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An automated NMR chemical shift assignment algorithm was developed using multi-objective optimization techniques. The problem is modeled as a combinatorial optimization problem and its objective parameters are defined separately in different score functions. Some of the heuristic approaches of evolutionary optimization are employed in this problem model. Both, a conventional genetic algorithm and multi-objective methods, i.e., the non-dominated sorting genetic algorithms II and III (NSGA2 and NSGA3), are applied to the problem. The multi-objective approaches consider each objective parameter separately, whereas the genetic algorithm followed a conventional way, where all objectives are combined in one score function. Several improvement steps and repetitions on these algorithms are performed and their combinations are also created as a hyper-heuristic approach to the problem. Additionally, a hill-climbing algorithm is also applied after the evolutionary algorithm steps. The algorithms are tested on several different datasets with a set of 11 commonly used spectra. The test results showed that our algorithm could assign both sidechain and backbone atoms fully automatically without any manual interactions. Our approaches could provide around a 65% success rate and could assign some of the atoms that could not be assigned by other methods.
We compiled an NMR data set consisting of exact nuclear Overhauser enhancement (eNOE) distance limits, residual dipolar couplings (RDCs) and scalar (J) couplings for GB3, which forms one of the largest and most diverse data set for structural characterization of a protein to date. All data have small experimental errors, which are carefully estimated. We use the data in the research article Vogeli et al., 2015, Complementarity and congruence between exact NOEs and traditional NMR probes for spatial decoding of protein dynamics, J. Struct. Biol., 191, 3, 306–317, doi:10.1016/j.jsb.2015.07.008 [1] for cross-validation in multiple-state structural ensemble calculation. We advocate this set to be an ideal test case for molecular dynamics simulations and structure calculations.
Human Transformer2-beta (hTra2-beta) is an important member of the serine/arginine-rich protein family, and contains one RNA recognition motif (RRM). It controls the alternative splicing of several pre-mRNAs, including those of the calcitonin/calcitonin gene-related peptide (CGRP), the survival motor neuron 1 (SMN1) protein and the tau protein. Accordingly, the RRM of hTra2-beta specifically binds to two types of RNA sequences [the CAA and (GAA)2 sequences]. We determined the solution structure of the hTra2-beta RRM (spanning residues Asn110–Thr201), which not only has a canonical RRM fold, but also an unusual alignment of the aromatic amino acids on the beta-sheet surface. We then solved the complex structure of the hTra2-beta RRM with the (GAA)2 sequence, and found that the AGAA tetra-nucleotide was specifically recognized through hydrogen-bond formation with several amino acids on the N- and C-terminal extensions, as well as stacking interactions mediated by the unusually aligned aromatic rings on the beta-sheet surface. Further NMR experiments revealed that the hTra2-beta RRM recognizes the CAA sequence when it is integrated in the stem-loop structure. This study indicates that the hTra2-beta RRM recognizes two types of RNA sequences in different RNA binding modes.
The CUG-binding protein 1 (CUG-BP1) is a member of the CUG-BP1 and ETR-like factors (CELF) family or the Bruno-like family and is involved in the control of splicing, translation and mRNA degradation. Several target RNA sequences of CUG-BP1 have been predicted, such as the CUG triplet repeat, the GU-rich sequences and the AU-rich element of nuclear pre-mRNAs and/or cytoplasmic mRNA. CUG-BP1 has three RNA-recognition motifs (RRMs), among which the third RRM (RRM3) can bind to the target RNAs on its own. In this study, we solved the solution structure of the CUG-BP1 RRM3 by hetero-nuclear NMR spectroscopy. The CUG-BP1 RRM3 exhibited a noncanonical RRM fold, with the four-stranded b-sheet surface tightly associated with the N-terminal extension. Furthermore, we determined the solution structure of the CUG-BP1 RRM3 in the complex with (UG)3 RNA, and discovered that the UGU trinucleotide is specifically recognized through extensive stacking interactions and hydrogen bonds within the pocket formed by the b-sheet surface and the N-terminal extension. This study revealed the unique mechanism that enables the CUG-BP1 RRM3 to discriminate the short RNA segment from other sequences, thus providing the molecular basis for the comprehension of the role of the RRM3s in the CELF/Bruno-like family.
1H-detected solid-state NMR experiments feasible at fast magic-angle spinning (MAS) frequencies allow accessing 1H chemical shifts of proteins in solids, which enables their interpretation in terms of secondary structure. Here we present 1H and 13C-detected NMR spectra of the RNA polymerase subunit Rpo7 in complex with unlabeled Rpo4 and use the 13C, 15N, and 1H chemical-shift values deduced from them to study the secondary structure of the protein in comparison to a known crystal structure. We applied the automated resonance assignment approach FLYA including 1H-detected solid-state NMR spectra and show its success in comparison to manual spectral assignment. Our results show that reasonably reliable secondary-structure information can be obtained from 1H secondary chemical shifts (SCS) alone by using the sum of 1Hα and 1HN SCS rather than by TALOS. The confidence, especially at the boundaries of the observed secondary structure elements, is found to increase when evaluating 13C chemical shifts, here either by using TALOS or in terms of 13C SCS.
Background: Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments.
Results: To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments.
Conclusions: Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.
Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.
A key function of reversible protein phosphorylation is to regulate protein–protein interactions, many of which involve short linear motifs (3–12 amino acids). Motif‐based interactions are difficult to capture because of their often low‐to‐moderate affinities. Here, we describe phosphomimetic proteomic peptide‐phage display, a powerful method for simultaneously finding motif‐based interaction and pinpointing phosphorylation switches. We computationally designed an oligonucleotide library encoding human C‐terminal peptides containing known or predicted Ser/Thr phosphosites and phosphomimetic variants thereof. We incorporated these oligonucleotides into a phage library and screened the PDZ (PSD‐95/Dlg/ZO‐1) domains of Scribble and DLG1 for interactions potentially enabled or disabled by ligand phosphorylation. We identified known and novel binders and characterized selected interactions through microscale thermophoresis, isothermal titration calorimetry, and NMR. We uncover site‐specific phospho‐regulation of PDZ domain interactions, provide a structural framework for how PDZ domains accomplish phosphopeptide binding, and discuss ligand phosphorylation as a switching mechanism of PDZ domain interactions. The approach is readily scalable and can be used to explore the potential phospho‐regulation of motif‐based interactions on a large scale.
Protein aggregation of the p63 transcription factor underlies severe skin fragility in AEC syndrome
(2018)
The p63 gene encodes a master regulator of epidermal commitment, development, and differentiation. Heterozygous mutations in the C-terminal domain of the p63 gene can cause ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome, a life-threatening disorder characterized by skin fragility and severe, long-lasting skin erosions. Despite deep knowledge of p63 functions, little is known about mechanisms underlying disease pathology and possible treatments. Here, we show that multiple AEC-associated p63 mutations, but not those causative of other diseases, lead to thermodynamic protein destabilization, misfolding, and aggregation, similar to the known p53 gain-of-function mutants found in cancer. AEC mutant proteins exhibit impaired DNA binding and transcriptional activity, leading to dominant negative effects due to coaggregation with wild-type p63 and p73. Importantly, p63 aggregation occurs also in a conditional knock-in mouse model for the disorder, in which the misfolded p63 mutant protein leads to severe epidermal defects. Variants of p63 that abolish aggregation of the mutant proteins are able to rescue p63’s transcriptional function in reporter assays as well as in a human fibroblast-to-keratinocyte conversion assay. Our studies reveal that AEC syndrome is a protein aggregation disorder and opens avenues for therapeutic intervention.
Structural and functional dissection of the DH and PH domains of oncogenic Bcr-Abl tyrosine kinase
(2017)
The two isoforms of the Bcr-Abl tyrosine kinase, p210 and p190, are associated with different leukemias and have a dramatically different signaling network, despite similar kinase activity. To provide a molecular rationale for these observations, we study the Dbl-homology (DH) and Pleckstrin-homology (PH) domains of Bcr-Abl p210, which constitute the only structural differences to p190. Here we report high-resolution structures of the DH and PH domains and characterize conformations of the DH–PH unit in solution. Our structural and functional analyses show no evidence that the DH domain acts as a guanine nucleotide exchange factor, whereas the PH domain binds to various phosphatidylinositol-phosphates. PH-domain mutants alter subcellular localization and result in decreased interactions with p210-selective interaction partners. Hence, the PH domain, but not the DH domain, plays an important role in the formation of the differential p210 and p190 Bcr-Abl signaling networks.