CheS-Mapper 2.0 for visual validation of (Q)SAR models

Martin Gütlein, Andreas Karwath, Stefan Kramer

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
65 Downloads (Pure)


Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking.
We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints.
Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://​ches-mapper.​org.
Graphical abstract
Comparing actual and predicted activity values with CheS-Mapper.
Original languageEnglish
Article number41
Number of pages18
JournalJournal of Cheminformatics
Publication statusPublished - 23 Sept 2014


  • cheminformatics
  • visualization
  • validation
  • graph mining
  • data mining
  • (Q)SAR
  • 3D space


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