Univ.-Prof. Mag. Dr. Johannes Kirchmair
Johannes Kirchmair
21 - 40 out of 142
Bajorath J, Gardner S, Grisoni F, Andrade CH, Kirchmair J, Landon M et al. First-generation themed article collections. Artificial Intelligence in the Life Sciences. 2023 Dec 15;4:100088. doi: 10.1016/j.ailsci.2023.100088

Scholz VA, Stork C, Frericks M, Kirchmair J. Computational prediction of the metabolites of agrochemicals formed in rats. Science of the Total Environment. 2023 Oct 15;895:165039. Epub 2023 Jun 22. doi: 10.1016/j.scitotenv.2023.165039

Gonzalez-Ponce K, Horta Andrade C, Hunter F, Kirchmair J, Martinez-Mayorga K, Medina-Franco JL et al. School of cheminformatics in Latin America. Journal of Cheminformatics. 2023 Sept 19;15(1):82. doi: 10.1186/s13321-023-00758-0

Resetar M, Tietcheu Galani BR, Tsamo AT, Chen Y, Schachner D, Stolzlechner S et al. Flindissone, a Limonoid Isolated from Trichilia prieuriana, Is an LXR Agonist. Journal of Natural Products. 2023 Aug 25;86(8):1901-1909. doi: 10.1021/acs.jnatprod.3c00059

Füzi B, Mathai N, Kirchmair J, Ecker GF. Toxicity prediction using target, interactome, and pathway profiles as descriptors. Toxicology Letters. 2023 May 15;381:20-26. doi: 10.1016/j.toxlet.2023.04.005

Listro R, Milli G, Pellegrini A, Motta C, Cavalloro V, Martino E et al. Structural Insights into the Ligand–LsrK Kinase Binding Mode: A Step Forward in the Discovery of Novel Antimicrobial Agents. Molecules. 2023 Mar 10;28(6):2542. doi: 10.3390/molecules28062542

Wiercioch M, Kirchmair J. DNN-PP: A novel Deep Neural Network approach and its applicability in drug-related property prediction. Expert systems with applications. 2023 Mar 1;213(B):119055. doi: 10.1016/j.eswa.2022.119055

Wasilewicz A, Kirchweger B, Bojkova D, Saad MJA, Langeder J, Butikofer M et al. Identification of Natural Products Inhibiting SARS-CoV-2 by Targeting Viral Proteases: A Combined in Silico and in Vitro Approach. Journal of Natural Products. 2023 Feb 24;86(2):264-275. Epub 2023 Jan 18. doi: 10.1021/acs.jnatprod.2c00843

Ehm P, Nelson N, Giehler S, Schaks M, Bettin B, Kirchmair J et al. Reduced expression and activity of patient-derived SHIP1 phosphatase domain mutants. Cellular signalling. 2023 Jan 1;101:110485. Epub 2022. doi: 10.1016/j.cellsig.2022.110485

Iobbi V, Donadio G, Lanteri AP, Maggi N, Kirchmair J, Parisi V et al. Metabolite profiling of "Eretto Liguria", an Italian local ecotype of Salvia rosmarinus, and antimicrobial activity against Pectobacterium carotovorum subsp. carotovorum. Planta Medica. 2023;89(14):1409-1409. doi: 10.1055/s-0043-1774222

Xue W, Wang Y, Lian X, Li X, Pang J, Kirchmair J et al. Discovery of N-quinazolinone-4-hydroxy-2-quinolone-3-carboxamides as DNA gyrase B-targeted antibacterial agents. Journal of Enzyme Inhibition and Medicinal Chemistry. 2022 Dec 31;37(1):1620-1631. doi: 10.1080/14756366.2022.2084088


Kirchweger B, Wasilewicz A, Fischhuber K, Tahir A, Chen Y, Heiss EH et al. In Silico and In Vitro Approach to Assess Direct Allosteric AMPK Activators from Nature. Planta Medica. 2022 Aug;88(09/10):794-804. doi: 10.1055/a-1797-3030

Fan N, Hirte S, Kirchmair J. Maximizing the Performance of Similarity-Based Virtual Screening Methods by Generating Synergy from the Integration of 2D and 3D Approaches. International Journal of Molecular Sciences. 2022 Jul 13;23(14):7747. doi: 10.3390/ijms23147747

Chen Y, Rosenkranz C, Hirte S, Kirchmair J. Ring systems in natural products: structural diversity, physicochemical properties, and coverage by synthetic compounds. Natural Product Reports - NPR. 2022 Jun 16;39(8):1544-1556. Epub 2022 Jun 16. doi: 10.1039/d2np00001f

Morger A, Garcia de Lomana M, Norinder U, Svensson F, Kirchmair J, Mathea M et al. Studying and mitigating the effects of data drifts on ML model performance at the example of chemical toxicity data. Scientific Reports. 2022 May 4;12(1):7244. doi: 10.1038/s41598-022-09309-3

Lomana MGD, Svensson F, Volkamer A, Mathea M, Kirchmair J. Consideration of predicted small-molecule metabolites in computational toxicology. Digital Discovery. 2022 Apr 1;1(2):158-172. doi: 10.1039/D1DD00018G

Hirte S, Burk O, Tahir A, Schwab M, Windshügel B, Kirchmair J. Development and Experimental Validation of Regularized Machine Learning Models Detecting New, Structurally Distinct Activators of PXR. Cells. 2022 Apr;11(8):1253. doi: 10.3390/cells11081253

Kirchweger B, Klein-Junior LC, Pretsch D, Chen Y, Cretton S, Gasper AL et al. Azepine-Indole Alkaloids From Psychotria nemorosa Modulate 5-HT2A Receptors and Prevent in vivo Protein Toxicity in Transgenic Caenorhabditis elegans. Frontiers in Neuroscience. 2022 Mar 14;16:826289. doi: 10.3389/fnins.2022.826289


21 - 40 out of 142

Computational approaches for predicting assay interference

Kirchmair, J. (Speaker)

23 May 2024

Activity: Talks and presentationsTalk or oral contributionScience to Science


Computational methods for early drug discovery

Kirchmair, J. (Speaker)

5 Apr 2024

Activity: Talks and presentationsTalk or oral contributionScience 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 presentationsTalk or oral contributionScience to Science


Maximizing the performance of similarity-based virtual screening methods

Kirchmair, J. (Speaker)

19 Apr 2023

Activity: Talks and presentationsTalk or oral contributionScience 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 presentationsTalk or oral contributionScience to Science


Cheminformatics in natural product-based drug discovery

Kirchmair, J. (Invited speaker)

24 Nov 2022

Activity: Talks and presentationsTalk or oral contributionScience 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 presentationsTalk or oral contributionScience 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 presentationsTalk or oral contributionScience to Science


Cheminformatics in Natural Product-Based Drug Discovery

Kirchmair, J. (Keynote speaker)

30 Aug 2022

Activity: Talks and presentationsTalk or oral contributionScience to Science


Computerbasierte Vorhersage des Metabolismus von Wirkstoffen

Kirchmair, J. (Invited speaker)

12 Jul 2022

Activity: Talks and presentationsTalk or oral contributionScience to Science


Cheminformatics in natural product-based drug discovery

Kirchmair, J. (Invited speaker)

30 Jun 2022

Activity: Talks and presentationsTalk or oral contributionScience to Science


Introduction to machine learning in early drug discovery

Kirchmair, J. (Invited speaker)

21 Jun 2022

Activity: Talks and presentationsTalk or oral contributionScience 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 presentationsTalk or oral contributionScience to Science


In silico prediction of xenobiotic metabolism

Kirchmair, J. (Invited speaker)

19 May 2022

Activity: Talks and presentationsTalk or oral contributionScience to Science


In silico prediction of drug metabolism

Kirchmair, J. (Invited speaker)

4 May 2022

Activity: Talks and presentationsTalk or oral contributionScience to Science


Computational prediction of the metabolic fate of small molecules

Kirchmair, J. (Speaker)

28 Sept 2021

Activity: Talks and presentationsTalk or oral contributionScience to Science


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

Kirchmair, J. (Speaker)

7 Jun 2021

Activity: Talks and presentationsTalk or oral contributionScience to Science


In silico prediction of the macromolecular targets of natural products

Kirchmair, J. (Speaker)

9 Mar 2021

Activity: Talks and presentationsTalk or oral contributionScience to Science


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

Kirchmair, J. (Speaker)

27 Jan 2021

Activity: Talks and presentationsTalk or oral contributionScience 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)

1/07/2530/06/29

Project: Research funding


AIDD: Advanced Machine Learning for Innovative Drug Discovery

Kirchmair, J. (Project Lead)

1/01/2131/12/24

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