Research projects

Thesis projects for BSc and MSc students

Method development for small-scale, semi-automated synthesis

The number of available methods for a chemical synthesis is high, as chemists now have access to various solvent systems, additives and catalysts. However, traditional synthetic approaches mainly rely on multiple validations and optimizations. In the era of virtual molecules, which are generated based on robust chemical reactions, such approach would mean a separate optimization for each of the molecules. Combinatoric libraries nowadays reach a multi-billion size, and when even a few hundred molecules are selected for synthesis, it is possible that each reaction will use different reactants. Therefore, there is a need for a limited number of generalized protocols, especially for the emerging automated synthesis approaches. The project focuses on identifying synthetic setups that provide sufficient selectivity, versatility and yields for the most commonly applied organic synthetic reactions.

Read more:

"Fully Automated Chemical Synthesis: Toward the Universal Synthesizer" - Org. Process Res. Dev. 2020, 24, 10, 2064-2077

"DIY Virtual Chemical Libraries - Novel Starting Points for Drug Discovery" - ACS Med. Chem. Lett. 2023, 14, 9, 1188-1197

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Investigation and extesnion of the chemical space

The currently accessible chemical spaces allow the in-silico investigations for various  players in the chemical industry. Researches demand more and more novel structures to search for promising compounds. However, the currently available spaces might be limited by the applied base chemicals and reactions. Before the extension possibilities of current spaces are investigated, a clear picture should be gathered on the content of spaces to see common and rare or missing structures. The transformation of chemical reactions to machine readable expressions (e.g. SMARTS, SMIRKS) can be used for the development of virtual chemical spaces. With the involvement of robust or unique chemical reactions, novel spaces could be developed that contain great amounts of novel or an extended number of very rare substructures for the research industry. The development of virtual chemical space to provide novel structures generally relies on the quality of encoded combination routes. Although various retrosynthetic tools and large spaces are generated, the laboratory phase success of syntheses can still show high variability. The practical reactivity of a site can be affected by various effects, ranging from nucleophilicity or steric hindrance, but the capture of combined effects would be crucial for the virtual-to-real transformation.

Read more:

"The Medicinal Chemist’s Toolbox: An Analysis of Reactions Used in the Pursuit of Drug Candidates" - J. Med. Chem. 2011, 54, 10, 3451-3479

"A Collection of Robust Organic Synthesis Reactions for In Silico Molecule Design" - J. Chem. Inf. Model. 2011, 51, 12, 3093–3098

"The next level in chemical space navigation: going far beyond enumerable compound libraries" - Drug Discovery Today 2019, 24, 1148-1156

Evaluation of phase equilibrium data 

Experimental phase equilibrium data play a significant role in the development of separation processes. As the quality of data has a great impact on the possible modelling of the equilibrium and therefore on the final design of a separation unit. Therefore, it is highly important to correctly and easily evaluate the preliminary results during experimentation and provide quick feedback on errors.

The correctly evaluated experimental data have only limited use unless they are converted to parameters suitable for modelling the behaviour of the components. The real application value of gathered parameters need to be evaluated via simulations and comparison with available information.

Read more:

"A fresh look at the thermodynamic consistency of vapour-liquid equilibria data" - J. Chem. Thermodyn. 2017, 105, 385-395

"Isobaric vapor–liquid equilibria and distillation process design for separating ketones in biomass pyrolysis oil" - J. Chem. Thermodyn. 2022, 164, 106622