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Univ.-Prof. Mag. Dr. Johannes Kirchmair
Johannes Kirchmair
T: +43-1-4277-55104
https://comp3d.univie.ac.at
Winter term 2025
262005 VO Introduction to Computational Biology and Drug Discovery
262006 UE Introduction to Computational Biology and Drug Discovery - Exercises
301817 VO MPM 7 - Lecture course: Model systems in precision medicine - in the context of signature diseases
321004 VO Physik und Informatik für PharmazeutInnen - B3
321028 VO Pharmazeutische Chemie 1 - B15
322001 VO (Bio)pharma. mit Wirkung auf metabol. Störungen & eingeschr. Organ- und Systemfunktionen - M1
322002 VO Antiinfektiva, Antineoplastika und (Bio)pharmazeutika mit Wirkung auf das Immunsystem - M2
322026 VU Ausgewählte Kapitel aus der pharmazeutisch-chemischen Forschung - M13
323005 VO Preclinical Drug Development - MPS4
323009 PR Lab Rotation I - MPS8
323010 PR Lab Rotation II - MPS8
323011 SE Proposal Writing - MPS9 - (2 Courses)
580008 SE SE Journal Club : Molecular Informatics
580009 SE SE Lecture Series Pharma and Food
Summer term 2025
301817 UE MPM 6 - Practical Course: Pharmacoinformatics and structure-based drug design
321029 VO Pharmazeutische Chemie 2 - B15
322026 VU Ausgewählte Kapitel aus der pharmazeutisch-chemischen Forschung - M13
323007 UE Experimental Methods in Drug Discovery und Preclinical Drug Development - MPS6 - (2 Courses)
323101 VU Pharmacoinformatics - MPS5
323102 VU Pharmacoinformatics Practical Course - MPS5
580006 SE Pharma Lectures
580009 SE Journal Club : Molecular Informatics
Winter term 2024
262005 VO Introduction to Computational Biology and Drug Discovery
262006 UE Introduction to Computational Biology and Drug Discovery - Exercises
301817 VO MPM 7 - Lecture course: Model systems in precision medicine - in the context of signature diseases
321028 VO Pharmazeutische Chemie 1 - B15
322001 VO (Bio)pharma. mit Wirkung auf metabol. Störungen & eingeschr. Organ- und Systemfunktionen - M1
322002 VO Antiinfektiva, Antineoplastika und (Bio)pharmazeutika mit Wirkung auf das Immunsystem - M2
322026 VU Ausgewählte Kapitel aus der pharmazeutisch-chemischen Forschung - M13
323009 PR Lab Rotation I - MPS8
323010 PR Lab Rotation II - MPS8
323011 SE Proposal Writing - MPS9 - (2 Courses)
580008 SE SE Journal Club : Molecular Informatics
580009 SE SE Lecture Series Pharma and Food
1 - 20 out of 144
Chen Y, Winiwarter S, Jacob RA, Ahlqvist M, Mazzolari A, Miljković F et al. Metabolite Identification Data in Drug Discovery, Part 2: Site-of-Metabolism Annotation, Analysis, and Exploration for Machine Learning. Molecular Pharmaceutics. 2025 Nov 3;22(11):6772-6787. doi: 10.1021/acs.molpharmaceut.5c00740
Foil DH, König J, Herrmann K, Jacob RA, Kneuer C, Kirchmair J. Comparative Chemical Space Analysis of Pesticides and Substances with Genotoxicity Data. Chemical Research in Toxicology. 2025 Oct 29. Epub 2025 Oct 29. doi: 10.1021/acs.chemrestox.5c00198
Zhang H, Welsch M, Schueller W, Kirchmair J. Trialblazer: A chemistry-focused predictor of toxicity risks in late-stage drug development. European Journal of Medicinal Chemistry. 2025 Oct 28;302(Pt 2):118306. doi: 10.1016/j.ejmech.2025.118306
Fooladi H, Vu TNL, Mathea M, Kirchmair J. Evaluating Machine Learning Models for Molecular Property Prediction: Performance and Robustness on Out-of-Distribution Data. Journal of Chemical Information and Modeling. 2025 Oct 13;65(19):9871-9891. doi: 10.1021/acs.jcim.5c00475
Schwarz PF, Perhal AF, Guder F, Hernández González JE, Janssen K, Sağıroğlu E et al. Identification of New Lupane-Type Triterpenoids as Inverse Agonists of RAR-Related Orphan Receptor Gamma (RORγ). Journal of Natural Products. 2025 Aug 22;88(8):1887-1900. doi: 10.1021/acs.jnatprod.5c00416
Gallegos-Alvarado RM, Romo-Pérez A, Miranda LD, Del Rayo Camacho-Corona M, Dueñas-González A, Kirchmair J et al. Cytotoxic, Antibacterial, and in Silico Pks13 Inhibitory Properties of Indole-Coupled Dihydrobenzo[c]phenanthridines. ChemMedChem. 2025 Aug 11;202500146. Epub 2025 Aug 11. doi: 10.1002/cmdc.202500146
Jacob RA, Mazzolari A, Kirchmair J. Automated Annotation of Sites of Metabolism from Biotransformation Data. Journal of Chemical Information and Modeling. 2025 Jul 14;65(13):7065-7080. doi: 10.1021/acs.jcim.5c00819
Vu TNL, Fooladi H, Kirchmair J. Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening. Journal of Chemical Information and Modeling. 2025 May 26;65(10):4833-4843. Epub 2025 May 9. doi: 10.1021/acs.jcim.5c00380
Palmacci V, Nahal Y, Welsch M, Engkvist O, Kaski S, Kirchmair J. E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays. Journal of Cheminformatics. 2025 Apr 29;17:64. doi: 10.1186/s13321-025-01014-3
Liu S, Wu J, Chen Y, Wolf CA, Bureik M, Kirchmair J et al. Integrated Virtual Screening Approach Identifies New CYP19A1 Inhibitors. Journal of Chemical Information and Modeling. 2025 Apr 14;65(7):3529-3543. Epub 2025 Mar 19. doi: 10.1021/acs.jcim.5c00204
Janssen K, Kirchmair J, Proppe J. Relevance and Potential Applications of C2-Carboxylated 1,3-Azoles. ChemMedChem. 2024 Nov 4;19(21):e202400307. e202400307. Epub 2024 Jul 18. doi: 10.1002/cmdc.202400307
Welsch M, Hirte S, Kirchmair J. Deciphering Molecular Embeddings with Centered Kernel Alignment. Journal of Chemical Information and Modeling. 2024 Oct 14;64(19):7303-7312. doi: 10.1021/acs.jcim.4c00837
Mohoric T, Wilm A, Onken S, Milovich A, Logavoch A, Ankli P et al. Increasing Accessibility of Bayesian Network-Based Defined Approaches for Skin Sensitisation Potency Assessment. Toxics. 2024 Sept 12;12(9):666. doi: 10.3390/toxics12090666
Agea MI, Čmelo I, Dehaen W, Chen Y, Kirchmair J, Sedlák D et al. Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library. Molecular Informatics. 2024 Aug 12;43(8):e202300316. Epub 2024 Aug 12. doi: 10.1002/minf.202300316
Phan-Xuan T, Schweidler S, Hirte S, Schüller M, Lin L, Khandelwal A et al. Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, In Silico Structure-Activity, and Immunoassay Performance. ACS Nano. 2024 Jul 23;18(29):19024-19037. Epub 2024 Jul 10. doi: 10.1021/acsnano.4c03053
Le NTH, Janssen K, Kirchmair J, Pieters L, Tuenter E. A mini-review of the anti-SARS-CoV-2 potency of Amaryllidaceae alkaloids. Phytomedicine. 2024 Jul;129:155576. Epub 2024. doi: 10.1016/j.phymed.2024.155576
Palmacci V, Hirte S, Hernández González JE, Montanari F, Kirchmair J. Statistical approaches enabling technology-specific assay interference prediction from large screening data sets. Artificial Intelligence in the Life Sciences. 2024 Jun;5:100099. doi: 10.1016/j.ailsci.2024.100099
Fooladi H, Hirte S, Kirchmair J. Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning. Journal of Chemical Information and Modeling. 2024 May 27;64(10):4031-4046. doi: 10.1021/acs.jcim.4c00160
Tan L, Hirte S, Palmacci V, Stork C, Kirchmair J. Tackling assay interference associated with small molecules. Nature Reviews. Chemistry. 2024 May;8:319-339. Epub 2024 Apr 15. doi: 10.1038/s41570-024-00593-3
Chen Y, Seidel T, Jacob RA, Hirte S, Mazzolari A, Pedretti A et al. Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation. Journal of Chemical Information and Modeling. 2024 Jan 22;64(2):348-358. Epub 2024 Jan 3. doi: 10.1021/acs.jcim.3c01588
1 - 20 out of 144

Computational approaches for predicting assay interference

Kirchmair, J. (Speaker)

23 May 2024

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Computational methods for early drug discovery

Kirchmair, J. (Speaker)

5 Apr 2024

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Activity Cliffs Go Smooth: Graph Siamese Neural Networks for Molecular Activity Prediction

Mqawass, G. (Speaker), Hirte, S. (Speaker), Kirchmair, J. (Speaker) & Kriege, N. M. (Speaker)

8 Dec 2023

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Maximizing the performance of similarity-based virtual screening methods

Kirchmair, J. (Speaker)

19 Apr 2023

Activity: Talks and presentations › Talk or oral contribution › Science to Science

In silico methods for flagging compounds that are likely to interfere with biological assays

Kirchmair, J. (Invited speaker)

16 Dec 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Cheminformatics in natural product-based drug discovery

Kirchmair, J. (Invited speaker)

24 Nov 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

From in silico to in vivo - Psychotria nemorosa alkaloids counter protein toxicity in Caenorhabditis elegans

Kirchweger, B. (Speaker), Klein-Junior, L. C. (Contributor), Pretsch, D. (Contributor), Chen, Y. (Contributor), Cretton, S. (Contributor), de Gasper, A. L. (Contributor), Heyden, Y. V. (Contributor), Christen, P. (Contributor), Kirchmair, J. (Contributor), Henriques, A. T. (Contributor) & Rollinger, J. M. (Contributor)

31 Aug 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Natural products against SARS-CoV-2 or how to catch a butterfly?

Wasilewicz, A. (Speaker), Kirchweger, B. (Contributor), Bojkova, D. (Contributor), Abi Saad, M. J. (Contributor), Langeder, J. (Contributor), Grienke, U. (Contributor), Cinatl, J. (Contributor), Orts, J. (Contributor), Kirchmair, J. (Contributor), Rabenau, H. F. (Contributor) & Rollinger, J. M. (Contributor)

31 Aug 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Cheminformatics in Natural Product-Based Drug Discovery

Kirchmair, J. (Keynote speaker)

30 Aug 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Computerbasierte Vorhersage des Metabolismus von Wirkstoffen

Kirchmair, J. (Invited speaker)

12 Jul 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Cheminformatics in natural product-based drug discovery

Kirchmair, J. (Invited speaker)

30 Jun 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Introduction to machine learning in early drug discovery

Kirchmair, J. (Invited speaker)

21 Jun 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

In silico and in vitro Approach to Assess Direct Allosteric AMPK Activators from Nature

Kirchweger, B. (Speaker), Wasilewicz, A. (Contributor), Fischhuber, K. (Contributor), Tahir, A. (Contributor), Chen, Y. (Contributor), Heiß, E. (Contributor), Langer, T. (Contributor), Kirchmair, J. (Contributor) & Rollinger, J. M. (Contributor)

20 May 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

In silico prediction of xenobiotic metabolism

Kirchmair, J. (Invited speaker)

19 May 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

In silico prediction of drug metabolism

Kirchmair, J. (Invited speaker)

4 May 2022

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Computational prediction of the metabolic fate of small molecules

Kirchmair, J. (Speaker)

28 Sept 2021

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Computational methods for flagging compounds likely to cause false outcomes in biological assays

Kirchmair, J. (Speaker)

7 Jun 2021

Activity: Talks and presentations › Talk or oral contribution › Science to Science

In silico prediction of the macromolecular targets of natural products

Kirchmair, J. (Speaker)

9 Mar 2021

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Computational prediction of xenobiotic metabolism (focus on AI/machine learning methods)

Kirchmair, J. (Speaker)

27 Jan 2021

Activity: Talks and presentations › Talk or oral contribution › Science to Science

Anti-Infectives Drug Discovery

Rollinger, J. M. (Project Lead), Dailey, L. A. (Co-Lead), Orts, J. (Co-Lead), Böttcher, T. (Co-Lead), Schmidt, M. (Co-Lead), Rademacher, C. J. H. (Co-Lead), Schützenmeister, N. (Co-Lead), Zotchev, S. (Co-Lead), Kirchmair, J. (Co-Lead) & Ortmayr, K. (Co-Lead)

1/07/25 → 30/06/29

Project: Research funding

AIDD: Advanced Machine Learning for Innovative Drug Discovery

Kirchmair, J. (Project Lead)

1/01/21 → 31/12/24

Project: Research funding

Department of Pharmaceutical Sciences

Josef-Holaubek-Platz 2 (UZA II)
1090 Wien
Room: 2G353

T: +43-1-4277-55104

johannes.kirchmair@univie.ac.at