Kurzprofil Assoz. Prof. Dr. Antonella Di Pizio


Leiterin der Arbeitsgruppe Molecular Modeling

Lise-Meitner-Str. 34
85354 Freising

Tel.: +49 8161 71-6516

E-Mail  ORCID 

Life is the result of the chemical activity of molecules, and decoding the molecule structures and their interactions is the key to understand and modulate protein function and biological activities. The Molecular Modeling group aims to investigate biomolecular interactions using computational tools, focusing on the complex food effector systems and their chemoreceptor-mediated interactions. Because of the challenges the food system currently faces, computational tools are essential for developing the next-generation methodology for food design. Using molecular docking, molecular dynamics simulations, pharmacophore modeling, QSAR, machine learning and virtual screening, our group develops predictive models to search and rationally design new ingredients for food reformulation, but also support the development of new therapeutic approaches, with the ultimate goal of improving health and quality of life.

  • Modeling chemosensory GPCRs to understand the molecular bases of ligand recognition and activation mechanism
  • Developing structure-based ligand design protocols to identify new taste- and odor-active compounds
  • Using chemoinformatics and structural bioinformatics approaches to investigate the combinatorial code of chemosensory perception
2023 – current Associate Professor for Chemoinformatics and Protein Modeling at the Department of Molecular Life Sciences at the School of Life Sciences
2018 – current Leibniz-Institute of Food Systems Biology at the TU Munich, Freising, Group leader Molecular Modeling
2013 – 2018 Hebrew University of Jerusalem, Rehovot, Israel, Senior Postdoc Taste lab
2009 – 2012 University of Chieti, Italy, Ph.D. student Pharmacy, Drug Science Department
2022 Leibniz Best Minds Programme for Women Professors
2020 Visiting Professorship, University of Milano, Department of Food, Environment and Nutritional Sciences
2019 Platinum Manfred Rothe Excellence Award in Flavor Research, sponsored by Nestlé, 12th Wartburg Symposium (Eisenach, Germany)
2013 Bernardo Nobile doctorate award VIII Edition, by Area Science park (Trieste).
2020 - Working Group Leader [WG3] and Management Committee (MC) member (Germany representative) of the ERNEST Cost Action CA18133
2020 - Editorial board member Frontiers in Molecular Biosciences
2022 – Modeling and simulations of Biological Macromolecules (WZ2235)
2022 – Drug and Protein Design (WZ2297)
2020 – Lecture & Seminar “Drug Discovery Chemistry” (CH0156), TU Munich
2020 – Lecture & Seminar “Introduction into Chemoinformatics and Bioinformatics for Food Scientists” (WZ1330), TU Munich

(See ORCID for complete list)

1. Di Pizio A*, Nicoli A. In silico molecular study of tryptophan bitterness. Molecules  2020, 25(20): 4623-4632, doi: 10.3390/molecules25204623

2. Cooper KW, Brann DH, Farruggia MC, Bhutani S, Pellegrino R, Tsukahara T, Weinreb C, Joseph PV, Larson ED, Parma V, Albers MW, Barlow LA*, Datta SR*, Di Pizio A*. COVID-19 and the chemical senses: supporting players take center stage. Neuron  2020, 107(2): 219-233, doi: 10.1016/j.neuron.2020.06.032.

3. Leung N, Thakur DP, Gurav AS, Kim SH, Di Pizio A, Niv MY, Montell C*. Functions of Opsins in Drosophila Taste. Current Biology  2020, 30: 1-13, doi: 10.1016/j.cub.2020.01.068.

4. Dunkel A, Hofmann T, Di Pizio A*. In-silico investigation of bitter hop-derived compounds and their cognate bitter taste receptors. Journal of Agricultural and Food Chemistry  2020, 68 (38): 10414-10423, doi: 10.1021/acs.jafc.9b07863.

5. Spaggiari G, Di Pizio A*, Cozzini P*. Sweet, umami and bitter taste receptors: State of the Art of in silico molecular modeling approaches. Trends in food science & technology  2020, 96: 21-29, doi: 10.1016/j.tifs.2019.12.002.

6. Di Pizio, A, Waterloo, LAW, Brox, R, Loeber, S, Weikert, D, Behrens, M*, Gmeiner, P*, and Niv, MY*. Rational design of agonists for the bitter taste receptor TAS2R14: from modeling to bench and back. Cell. Mol. Life Sci. 2020, 77: 531-542.

*=corresponding author