Accurate measurement of (3)J(HNHα) couplings in small or disordered proteins from WATERGATE-optimized TROSY spectra

Reversible phase separation of ESCRT protein ALIX through tyrosine phosphorylation

Cytokinetic abscission, the last step of cell division, is regulated by the ESCRT machinery. In response to mitotic errors, ESCRT proteins, namely, ALIX, CHMP4B, and CHMP4C, accumulate in the cytosolic compartments termed "abscission checkpoint bodies" (ACBs) to delay abscission and prevent tumorigenesis. ALIX contributes to the biogenesis and stability of ACBs via an unknown mechanism. We show that ALIX phase separates into nondynamic condensates in vitro and in vivo, mediated by the amyloidogenic portion of its proline-rich domain. ALIX condensates confined CHMP4 paralogs in vitro. These condensates dissolved and reformed upon reversible tyrosine phosphorylation of ALIX, mediated by Src kinase and PTP1B, and sequestration of CHMP4C altered their Src-mediated dissolution. NMR analysis revealed how ALIX triggers the activation of CHMP4 proteins, which is required for successful abscission. These results implicate ALIX's phase separation in the modulation of ACBs. This study also highlights how posttranslational modifications can control protein phase separation.

Longitudinal Spin Order Labeling on Multiple Quantum Coherences Enables NMR Analysis of Intrinsically Disordered Proteins at Ultrahigh Resolution

Intrinsically disordered proteins (IDPs) play an important role in cell signaling, and NMR is well-suited to study conformational ensembles and dynamics of IDPs. However, the intrinsic flexibility of IDPs often results in severe spectral overlap, which hampers accurate NMR data analysis. By labeling the longitudinal spin order of an α proton (i.e., H^α_z) on multiple quantum coherences of backbone nuclei (e.g., N_yC'_xC^α_y), we were able to apply pre-homonuclear decoupling (PHD) to transverse relaxation-optimized spectroscopy (TROSY). The proposed scheme provides ultrahigh resolution in both amide proton and nitrogen dimensions, as illustrated in the analysis of Tau and alpha-synuclein (α-Syn) proteins. The PHD-TROSY readout enabled complete backbone resonance assignment of α-Syn using a single 3D HNCA experiment performed on a 600 MHz NMR spectrometer.

What Drives 15N Spin Relaxation in Disordered Proteins? Combined NMR/MD Study of the H4 Histone Tail

Backbone (¹⁵N) NMR relaxation is one of the main sources of information on dynamics of disordered proteins. Yet, we do not know very well what drives ¹⁵N relaxation in such systems, i.e., how different forms of motion contribute to the measurable relaxation rates. To address this problem, we have investigated, both experimentally and via molecular dynamics simulations, the dynamics of a 26-residue peptide imitating the N-terminal portion of the histone protein H4. One part of the peptide was found to be fully flexible, whereas the other part features some transient structure (a hairpin stabilized by hydrogen bonds). The following motional modes proved relevant for ¹⁵N relaxation. 1) Sub-picosecond librations attenuate relaxation rates according to S² ∼0.85-0.90. 2) Axial peptide-plane fluctuations along a stretch of the peptide chain contribute to relaxation-active dynamics on a fast timescale (from tens to hundreds of picoseconds). 3) φ/ψ backbone jumps contribute to relaxation-active dynamics on both fast (from tens to hundreds of picoseconds) and slow (from hundreds of picoseconds to a nanosecond) timescales. The major contribution is from polyproline II (PPII) ↔ β transitions in the Ramachandran space; in the case of glycine residues, the major contribution is from PPII ↔ (β) ↔ rPPII transitions, in which rPPII is the mirror-image (right-handed) version of the PPII geometry, whereas β geometry plays the role of an intermediate state. 4) Reorientational motion of certain (sufficiently long-lived) elements of transient structure, i.e., rotational tumbling, contributes to slow relaxation-active dynamics on ∼1-ns timescale (however, it is difficult to isolate this contribution). In conclusion, recent advances in the area of force-field development have made it possible to obtain viable Molecular Dynamics models of protein disorder. After careful validation against the experimental relaxation data, these models can provide a valuable insight into mechanistic origins of spin relaxation in disordered peptides and proteins.

Prediction of nearest neighbor effects on backbone torsion angles and NMR scalar coupling constants in disordered proteins

Using fine-tuned hydrogen bonding criteria, a library of coiled peptide fragments has been generated from a large set of high-resolution protein X-ray structures. This library is shown to be an improved representation of ϕ/ψ torsion angles seen in intrinsically disordered proteins (IDPs). The ϕ/ψ torsion angle distribution of the library, on average, provides good agreement with experimentally observed chemical shifts and ³ J_HN-Hα coupling constants for a set of five disordered proteins. Inspection of the coil library confirms that nearest-neighbor effects significantly impact the ϕ/ψ distribution of residues in the coil state. Importantly, ³ J_HN-Hα coupling constants derived from the nearest-neighbor modulated backbone ϕ distribution in the coil library show improved agreement to experimental values, thereby providing a better way to predict ³ J_HN-Hα coupling constants for IDPs, and for identifying locations that deviate from fully random behavior.

Atomic-resolution map of the interactions between an amyloid inhibitor protein and amyloid β (Aβ) peptides in the monomer and protofibril states

Self-association of amyloid β (Aβ) peptides is a hallmark of Alzheimer's disease and serves as a general prototype for amyloid formation. A key endogenous inhibitor of Aβ self-association is human serum albumin (HSA), which binds ∼90% of plasma Aβ. However, the exact molecular mechanism by which HSA binds Aβ monomers and protofibrils is not fully understood. Here, using dark-state exchange saturation transfer NMR and relaxation experiments complemented by morphological characterization, we mapped the HSA-Aβ interactions at atomic resolution by examining the effects of HSA on Aβ monomers and soluble high-molecular weight oligomeric protofibrils. We found that HSA binds both monomeric and protofibrillar Aβ, but the affinity of HSA for Aβ monomers is lower than for Aβ protofibrils (K_d values are submillimolar rather than micromolar) yet physiologically relevant because of the ∼0.6-0.7 mm plasma HSA concentration. In both Aβ protofibrils and monomers, HSA targets key Aβ self-recognition sites spanning the β strands found in cross-β protofibril structures, leading to a net switch from direct to tethered contacts between the monomeric Aβ and the protofibril surface. These HSA-Aβ interactions are isoform-specific, because the HSA affinity of Aβ monomers is lower for Aβ(1-42) than for Aβ(1-40). In addition, the HSA-induced perturbations of the monomer/protofibrils pseudo-equilibrium extend to the C-terminal residues in the Aβ(1-42) isoform but not in Aβ(1-40). These results provide an unprecedented view of how albumin interacts with Aβ and illustrate the potential of dark-state exchange saturation transfer NMR in mapping the interactions between amyloid-inhibitory proteins and amyloidogenic peptides.

Is the Conformational Ensemble of Alzheimer's Aβ10-40 Peptide Force Field Dependent?

By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Aβ10-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Aβ10-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Aβ10-40 ³J_HNHα-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Aβ1-40 peptide. Our study led us to several conclusions. First, all force fields predict that Aβ adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Aβ10-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate β-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Aβ collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of ³J_HNHα-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Aβ10-40 and experimental Aβ1-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Aβ1-40 or Aβ1-42. This observation suggests that the differences in the conformational ensembles of Aβ10-40 and Aβ1-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Aβ10-40 conformational ensemble.

Dependence of protein conformational ensembles on force field parameterizations limits the predictive power of molecular dynamics simulations. To address this problem, we evaluated five all-atom force fields for their consistency in reproducing the conformational ensemble of Alzheimer’s Aβ10-40 peptide. To generate conformational ensembles, we have used replica exchange molecular dynamics and computed Aβ10-40 secondary and tertiary structures. We found that, although all force fields predict Aβ10-40 unfolded structure, they strongly disagree on helix and β propensities and tertiary structure distributions. We have also calculated Aβ10-40 J-coupling and residual dipolar coupling constants and compared them with the experimental data for the full-length Aβ1-40 peptide. Unexpectedly, we determined that in silico Aβ10-40 and experimental Aβ1-40 constants are in better agreement than these quantities computed and measured previously for identical peptides, such as Aβ1-40 or Aβ1-42. We then concluded that the conformational ensembles of Aβ10-40 and Aβ1-40 are similar and on this basis argue that CHARMM36 force field with standard TIP3P water model provides the most accurate description of Aβ10-40. Although our objective was not to evaluate the biomolecular force fields in general, our study is expected to facilitate their proper selection for the simulations of Alzheimer’s peptides.

ARTSY-J: Convenient and precise measurement of (3)JHNHα couplings in medium-size proteins from TROSY-HSQC spectra

A new and convenient method, named ARTSY-J, is introduced that permits extraction of the (3)JHNHα couplings in proteins from the relative intensities in a pair of (15)N-(1)H TROSY-HSQC spectra. The pulse scheme includes (3)JHNHα dephasing of the narrower TROSY (1)H(N)-{(15)N} doublet component during a delay, integrated into the regular two-dimensional TROSY-HSQC pulse scheme, and compares the obtained intensity with a reference spectrum where (3)JHNHα dephasing is suppressed. The effect of passive (1)H(α) spin flips downscales the apparent (3)JHNHα coupling by a uniform factor that depends approximately linearly on both the duration of the (3)JHNHα dephasing delay and the (1)H-(1)H cross relaxation rate. Using such a correction factor, which accounts for the effects of both inhomogeneity of the radiofrequency field and (1)H(α) spin flips, agreement between prior and newly measured values for the small model protein GB3 is better than 0.3Hz. Measurement for the HIV-1 protease homodimer (22kDa) yields (3)JHNHα values that agree to better than 0.7Hz with predictions made on the basis of a previously parameterized Karplus equation. Although for Gly residues the two individual (3)JHNHα couplings cannot be extracted from a single set of ARTSY-J spectra, the measurement provides valuable ϕ angle information.

Monomeric Aβ(1-40) and Aβ(1-42) Peptides in Solution Adopt Very Similar Ramachandran Map Distributions That Closely Resemble Random Coil

The pathogenesis of Alzheimer’s disease is characterized by the aggregation and fibrillation of amyloid peptides Aβ^1–40 and Aβ^1–42 into amyloid plaques. Despite strong potential therapeutic interest, the structural pathways associated with the conversion of monomeric Aβ peptides into oligomeric species remain largely unknown. In particular, the higher aggregation propensity and associated toxicity of Aβ^1–42 compared to that of Aβ^1–40 are poorly understood. To explore in detail the structural propensity of the monomeric Aβ^1–40 and Aβ^1–42 peptides in solution, we recorded a large set of nuclear magnetic resonance (NMR) parameters, including chemical shifts, nuclear Overhauser effects (NOEs), and J couplings. Systematic comparisons show that at neutral pH the Aβ^1–40 and Aβ^1–42 peptides populate almost indistinguishable coil-like conformations. Nuclear Overhauser effect spectra collected at very high resolution remove assignment ambiguities and show no long-range NOE contacts. Six sets of backbone J couplings (³J_HNHα, ³J_C′C′, ³J_C′Hα, ¹J_HαCα, ²J_NCα, and ¹J_NCα) recorded for Aβ^1–40 were used as input for the recently developed MERA Ramachandran map analysis, yielding residue-specific backbone ϕ/ψ torsion angle distributions that closely resemble random coil distributions, the absence of a significantly elevated propensity for β-conformations in the C-terminal region of the peptide, and a small but distinct propensity for α_L at K28. Our results suggest that the self-association of Aβ peptides into toxic oligomers is not driven by elevated propensities of the monomeric species to adopt β-strand-like conformations. Instead, the accelerated disappearance of Aβ NMR signals in D₂O over H₂O, particularly pronounced for Aβ^1–42, suggests that intermolecular interactions between the hydrophobic regions of the peptide dominate the aggregation process.