The secrets of life lie in the molecular flexibility.

Welcome to Prof. Mariusz Jaremko's research group, the

Flexible Systems Lab!

Our research group works mainly on metabolites which are important for human health, and our current main focus in this discipline is oriented towards food, food safety, food quality, and food fraud by utilizing state-of-the-art instrumentation in metabolomics studies. We are also working on aggregation of amylin, a biological peptide that is connected tightly with diabetes II, a disease that is closely related to unhealthy diets. So, food science and the consequences of the food we eat are one of the main areas which the group Flexible Systems investigates. We are also working to develop methods and pulse programs in Nuclear Magnetic Resonance (NMR) that allow us to uncover obscured metabolites and to detect them at lower concentrations, in order to understand metabolic pathways better. 


Why the name Flexible Systems?

It's simple; because metabolites, as well as amylin and its analogues, are very flexible systems i.e. amylin does not have a defined 3D structure, and in the case of the small molecules and metabolites we study, while they do have defined structures, they often exhibit very high levels of dynamic flexibility due to their size.

Untangling untidy folds to understand diseases

Copper ions could play a key role when peptide folding goes wrong and leads to harmful aggregates.

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Picking the best methods for metabolomics research

Comparison of different nuclear magnetic resonance spectroscopy methods has helped to identify the most robust approach for studying different types of biomolecules.

Latest Publications

The robust NMR toolbox for metabolomics

by Kousik Chandra, Samah Al-Harthi, Fatimah Almulhim, Abdul-Hamid Emwas, Lukasz Jaremko, Mariusz Jaremko
Review Article Year: 2021 DOI: https://doi.org/10.1039/D1MO00118C

Abstract

Here, we implemented and validated a suite of selective and non-selective CPMG-filtered 1D and 2D TOCSY/HSQC experiments for metabolomics research. They facilitated the unambiguous identification of metabolites embedded in broad lipid and protein signals. The 2D spectra improved non-targeted analysis by removing the background broad signals of macromolecules.