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A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed ( ϕ , ψ ) torsion angles of ca 12º. TALOS-N also reports sidechain χ 1 rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.

NMR chemical shifts in proteins depend strongly on local structure. The program TALOS establishes an empirical relation between ¹³C, ¹⁵N and ¹H chemical shifts and backbone torsion angles [Greek Phi symbol] and ψ (Cornilescu et al. J Biomol NMR 13 289-302, 1999). Extension of the original 20-protein database to 200 proteins increased the fraction of residues for which backbone angles could be predicted from 65 to 74%, while reducing the error rate from 3 to 2.5%. Addition of a two-layer neural network filter to the database fragment selection process forms the basis for a new program, TALOS+, which further enhances the prediction rate to 88.5%, without increasing the error rate. Excluding the 2.5% of residues for which TALOS+ makes predictions that strongly differ from those observed in the crystalline state, the accuracy of predicted [Greek Phi symbol] and ψ angles, equals ±13°. Large discrepancies between predictions and crystal structures are primarily limited to loop regions, and for the few cases where multiple X-ray structures are available such residues are often found in different states in the different structures. The TALOS+ output includes predictions for individual residues with missing chemical shifts, and the neural network component of the program also predicts secondary structure with good accuracy.

The small heat-shock protein HSP27 is a redox-sensitive molecular chaperone that is expressed throughout the human body. Here, we describe redox-induced changes to the structure, dynamics, and function of HSP27 and its conserved α-crystallin domain (ACD). While HSP27 assembles into oligomers, we show that the monomers formed upon reduction are highly active chaperones in vitro, but are susceptible to self-aggregation. By using relaxation dispersion and high-pressure nuclear magnetic resonance (NMR) spectroscopy, we observe that the pair of β-strands that mediate dimerisation partially unfold in the monomer. We note that numerous HSP27 mutations associated with inherited neuropathies cluster to this dynamic region. High levels of sequence conservation in ACDs from mammalian sHSPs suggest that the exposed, disordered interface present in free monomers or oligomeric subunits may be a general, functional feature of sHSPs. The small heat-shock protein HSP27 occurs predominantly in oligomeric forms, which makes its structural characterisation challenging. Here the authors employ CPMG and high-pressure NMR with native mass spectrometry and biophysical assays to show that the active monomeric form of HSP27 is substantially disordered and highly chaperone-active.

The important role of structural dynamics in protein function is widely recognized. Thermal or B-factors and their anisotropy, seen in x-ray analysis of protein structures, report on the presence of atomic coordinate heterogeneity that can be attributed to motion. However, their quantitative evaluation in terms of protein dynamics by x-ray ensemble refinement remains challenging. NMR spectroscopy provides quantitative information on the amplitudes and time scales of motional processes. Unfortunately, with a few exceptions, the NMR data do not provide direct insights into the atomic details of dynamic trajectories. Residual dipolar couplings, measured by solution NMR, are very precise parameters reporting on the time-averaged bond-vector orientations and may offer the opportunity to derive correctly weighted dynamic ensembles of structures for cases where multiple high-resolution x-ray structures are available. Applications to the SARS-CoV-2 main protease, Mpro, and ubiquitin highlight this complementarity of NMR and crystallography for quantitative assessment of internal motions.

Chemical shifts of nuclei in or attached to a protein backbone are exquisitely sensitive to their local environment. A computer program, SPARTA, is described that uses this correlation with local structure to predict protein backbone chemical shifts, given an input three-dimensional structure, by searching a newly generated database for triplets of adjacent residues that provide the best match in [Greek Phi symbol]/ψ/χ¹ torsion angles and sequence similarity to the query triplet of interest. The database contains ¹⁵N, ¹HN, ¹Hα, ¹³Cα, ¹³Cβ and ¹³C' chemical shifts for 200 proteins for which a high resolution X-ray (<=2.4 Å) structure is available. The relative importance of the weighting factors for the [Greek Phi symbol]/ψ/χ¹ angles and sequence similarity was optimized empirically. The weighted, average secondary shifts of the central residues in the 20 best-matching triplets, after inclusion of nearest neighbor, ring current, and hydrogen bonding effects, are used to predict chemical shifts for the protein of known structure. Validation shows good agreement between the SPARTA-predicted and experimental shifts, with standard deviations of 2.52, 0.51, 0.27, 0.98, 1.07 and 1.08 ppm for ¹⁵N, ¹HN, ¹Hα, ¹³Cα, ¹³Cβ and ¹³C', respectively, including outliers.

We present a program, named Promega, to predict the Xaa-Pro peptide bond conformation on the basis of backbone chemical shifts and the amino acid sequence. Using a chemical shift database of proteins of known structure together with the PDB-extracted amino acid preference of cis Xaa-Pro peptide bonds, a cis/trans probability score is calculated from the backbone and ¹³Cβ chemical shifts of the proline and its neighboring residues. For an arbitrary number of input chemical shifts, which may include Pro-¹³Cγ, Promega calculates the statistical probability that a Xaa-Pro peptide bond is cis. Besides its potential as a validation tool, Promega is particularly useful for studies of larger proteins where Pro-¹³Cγ assignments can be challenging, and for on-going efforts to determine protein structures exclusively on the basis of backbone and ¹³Cβ chemical shifts.

All but five of the N-terminal 23 residues of the HA2 domain of the influenza virus glycoprotein hemagglutinin (HA) are strictly conserved across all 16 serotypes of HA genes. The structure and function of this HA2 fusion peptide (HAfp) continues to be the focus of extensive biophysical, computational, and functional analysis, but most of these analyses are of peptides that do not include the strictly conserved residues Trp²¹-Tyr²²-Gly²³. The heteronuclear triple resonance NMR study reported here of full length HAfp of sero subtype H1, solubilized in dodecylphosphatidyl choline, reveals a remarkably tight helical hairpin structure, with its N-terminal α-helix (Gly¹-Gly¹²) packed tightly against its second α-helix (Trp¹⁴-Gly²³), with six of the seven conserved Gly residues at the interhelical interface. The seventh conserved Gly residue in position 13 adopts a positive {phi} angle, enabling the hairpin turn that links the two helices. The structure is stabilized by multiple interhelical CαH to C = O hydrogen bonds, characterized by strong interhelical HN-Hα and Hα-Hα NOE contacts. Many of the previously identified mutations that make HA2 nonfusogenic are also incompatible with the tight antiparallel hairpin arrangement of the HAfp helices.¹⁵N relaxation analysis indicates the structure to be highly ordered on the nanosecond time scale, and NOE analysis indicates HAfp is located at the water-lipid interface, with its hydrophobic surface facing the lipid environment, and the Gly-rich side of the helix-helix interface exposed to solvent.

Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the ¹³Cα, ¹³Cβ, ¹³C', ¹⁵N, ¹Hα and ¹HN NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 Å root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination.

The molecular mechanism through which the interaction of a clonotypic αβ T-cell receptor (TCR) with a peptide-loaded major histocompatibility complex (p/MHC) leads to T-cell activation is not yet fully understood. Here we exploit a high-affinity TCR (B4.2.3) to examine the structural changes that accompany binding to its p/MHC ligand (P18-I10/H2-D d ). In addition to conformational changes in complementarity-determining regions (CDRs) of the TCR seen in comparison of unliganded and bound X-ray structures, NMR characterization of the TCR β-chain dynamics reveals significant chemical shift effects in sites removed from the MHC-binding site. Remodelling of electrostatic interactions near the Cβ H3 helix at the membrane-proximal face of the TCR, a region implicated in interactions with the CD3 co-receptor, suggests a possible role for an allosteric mechanism in TCR signalling. The contribution of these TCR residues to signal transduction is supported by mutagenesis and T-cell functional assays. Binding of T cell receptors (TCR) to peptide-loaded major histocompatibility complexes (p/MHC) leads to T-cell activation. Here the authors give structural insights into T-cell signalling and show that p/MHC binding induces conformational changes at the membrane-proximal site of the TCR.