Shared Structural Features Research Articles

Shared structural features of Miro binding control mitochondrial homeostasis

Miro proteins are universally conserved mitochondrial calcium-binding GTPases that regulate a multitude of mitochondrial processes, including transport, clearance, and lipid trafficking. The exact role of Miro in these functions is unclear but involves binding to a variety of client proteins. How this binding is operated at the molecular level and whether and how it is important for mitochondrial health, however, remains unknown. Here, we show that known Miro interactors—namely, CENPF, Trak, and MYO19—all use a similar short motif to bind the same structural element: a highly conserved hydrophobic pocket in the first calcium-binding domain of Miro. Using these Miro-binding motifs, we identified direct interactors de novo, including MTFR1/2/1L, the lipid transporters Mdm34 and VPS13D, and the ubiquitin E3-ligase Parkin. Given the shared binding mechanism of these functionally diverse clients and its conservation across eukaryotes, we propose that Miro is a universal mitochondrial adaptor coordinating mitochondrial health.

Decoding the relationship between cow's milk proteins and development of type 1 diabetes mellitus.

To analyze in silico the evidence of molecular mimicry between human beta-cell autoantigens and cow's milk proteins as a potential type 1 diabetes mellitus (T1DM) trigger. The in silico analysis was performed using bioinformatics tools to compare the amino acid sequences of cow's milk proteins (bovine serum albumin [BSA] and beta-lactoglobulin [BLG]) and human beta-cell autoantigens (glutamic acid decarboxylase-65 [GAD-65], insulin, and zinc transporter 8 [ZnT8]). The structural and functional characteristics of the proteins were analyzed to identify potential molecular mimicry mechanisms. The results of the in silico analysis showed significant sequence similarity between BSA/BLG and GAD-65/human insulin/ZnT8, ranging from 19.64% to 27.27%. The cow's milk proteins evaluated shared structural features with the beta-cell antigens selected for comparison, indicating a potential for molecular mimicry between these proteins. The findings of this study provide further evidence for a potential role of cow's milk proteins in triggering T1DM. The in silico analysis suggests that molecular mimicry mechanisms between cow's milk proteins and human beta-cell antigens may contribute to the autoimmune response leading to T1DM.

LORA, Lipid Over-Representation Analysis Based on Structural Information.

With the increasing number of lipidomic studies, there is a need for an efficient and automated analysis of lipidomic data. One of the challenges faced by most existing approaches to lipidomic data analysis is lipid nomenclature. The systematic nomenclature of lipids contains all available information about the molecule, including its hierarchical representation, which can be used for statistical evaluation. The Lipid Over-Representation Analysis (LORA) web application (https://lora.metabolomics.fgu.cas.cz) analyzes this information using the Java-based Goslin framework, which translates lipid names into a standardized nomenclature. Goslin provides the level of lipid hierarchy, including information on headgroups, acyl chains, and their modifications, up to the "complete structure" level. LORA allows the user to upload the experimental query and reference data sets, select a grammar for lipid name normalization, and then process the data. The user can then interactively explore the results and perform lipid over-representation analysis based on selected criteria. The results are graphically visualized according to the lipidome hierarchy. The lipids present in the most over-represented terms (lipids with the highest number of enriched shared structural features) are defined as Very Important Lipids (VILs). For example, the main result of a demo data set is the information that the query is significantly enriched with "glycerophospholipids" containing "acyl 20:4" at the "sn-2 position". These terms define a set of VILs (e.g., PC 18:2/20:4;O and PE 16:0/20:4(5,8,10,14);OH). All results, graphs, and visualizations are summarized in a report. LORA is a tool focused on the smart mining of epilipidomics data sets to facilitate their interpretation at the molecular level.

Snapshots of ABCG1 and ABCG5/G8: A Sterol's Journey to Cross the Cellular Membranes.

The subfamily-G ATP-binding cassette (ABCG) transporters play important roles in regulating cholesterol homeostasis. Recent progress in the structural data of ABCG1 and ABCG5/G8 disclose putative sterol binding sites that suggest the possible cholesterol translocation pathway. ABCG1 and ABCG5/G8 share high similarity in the overall molecular architecture, and both transporters appear to use several unique structural motifs to facilitate cholesterol transport along this pathway, including the phenylalanine highway and the hydrophobic valve. Interestingly, ABCG5/G8 is known to transport cholesterol and phytosterols, whereas ABCG1 seems to exclusively transport cholesterol. Ligand docking analysis indeed suggests a difference in recruiting sterol molecules to the known sterol-binding sites. Here, we further discuss how the different and shared structural features are relevant to their physiological functions, and finally provide our perspective on future studies in ABCG cholesterol transporters.

Crystal structure of an inorganic pyrophosphatase from Chlamydia trachomatis D/UW-3/Cx.

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted infections globally and is one of the most commonly reported infections in the United States. There is a need to develop new therapeutics due to drug resistance and the failure of current treatments to clear persistent infections. Structures of potential C. trachomatis rational drug-discovery targets, including C. trachomatis inorganic pyrophosphatase (CtPPase), have been determined bythe Seattle Structural Genomics Center for Infectious Disease. Inorganic pyrophosphatase hydrolyzes inorganic pyrophosphate during metabolism. Furthermore, bacterial inorganic pyrophosphatases have shown promise for therapeutic discovery. Here, a 2.2 Å resolution X-ray structure of CtPPase is reported. The crystal structure of CtPPase reveals shared structural features that may facilitate the repurposing of inhibitors identified for bacterial inorganic pyrophosphatases as starting points for new therapeutics for C. trachomatis.

Phenolic sucrose esters: evolution, regulation, biosynthesis, and biological functions.

Phenolic sucrose esters (PSEs) are a diverse group of specialized metabolites that are present in several angiosperm lineages. Phylogenetic reconstruction and structural variation suggest that these metabolites may have evolved independently in monocots and dicots. Constitutive variation in PSE abundance across plant organs and developmental stages is correlated with transcriptional regulation of the upstream phenylpropanoid pathway, whereas pathogen induction is regulated by stress-related phytohormones such as ethylene. Shared structural features of PSEs indicate that their biosynthesis may involve one or more hydroxycinnamoyl transferases and BAHD acetyltransferases, which could be identified by correlative analyses of multi-omics datasets. Elucidation of the core biosynthetic pathway of PSEs will be essential for more detailed studies of the biological function of these compounds and their potential medicinal and agricultural applications.

Sulfur-mobilizing Enzymes Involved in Iron-sulfur Cluster Biosynthesis: Shared Structural Features and Functional Diversity

Sulfur-mobilizing Enzymes Involved in Iron-sulfur Cluster Biosynthesis: Shared Structural Features and Functional Diversity

3-D Inspection Method for Industrial Product Assembly Based on Single X-Ray Projections

Industrial product assembly inspection is an indispensable part of industrial production, directly affecting product performance and reliability. Due to the capsulation of many products, most of the current inspection methods are based on X-ray technologies, such as digital radiography (DR) and computed tomography (CT). The inspection methods based on DR are fast but cannot obtain the spatial distributions or interrelationships of the assembled components and are easily affected by the occlusion of internal components. The detection methods based on CT can reconstruct the 3-D volume of a product and have high detection accuracy but cannot achieve real-time inspection because of the reconstruction speed. To address the above problems, we propose an inspection method based on a single-projection reconstruction network for industrial product assembly. An improved autoencoder network is trained to learn the shared structural features in 3-D volumes from 2-D projections, realizing the reconstruction of the 3-D volume at a specific viewing angle from a single projection from any viewing angle. The 3-D volumes output by the network are used to detect the position and posture of the components in the product to judge whether the product has been assembled correctly. The feasibility of the proposed method is verified with the data of a certain fuse under different assembly conditions. The experimental results show that the proposed method can improve the inspection efficiency, reduce the inspection costs, and simplify the imaging system.

Utility of Ion-Mobility Spectrometry for Deducing Branching of Multiply Charged Glycans and Glycopeptides in a High-Throughput Positive ion LC-FLR-IMS-MS Workflow

High-throughput glycan analysis has become an important part of biopharmaceutical production and quality control. However, it is still a significant challenge in the field of glycomics to easily deduce isomeric glycan structures, especially in a high-throughput manner. Ion mobility spectrometry (IMS) is an excellent tool for differentiating isomeric glycan structures. However, demonstrations of the utility of IMS in high-throughput workflows such as liquid chromatography-fluorescence-mass spectrometry (LC-FLR-MS) workflows have been limited with only a small amount of collision cross section (CCS) data available. In particular, IMS data of glycan fragments obtained in positive ion mode are limited in comparison to those obtained in negative ion mode despite positive ion mode being widely used for glycomics. Here, we describe IMS TWCCSN2 data obtained from a high-throughput LC-FLR-IMS-MS workflow in positive ion mode. We obtained IMS data from a selection of RapiFluor-MS (RFMS) labeled N-glycans and also glycopeptides. We describe how IMS is able to distinguish isomeric N-glycans and glycopeptides using both intact IMS and fragment-based IMS glycan sequencing experiments in positive ion mode, without significantly altering the high-throughput nature of the analysis. For the first time, we were able to successfully use IMS in positive ion mode to determine the branching of isomeric glycopeptides and RFMS labeled glycans. Further, we highlight that IMS glycan sequencing of fragments obtained from RFMS labeled glycans was similar to that of glycopeptides. Finally, we show that the IMS glycan sequencing approach can highlight shared structural features of nonisomeric glycans in a high-throughput LC-FLR-IMS-MS workflow.

Picky ABCG5/G8 and promiscuous ABCG2 - a tale of fatty diets and drug toxicity.

Structural data on ABCG5/G8 and ABCG2 reveal a unique molecular architecture for subfamily G ATP‐binding cassette (ABCG) transporters and disclose putative substrate‐binding sites. ABCG5/G8 and ABCG2 appear to use several unique structural motifs to execute transport, including the triple helical bundles, the membrane‐embedded polar relay, the re‐entry helices, and a hydrophobic valve. Interestingly, ABCG2 shows extreme substrate promiscuity, whereas ABCG5/G8 transports only sterol molecules. ABCG2 structures suggest a large internal cavity, serving as a binding region for substrates and inhibitors, while mutational and pharmacological analyses support the notion of multiple binding sites. By contrast, ABCG5/G8 shows a collapsed cavity of insufficient size to hold substrates. Indeed, mutational analyses indicate a sterol‐binding site at the hydrophobic interface between the transporter and the lipid bilayer. In this review, we highlight key differences and similarities between ABCG2 and ABCG5/G8 structures. We further discuss the relevance of distinct and shared structural features in the context of their physiological functions. Finally, we elaborate on how ABCG2 and ABCG5/G8 could pave the way for studies on other ABCG transporters.

HER family in cancer progression: From discovery to 2020 and beyond.

The human epidermal growth factor receptor (HER) family of receptor tyrosine kinases (RTKs) are among the first layer of molecules that receive, interpret, and transduce signals leading to distinct cancer cell phenotypes. Since the discovery of the tooth-lid factor-later characterized as the epidermal growth factor (EGF)-and its high-affinity binding EGF receptor, HER kinases have emerged as one of the commonly upregulated or hyperactivated or mutated kinases in epithelial tumors, thus allowing HER1-3 family members to regulate several hallmarks of cancer development and progression. Each member of the HER family exhibits shared and unique structural features to engage multiple receptor activation modes, leading to a range of overlapping and distinct phenotypes. EGFR, the founding HER family member, provided the roadmap for the development of the cell surface RTK-directed targeted cancer therapy by serving as a prototype/precursor for the currently used HER-directed cancer drugs. We herein provide a brief account of the discoveries, defining moments, and historical context of the HER family and guidepost advances in basic, translational, and clinical research that solidified a prominent position of the HER family in cancer research and treatment. We also discuss the significance of HER3 pseudokinase in cancer biology; its unique structural features that drive transregulation among HER1-3, leading to a superior proximal signaling response; and potential role of HER3 as a shared effector of acquired therapeutic resistance against diverse oncology drugs. Finally, we also narrate some of the current drawbacks of HER-directed therapies and provide insights into postulated advances in HER biology with extensive implications of these therapies in cancer research and treatment.

Indomethacin Enhances Type 1 Cannabinoid Receptor Signaling.

In addition to its known actions as a non-selective cyclooxygenase (COX) 1 and 2 inhibitor, we hypothesized that indomethacin can act as an allosteric modulator of the type 1 cannabinoid receptor (CB1R) because of its shared structural features with the known allosteric modulators of CB1R. Indomethacin enhanced the binding of [3H]CP55940 to hCB1R and enhanced AEA-dependent [35S]GTPγS binding to hCB1R in Chinese hamster ovary (CHO) cell membranes. Indomethacin (1 μM) also enhanced CP55940-dependent βarrestin1 recruitment, cAMP inhibition, ERK1/2 and PLCβ3 phosphorylation in HEK293A cells expressing hCB1R, but not in cells expressing hCB2R. Finally, indomethacin enhanced the magnitude and duration of CP55940-induced hypolocomotion, immobility, hypothermia, and anti-nociception in C57BL/6J mice. Together, these data support the hypothesis that indomethacin acted as a positive allosteric modulator of hCB1R. The identification of structural and functional features shared amongst allosteric modulators of CB1R may lead to the development of novel compounds designed for greater CB1R or COX selectivity and compounds designed to modulate both the prostaglandin and endocannabinoid systems.

Linking the Sequence, Anti-Tumor Function, and Shared Structural Features of Class Ib Hydrophobins

Hydrophobins are low molecular weight (5-20 kDa) self-assembling proteins secreted by fungi that accumulate at hydrophobic-hydrophilic interfaces and are extremely surface-active. Hydrophobins may undergo structural rearrangement and oligomerize to form rodlets, which are an insoluble functional amyloid that coats fungal spores to act as a water repellent, facilitate dispersal into the air, and prevent immune recognition. Due to their biochemical properties hydrophobins are a target a wide range of potential commercial applications. Hydrohphobins might also find use as a cancer treatment as they have also been shown to have anti-tumor properties, although the precise mechanism of this action is unclear. To better understand which sequence characteristics determine hydrophobin properties, we are characterizing the structure and properties of class IB hydrophobins from various fungal sources. Target proteins from Serpula lacrymans (SL1), Wallemia ichthyophaga (WI1), and Phanerochaete carnosa (PC1) were chosen for study due to their different sequence composition. We expressed uniformly 13C/15N-labeled protein in E. coli and then purified it to homogeneity using Ni2+ affinity and RP-HPLC and determined the high-resolution structure using NMR spectroscopy. We discovered that each hydrophobin contains shared structural features despite their dissimilar sequence compositions. The core feature is a four strand anti-parallel β-sheet that is connected by three loop sequences (L1-L3). In all hydrophobins the β-sheet folds to form a β-barrel-like structure, however the first loop is disordered in WI1 while it is an a-helix in SL1 and PC1. Spectroscopic amyloid formation assays indicate that these hydrophobins have differing propensities to form rodlets and are using AFM to characterize rodlet morphology. We are also examining which sequence and structure characteristics of hydrophobins influence their anti-tumour activity. Overall, this work will provide a fundamental correlation between the structure, function, and anti-tumour properties of hydrophobins.

TCRmodel: high resolution modeling of T cell receptors from sequence.

T cell receptors (TCRs), along with antibodies, are responsible for specific antigen recognition in the adaptive immune response, and millions of unique TCRs are estimated to be present in each individual. Understanding the structural basis of TCR targeting has implications in vaccine design, autoimmunity, as well as T cell therapies for cancer. Given advances in deep sequencing leading to immune repertoire-level TCR sequence data, fast and accurate modeling methods are needed to elucidate shared and unique 3D structural features of these molecules which lead to their antigen targeting and cross-reactivity. We developed a new algorithm in the program Rosetta to model TCRs from sequence, and implemented this functionality in a web server, TCRmodel. This web server provides an easy to use interface, and models are generated quickly that users can investigate in the browser and download. Benchmarking of this method using a set of nonredundant recently released TCR crystal structures shows that models are accurate and compare favorably to models from another available modeling method. This server enables the community to obtain insights into TCRs of interest, and can be combined with methods to model and design TCR recognition of antigens. The TCRmodel server is available at: http://tcrmodel.ibbr.umd.edu/.

Shared structural features of the 9aaTAD family in complex with CBP.

A number of transactivation domains for transcription factors including p53, E2A/HEB, MLL, cMyb, CREB, FOXO3, Gcn4, Oaf1 and Pdr1 have been reported to interact with the KIX domain of general transcriptional mediators CBP, p300 or MED15. Most of those factors belong to the already established Nine amino acid Transactivation Domain (9aaTAD) family. By using available structural data, we found binding analogy for the 9aaTAD in the MLL-KIX and also E2A/HEB-KIX complexes. We recognized two distinct TAD formations in the KIX complex. In the E2A/HEB-KIX complex, the leucine position is determined by the prolonged helical structure including the 9aaTAD and the leucine (long-helical TAD). However in the MLL-KIX complex, the equal position of 9aaTAD and proximal leucine is achieved differently by leucine-turn-helix structural architecture. Furthermore, the FOXO3-KIX complex shares structural analogy with the E2A-KIX complex in respect of both 9aaTAD and proximal leucine. Next, from (i) sequence alignment of the identified 9aaTADs in p53, E2A/HEB and MLL proteins and (ii) the resolved structure of the MLL-KIX and E2A/HEB-KIX complexes, we generated a plausible structural model for p53 that could be used also for other members of the 9aaTAD family. The position of 9aaTADs in Oaf1-, Pdr1- and Gcn4-MED15 KIX complexes and 9aaTAD composition are in good agreement with E2A, MLL, FOXO3 and p53. Analyses of structural data in this study define fundamental structural requirements and shed more light on the ambiguous 9aaTAD domain.

Transfer learning for Bayesian discovery of multiple Bayesian networks

Bayesian network structure learning algorithms with limited data are being used in domains such as systems biology and neuroscience to gain insight into the underlying processes that produce observed data. Learning reliable networks from limited data is difficult; therefore, transfer learning can improve the robustness of learned networks by leveraging data from related tasks. Existing transfer learning algorithms for Bayesian network structure learning give a single maximum a posteriori estimate of network models. Yet, many other models may be equally likely, and so a more informative result is provided by Bayesian structure discovery. Bayesian structure discovery algorithms estimate posterior probabilities of structural features, such as edges. We present transfer learning for Bayesian structure discovery which allows us to explore the shared and unique structural features among related tasks. Efficient computation requires that our transfer learning objective factors into local calculations, which we prove is given by a broad class of transfer biases. Theoretically, we show the efficiency of our approach. Empirically, we show that compared to single-task learning, transfer learning is better able to positively identify true edges. We apply the method to whole-brain neuroimaging data.

Expanding the olfactory code by in silico decoding of odor-receptor chemical space

Coding of information in the peripheral olfactory system depends on two fundamental : interaction of individual odors with subsets of the odorant receptor repertoire and mode of signaling that an individual receptor-odor interaction elicits, activation or inhibition. We develop a cheminformatics pipeline that predicts receptor-odorant interactions from a large collection of chemical structures (>240,000) for receptors that have been tested to a smaller panel of odorants (∼100). Using a computational approach, we first identify shared structural features from known ligands of individual receptors. We then use these features to screen in silico new candidate ligands from >240,000 potential volatiles for several Odorant receptors (Ors) in the Drosophila antenna. Functional experiments from 9 Ors support a high success rate (∼71%) for the screen, resulting in identification of numerous new activators and inhibitors. Such computational prediction of receptor-odor interactions has the potential to enable systems level analysis of olfactory receptor repertoires in organisms. DOI:http://dx.doi.org/10.7554/eLife.01120.001.

Combinatorial Clustering of Residue Position Subsets Predicts Inhibitor Affinity across the Human Kinome

The protein kinases are a large family of enzymes that play fundamental roles in propagating signals within the cell. Because of the high degree of binding site similarity shared among protein kinases, designing drug compounds with high specificity among the kinases has proven difficult. However, computational approaches to comparing the 3-dimensional geometry and physicochemical properties of key binding site residue positions have been shown to be informative of inhibitor selectivity. The Combinatorial Clustering Of Residue Position Subsets (ccorps) method, introduced here, provides a semi-supervised learning approach for identifying structural features that are correlated with a given set of annotation labels. Here, ccorps is applied to the problem of identifying structural features of the kinase atp binding site that are informative of inhibitor binding. ccorps is demonstrated to make perfect or near-perfect predictions for the binding affinity profile of 8 of the 38 kinase inhibitors studied, while only having overall poor predictive ability for 1 of the 38 compounds. Additionally, ccorps is shown to identify shared structural features across phylogenetically diverse groups of kinases that are correlated with binding affinity for particular inhibitors; such instances of structural similarity among phylogenetically diverse kinases are also shown to not be rare among kinases. Finally, these function-specific structural features may serve as potential starting points for the development of highly specific kinase inhibitors.

Innate immunostimulatory properties of allergens and their relevance to food allergy

Food allergy is an increasingly prevalent disease of immune dysregulation directed to a small subset of proteins. Shared structural and functional features of allergens, such as glycosylation, lipid-binding and protease activity may provide insight into the mechanisms involved in the induction of primary Th2 immune responses. We review the literature of innate Th2-type immune activation as a context for better understanding the properties of allergens that contribute to the induction of Th2-biased immune responses in at least a subset of individuals. Th2-priming signals have been largely identified in the context of parasite immunity and wound healing. Some of the features of parasite antigens and the innate immune responses to them are now understood to play a role in allergic inflammation as well. These include both exogenous and endogenous activators of innate immunity and subsequent release of key cytokine mediators such as thymic stromal lymphopoietin (TSLP), interleukin (IL)-25 and IL-33. Moreover, numerous innate immune cells including epithelium, dendritic cells, basophils, innate lymphoid cells and others all interact to shape the adaptive Th2 immune response. Progress toward understanding Th2-inducing innate immune signals more completely may lead to novel strategies for primary prevention and therapy of respiratory and food allergies.

Single-Molecule Technique Links Structural Fluctuations of Proteins to Brain Diseases

​DiseasesDiseases such as Alzheimer's, Parkinson's, and Huntington's are characterized by a dramatic loss of neurons and are believed to be caused by the accumulation of neurotoxic proteins either inside or outside of cells. Although distinct neurotoxic proteins are implicated in various neurodegenerative disorders, they are thought to undergo a structural change that triggers protein aggregation and a series of events resulting in cell death. However, established techniques have made it challenging for scientists to determine the key conformational change at the molecular level that leads to disease. Conformational polymorphism of a neurotoxic protein. In this issue of PLoS Biology, a team led by Mariano Carrion-Vazquez at the Cajal Institute used a novel approach to unmistakably identify specific structural conformations of individual molecules, thereby revealing how these conformations relate to cellular dysfunction in a range of neurodegenerative diseases. The researchers found that extremely stable molecular conformations in various neurotoxic proteins are associated with protein aggregation. Moreover, their results suggest that a single drug may be able to target shared structural features in these proteins, which could help to prevent or treat multiple neurodegenerative disorders. By modifying existing protocols for a high-resolution biophysical technique known as atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS), Carrion-Vazquez and his team achieved an unprecedented level of data quality, which allowed them to carefully examine the mechanical stability of molecular conformations in neurotoxic proteins. Using this tool, they measured the forces necessary to unfold the proteins by attaching one end of the proteins to a sharp tip and the other end to a surface, which stretched the proteins when the surface was pulled away from the tip. To avoid data contamination that has plagued past experiments, they inserted the proteins of interest into protective carrier proteins. Using AFM-based SMFS, the researchers found a higher frequency of stable conformations in fatal proteins implicated in Alzheimer's, Parkinson's, Huntington's, and prion diseases than in nontoxic proteins. These structures were even more abundant in mutated proteins that are linked to the early onset and increased severity of disease. The structural stability of a small fraction of these conformations was the highest ever reported for any protein. Moreover, the robust conformations were associated with protein aggregation, and these structures formed less frequently when the noxious proteins were exposed to a neuroprotective peptide that inhibits the abnormal accumulation of proteins. The sturdy conformations may mechanically jam the cell's protein-processing machinery, interfere with the breakdown of damaged or aggregated proteins, or otherwise stymie essential cell functions. Based on their findings, Carrion-Vazquez and his collaborators suggest that extremely robust conformations are the primary cause of neurodegenerative disorders, so they could serve as ideal pharmacological targets as well as potential biomarkers for the early detection of disease. Their new approach opens the door to not only understanding the role of harmful protein accumulation in various conditions, but also developing effective therapeutic strategies. Hervas R, Oroz J, Galera-Prat A, Goni O, Valbuena A, et al. (2012) Common Features at the Start of the Neurodegeneration Cascade. doi:10.1371/journal.pbio.1001335