Applications of NMR and computational methodologies to study protein dynamics

Abstract

Overwhelming evidence now illustrates the defining role of atomic-scale protein flexibility in biological events such as allostery, cell signaling, and enzyme catalysis. Over the years, spin relaxation nuclear magnetic resonance (NMR) has provided significant insights on the structural motions occurring on multiple time frames over the course of a protein life span. The present review article aims to illustrate to the broader community how this technique continues to shape many areas of protein science and engineering, in addition to being an indispensable tool for studying atomic-scale motions and functional characterization. Continuing developments in underlying NMR technology alongside software and hardware developments for complementary computational approaches now enable methodologies to routinely provide spatial directionality and structural representations traditionally harder to achieve solely using NMR spectroscopy. In addition to its well-established role in structural elucidation, we present recent examples that illustrate the combined power of selective isotope labeling, relaxation dispersion experiments, chemical shift analyses, and computational approaches for the characterization of conformational sub-states in proteins and enzymes.

Coarse-grain simulations on NMR conformational ensembles highlight functional residues in proteins

“…From a theoretical point of view, numerous tools are nowadays available for investigating protein dynamics 14,17 . Classic all-atom Molecular Dynamics (MD) simulations represent a common strategy, sometimes combined with experimental approaches [18][19] , which can however be computationally costly when working on large systems or modeling events taking place on a long time-scale 20 . Another option is to use coarse-grain models, that combine simplified protein representations and energy functions [21][22][23] .…”

“…! 4 Since its initial developments a few decades ago, NMR spectroscopy has turned out to be a powerful tool for exploring the structure and dynamics of proteins in solution 18,[30][31][32] . In particular, proteic entries in the Protein Data Bank 33 (PDB) produced by solution NMR often provide a conformational ensemble containing between 10 and 30 structural models instead of a single structure.…”

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport

“…Parameters such as conformational exchange rates or backbone NH-bond fluctuations are mostly straightforward to assess structurally [e.g. 50, 51]. Other observables in NMR can be more challenging to translate into dynamic or structural properties of the molecule investigated: for example, chemical shifts reflect local structure, transitions, and population occupancies of states.…”

Mechanical variations in proteins with large-scale motions highlight the formation of structural locks

“…Protein motions are difficult to observe directly using experimental approaches, as they can cover a wide range of timescales, from a few picoseconds to 10's of millisecond or more (Dror et al, 2012). Therefore, numerous techniques are now available to study protein motions on a range of different timescales, such as NMR (Kovermann et al, 2016;Narayanan et al, 2017), single molecule approaches ( Colomb and Sarkar, 2015), time-resolved X-ray crystallography (Levantino et al, 2015;Meisburger et al, 2017), FRET (Dimura et al, 2016;Lerner et al, 2018) or SAXS (Kikhney and Svergun, 2015), which can be used alone or combined together (Debiec et al, 2018). From a theoretical perspective, Molecular Dynamics (MD) simulations represent a classic alternative and will often complement experimental work (Debiec et al, 2018;Feng et al, 2016;Narayanan et al, 2017).…”

“…Therefore, numerous techniques are now available to study protein motions on a range of different timescales, such as NMR (Kovermann et al, 2016;Narayanan et al, 2017), single molecule approaches ( Colomb and Sarkar, 2015), time-resolved X-ray crystallography (Levantino et al, 2015;Meisburger et al, 2017), FRET (Dimura et al, 2016;Lerner et al, 2018) or SAXS (Kikhney and Svergun, 2015), which can be used alone or combined together (Debiec et al, 2018). From a theoretical perspective, Molecular Dynamics (MD) simulations represent a classic alternative and will often complement experimental work (Debiec et al, 2018;Feng et al, 2016;Narayanan et al, 2017). Still, the use of all-atom MD remains a costly strategy to access rare events, such as slow, large-amplitude conformational transitions, and usually requires the development of enhanced sampling strategies (Greener et al, 2017;Maximova et al, 2016;Romanowska et al, 2012;Seyler and Beckstein, 2014), or access to remarkable computational power (Shaw et al, 2010).…”