Tetko lab

Chemoinformatics & Chemical Biology group develops computational tools for drug discovery, including Virtual Computational Chemistry Laboratory (VCCLAB) http://www.vcclab.org and On-line CHEmical Modeling Environment (OCHEM) https://ochem.eu in close collaboration with its spin-off company BIGCHEM GmbH (https://bigchem.de).

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About us

Our expertise covers:

• Development of QSPR models to predict physico-chemical and biological activity of molecules

• Use of different structure representations (topological, inductive, quantum-chemical, shape signatures, pH-dependent descriptors, etc.) as well as representation learning to achieve the most accurate predictions

• Use of a large set of linear and non-linear machine learning methods to address data of different complexity and nature

• Interpretation of structure-activity relationships

• Estimation of the accuracy of predictions

• Experimental design to identify a representative set of molecules

• Analysis and interpretation of large datasets of molecules

• Chemoinformatics software development

• Prediction of chemical reactions

Dr. Igor Tetko

Research Group Leader View profile

Varvara Voinarovska

Paula Torren-Peraire

PhD student

Peter Hartog

PhD student

Nesma Mousa

Master student

Mark Embrechts

Fabian Krüger

• Development of QSPR models to predict physico-chemical and biological activity of molecules

• Use of different structure representations (topological, inductive, quantum-chemical, shape signatures, pH-dependent descriptors, etc.) as well as representation learning to achieve the most accurate predictions

• Use of a large set of linear and non-linear machine learning methods to address data of different complexity and nature

• Interpretation of structure-activity relationships

• Estimation of the accuracy of predictions

• Experimental design to identify a representative set of molecules

• Analysis and interpretation of large datasets of molecules

• Chemoinformatics software development

• Prediction of chemical reactions

Publications

Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes.

2025 Scientific Article in Journal of Cheminformatics

Krüger, F. ; Östman, J. ; Mervin, L. ; Tetko, I.V. ; Engkvist, O.

Publishing neural networks in drug discovery might compromise training data privacy.

2025 Scientific Article in Journal of Cheminformatics

Torren Peraire, P. ; Verhoeven, J.E. ; Herman, D.S. ; Ceulemans, H. ; Tetko, I.V. ; Wegner, J.K.

Improving route development using convergent retrosynthesis planning.

2025 Scientific Article in Journal of Chemical Information and Modeling

Hartog, P. ; Westerlund, A.M. ; Tetko, I.V. ; Genheden, S.

Investigations into the efficiency of computer-aided synthesis planning.

2025 Scientific Article in Chemical Science

Van Herck, J. ; Gil, M.V. ; Jablonka, K.M. ; Abrudan, A. ; Anker, A.S. ; Asgari, M. ; Blaiszik, B. ; Buffo, A. ; Choudhury, L. ; Corminboeuf, C. ; Daglar, H. ; Elahi, A.M. ; Foster, I.T. ; García, S.A. ; Garvin, M. ; Godin, G. ; Good, L.L. ; Gu, J. ; Xiao Hu, N. ; Jin, X. ; Junkers, T. ; Keskin, S. ; Knowles, T.P.J. ; Laplaza, R. ; Lessona, M. ; Majumdar, S.K. ; Mashhadimoslem, H. ; McIntosh, R.D. ; Moosavi, S.M. ; Mouriño, B. ; Nerli, F. ; Pevida, C. ; Poudineh, N. ; Rajabi-Kochi, M. ; Saar, K.L. ; Hooriabad Saboor, F. ; Sagharichiha, M. ; Schmidt, K.J. ; Shi, J. ; Simone, E. ; Svatunek, D. ; Taddei, M. ; Tetko, I.V. ; Tolnai, D. ; Vahdatifar, S. ; Whitmer, J. ; Wieland, D.C.F. ; Willumeit-Römer, R. ; Züttel, A. ; Smit, B.

Tetko Lab

About us