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Univ.-Prof. Mag. Dr. Johannes Kirchmair
Johannes Kirchmair
T: +43-1-4277-55104
https://comp3d.univie.ac.at
Winter term 2026
262005 VO Introduction to Computational Biology and Drug Discovery
262006 UE Introduction to Computational Biology and Drug Discovery - Exercises
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)
581009 SE SE Journal Club : Molecular Informatics
581010 SE SE Lecture Series Pharma and Food
581012 SE Anti-Infective Drug Discovery
Summer term 2026
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 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
61 - 80 out of 153
Garcia de Lomana M, Morger A, Norinder U, Buesen R, Landsiedel R, Volkamer A et al. ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities. Journal of Chemical Information and Modeling. 2021 Jun 21;61(7):3255–3272. doi: 10.1021/acs.jcim.1c00451
Medina-Franco JL, Martinez-Mayorga K, Gortari EF, Kirchmair J, Bajorath J. Rationality over fashion and hype in drug design. F1000Research. 2021 May 18;10:397. doi: 10.12688/f1000research.52676.1
Ingwersen T, Linnenberg C, D'Acunto E, Temori S, Paolucci I, Wasilewski D et al. G392E neuroserpin causing the dementia FENIB is secreted from cells but is not synaptotoxic. Scientific Reports. 2021 Apr 22;11(1):8766. doi: 10.1038/s41598-021-88090-1
Li S, Ding Y, Chen M, Chen Y, Kirchmair J, Zhu Z et al. HDAC3i-Finder: A Machine Learning-based Computational Tool to Screen for HDAC3 Inhibitors. Molecular Informatics. 2021 Mar;40(3):2000105. Epub 2020 Oct 16. doi: 10.1002/minf.202000105
de Bruyn Kops C, Šícho M, Mazzolari A, Kirchmair J. GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations of Xenobiotics. Chemical Research in Toxicology. 2021 Feb 15;34(2):286-299. Epub 2020 Aug 10. doi: 10.1021/acs.chemrestox.0c00224
Garcia de Lomana M, Weber AG, Birk B, Landsiedel R, Achenbach J, Schleifer KJ et al. In Silico Models to Predict the Perturbation of Molecular Initiating Events Related to Thyroid Hormone Homeostasis. Chemical Research in Toxicology. 2021 Feb 15;34(2):396-411. Epub 2020 Nov 13. doi: 10.1021/acs.chemrestox.0c00304
Wilm A, Norinder U, Agea MI, de Bruyn Kops C, Stork C, Kühnl J et al. Skin Doctor CP: Conformal Prediction of the Skin Sensitization Potential of Small Organic Molecules. Chemical Research in Toxicology. 2021 Feb 15;34(2):330-344. Epub 2020 Dec 9. doi: 10.1021/acs.chemrestox.0c00253
Dreger A, Hoff K, Agoglitta O, Hotop SK, Brönstrup M, Heisig P et al. Antibacterial activity of xylose-derived LpxC inhibitors - Synthesis, biological evaluation and molecular docking studies. Bioorganic Chemistry. 2021 Feb;107:104603. doi: 10.1016/j.bioorg.2020.104603
Chen Y, Kirchmair J. Cheminformatics in Natural Product-Based Drug Discovery. Molecular Informatics. 2020 Dec;39(12):2000171. doi: 10.1002/minf.202000171
Linciano P, Cavalloro V, Martino E, Kirchmair J, Listro R, Rossi D et al. Tackling Antimicrobial Resistance with Small Molecules Targeting LsrK: Challenges and Opportunities. Journal of Medicinal Chemistry. 2020 Nov 5;63(24):15243–15257. doi: 10.1021/acs.jmedchem.0c01282
Kirchmair J. Molecular Informatics in Natural Products Research. Molecular Informatics. 2020 Nov;39(11):2000206. doi: 10.1002/minf.202000206
Chen Y, Mathai N, Kirchmair J. Scope of 3D Shape-Based Approaches in Predicting the Macromolecular Targets of Structurally Complex Small Molecules Including Natural Products and Macrocyclic Ligands. Journal of Chemical Information and Modeling. 2020 Jun 22;60(6):2858-2875. doi: 10.1021/acs.jcim.0c00161
Mathai N, Chen Y, Kirchmair J. Validation strategies for target prediction methods. Briefings in bioinformatics. 2020 May 21;21(3):791-802. doi: 10.1093/bib/bbz026
Mathai N, Kirchmair J. Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope. International Journal of Molecular Sciences. 2020 May;21(10):3585. doi: 10.3390/ijms21103585
Fan N, Bauer CA, Stork C, de Bruyn Kops C, Kirchmair J. ALADDIN: Docking Approach Augmented by Machine Learning for Protein Structure Selection Yields Superior Virtual Screening Performance. Molecular Informatics. 2020 Apr;39(4):1900103. doi: 10.1002/minf.201900103
Stork C, Embruch G, Šícho M, de Bruyn Kops C, Chen Y, Svozil D et al. NERDD: a web portal providing access to in silico tools for drug discovery. Bioinformatics. 2020 Feb 15;36(4):1291-1292. doi: 10.1093/bioinformatics/btz695
Xue W, Li X, Ma G, Zhang H, Chen Y, Kirchmair J et al. N-thiadiazole-4-hydroxy-2-quinolone-3-carboxamides bearing heteroaromatic rings as novel antibacterial agents: Design, synthesis, biological evaluation and target identification. European Journal of Medicinal Chemistry. 2020 Feb 15;188:112022. doi: 10.1016/j.ejmech.2019.112022
Langeder J, Grienke U, Chen Y, Kirchmair J, Schmidtke M, Rollinger JM. Natural products against acute respiratory infections: Strategies and lessons learned. Journal of Ethnopharmacology. 2020 Feb 10;248:112298. doi: 10.1016/j.jep.2019.112298
Ehm PAH, Lange F, Hentschel C, Jepsen A, Glück M, Nelson N et al. Analysis of the FLVR motif of SHIP1 and its importance for the protein stability of SH2 containing signaling proteins. Cellular signalling. 2019 Nov;63:109380. doi: 10.1016/j.cellsig.2019.109380
Wilm A, Stork C, Bauer C, Schepky A, Kühnl J, Kirchmair J. Skin Doctor: Machine Learning Models for Skin Sensitization Prediction that Provide Estimates and Indicators of Prediction Reliability. International Journal of Molecular Sciences. 2019 Oct;20(19):4833. doi: 10.3390/ijms20194833
61 - 80 out of 153

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 → 31/01/30

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