Single-shot NMR measurement of protein unfolding landscapes

An "Onion-like" Model of Protein Unfolding: Collective versus Site Specific Approaches

Approximating protein unfolding by an all-or-none cooperative event is a convenient assumption that can provide precious global information on protein stability. It is however quickly emerging that the scenario is far more complex and that global denaturation curves often hide a rich heterogeneity of states that are largely probe dependent. In this review, we revisit the importance of gaining site-specific information on the unfolding process. We focus on nuclear magnetic resonance, as this is the main technique able to provide site-specific information. We review historical and most modern approaches that have allowed an appreciable advancement of the field of protein folding. We also demonstrate how unfolding is a reporter dependent event, suggesting the outmost importance of selecting the reporter carefully.

Automation of peak-tracking analysis of stepwise perturbed NMR spectra

We describe a new algorithmic approach able to automatically pick and track the NMR resonances of a large number of 2D NMR spectra acquired during a stepwise variation of a physical parameter. The method has been named Trace in Track (TINT), referring to the idea that a gaussian decomposition traces peaks within the tracks recognised through 3D mathematical morphology. It is capable of determining the evolution of the chemical shifts, intensity and linewidths of each tracked peak.The performances obtained in term of track reconstruction and correct assignment on realistic synthetic spectra were high above 90% when a noise level similar to that of experimental data were considered. TINT was applied successfully to several protein systems during a temperature ramp in isotope exchange experiments. A comparison with a state-of-the-art algorithm showed promising results for great numbers of spectra and low signal to noise ratios, when the graduality of the perturbation is appropriate. TINT can be applied to different kinds of high throughput chemical shift mapping experiments, with quasi-continuous variations, in which a quantitative automated recognition is crucial.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Structure, folding dynamics, and amyloidogenesis of D76N β2-microglobulin: roles of shear flow, hydrophobic surfaces, and α-crystallin

Systemic amyloidosis is a fatal disease caused by misfolding of native globular proteins, which then aggregate extracellularly as insoluble fibrils, damaging the structure and function of affected organs. The formation of amyloid fibrils in vivo is poorly understood. We recently identified the first naturally occurring structural variant, D76N, of human β₂-microglobulin (β₂m), the ubiquitous light chain of class I major histocompatibility antigens, as the amyloid fibril protein in a family with a new phenotype of late onset fatal hereditary systemic amyloidosis. Here we show that, uniquely, D76N β₂m readily forms amyloid fibrils in vitro under physiological extracellular conditions. The globular native fold transition to the fibrillar state is primed by exposure to a hydrophobic-hydrophilic interface under physiological intensity shear flow. Wild type β₂m is recruited by the variant into amyloid fibrils in vitro but is absent from amyloid deposited in vivo. This may be because, as we show here, such recruitment is inhibited by chaperone activity. Our results suggest general mechanistic principles of in vivo amyloid fibrillogenesis by globular proteins, a previously obscure process. Elucidation of this crucial causative event in clinical amyloidosis should also help to explain the hitherto mysterious timing and location of amyloid deposition.