Exploring Seipin: From Biochemistry to Bioinformatics Predictions.
Ontology highlight
ABSTRACT:
SUBMITTER: Craveiro Sarmento AS
PROVIDER: S-EPMC6192094 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Reagents that bind tightly and specifically to biomolecules of interest remain essential in the exploration of biology and in their ultimate application to medicine. Besides ligands for receptors of known specificity, agents commonly used for this purpose are monoclonal antibodies derived from mice, rabbits, and other animals. However, such antibodies can be expensive to produce, challenging to engineer, and are not necessarily stable in the context of the cellular cytoplasm, a reducing environment. Heavy chain-only antibodies, discovered in camelids, have been truncated to yield single-domain antibody fragments (VHHs or nanobodies) that overcome many of these shortcomings. Whereas they are known as crystallization chaperones for membrane proteins or as simple alternatives to conventional antibodies, nanobodies have been applied in settings where the use of standard antibodies or their derivatives would be impractical or impossible. We review recent examples in which the unique properties of nanobodies have been combined with complementary methods, such as chemical functionalization, to provide tools with unique and useful properties.
| S-EPMC7650250 | biostudies-literature
Project description:In Escherichia coli, YaeT, together with four lipoproteins, YfgL, YfiO, NlpB, and SmpA, forms a complex that is essential for beta-barrel outer membrane protein biogenesis. Data suggest that YfgL and YfiO make direct but independent physical contacts with YaeT. Whereas the YaeT-YfiO interaction needs NlpB and SmpA for complex stabilization, the YaeT-YfgL interaction does not. Using bioinformatics, genetics, and biochemical approaches, we have identified three residues, L173, L175, and R176, in the mature YfgL protein that are critical for both function and interactions with YaeT. A single substitution at any of these sites produces no phenotypic defect, but two or three simultaneous alterations produce mild or yfgL-null phenotypes, respectively. Interestingly, biochemical data show that all YfgL variants, including those with single substitutions, have weakened in vivo YaeT-YfgL interaction. These defects are not due to mislocalization or low steady-state levels of YfgL. Cysteine-directed cross-linking data show that the region encompassing L173, L175, and R176 makes direct contact with YaeT. Using the same genetic and biochemical strategies, it was found that altering residues D227 and D229 in another region of YfgL from E221 to D229 resulted in defective YaeT bindings. In contrast, mutational analysis of conserved residues V319 to H328 of YfgL shows that they are important for YfgL biogenesis but not YfgL-YaeT interactions. The five YfgL mutants defective in YaeT associations and the yfgL background were used to show that SurA binds to YaeT (or another complex member) without going through YfgL.
| S-EPMC2258660 | biostudies-literature
Project description:Interpreting three-dimensional models of biological macromolecules is a key skill in biochemistry, closely tied to students' visuospatial abilities. As students interact with these models and explain biochemical concepts, they often use gesture to complement verbal descriptions. Here, we utilize an embodied cognition-based approach to characterize undergraduate students' gesture production as they described and interpreted an augmented reality (AR) model of potassium channel structure and function. Our analysis uncovered two emergent patterns of gesture production employed by students, as well as common sets of gestures linked across categories of biochemistry content. Additionally, we present three cases that highlight changes in gesture production following interaction with a 3D AR visualization. Together, these observations highlight the importance of attending to gesture in learner-centered pedagogies in undergraduate biochemistry education.
| S-EPMC11235103 | biostudies-literature
Project description:Honeybee larvae produce a silk made up of proteins in predominantly a coiled coil molecular structure. These proteins can be produced in recombinant systems, making them desirable templates for the design of advanced materials. However, the atomic level structure of these proteins is proving difficult to determine: firstly, because coiled coils are difficult to crystalize; and secondly, fibrous proteins crystalize as fibres rather than as discrete protein units. In this study, we synthesised peptides from the central structural domain, as well as the N- and C-terminal domains, of the honeybee silk. We used circular dichroism spectroscopy, infrared spectroscopy, and molecular dynamics to investigate the folding behaviour of the central domain peptides. We found that they folded as predicted by bioinformatics analysis, giving the protein engineer confidence in bioinformatics predictions to guide the design of new functionality into these protein templates. These results, along with the infrared structural analysis of the N- and C-terminal domain peptides and the comparison of peptide film properties with those of the full-length AmelF3 protein, provided significant insight into the structural elements required for honeybee silk protein to form into stable materials.
| S-EPMC6403662 | biostudies-literature
Project description:The human lipodystrophy gene product Berardinelli-Seip congenital lipodystrophy 2/seipin has been implicated in adipocyte differentiation, lipid droplet (LD) formation, and motor neuron development. However, the molecular function of seipin and its disease-causing mutants remains to be elucidated. Here, we characterize seipin and its mis-sense mutants: N88S/S90L (both linked to motoneuron disorders) and A212P (linked to lipodystrophy) in cultured mammalian cells. Knocking down seipin significantly increases oleate incorporation into triacylglycerol (TAG) and the steady state level of TAG, and induces the proliferation and clustering of small LDs. By contrast, overexpression of seipin reduces TAG synthesis, leading to decreased formation of LDs. Expression of the A212P mutant, however, had little effect on LD biogenesis. Surprisingly, expression of N88S or S90L causes the formation of many small LDs reminiscent of seipin deficient cells. This dominant-negative effect may be due to the N88S/S90L-induced formation of inclusions where wild-type seipin can be trapped. Importantly, coexpression of wild-type seipin and the N88S or S90L mutant can significantly reduce the formation of inclusions. Finally, we demonstrate that seipin can interact with itself and its mutant forms. Our results provide important insights into the biochemical characteristics of seipin and its mis-sense mutants, and suggest that seipin may function to inhibit lipogenesis.
| S-EPMC3220282 | biostudies-literature
Project description:Casein kinase 2 (CK2) is a highly pleiotropic serine-threonine kinase, which catalyzed phosphorylation of more than 300 proteins that are implicated in regulation of many cellular functions, such as signal transduction, transcriptional control, apoptosis and the cell cycle. On the other hand, CK2 is abnormally elevated in a variety of tumors, and is considered as a promising therapeutic target. The currently available ATP-competitive CK2 inhibitors, however, lack selectivity, which has impeded their development in cancer therapy. Because allosteric inhibitors can avoid the shortcomings of conventional kinase inhibitors, this study was aimed to discover a new allosteric site in CK2? and to investigate the effects of mutations in this site on the activity of CK2?. Using Allosite based on protein dynamics and structural alignment, we predicted a new allosteric site that was partly located in the ?C helix of CK2?. Five residues exposed on the surface of this site were mutated to validate the prediction. Kinetic analyses were performed using a luminescent ADP detection assay by varying the concentrations of a peptide substrate, and the results showed that the mutations I78C and I78W decreased CK2? activity, whereas V31R, K75E, I82C and P109C increased CK2? activity. Potential allosteric pathways were identified using the Monte Carlo path generation approach, and the results of these predicted allosteric pathways were consistent with the mutation analysis. Multiple sequence alignments of CK2? with the other kinases in the family were conducted using the ClustalX method, which revealed the diversity of the residues in the site. In conclusion, we identified a new allosteric site in CK2? that can be altered to modulate the activity of the kinase. Because of the high diversity of the residues in the site, the site can be targeted using rational drug design of specific CK2? inhibitors for biological relevance.
| S-EPMC5719156 | biostudies-literature
Project description:To improve coastal adaptation and management, it is critical to better understand and predict the characteristics of sea levels. Here, we explore the capabilities of artificial intelligence, from four deep learning methods to predict the surge component of sea-level variability based on local atmospheric conditions. We use an Artificial Neural Networks, Convolutional Neural Network, Long Short-Term Memory layer (LSTM) and a combination of the latter two (ConvLSTM), to construct ensembles of Neural Network (NN) models at 736 tide stations globally. The NN models show similar patterns of performance, with much higher skill in the mid-latitudes. Using our global model settings, the LSTM generally outperforms the other NN models. Furthermore, for 15 stations we assess the influence of adding complexity more predictor variables. This generally improves model performance but leads to substantial increases in computation time. The improvement in performance remains insufficient to fully capture observed dynamics in some regions. For example, in the tropics only modelling surges is insufficient to capture intra-annual sea level variability. While we focus on minimising mean absolute error for the full time series, the NN models presented here could be adapted for use in forecasting extreme sea levels or emergency response.
| S-EPMC8390491 | biostudies-literature
Project description:Flavonoids are the largest class of plant polyphenols, with common structure of diphenylpropanes, consisting of two aromatic rings linked through three carbons and are abundant in both daily diets and medicinal plants. Fueled by the recognition of consuming flavonoids to get better health, researchers became interested in deciphering how flavonoids alter the functions of human body. Here, systematic studies were performed on 679 flavonoid compounds and 481 corresponding targets through bioinformatics analysis. Multiple human diseases related pathways including cancers, neuro-disease, diabetes, and infectious diseases were significantly regulated by flavonoids. Specific functions of each flavonoid subclass were further analyzed in both target and pathway level. Flavones and isoflavones were significantly enriched in multi-cancer related pathways, flavan-3-ols were found focusing on cellular processing and lymphocyte regulation, flavones preferred to act on cardiovascular related activities and isoflavones were closely related with cell multisystem disorders. Relationship between chemical constitution fragment and biological effects indicated that different side chain could significantly affect the biological functions of flavonoids subclasses. Results will highlight the common and preference functions of flavonoids and their subclasses, which concerning their pharmacological and biological properties.
| S-EPMC6104453 | biostudies-literature
Project description:Seipin is a transmembrane protein that resides in the endoplasmic reticulum and concentrates at junctions between the ER and cytosolic lipid droplets. Mutations in the human seipin gene, including the missense mutation A212P, lead to congenital generalized lipodystrophy (CGL), characterized by the lack of normal adipose tissue and accumulation of fat in liver and muscles. In both yeast and CGL patient fibroblasts, seipin is required for normal lipid droplet morphology; in its absence droplets appear to bud abnormally from the ER. Here we report the first purification and physical characterization of seipin. Yeast seipin is in a large discrete protein complex. Affinity purification demonstrated that seipin is the main if not exclusive protein in the complex. Detergent sucrose gradients in H(2)O, and D(2)O and gel filtration were used to determine the size of the seipin complex and account for detergent binding. Both seipin-myc13 (seipin fused to 13 tandem copies of the myc epitope) expressed from the endogenous promoter and overexpressed seipin-mCherry form ?500 kDa proteins consisting of about 9 copies of seipin. The yeast orthologue of the human A212P allele forms only smaller complexes and is unstable; we hypothesize that this accounts for its null phenotype in humans. Seipin appears as a toroid by negative staining electron microscopy. We speculate that seipin plays at least a structural role in organizing droplets or in communication between droplets and ER.
| S-EPMC3086013 | biostudies-literature
Project description:BACKGROUND: The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. RESULTS: This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. CONCLUSION: We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.
| S-EPMC1885847 | biostudies-other