Solution Structure of the Cutibacterium acnes-Specific Protein RoxP and Insights Into Its Antioxidant Activity.

Cutibacterium acnes is a predominant bacterium on human skin and is generally regarded as commensal. Recently, the abundantly secreted protein produced by C. acnes, RoxP, was shown to alleviate radical-induced cell damage, presumably via antioxidant activity, which could potentially be harnessed to fortify skin barrier function. The aim of this study was to determine the structure of RoxP and elucidate the mechanisms behind its antioxidative effect. Here, we present the solution structure of RoxP revealing a compact immunoglobulin-like domain containing a long flexible loop which, in concert with the core domain, forms a positively charged groove that could function as a binding site for cofactors or substrates. Although RoxP shares structural features with cell-adhesion proteins, we show that it does not appear to be responsible for adhesion of C. acnes bacteria to human keratinocytes. We identify two tyrosine-containing stretches located in the flexible loop of RoxP, which appear to be responsible for the antioxidant activity of RoxP.

CheSPI: chemical shift secondary structure population inference.

NMR chemical shifts (CSs) are delicate reporters of local protein structure, and recent advances in random coil CS (RCCS) prediction and interpretation now offer the compelling prospect of inferring small populations of structure from small deviations from RCCSs. Here, we present CheSPI, a simple and efficient method that provides unbiased and sensitive aggregate measures of local structure and disorder. It is demonstrated that CheSPI can predict even very small amounts of residual structure and robustly delineate subtle differences into four structural classes for intrinsically disordered proteins. For structured regions and proteins, CheSPI provides predictions for up to eight structural classes, which coincide with the well-known DSSP classification. The program is freely available, and can either be invoked from URL www.protein-nmr.org as a web implementation, or run locally from command line as a python program. CheSPI generates comprehensive numeric and graphical output for intuitive annotation and visualization of protein structures. A number of examples are provided.

ODiNPred: comprehensive prediction of protein order and disorder.

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however, notoriously difficult to predict the degree of local flexibility within structured domains and the presence and nuances of localized rigidity within intrinsically disordered regions. To identify such instances, we used the CheZOD database, which encompasses accurate, balanced, and continuous-valued quantification of protein (dis)order at amino acid resolution based on NMR chemical shifts. To computationally forecast the spectrum of protein disorder in the most comprehensive manner possible, we constructed the sequence-based protein order/disorder predictor ODiNPred, trained on an expanded version of CheZOD. ODiNPred applies a deep neural network comprising 157 unique sequence features to 1325 protein sequences together with the experimental NMR chemical shift data. Cross-validation for 117 protein sequences shows that ODiNPred better predicts the continuous variation in order along the protein sequence, suggesting that contemporary predictors are limited by the quality of training data. The inclusion of evolutionary features reduces the performance gap between ODiNPred and its peers, but analysis shows that it retains greater accuracy for the more challenging prediction of intermediate disorder.

POTENCI: prediction of temperature, neighbor and pH-corrected chemical shifts for intrinsically disordered proteins.

Chemical shifts contain important site-specific information on the structure and dynamics of proteins. Deviations from statistical average values, known as random coil chemical shifts (RCCSs), are extensively used to infer these relationships. Unfortunately, the use of imprecise reference RCCSs leads to biased inference and obstructs the detection of subtle structural features. Here we present a new method, POTENCI, for the prediction of RCCSs that outperforms the currently most authoritative methods. POTENCI is parametrized using a large curated database of chemical shifts for protein segments with validated disorder; It takes pH and temperature explicitly into account, and includes sequence-dependent nearest and next-nearest neighbor corrections as well as second-order corrections. RCCS predictions with POTENCI show root-mean-square values that are lower by 25-78%, with the largest improvements observed for 1Hα and 13C'. It is demonstrated how POTENCI can be applied to analyze subtle deviations from RCCSs to detect small populations of residual structure in intrinsically disorder proteins that were not discernible before. POTENCI source code is available for download, or can be deployed from the URL http://www.protein-nmr.org .

In situ high-resolution structure of the baseplate antenna complex in Chlorobaculum tepidum.

Photosynthetic antenna systems enable organisms harvesting light and transfer the energy to the photosynthetic reaction centre, where the conversion to chemical energy takes place. One of the most complex antenna systems, the chlorosome, found in the photosynthetic green sulfur bacterium Chlorobaculum (Cba.) tepidum contains a baseplate, which is a scaffolding super-structure, formed by the protein CsmA and bacteriochlorophyll a. Here we present the first high-resolution structure of the CsmA baseplate using intact fully functional, light-harvesting organelles from Cba. tepidum, following a hybrid approach combining five complementary methods: solid-state NMR spectroscopy, cryo-electron microscopy, isotropic and anisotropic circular dichroism and linear dichroism. The structure calculation was facilitated through development of new software, GASyCS for efficient geometry optimization of highly symmetric oligomeric structures. We show that the baseplate is composed of rods of repeated dimers of the strongly amphipathic CsmA with pigments sandwiched within the dimer at the hydrophobic side of the helix.

Accurate measurements of ¹³C-¹³C distances in uniformly ¹³C-labeled proteins using multi-dimensional four-oscillating field solid-state NMR spectroscopy.

Application of sets of (13)C-(13)C internuclear distance restraints constitutes a typical key element in determining the structure of peptides and proteins by magic-angle-spinning solid-state NMR spectroscopy. Accurate measurements of the structurally highly important (13)C-(13)C distances in uniformly (13)C-labeled peptides and proteins, however, pose a big challenge due to the problem of dipolar truncation. Here, we present novel two-dimensional (2D) solid-state NMR experiments capable of extracting distances between carbonyl ((13)C') and aliphatic ((13)C(aliphatic)) spins with high accuracy. The method is based on an improved version of the four-oscillating field (FOLD) technique [L. A. Straasø, M. Bjerring, N. Khaneja, and N. C. Nielsen, J. Chem. Phys. 130, 225103 (2009)] which circumvents the problem of dipolar truncation, thereby offering a base for accurate extraction of internuclear distances in many-spin systems. The ability to extract reliable accurate distances is demonstrated using one- and two-dimensional variants of the FOLD experiment on uniformly (13)C,(15)N-labeled-L-isoleucine. In a more challenging biological application, FOLD 2D experiments are used to determine a large number of (13)C'-(13)C(aliphatic) distances in amyloid fibrils formed by the SNNFGAILSS fibrillating core of the human islet amyloid polypeptide with uniform (13)C,(15)N-labeling on the FGAIL fragment.

VirtualSpectrum, a tool for simulating peak list for multi-dimensional NMR spectra.

NMR spectroscopy is a widely used technique for characterizing the structure and dynamics of macromolecules. Often large amounts of NMR data are required to characterize the structure of proteins. To save valuable time and resources on data acquisition, simulated data is useful in the developmental phase, for data analysis, and for comparison with experimental data. However, existing tools for this purpose can be difficult to use, are sometimes specialized for certain types of molecules or spectra, or produce too idealized data. Here we present a fast, flexible and robust tool, VirtualSpectrum, for generating peak lists for most multi-dimensional NMR experiments for both liquid and solid state NMR. It is possible to tune the quality of the generated peak lists to include sources of artifacts from peak overlap, noise and missing signals. VirtualSpectrum uses an analytic expression to represent the spectrum and derive the peak positions, seamlessly handling overlap between signals. We demonstrate our tool by comparing simulated and experimental spectra for different multi-dimensional NMR spectra and analyzing systematically three cases where overlap between peaks is particularly relevant; solid state NMR data, liquid state NMR homonuclear (1)H and (15)N-edited spectra, and 2D/3D heteronuclear correlation spectra of unstructured proteins. We analyze the impact of protein size and secondary structure on peak overlap and on the accuracy of structure determination based on data of different qualities simulated by VirtualSpectrum.

Automated robust and accurate assignment of protein resonances for solid state NMR.

The process of resonance assignment represents a time-consuming and potentially error-prone bottleneck in structural studies of proteins by solid-state NMR (ssNMR). Software for the automation of this process is therefore of high interest. Procedures developed through the last decades for solution-state NMR are not directly applicable for ssNMR due to the inherently lower data quality caused by lower sensitivity and broader lines, leading to overlap between peaks. Recently, the first efforts towards procedures specifically aimed for ssNMR have been realized (Schmidt et al. in J Biomol NMR 56(3):243-254, 2013). Here we present a robust automatic method, which can accurately assign protein resonances using peak lists from a small set of simple 2D and 3D ssNMR experiments, applicable in cases with low sensitivity. The method is demonstrated on three uniformly (13)C, (15)N labeled biomolecules with different challenges on the assignments. In particular, for the immunoglobulin binding domain B1 of streptococcal protein G automatic assignment shows 100% accuracy for the backbone resonances and 91.8% when including all side chain carbons. It is demonstrated, by using a procedure for generating artificial spectra with increasing line widths, that our method, GAMES_ASSIGN can handle a significant amount of overlapping peaks in the assignment. The impact of including different ssNMR experiments is evaluated as well.

Mutation in transforming growth factor beta induced protein associated with granular corneal dystrophy type 1 reduces the proteolytic susceptibility through local structural stabilization.

Hereditary mutations in the transforming growth factor beta induced (TGFBI) gene cause phenotypically distinct corneal dystrophies characterized by protein deposition in cornea. We show here that the Arg555Trp mutant of the fourth fasciclin 1 (FAS1-4) domain of the protein (TGFBIp/keratoepithelin/ßig-h3), associated with granular corneal dystrophy type 1, is significantly less susceptible to proteolysis by thermolysin and trypsin than the WT domain. High-resolution liquid-state NMR of the WT and Arg555Trp mutant FAS1-4 domains revealed very similar structures except for the region around position 555. The Arg555Trp substitution causes Trp555 to be buried in an otherwise empty hydrophobic cavity of the FAS1-4 domain. The first thermolysin cleavage in the core of the FAS1-4 domain occurs on the N-terminal side of Leu558 adjacent to the Arg555 mutation. MD simulations indicated that the C-terminal end of helix α3' containing this cleavage site is less flexible in the mutant domain, explaining the observed proteolytic resistance. This structural change also alters the electrostatic properties, which may explain increased propensity of the mutant to aggregate in vitro with 2,2,2-trifluoroethanol. Based on our results we propose that the Arg555Trp mutation disrupts the normal degradation/turnover of corneal TGFBIp, leading to accumulation and increased propensity to aggregate through electrostatic interactions.

Symmetry-based dipolar recoupling by optimal control: band-selective experiments for assignment of solid-state NMR spectra of proteins.

We present design of novel low-power homonuclear dipolar recoupling experiments for magic-angle-spinning solid-state NMR studies of proteins. The pulse sequences are developed by combining principles of symmetry-based dipolar recoupling and optimal control-based pulse sequence design. The scaffold of the pulse sequences is formed by known CN-type recoupling sequences, while the intrinsic sequence elements are designed using optimal control. This procedure allows for the development of high-performance pulse sequences demanding significantly weaker rf fields than previous symmetry-based pulse sequences while compensating for rf inhomogeneity and providing excitation over relevant ranges of chemical shifts for biological applications. The new recoupling experiments, referred to as optimal control CN ((OC)CN), are demonstrated numerically and experimentally by two-dimensional (2D) (13)C-(13)C and three-dimensional (3D) (15)N-(13)C-(13)C chemical shift correlation experiments on uniformly (13)C, (15)N-labeled ubiquitin. Exploiting the double-quantum, band-selective dipolar recoupling properties of the (OC)CN experiments, we demonstrate significant sensitivity enhancement for 2D and 3D correlation spectra showing exclusively one- or two-bond correlations.