[Back]
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
41 - 60 out of 142
Stork C, Mathai N, Kirchmair J. Computational prediction of frequent hitters in target-based and cell-based assays. Artificial Intelligence in the Life Sciences. 2021 Dec;1:100007. doi: 10.1016/j.ailsci.2021.100007
Wiercioch M, Kirchmair J. Dealing with a data-limited regime: Combining transfer learning and transformer attention mechanism to increase aqueous solubility prediction performance. Artificial Intelligence in the Life Sciences. 2021 Dec;1:100021. doi: 10.1016/j.ailsci.2021.100021
Plonka W, Stork C, Šícho M, Kirchmair J. CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes. Bioorganic & Medicinal Chemistry. 2021 Sept 15;46:116388. Epub 2021 Aug 28. doi: 10.1016/j.bmc.2021.116388
Ntie-Kang F, Telukunta KK, Fobofou SAT, Chukwudi Osamor V, Egieyeh SA, Valli M et al. Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop. Journal of Cheminformatics. 2021 Sept 6;13(1):64. doi: 10.1186/s13321-021-00546-8
Nelson N, Razeto A, Gilardi A, Grättinger M, Kirchmair J, Jücker M. AKT1 and PTEN show the highest affinities among phosphoinositide binding proteins for the second messengers PtdIns(3,4,5)P3 and PtdIns(3,4)P2. Biochemical and Biophysical Research Communications. 2021 Sept 3;568:110-115. Epub 2021 Jun 29. doi: 10.1016/j.bbrc.2021.06.027
Holmer M, de Bruyn Kops C, Stork C, Kirchmair J. CYPstrate: A Set of Machine Learning Models for the Accurate Classification of Cytochrome P450 Enzyme Substrates and Non-Substrates. Molecules (Basel, Switzerland). 2021 Aug 2;26(15):4678. doi: 10.3390/molecules26154678
Mathai N, Stork C, Kirchmair J. BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space. International Journal of Molecular Sciences. 2021 Aug;22(15):7773. doi: 10.3390/ijms22157773
Wilm A, Lomana MGD, Stork C, Mathai N, Hirte S, Norinder U et al. Predicting the Skin Sensitization Potential of Small Molecules with Machine Learning Models Trained on Biologically Meaningful Descriptors. Pharmaceuticals. 2021 Aug;14(8):790. doi: 10.3390/ph14080790
Paraschiakos T, Flat W, Chen Y, Kirchmair J, Windhorst S. Mechanism of BIP-4 mediated inhibition of InsP3Kinase-A. Bioscience Reports. 2021 Jul;41(7):BSR20211259. Epub 2021 Jul 7. doi: 10.1042/BSR20211259
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
41 - 60 out of 142

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