The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge
SLAS DISCOVERY, vol. 29, pp. 100144
Abstract
The EUOS/SLAS challenge aimed to facilitate the development of reliable algorithms to predict the aqueous solubility of small molecules using experimental data from 100 K compounds. In total, hundred teams took part in the challenge to predict low, medium and highly soluble compounds as measured by the nephelometry assay. This article describes the winning model, which was developed using the publicly available Online CHEmical database and Modeling environment (OCHEM) available on the website https://ochem.eu/article/27. We describe in detail the assumptions and steps used to select methods, descriptors and strategy which contributed to the winning solution. In particular we show that consensus based on 28 models calculated using descriptor-based and representation learning methods allowed us to obtain the best score, which was higher than those based on individual approaches or consensus models developed using each individual approach. A combination of diverse models allowed us to decrease both bias and variance of individual models and to calculate the highest score. The model based on Transformer CNN contributed the best individual score thus highlighting the power of Natural Language Processing (NLP) methods. The inclusion of information about aleatoric uncertainty would be important to better understand and use the challenge data by the contestants.
Authors 5
-
Affiliation as printed
Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Munich-Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), DE-85764 Neuherberg, Germany
-
Affiliation as printed
Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Munich-Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), DE-85764 Neuherberg, Germany
-
Leiden University · National Infrastructure for Chemical Biology · University of Chemistry and Technology, Prague
Affiliation as printed
Leiden Academic Centre for Drug Research, Leiden University, 55 Einsteinweg, 2333 CC Leiden, the Netherlands; CZ-OPENSCREEN: National Infrastructure for Chemical Biology, Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology Prague, Technická 5, 166 28, Prague, Czech Republic
CZ-OPENSCREEN: National Infrastructure for Chemical Biology, Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology Prague, Technická 5, 166 28, Prague, Czech Republic
Leiden Academic Centre for Drug Research, Leiden University, 55 Einsteinweg, 2333 CC Leiden, The Netherlands
-
DSM-Firmenich AG (Switzerland)
Affiliation as printed
dsm-firmenich SA, Rue de la Bergère 7, CH-1242 Satigny, Switzerland
-
Igor V. Tetko corresponding
Affiliation as printed
Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Munich-Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), DE-85764 Neuherberg, Germany; BIGCHEM GmbH, Valerystr. 49, DE-85716 Unterschleißheim, Germany. Electronic address: igor.tetko@helmholtz-munich.de
BIGCHEM GmbH, Valerystr. 49, DE-85716 Unterschleißheim, Germany
Institute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Munich-Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), DE-85764 Neuherberg, Germany
Cited by 20 stored of 21
20 results
No patents citing this paper on Lens.org (checked 2026-10-11).