NeGeMac - Research Platform

Next Generation Macrocycles to Address Challenging Protein Interfaces

The NeGeMac research platform addresses several important aspects of the early chemical drug discovery phase:

  • data science and deep learning,
  • computer‐assisted protein interaction analysis, as well as the
  • conformational analysis and prioritization of innovative macrocycles,

which became available recently by applying modern and environmentally efficient organic synthesis methods.

These complementary basic research concepts together provide ‐ as an example, applied to therapeutically interesting protein targets ‐ the basis for the identification of promising starting materials for medicinal chemistry optimization programs. The nationally and internationally wellembedded team put together for this proposal uses this concept to generate potent platform technology that enhances the visibility of the University of Vienna in the area of biopharmaceutical basic research, as well as possibilities for later translational exploitation of the highly effective lead structures that will have been created.


Nuno Maulide (Faculty of Chemistry)


Gerhard Ecker (Faculty of Life Sciences)
Thierry Langer (Faculty of Life Sciences)


Synthetic Methodology Development (N. Maulide)
Data Science and Modeling (G. Ecker)
Chemoinformatics (T. Langer)

More Information


  • Research Team

    Nuno Maulide is Full Professor of Organic Synthesis at the Department of Organic Chemistry. His research interests focus on rearrangement reactions, catalysis (two areas which are directly implicated in this research platform) as well as stereoselective synthesis of bioactive man‐made and naturally occuring substances. The Maulide group is well‐known for their contributions to diastereodivergent asymmetric catalysis [17], sulfonium‐accelerated rearrangements [18], molecular editing of bioactive substances [19] and total synthesis of natural products [20]. Nuno Maulide is also Adjunct PI at the Center for Molecular Medicine of the Austrian Academy of Sciences and since 2019 leads a Christian Doppler Laboratory with Boehringer Ingelheim as cooperation partner, two vehicles where the classical boundaries between chemistry/biology/medicine are currently being crossed. The Maulide group will be responsible for synthetic efforts as well as participating in the feedback loop between design and synthesis.


    Gerhard Ecker is Full Professor of Pharmacoinformatics at the Department of Pharmaceutical Chemistry. The groups’ expertise lies on structural modelling of proteins, structure‐based drug design, chemometric and in silico chemogenomic methods, statistical modelling and machine learning approaches for development of predictive computational systems with focus on transporters ( In recent years, integration and mining of open data sources for answering complex drug‐discovery related research questions such as toxicity prediction became an increasingly important topic. Especially the generation of data mining workflows, as well as knowledge on transporter modeling will be of special use for the research platform. He was also academic coordinator of the Open PHACTS project, which generated a semantically integrated life science data platform. The Ecker group has a long standing expertise in modeling of transmembrane membrane transporter. To overcome the limitations of scoring functions, the group developed a workflow which heavily relies on experimental data for validation of docking poses. This was first exemplified for the binding hypothesis of diazepam in the GABA receptor [12], which recently was experimentally confirmed by the respective Cryo‐EM structure. With the coordination of the Open PHACTS project, the group gained strong expertise in data mining and semantic technologies for data integration. This led to the development of workflows which enable complex queries, thus guiding phenotypic screening [21] and repurposing strategies (Gurinova, unpublished). In this project, the Ecker group will conduct an exhaustive analysis of the knowledge available on macrocycles and their interaction with SLC‐transporter. This will guide the selection of a small set of target proteins and chemical scaffolds. Subsequently, protein homology models of the transporter will be established and binding hypotheses for macrocycles binding to these transporter will be derived using our data guided protocol. This will guide synthesis of small focused libraries, which will allow to further refine the binding hypotheses. 


    Thierry Langer is full professor of Pharmaceutical Chemistry at the Department of Pharmaceutical Chemistry since 2013 with major interests (i) in the design and development of novel computational tools for addressing chemoinformatic and medicinal chemistry problems, (ii) in the application of such tools for computer‐assisted conception of new bio‐active molecules, and (iii) in the synthesis of such compounds. He has published more than 200 peer reviewed publications and book chapters (Scopus h‐index 51). In addition to his academic track record, he has experience in the life science industry: In 2003, he co‐founded Inte:Ligand GmbH, a software development entity located in Vienna, Austria; From 2008 to 2013, he was CEO of Prestwick Chemical Ltd., France: Under his leadership, several compounds progressed into clinical development. Within the NeGeMac platform, his group will be responsible for all chemoinformatics related tasks, ranging from conformational analysis to target protein binding site analysis and compound prioritization. Most relevant achievements to the proposal include scientific leadership in the development of the software platform LigandScout [16] as well as the IL Pharmacophore Databases (commercialized both by Inte:Ligand GmbH, Vienna, Austria). 



    1. César‐Razquin, A., Snijder, B., Frappier‐Brinton, T., Isserlin, R., Gyimesi, G., Bai, X., Reithmeier, R.A., Hepworth, D., Hediger, M.A., Edwards, A.M., Superti‐Furga, G. A Call for Systematic Research on Solute Carriers, Cell; 162(3):478‐87 (2015).
    2. Wagner, V., Jantz, L. Briem, H., Sommer, K., Rare, M., Christ, C. D. Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation, ChemMedChem; 12(22):1866‐1872 (2017).
    3. Gao, C., Park, M.‐S., Stern, H. A., Accounting for Ligand Conformational Restriction in Calculations of Protein‐Ligand Binding Affinities, Biophys. J.; 98(5)901:910 (2010).
    4. Li, J., Preinfalk, A., Maulide, N. Enantioselective Redox‐Neutral Coupling of Aldehydes and Alkenes by an Iron‐Catalyzed Catch‐Release Tethering Approach, J. Am. Chem. Soc. 141:143‐ 147 (2019).
    5. Li, J., Preinfalk, A., Maulide, N. Diastereo‐ and Enantioselective Access to Stereotriads Through a Flexible Coupling of Substituted Aldehydes and Alkenes, Angew. Chem. Int. Ed. 58:5887‐ 5900 (2019).
    6. Williams AJ, Harland L, Groth P, Pettifer S, Chichester C, Willighagen EL, Evelo CT, Blomberg N, Ecker GF, Goble C, Mons B. Open PHACTS: Semantic interoperability for drug discovery (2012). Drug Discovery Today17, 1188‐98;
    7. Azzaoui K, Jacoby E, Senger S, Rodriguez EC, Loza M, Zdrazil B, Pinto M, Williams AJ, De la Torre V, Mestres J, Pastor M, Taboureau O, Rarey M, Chichester C, Petiffer S, Blomberg N, Harland L, Williams‐Jones B, Ecker GF. Scientific competency questions as basis for the development of a semantically enriched Open Pharmacological Space (2013). Drug Discov Today 18:843‐52,
    8. Klepsch F, Chiba P, Ecker GF. Exhaustive sampling of docking poses reveals binding hypotheses for propafenone type inhibitors of P‐glycoprotein. PLoS Comp Biol7, e1002036 (2011),
    9. Jain S, Grandits M, Ecker GF. Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP (2017). J Comp‐Aided Mol Des31:507‐521;
    10. Sarker S, Weissensteiner R, Steiner I, Sitte HH, Ecker GF, Freissmuth M, Sucic S. The highaffinity binding site for tricyclic antidepressants resides in the outer vestibule of the serotonin tranporter. Mol Pharmacol 78, 1026‐35 (2010),
    11. Jorgensen L, Al‐Khawaja A, Kickinger S, Vogensen SB, Skovgaard‐Petersen J, Rosenthal E, Borkar N, Löffler R, Madsen KK, Bräuner‐Osborne H, Schousboe A, Ecker GF, Wellendorph P, Clausen RP (2017). Structure‐activity relationship, pharmacological characterization, and molecular modeling of noncompetitive inhibitors of the betaine/g‐aminobutyric acid transporter 1. J. Med. Chem. 60: 8834‐8846.
    12. Richter L, de Graaf C, Sieghart W, Varagic Z, Mörzinger M, de Esch IJP, Ecker GF, Ernst M. Diazepam‐bound GABAA receptor models identify new benzodiazepine binding‐site ligands. Nature Chem Biol8, 455‐64 (2012).
    13. Singh N, Scalise M, Galluccio M, Wieder M, Seidel T, Langer T, Indiveri C, Ecker GF (2018). Discovery of potent inhibitors for the Large Neutral Amino Acid Transporter 1 (LAT1) by structure‐based methods. Int J Mol Sci 20:27;
    14. Schütz, D. A. et al. GRAIL: GRids of phArmacophore Interaction fieLds. J. Chem. Theory Comput. 14 (9), 4958‐4970 (2018)
    15. Poli, G., Seidel, T., Langer, T. Conformational Sampling of Small Molecules with iCon: Performance Assessment in Comparison with OMEGA. Front. Chem. 6, 229 (2018)
    16. Wolber, G., Langer, T. LigandScout: 3‐D pharmacophores derived from protein‐bound ligands and their use as virtual screening filters. J. Chem. Inf. Model. 45, 160‐169 (2005)
    17. Luparia, M., Oliveira, M. T., Audisio, D., Frebault, F., Maulide, N. Catalytic Asymmetric Diastereodivergent Deracemisation, Angew. Chem. Int. Ed. 50:12631‐12635 (2011).
    18. Kaldre, D., Klose, I., Maulide, N., Stereodivergent Synthesis of 1,4‐dicarbonyls by traceless charge‐accelerated sulfonium rearrangement, Science 361:664‐667 (2018).
    19. Adler, P., Teskey, C. J., Kaiser, D., Holy, M., Sitte, H. H., Maulide, N. ɑ‐Fluorination of carbonyls with nucleophilic fluorine, Nat. Chem. 11:329‐334 (2019).
    20. O’Donovan, D., Maulide, N. et. al. C‐H Activation Enables a Concise Total Synthesis of Quinine and Analogues with Enhanced Antimalarial Activity, Angew. Chem. Int. Ed. 57(33):10737‐ 10741 (2018).
    21. Digles D, Zdrazil B, Neefs J‐M, van Vlijmen H, Herhaus C, Caracoti A, Brea J, Roibas B, Loza MI, Queralt‐Rosinach N, Furlong LI, Gaulton A, Bartek L, Senger S, Chichester C, Enkvist O, Evelo CT, Marren D, Ecker GF, Jacoby E. Open PHACTS Computational Protocols for in silico Target Validation of Cellular Phenotypic Screens: Knowing the Knowns (2016). Med Chem Commun 7:1237‐1244;
  • About Research Platforms

    Research platforms address academic questions that can only be studied from an interdisciplinary perspective. Thus, the underlying goal is the promotion of especially innovative, interdisciplinary research projects at the University of Vienna.

    After international appraisal of the 20 applications received, the Rectorate decided to set up eleven projects in the course of 2020 and to fund these with up to EUR 600,000 each for a period of four years.

    Read more about other Research Platforms at the University of Vienna and the Faculty of Life Sciences.