Predictive Atomic Resolution Descriptions of Intrinsically Disordered hTau40 and α-Synuclein in Solution from NMR and Small Angle Scattering

Abstract

The development of molecular descriptions of intrinsically disordered proteins (IDPs) is essential for elucidating conformational transitions that characterize common neurodegenerative disorders. We use nuclear magnetic resonance, small angle scattering, and molecular ensemble approaches to characterize the IDPs Tau and α-synuclein. Ensemble descriptions of IDPs are highly underdetermined due to the inherently large number of degrees of conformational freedom compared with available experimental measurements. Using extensive cross-validation we show that five different types of independent experimental parameters are predicted more accurately by selected ensembles than by statistical coil descriptions. The improvement increases in regions whose local sampling deviates from statistical coil, validating the derived conformational description. Using these approaches we identify enhanced polyproline II sampling in aggregation-nucleation sites, supporting suggestions that this region of conformational space is important for aggregation.

Discrete Molecular Dynamics Approach to the Study of Disordered and Aggregating Proteins

“…Thus, it seems that DMD/PACSAB simulations are able to provide a reasonable description of the complex conformational landscape of the long α-synuclein protein. Focusing in more local structural characteristics, we have not found any persistent secondary structure along the protein chain, in agreement with the experimental observations obtained from NMR measurements 39 . The color scale (arbitrary units), goes from blue (no contacts) to red (many contacts).…”

Intrinsically Disordered Proteins: Where Computation Meets Experiment

“…Thus, the BW formalism allows the user to use quantitative experimental measurements, such as NMR or SAXS data, to construct conformational ensembles, and produces a measure of the model's statistical uncertainty. Cross-validating an ensemble with independent experimental data provides an additional method for justifying an ensemble [72,73]. To illustrate how computational tools can be used to study IDPs, in the remaining sections we focus on two IDPs that have been implicated in human disease.…”

“…Combining experimental measurements from different sources with computational studies has shown promise in generating conformational ensembles of IDPs [71][72][73]. In the following section, we discuss how computation can be used to gain further insight into the conformational ensemble of IDPs from experimentally garnered data.…”

Inferring Properties of Disordered Chains From FRET Transfer Efficiencies

“…Studying the structure, dynamics and function of these disordered polypeptide chains, as well as other disordered biopolymers, requires new experimental methods, and new methods of interpreting the data, since they are inherently averaged over a broad ensemble of heteropolymer configurations [2][3][4] . Examples of experiments which can help address this challenge include: nuclear magnetic resonance (NMR), which can provide short-range structural information via scalar coupling, chemical shift and NOE data 5 , as well as long-range information by paramagnetic relaxation enhancement (PRE) measurements 6 , and global information from diffusion coefficient measurements; light-scattering 7 and two-focus FCS 4,8 , which also yield diffusion coefficients and hence hydrodynamic radius; small-angle X-ray (or neutron) scattering (SAXS or SANS), which directly gives information on inter-and intramolecular pair distance distributions 9 ; and Förster resonance energy transfer (FRET), in particular single-molecule FRET, which probes the distribution of distances between pairs of chromophore labels attached to the molecule of interest, as well as the associated dynamics, and often enables structured and unstructured subpopulations to be separated 10,11 .…”