How T118M peripheral myelin protein 22 predisposes humans to Charcot-Marie-Tooth disease.

Data from gnomAD indicate that a missense mutation encoding the T118M variation in human peripheral myelin protein 22 (PMP22) is found in roughly one of every 75 genomes of western European lineage (1:120 in the overall human population). It is unusual among PMP22 variants that cause Charcot-Marie-Tooth (CMT) disease in that it is not 100% penetrant. Here, we conducted cellular and biophysical studies to determine why T118M PMP22 predisposes humans to CMT, but with only incomplete penetrance. We found that T118M PMP22 is prone to mistraffic but differs even from the WT protein in that increased expression levels do not result in a reduction in trafficking efficiency. Moreover, the T118M mutant exhibits a reduced tendency to form large intracellular aggregates relative to other disease mutants and even WT PMP22. NMR spectroscopy revealed that the structure and dynamics of T118M PMP22 resembled those of WT. These results show that the main consequence of T118M PMP22 in WT/T118M heterozygous individuals is a reduction in surface-trafficked PMP22, unaccompanied by formation of toxic intracellular aggregates. This explains the incomplete disease penetrance and the mild neuropathy observed for WT/T118M CMT cases. We also analyzed BioVU, a biobank linked to deidentified electronic medical records, and found a statistically robust association of the T118M mutation with the occurrence of long and/or repeated episodes of carpal tunnel syndrome. Collectively, our results illuminate the cellular effects of the T118M PMP22 variation leading to CMT disease and indicate a second disorder for which it is a risk factor.

Ion mobility-mass spectrometry reveals the role of peripheral myelin protein dimers in peripheral neuropathy.

Peripheral myelin protein (PMP22) is an integral membrane protein that traffics inefficiently even in wild-type (WT) form, with only 20% of the WT protein reaching its final plasma membrane destination in myelinating Schwann cells. Misfolding of PMP22 has been identified as a key factor in multiple peripheral neuropathies, including Charcot-Marie-Tooth disease and Dejerine-Sottas syndrome. While biophysical analyses of disease-associated PMP22 mutants show altered protein stabilities, leading to reduced surface trafficking and loss of PMP22 function, it remains unclear how destabilization of PMP22 mutations causes mistrafficking. Here, native ion mobility-mass spectrometry (IM-MS) is used to compare the gas phase stabilities and abundances for an array of mutant PM22 complexes. We find key differences in the PMP22 mutant stabilities and propensities to form homodimeric complexes. Of particular note, we observe that severely destabilized forms of PMP22 exhibit a higher propensity to dimerize than WT PMP22. Furthermore, we employ lipid raft-mimicking SCOR bicelles to study PMP22 mutants, and find that the differences in dimer abundances are amplified in this medium when compared to micelle-based data, with disease mutants exhibiting up to 4 times more dimer than WT when liberated from SCOR bicelles. We combine our findings with previous cellular data to propose that the formation of PMP22 dimers from destabilized monomers is a key element of PMP22 mistrafficking.

Dodecyl-ß-melibioside Detergent Micelles as a Medium for Membrane Proteins.

There remains a need for new non-ionic detergents that are suitable for use in biochemical and biophysical studies of membrane proteins. Here we explore the properties of n-dodecyl-ß-melibioside (ß-DDMB) micelles as a medium for membrane proteins. Melibiose is d-galactose-α(1→6)-d-glucose. Light scattering showed the ß-DDMB micelle to be roughly 30 kDa smaller than micelles formed by the commonly used n-dodecyl-ß-maltoside (ß-DDM). ß-DDMB stabilized diacylglycerol kinase (DAGK) against thermal inactivation. Moreover, activity assays conducted using aliquots of DAGK purified into ß-DDMB yielded activities that were 40% higher than those of DAGK purified into ß-DDM. ß-DDMB yielded similar or better TROSY-HSQC NMR spectra for two single-pass membrane proteins and the tetraspan membrane protein peripheral myelin protein 22. ß-DDMB appears be a useful addition to the toolbox of non-ionic detergents available for membrane protein research.

Mapping the Hydrogen Bond Networks in the Catalytic Subunit of Protein Kinase A Using H/D Fractionation Factors.

Protein kinase A is a prototypical phosphoryl transferase, sharing its catalytic core (PKA-C) with the entire kinase family. PKA-C substrate recognition, active site organization, and product release depend on the enzyme's conformational transitions from the open to the closed state, which regulate its allosteric cooperativity. Here, we used equilibrium nuclear magnetic resonance hydrogen/deuterium (H/D) fractionation factors (φ) to probe the changes in the strength of hydrogen bonds within the kinase upon binding the nucleotide and a pseudosubstrate peptide (PKI5-24). We found that the φ values decrease upon binding both ligands, suggesting that the overall hydrogen bond networks in both the small and large lobes of PKA-C become stronger. However, we observed several important exceptions, with residues displaying higher φ values upon ligand binding. Notably, the changes in φ values are not localized near the ligand binding pockets; rather, they are radiated throughout the entire enzyme. We conclude that, upon ligand and pseudosubstrate binding, the hydrogen bond networks undergo extensive reorganization, revealing that the open-to-closed transitions require global rearrangements of the internal forces that stabilize the enzyme's fold.

Optimizing NMR fragment-based drug screening for membrane protein targets.

NMR spectroscopy has played a pivotal role in fragment-based drug discovery by coupling detection of weak ligand-target binding with structural mapping of the binding site. Fragment-based screening by NMR has been successfully applied to many soluble protein targets, but only to a limited number of membrane proteins, despite the fact that many drug targets are membrane proteins. This is partly because of difficulties preparing membrane proteins for NMR-especially human membrane proteins-and because of the inherent complexity associated with solution NMR spectroscopy on membrane protein samples, which require the inclusion of membrane-mimetic agents such as micelles, nanodiscs, or bicelles. Here, we developed a generalizable protocol for fragment-based screening of membrane proteins using NMR. We employed two human membrane protein targets, both in fully protonated detergent micelles: the single-pass C-terminal domain of the amyloid precursor protein, C99, and the tetraspan peripheral myelin protein 22 (PMP22). For both we determined the optimal NMR acquisition parameters, protein concentration, protein-to-micelle ratio, and upper limit to the concentration of D6-DMSO in screening samples. Furthermore, we conducted preliminary screens of a plate-format molecular fragment mixture library using our optimized conditions and were able to identify hit compounds that selectively bound to the respective target proteins. It is hoped that the approaches presented here will be useful in complementing existing methods for discovering lead compounds that target membrane proteins.

Brain-Inspired Image Perceptual Quality Assessment based on EEG: A QoE Perspective.

Human-oriented image communication should take the quality of experience (QoE) as an optimization goal, which requires effective image perceptual quality metrics. However, traditional user-based assessment metrics are limited by the deviation caused by human high-level cognitive activities. To tackle this issue, in this paper, we construct a brain response-based image perceptual quality metric and develop a brain-inspired network to assess the image perceptual quality based on it. Our method aims to establish the relationship between image quality changes and underlying brain responses in image compression scenarios using the electroencephalography (EEG) approach. We first establish EEG datasets by collecting the corresponding EEG signals when subjects watch distorted images. Then, we design a measurement model to extract EEG features that reflect human perception to establish a new image perceptual quality metric: EEG perceptual score (EPS). To use this metric in practical scenarios, we embed the brain perception process into a prediction model to generate the EPS directly from the input images. Experimental results show that our proposed measurement model and prediction model can achieve better performance. The proposed brain response-based image perceptual quality metric can measure the human brain's perceptual state more accurately, thus performing a better assessment of image perceptual quality.

Federated Learning Via Inexact ADMM.

One of the crucial issues in federated learning is how to develop efficient optimization algorithms. Most of the current ones require full device participation and/or impose strong assumptions for convergence. Different from the widely-used gradient descent-based algorithms, in this article, we develop an inexact alternating direction method of multipliers (ADMM), which is both computation- and communication-efficient, capable of combating the stragglers' effect, and convergent under mild conditions. Furthermore, it has high numerical performance compared with several state-of-the-art algorithms for federated learning.

ATP-competitive inhibitors modulate the substrate binding cooperativity of a kinase by altering its conformational entropy.

ATP-competitive inhibitors are currently the largest class of clinically approved drugs for protein kinases. By targeting the ATP-binding pocket, these compounds block the catalytic activity, preventing substrate phosphorylation. A problem with these drugs, however, is that inhibited kinases may still recognize and bind downstream substrates, acting as scaffolds or binding hubs for signaling partners. Here, using protein kinase A as a model system, we show that chemically different ATP-competitive inhibitors modulate the substrate binding cooperativity by tuning the conformational entropy of the kinase and shifting the populations of its conformationally excited states. Since we found that binding cooperativity and conformational entropy of the enzyme are correlated, we propose a new paradigm for the discovery of ATP-competitive inhibitors, which is based on their ability to modulate the allosteric coupling between nucleotide and substrate-binding sites.

Genetic intolerance analysis as a tool for protein science.

Recent advances in whole genome and exome sequencing have dramatically increased the database of human gene variations. There are now enough sequenced human exomes and genomes to begin to identify gene variations that are notable because they are NOT observed in sequenced human genomes, apparently because they are subject to "purifying selection", exemplifying genetic intolerance. Such "dysprocreative" gene variations are embryonic lethal or prevent reproduction through any one of a number of possible mechanisms. Here we review an emerging quantitative approach, "Missense Tolerance Ratio" (MTR) analysis, that is used to assess protein-encoding gene (cDNA) sequence intolerance to missense mutations based on analysis of the >100 K and growing number of currently available human genome and exome sequences. This approach is already useful for analyzing intolerance to mutations in cDNA segments with a resolution on the order of 90 bases. Moreover, as the number of sequenced genomes/exomes increases by orders of magnitude it may eventually be possible to assess mutational tolerance in a statistically robust manner at or near single site resolution. Here we focus on how cDNA intolerance analysis complements other bioinformatic methods to illuminate structure-folding-function relationships for the encoded proteins. A set of disease-linked membrane proteins is employed to provide examples.

Multi-state recognition pathway of the intrinsically disordered protein kinase inhibitor by protein kinase A.

In the nucleus, the spatiotemporal regulation of the catalytic subunit of cAMP-dependent protein kinase A (PKA-C) is orchestrated by an intrinsically disordered protein kinase inhibitor, PKI, which recruits the CRM1/RanGTP nuclear exporting complex. How the PKA-C/PKI complex assembles and recognizes CRM1/RanGTP is not well understood. Using NMR, SAXS, fluorescence, metadynamics, and Markov model analysis, we determined the multi-state recognition pathway for PKI. After a fast binding step in which PKA-C selects PKI's most competent conformations, PKI folds upon binding through a slow conformational rearrangement within the enzyme's binding pocket. The high-affinity and pseudo-substrate regions of PKI become more structured and the transient interactions with the kinase augment the helical content of the nuclear export sequence, which is then poised to recruit the CRM1/RanGTP complex for nuclear translocation. The multistate binding mechanism featured by PKA-C/PKI complex represents a paradigm on how disordered, ancillary proteins (or protein domains) are able to operate multiple functions such as inhibiting the kinase while recruiting other regulatory proteins for nuclear export.

Globally correlated conformational entropy underlies positive and negative cooperativity in a kinase's enzymatic cycle.

Enzymes accelerate the rate of chemical transformations by reducing the activation barriers of uncatalyzed reactions. For signaling enzymes, substrate recognition, binding, and product release are often rate-determining steps in which enthalpy-entropy compensation plays a crucial role. While the nature of enthalpic interactions can be inferred from structural data, the molecular origin and role of entropy in enzyme catalysis remains poorly understood. Using thermocalorimetry, NMR, and MD simulations, we studied the conformational landscape of the catalytic subunit of cAMP-dependent protein kinase A, a ubiquitous phosphoryl transferase involved in a myriad of cellular processes. Along the enzymatic cycle, the kinase exhibits positive and negative cooperativity for substrate and nucleotide binding and product release. We found that globally coordinated changes of conformational entropy activated by ligand binding, together with synchronous and asynchronous breathing motions of the enzyme, underlie allosteric cooperativity along the kinase's cycle.

Conformational Landscape of the PRKACA-DNAJB1 Chimeric Kinase, the Driver for Fibrolamellar Hepatocellular Carcinoma.

In fibrolamellar hepatocellular carcinoma a single genetic deletion results in the fusion of the first exon of the heat shock protein 40, DNAJB1, which encodes the J domain, with exons 2-10 of the catalytic subunit of protein kinase A, PRKACA. This produces an enzymatically active chimeric protein J-PKAcα. We used molecular dynamics simulations and NMR to analyze the conformational landscape of native and chimeric kinase, and found an ensemble of conformations. These ranged from having the J-domain tucked under the large lobe of the kinase, similar to what was reported in the crystal structure, to others where the J-domain was dislodged from the core of the kinase and swinging free in solution. These simulated dislodged states were experimentally captured by NMR. Modeling of the different conformations revealed no obvious steric interactions of the J-domain with the rest of the RIIß holoenzyme.

Tunable Liaisons: eEF-2K, CaM, and Calcium.

In this issue of Structure, Lee et al. (2016) perform NMR analysis of calmodulin (CaM) binding to the eukaryotic elongation factor 2 kinase (eEF-2K). They find that eEF-2K interacts mainly with the C lobe of CaM in a Ca(2+)-tunable manner, revealing a high level of control in cellular homeostasis.

A Semiautomated Assignment Protocol for Methyl Group Side Chains in Large Proteins.

The developments of biosynthetic specific labeling strategies for side-chain methyl groups have allowed structural and dynamic characterization of very large proteins and protein complexes. However, the assignment of the methyl-group resonances remains an Achilles' heel for NMR, as the experiments designed to correlate side chains to the protein backbone become rather insensitive with the increase of the transverse relaxation rates. In this chapter, we outline a semiempirical approach to assign the resonances of methyl-group side chains in large proteins. This method requires a crystal structure or an NMR ensemble of conformers as an input, together with NMR data sets such as nuclear Overhauser effects (NOEs) and paramagnetic relaxation enhancements (PREs), to be implemented in a computational protocol that provides a probabilistic assignment of methyl-group resonances. As an example, we report the protocol used in our laboratory to assign the side chains of the 42-kDa catalytic subunit of the cAMP-dependent protein kinase A. Although we emphasize the labeling of isoleucine, leucine, and valine residues, this method is applicable to other methyl group side chains such as those of alanine, methionine, and threonine, as well as reductively methylated cysteine side chains.

Uncoupling Catalytic and Binding Functions in the Cyclic AMP-Dependent Protein Kinase A.

The canonical function of kinases is to transfer a phosphoryl group to substrates, initiating a signaling cascade; while their non-canonical role is to bind other kinases or substrates, acting as scaffolds, competitors, and signal integrators. Here, we show how to uncouple kinases' dual function by tuning the binding cooperativity between nucleotide (or inhibitors) and substrate allosterically. We demonstrate this new concept for the C subunit of protein kinase A (PKA-C). Using thermocalorimetry and nuclear magnetic resonance, we found a linear correlation between the degree of cooperativity and the population of the closed state of PKA-C. The non-hydrolyzable ATP analog (ATPγC) does not follow this correlation, suggesting that changing the chemical groups around the phosphoester bond can uncouple kinases' dual function. Remarkably, this uncoupling was also found for two ATP-competitive inhibitors, H89 and balanol. Since the mechanism for allosteric cooperativity is not conserved in different kinases, these results may suggest new approaches for designing selective kinase inhibitors.