Research project NMR

Improving chemical shift-based methods in NMR.

We are continuing to work on approaches that interpret and use chemical shift data from Nuclear Magnetic Resonance (NMR), in order to improve our protein sequence-based predictions. The statistical analysis of NMR data forms the basis of most of our research: a good and extensive data set is the key to developing any new prediction or validation methodology. We focus on local residue interactions between amino acids close to each other in the sequence, which are key determinants of protein conformation (and, we think, dynamics). This behaviour is therefore already present in peptides (short proteins), where in collaboration with Prof. Alonso (VUB) we are starting to use state-of-the-art quantum chemical calculations to explore whether we can create a computational framework that can estimate the effect amino acid modifications (such as phosphorylation) will likely have on the conformation and dynamics of proteins.


G.0328.16N (Jan. 1, 2016-Dec. 31, 2019)
FoldMod - The role of local amino acid interactions in the folding of proteins, the stability of their fold and the location of post-translational modifications.


CING (Software tool, External collaboration)

ST resource  CING
CING is a software suite for the validation of NMR structure ensembles.