Piir, Jaan Leis (2024-10-25)

  Abstract: Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experimental conditions and on the development of the mathematical model that would allow describing the molecular ...

  Regression
• Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924. 

  Published: Georgios Chrysochoou, Sulev Sild (2024-10-21)

  Abstract: Recent years have seen a substantial growth in the adoption of machine learning approaches for the purposes of quantitative structure-activity relationship (QSAR) development. Such a trend has coincided with desire to see a shifting in the focus of methodology employed within chemical safety assessment: away from traditional reliance upon animalintensive in ...

  Regression
• Kotli, M.; Piir, G.; Maran, U. Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data. ACS Omega 2025, 10, 4732–4744. 

  Published: Mihkel Kotli, Geven Piir, Uko Maran (2024-10-09)

  Abstract: The earthworm is a key indicator species in soil ecosystems. This makes the reproductive toxicity of chemical compounds to earthworms a desired property of determination and makes computational models necessary for descriptive and predictive purposes. Thus, the aim was to develop an advanced Quantitative Structure–Activity Relationship modeling approach for ...

  EcoTox Classification PredictFromStructure

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