From molecular interaction networks to personalized drug treatment
Stelzl, Ulrich, Univ.-Prof. Dipl.-Ing. Dr.rer.nat.
Hartler, Jürgen, Ass.-Prof. Dipl.-Ing. Dr.techn.
Halwachs-Wenzl, Bettina, Dipl.-Ing. Dr.techn. BSc
Jany-Luig, Evelyne, M.Sc. (on educational leave)
Kunowska, Natalia, Dr.rer.nat.
Annerer-Walcher, Lukas, Dipl.-Ing.
Auernig, Elisabeth, Mag.pharm.
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The group is focusing on the analysis of molecular interaction networks with the aim to understand the dynamics of molecular networks underlying cellular processes related to human disease. Experimental functional genomics techniques, e.g. HTP Y2H screening, are utilized in combination with biochemical, cell biological and computational methods.
Current DNA sequencing approaches and mass spectrometry based proteomics technologies allow the simultaneous measurements of gene/protein variants for series of cell types, conditions or disease states. In particular the discovery of new somatic mutations in health and disease has vastly outpaced our ability to assess their functional roles. As most of the variation alone is not causal with respect to the observed phenotype, the question arises how to systematically analyze the large number of molecular variation and how to assess the importance of combined changes for cellular function, disease development and drug action? In our work we focus on the systematic analyses of the functional impact of genetic variation and post-translational protein modification on protein-protein interaction, which as universal protein function underlies cellular phenotypes. Using deep scanning mutagenesis approaches we bridge the knowledge gap between nucleotide resolution genomics and protein resolution proteomics.
Network biology offers a more comprehensive understanding of biological processes. Advances in systems biology indicate that complex diseases may not be treated effectively by interventions at single drug targets and with single drugs. Network biology will advance our understanding of drug action and will be an important piece in developing individualized medicine.
Recommended reading on interaction networks / network biology / network pharmacology:
Systematic interaction studies in human disease research, a technology feature free at Nature magazine: Protein maps chart the causes of disease by Marissa Fessenden (Bozeman|Montana)
A new discipline: network science !? An insight commentary at Nature Physics suggests ... The network takeover by Albert-László Barabási (Boston|Massachusetts)
Updated research records can be found at
pubmed, PMC Europe, google scholar, scopus or researcherID.
Recent selected publications
Jehle S, Kunowska N, Benlasfer N, Woodsmith J, Weber G, Wahl MC, Stelzl U (2022);
A human kinase yeast array for the identification of kinases modulating phosphorylation-dependent protein-protein interactions;
Mol Syst Biol 18: e10820 ; doi: 10.15252/msb.202110820
article link at EMBO press
Kunowska N, Stelzl U (2022);
Decoding the cellular effects of genetic variation through interaction proteomics;
Curr Opin Chem Biol 66: 102100 ; doi: 10.1016/j.cbpa.2021.102100
article link at Sciencedirect
Moesslacher CS, Kohlmayr JM, Stelzl U(2021);
Exploring absent protein function in yeast: assaying post translational modification and human genetic variation;
Microb Cell 8: 164-183; doi: 10.15698/mic2021.08.756
article link at microbialcell
Woodsmith J, Casado-Medrano V, Benlasfer N, Eccles RL, Hutten S, Heine CL, Thormann V, Abou-Ajram C, Rocks O, Dormann D, Stelzl U (2018)
Interaction modulation through arrays of clustered methyl-arginine protein modifications.
Life Sci Alliance 1: e201800178.
article link at EMBO press
Woodsmith J, Apelt L, Casado-Medrano V, Özkan Z, Timmermann B, Stelzl U (2017)
Protein interaction perturbation profiling at amino-acid resolution.
Nat Methods 14: 1548-7091.
article link at nature methods
Corwin T, Woodsmith J, Apelt F, Fontaine JF, Meierhofer D, Helmuth J, Grossmann A, Andrade-Navarro MA, Ballif BA, Stelzl U (2017)
Defining Human Tyrosine Kinase Phosphorylation Networks Using Yeast as an In Vivo Model Substrate.
Cell Syst. 5:128-139.
article link free at cell press