Comparative Analysis of Protein-Bound Ligand Conformations with Respect to Catalyst's Conformational Space Subsampling Algorithms. - Johannes Kirchmair; Christian Laggner; Gerhard Wolber; Thierry Langer (J. Chem. Inf. Model., 2005)

Comparative Performance Assessment of the Conformational Model Generators Omega and Catalyst: A Large-Scale Survey on the Retrieval of Protein-Bound Ligand Conformations. - Johannes Kirchmair; Gerhard Wolber; Christian Laggner; Thierry Langer (J. Chem. Inf. Model., 2006)

Pharmacophore modeling and parallel screening for PPAR ligands. - Patrick Markt; Daniela Schuster 001; Johannes Kirchmair; Christian Laggner; Thierry Langer (J. Comput. Aided Mol. Des., 2007)

Fast and Efficient in Silico 3D Screening: Toward Maximum Computational Efficiency of Pharmacophore-Based and Shape-Based Approaches. - Johannes Kirchmair; Stojanka Ristic; Kathrin Eder; Patrick Markt; Gerhard Wolber; Christian Laggner; Thierry Langer (J. Chem. Inf. Model., 2007)

CAESAR: A New Conformer Generation Algorithm Based on Recursive Buildup and Local Rotational Symmetry Consideration. - Jiabo Li; Tedman Ehlers; Jon M. Sutter; Shikha Varma-O'Brien; Johannes Kirchmair (J. Chem. Inf. Model., 2007)

Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection - What can we learn from earlier mistakes? - Johannes Kirchmair; Patrick Markt; Simona Distinto; Gerhard Wolber; Thierry Langer (J. Comput. Aided Mol. Des., 2008)

Discovery of Novel Cathepsin S Inhibitors by Pharmacophore-Based Virtual High-Throughput Screening. - Patrick Markt; Caroline McGoohan; Brian Walker; Johannes Kirchmair; Clemens Feldmann; Gabriella De Martino; Gudrun M. Spitzer; Simona Distinto; Daniela Schuster 001; Gerhard Wolber; Christian Laggner; Thierry Langer (J. Chem. Inf. Model., 2008)

How To Optimize Shape-Based Virtual Screening: Choosing the Right Query and Including Chemical Information. - Johannes Kirchmair; Simona Distinto; Patrick Markt; Daniela Schuster 001; Gudrun M. Spitzer; Klaus R. Liedl; Gerhard Wolber (J. Chem. Inf. Model., 2009)

Hydrogen-Bonding Patterns of Minor Groove-Binder-DNA Complexes Reveal Criteria for Discovery of New Scaffolds. - Gudrun M. Spitzer; Bernd Wellenzohn; Patrick Markt; Johannes Kirchmair; Thierry Langer; Klaus R. Liedl (J. Chem. Inf. Model., 2009)

Critical Comparison of Virtual Screening Methods against the MUV Data Set. - Pekka Tiikkainen; Patrick Markt; Gerhard Wolber; Johannes Kirchmair; Simona Distinto; Antti Poso; Olli-P. Kallioniemi (J. Chem. Inf. Model., 2009)

One Concept, Three Implementations of 3D Pharmacophore-Based Virtual Screening: Distinct Coverage of Chemical Search Space. - Gudrun M. Spitzer; Mathias Heiss; Martina Mangold; Patrick Markt; Johannes Kirchmair; Gerhard Wolber; Klaus R. Liedl (J. Chem. Inf. Model., 2010)

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms. - Johannes Kirchmair; Mark J. Williamson; Jonathan D. Tyzack; Lu Tan; Peter J. Bond; Andreas Bender 002; Robert C. Glen (J. Chem. Inf. Model., 2012)

Quantifying the shifts in physicochemical property space introduced by the metabolism of small organic molecules. - Johannes Kirchmair; Andrew Howlett; Julio E. Peironcely; Daniel S. Murrell; Mark J. Williamson; Samuel E. Adams; Thomas Hankemeier; Leo van Buren; Guus Duchateau; Werner Klaffke; Robert C. Glen (J. Cheminformatics, 2013)

How Do Metabolites Differ from Their Parent Molecules and How Are They Excreted? - Johannes Kirchmair; Andrew Howlett; Julio E. Peironcely; Daniel S. Murrell; Mark J. Williamson; Samuel E. Adams; Thomas Hankemeier; Leo van Buren; Guus Duchateau; Werner Klaffke; Robert C. Glen (J. Chem. Inf. Model., 2013)

FAst MEtabolizer (FAME): A Rapid and Accurate Predictor of Sites of Metabolism in Multiple Species by Endogenous Enzymes. - Johannes Kirchmair; Mark J. Williamson; Avid M. Afzal; Jonathan D. Tyzack; Alison P. K. Choy; Andrew Howlett; Patrik Rydberg; Robert C. Glen (J. Chem. Inf. Model., 2013)

Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers. - Jonathan D. Tyzack; Hamse Y. Mussa; Mark J. Williamson; Johannes Kirchmair; Robert C. Glen (J. Cheminformatics, 2014)

High-Quality Dataset of Protein-Bound Ligand Conformations and Its Application to Benchmarking Conformer Ensemble Generators. - Nils-Ole Friedrich; Agnes Meyder; Christina de Bruyn Kops; Kai Sommer; Florian Flachsenberg; Matthias Rarey; Johannes Kirchmair (J. Chem. Inf. Model., 2017)

Alignment-Based Prediction of Sites of Metabolism. - Christina de Bruyn Kops; Nils-Ole Friedrich; Johannes Kirchmair (J. Chem. Inf. Model., 2017)

FAME 2: Simple and Effective Machine Learning Model of Cytochrome P450 Regioselectivity. - Martin Sícho; Christina de Bruyn Kops; Conrad Stork; Daniel Svozil; Johannes Kirchmair (J. Chem. Inf. Model., 2017)

Data Resources for the Computer-Guided Discovery of Bioactive Natural Products. - Ya Chen 002; Christina de Bruyn Kops; Johannes Kirchmair (J. Chem. Inf. Model., 2017)

Benchmarking Commercial Conformer Ensemble Generators. - Nils-Ole Friedrich; Christina de Bruyn Kops; Florian Flachsenberg; Kai Sommer; Matthias Rarey; Johannes Kirchmair (J. Chem. Inf. Model., 2017)

Characterization of the Chemical Space of Known and Readily Obtainable Natural Products. - Ya Chen 002; Marina Garcia de Lomana; Nils-Ole Friedrich; Johannes Kirchmair (J. Chem. Inf. Model., 2018)

Conformator: A Novel Method for the Generation of Conformer Ensembles. - Nils-Ole Friedrich; Florian Flachsenberg; Agnes Meyder; Kai Sommer; Johannes Kirchmair; Matthias Rarey (J. Chem. Inf. Model., 2019)

FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes. - Martin Sícho; Conrad Stork; Angelica Mazzolari; Christina de Bruyn Kops; Alessandro Pedretti; Bernard Testa; Giulio Vistoli; Daniel Svozil; Johannes Kirchmair (J. Chem. Inf. Model., 2019)

Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters. - Conrad Stork; Ya Chen 002; Martin Sícho; Johannes Kirchmair (J. Chem. Inf. Model., 2019)

Validation strategies for target prediction methods. - Neann Mathai; Ya Chen 002; Johannes Kirchmair (Briefings Bioinform., 2020)

NERDD: a web portal providing access to in silico tools for drug discovery. - Conrad Stork; Gerd Embruch; Martin Sícho; Christina de Bruyn Kops; Ya Chen 002; Daniel Svozil; Johannes Kirchmair (Bioinform., 2020)

Scope of 3D Shape-Based Approaches in Predicting the Macromolecular Targets of Structurally Complex Small Molecules Including Natural Products and Macrocyclic Ligands. - Ya Chen 002; Neann Mathai; Johannes Kirchmair (J. Chem. Inf. Model., 2020)

Rationality over fashion and hype in drug design. - José L. Medina-Franco; Karina Martínez-Mayorga; Eli Fernández-de Gortari; Johannes Kirchmair; Jürgen Bajorath (F1000Research, 2021)

Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop. - Fidele Ntie-Kang; Kiran K. Telukunta; Serge A. T. Fobofou; Victor Chukwudi Osamor; Samuel A. Egieyeh; Marilia Valli; Yannick Djoumbou Feunang; Maria Sorokina; Conrad Stork; Neann Mathai; Paul F. Zierep; Ana L. Chávez-Hernández; et al. (J. Cheminformatics, 2021)

ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities. - Marina Garcia de Lomana; Andrea Morger; Ulf Norinder; Roland Buesen; Robert Landsiedel; Andrea Volkamer; Johannes Kirchmair; Miriam Mathea (J. Chem. Inf. Model., 2021)

DNN-PP: A novel Deep Neural Network approach and its applicability in drug-related property prediction. - Magdalena Wiercioch; Johannes Kirchmair (Expert Syst. Appl., 2023)

School of cheminformatics in Latin America. - Karla Gonzalez-Ponce; Carolina Horta Andrade; Fiona M. I. Hunter; Johannes Kirchmair; Karina Martínez-Mayorga; José L. Medina-Franco; Matthias Rarey; Alexander Tropsha; Alexandre Varnek; Barbara Zdrazil (J. Cheminformatics, 2023)

Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation. - Ya Chen 002; Thomas Seidel; Roxane Axel Jacob; Steffen Hirte; Angelica Mazzolari; Alessandro Pedretti; Giulio Vistoli; Thierry Langer; Filip Miljkovic; Johannes Kirchmair (J. Chem. Inf. Model., 2024)

Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning. - Hosein Fooladi; Steffen Hirte; Johannes Kirchmair (J. Chem. Inf. Model., 2024)

Deciphering Molecular Embeddings with Centered Kernel Alignment. - Matthias Welsch; Steffen Hirte; Johannes Kirchmair (J. Chem. Inf. Model., 2024)

Automated Annotation of Sites of Metabolism from Biotransformation Data. - Roxane Axel Jacob; Angelica Mazzolari; Johannes Kirchmair (J. Chem. Inf. Model., 2025)

Site-of-Metabolism Prediction with Aleatoric and Epistemic Uncertainty Quantification. - Roxane Axel Jacob; Oliver Wieder; Ya Chen 002; Angelica Mazzolari; Andreas Bergner; Klaus-Jürgen Schleifer; Johannes Kirchmair (J. Chem. Inf. Model., 2025)

Integrated Virtual Screening Approach Identifies New CYP19A1 Inhibitors. - Sijie Liu; Jie Wu; Ya Chen 002; Clemens Alexander Wolf; Matthias Bureik; Johannes Kirchmair; Mario Andrea Marchisio; Gerhard Wolber (J. Chem. Inf. Model., 2025)

Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening. - Thi Ngoc Lan Vu; Hosein Fooladi; Johannes Kirchmair (J. Chem. Inf. Model., 2025)

E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays. - Vincenzo Palmacci; Yasmine Nahal; Matthias Welsch; Ola Engkvist; Samuel Kaski; Johannes Kirchmair (J. Cheminformatics, 2025)