91探花

University 91探花
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  4. Gergely Katona

Gergely Katona

Professor

Department of Chemistry & Molecular Biology
Telephone
+46 709-12 33 09
Mail
gergely.katona@cmb.gu.se
Visiting address
Medicinaregatan 7 B
41390 G枚teborg
Room number
1213
Postal address
Box 462
40530 G枚teborg

About Gergely Katona

Structural biology

Our research group specializes in crystallographic investigations, with a particular emphasis on exploring the dynamic states of proteins. While this technique has proven invaluable, its technical limitations have made it challenging to study proteins and enzymes in action. To address this hurdle, our team has pioneered the use of chemical and physical triggering and trapping techniques, enabling us to examine reacting enzymes at various intermediate states. Once these states are successfully established, we employ a range of X-ray techniques to delve into their molecular structures.

Our studies offer dual benefits. Firstly, they contribute to the advancement of cutting-edge techniques specifically designed for studying enzymes engaged in catalytic activity. This aspect is crucial as it paves the way for future investigations in this field. Secondly, our findings provide valuable insights into the intricate workings of specific enzymes, enhancing our understanding of their functional mechanisms.

For more detailed information about our research and the exciting projects we undertake, explore Gergely's research website at .

Artificial Intelligence and Machine Learning

Gergely Katona started his work in the field of AI in projects relating to measurement of crystallographic data. This specialized field of science has vast applications in time-resolved structural determination and single wavelength anomalous diffraction (SAD). He also used advanced Bayesian methods for more accurate and efficient data analysis in biophysical experiments, such as microscale thermophoresis (MST), biolayer interferometry (BLI), and nuclear magnetic resonance spectroscopy (NMR), in order to e.g. predict how these experiments would evolve over time or with changes in ligand concentration. Other exciting applications of artificial intelligence in the field of biomedicine involves cancer and inflammatory diseases, with focus on the protein survivin, which plays a crucial role in various diseases. By using neural networks, Gergely was able to identify the peptides that could interact best with survivin, allowing researchers to develop more effective treatments. This work has also led to the registration of a patent related to the discovery of suitable peptides targeting specific proteins and biological functions, as well as the prediction of the fitness of mutations.

Gergely holds the position of Chairman of the Chemistry Program Committee and serves as the main examiner for the field of Chemistry.

Additionally, Gergely is actively involved in teaching various courses, including:

  • KEM350: Design and Production of Biomolecules
  • KEM360: Biomolecular Structure and Dynamics
  • KEM011: Basic Chemistry
  • KER210: Analytical Pharmaceutical Chemistry
  • KMB056: Molecular Biotechnology

Moreover, Gergely takes on the responsibility of supervising doctoral, master, and bachelor students, focusing on their training in method development and equipping them with universal skills to conduct independent research.

Furthermore, Gergely undertakes the task of reviewing applications for the iNEXT network and beamlines at EMBL Hamburg.