336 research outputs found

    A Genetic Algorithm for Scale-Based Translocon Simulation

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    Discriminating between secreted and membrane proteins is a challenging task. A recent and important discovery to understand the machinery responsible of the insertion of membrane proteins was the results of Hessa experiments [9]. The authors developed a model system for measuring the ability of insertion of engineered hydrophobic amino acid segments in the membrane. The main results of these experiments are summarized in a new ”biological hydrophobicity scale”. In this scale, each amino acid is represented by a curve that indicates its contribution to the process of protein insertion according to its position inside the membrane. We follow the same hypothesis as Hessa but we propose to determine “in silico” the hydrophobicity scale. This goal is formalized as an optimization problem, where we try to define a set of curves that gives the best discrimination between signal peptide and protein segments which cross the membrane. This paper describes the genetic algorithm that we developed to solve this problem and the experiments that we conducted to assess its performance

    Hydrophobically stabilized open state for the lateral gate of the Sec translocon

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    The Sec translocon is a central component of cellular pathways for protein translocation and membrane integration. Using both atomistic and coarse-grained molecular simulations, we investigate the conformational landscape of the translocon and explore the role of peptide substrates in the regulation of the translocation and integration pathways. Inclusion of a hydrophobic peptide substrate in the translocon stabilizes the opening of the lateral gate for membrane integration, whereas a hydrophilic peptide substrate favors the closed lateral gate conformation. The relative orientation of the plug moiety and a peptide substrate within the translocon channel is similarly dependent on whether the substrate is hydrophobic or hydrophilic in character, and the energetics of the translocon lateral gate opening in the presence of a peptide substrate is governed by the energetics of the peptide interface with the membrane. Implications of these results for the regulation of Sec-mediated pathways for protein translocation vs. membrane integration are discussed

    Heterozygous Loss-of-Function SEC61A1 Mutations Cause Autosomal-Dominant Tubulo-Interstitial and Glomerulocystic Kidney Disease with Anemia

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    Autosomal-dominant tubulo-interstitial kidney disease (ADTKD) encompasses a group of disorders characterized by renal tubular and interstitial abnormalities, leading to slow progressive loss of kidney function requiring dialysis and kidney transplantation. Mutations in UMOD, MUC1, and REN are responsible for many, but not all, cases of ADTKD. We report on two families with ADTKD and congenital anemia accompanied by either intrauterine growth retardation or neutropenia. Ultrasound and kidney biopsy revealed small dysplastic kidneys with cysts and tubular atrophy with secondary glomerular sclerosis, respectively. Exclusion of known ADTKD genes coupled with linkage analysis, whole-exome sequencing, and targeted re-sequencing identified heterozygous missense variants in SEC61A1—c.553A>G (p.Thr185Ala) and c.200T>G (p.Val67Gly)—both affecting functionally important and conserved residues in SEC61. Both transiently expressed SEC6A1A variants are delocalized to the Golgi, a finding confirmed in a renal biopsy from an affected individual. Suppression or CRISPR-mediated deletions of sec61al2 in zebrafish embryos induced convolution defects of the pronephric tubules but not the pronephric ducts, consistent with the tubular atrophy observed in the affected individuals. Human mRNA encoding either of the two pathogenic alleles failed to rescue this phenotype as opposed to a complete rescue by human wild-type mRNA. Taken together, these findings provide a mechanism by which mutations in SEC61A1 lead to an autosomal-dominant syndromic form of progressive chronic kidney disease. We highlight protein translocation defects across the endoplasmic reticulum membrane, the principal role of the SEC61 complex, as a contributory pathogenic mechanism for ADTKD

    Identification and modeling of a novel chloramphenicol resistance protein detected by functional metagenomics in a wetland of Lerma, Mexico

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    The exploration of novel antibiotic resistance determinants in a particular environment may be limited because of the presence of uncultured microorganisms. In this work, a culture independent approach based on functional metagenomics was applied to search for chloramphenicol resistance genes in agro-industrial wastewater in Lerma de Villada, Mexico. To this end, a metagenomic library was generated in Escherichia coli DH10B containing DNA isolated from environmental samples of the residual arsenic-enriched (10 mg/ml) effl uent. One resistant clone was detected in this library and further analyzed. An open reading frame similar to a multidrug resistance protein from Aeromonas salmonicida and responsible for chloramphenicol resistance was identifi ed, sequenced, and found to encode a member of the major facilitator superfamily (MFS). Our results also showed that the expression of this gene restored streptomycin sensitivity in E. coli DH10B cells. To gain further insight into the phenotype of this MFS family member, we developed a model of the membrane protein multiporter that, in addition, may serve as a template for developing new antibiotics. [Int Microbiol 2013; 16(2):103-111]Keywords: Escherichia coli; chloramphenicol; functional metagenomics; major facilitator superfamily; homology models; membrane proteins; arseni

    Dynamic action of the Sec machinery during initiation, protein translocation and termination

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    Protein translocation across cell membranes is a ubiquitous process required for protein secretion and membrane protein insertion. In bacteria, this is mostly mediated by the conserved SecYEG complex, driven through rounds of ATP hydrolysis by the cytoplasmic SecA, and the trans-membrane proton motive force. We have used single molecule techniques to explore SecY pore dynamics on multiple timescales in order to dissect the complex reaction pathway. The results show that SecA, both the signal sequence and mature components of the pre-protein, and ATP hydrolysis each have important and specific roles in channel unlocking, opening and priming for transport. After channel opening, translocation proceeds in two phases: a slow phase independent of substrate length, and a length-dependent transport phase with an intrinsic translocation rate of ~40 amino acids per second for the proOmpA substrate. Broad translocation rate distributions reflect the stochastic nature of polypeptide transport

    Computational Molecular Biophysics of Membrane Reactions

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    Proteins are nanoscale molecules that perform functions essential for biological life. Membranes surrounding cells, for example, contain receptor proteins that mediate communication between the cell and the external milieu, membrane transporters that transport ions and larger compounds across the membranes, and enzymes that catalyze chemical reactions. Likewise, soluble proteins found in interior of the cell include motor proteins that move other proteins around, enzymes that bind to and repair breaks in the DNA, and proteins that help control the cellular clock. Mutations in genes that encode proteins can cause disease, as is the case of cystic fibrosis, a disease that associates with mutation of a chloride channel called the cystic fibrosis transmembrane conductance regulator.1 The essential functions they perform in the cell makes proteins essential drug targets for modern bio-medical applications. An important example here is the programmed death ligand-1 (PD-L1), which is a valuable target for modern immunotherapy.2-4 Predicting how a protein responds to a drug molecule, or using the protein as inspiration for biotechnological applications, require knowledge of how that protein works. As proteins are dynamic entities and protein dynamics are essential for function,5-8 describing the mechanism of action of a protein requires knowledge about the protein motions in fluid environments. Theoretical biophysics provides valuable tools to characterize protein reaction mechanisms and protein motions at the atomic level of detail. This Habilitation Thesis presents research on using theoretical biophysics approaches to decipher how proteins work. The focus of the research is on membrane proteins and reactions that occur at lipid membrane interfaces. The central question I address is the role of dynamic hydrogen (H) bonds in protein function and membrane interactions. The methods used include quantum mechanical (QM) computations of small molecules, combined quantum mechanics/molecular mechanics (QM/MM) of chemical reactions in protein environments, classical mechanical computations of large protein and membrane systems, and bridging numerical simulations to bioinformatics. In my research group we developed algorithms to identify H-bond networks in proteins and membrane environments, and to characterize the dynamics of these networks. To extend the applicability of numerical computations to bio-systems that bind drug-like compounds, we derive parameters for a potential energy function widely used in the field. The main research topics and specific questions addressed are summarized below together with a discussion of the computational approaches used

    Shape transformations of lipid vesicles by insertion of bulky-head lipids

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    Lipid vesicles, in particular Giant Unilamellar Vesicles (GUVs), have been increasingly important as compartments of artificial cells to reconstruct living cell-like systems in a bottom-up fashion. Here, we report shape transformations of lipid vesicles induced by polyethylene glycol-lipid conjugate (PEG lipids). Statistical analysis of deformed vesicle shapes revealed that shapes vesicles tend to deform into depended on the concentration of the PEG lipids. When compared with theoretically simulated vesicle shapes, those shapes were found to be more energetically favorable, with lower membrane bending energies than other shapes. This result suggests that the vesicle shape transformations can be controlled by externally added membrane molecules, which can serve as a potential method to control the replications of artificial cells

    Computational analysis of membrane transporters and their substrates

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    In this thesis, we developed, implemented and applied bioinformatics tools/techniques in three projects that aim at characterising functional properties of membrane transport systems as well as their interactions with substrates and non-substrates. In the first project, we developed a novel method for MdfA sub- strate classification. MdfA is a multidrug membrane transporter of E. coli, which is responsible for recognising and transporting a wide spectrum of substrates with unrelated properties. Unlike other conventional methods that utilised general features such as sequence derived information, molecular descriptors, etc. , the new method incorporates protein-ligand structural interactions and potential energy information derived from molecular dynamics simulations. However, the method still encountered difficulties with the structural similarity problem between substrates and non-substrates. The new method achieved a decent performance with 73.12% of classification accuracy. Regardless, this is the first method that considers protein- ligand interactions in a classification problem related to membrane transport. In the next project, we analysed the proteomics data from Sec61α and TRAP silencing experiments to reveal and characterise TRAP substrates. TRAP is an assisting component of the translocon complex, which is responsible for protein translocation across the membrane of the endoplasmic reticulum. We successfully identified a set of TRAP dependent proteins from mass spectrometry proteomics data. Furthermore, our analysis revealed that the signal peptides of TRAP substrates showed a low hydrophobicity tendency as well as significantly increased glycine and proline content. We propose that TRAP may be responsible for helping those proteins carrying signal peptides with high glycine-proline content and low hydrophobicity to migrate easily through the Sec61α channel. In the last project, we applied molecular docking to investigate the binding modes of several eeyarestatin compounds (ES1, ES24, ES35 and ES47) to a structural homology model of human Sec61α protein. The Sec61α channel is not only responsible for protein translocation but also promotes Ca2+ leakage. Based on the docking results, we found that the energetically most favourable binding positions of ES1 and ES24 are located in between the H2 and H7 helices, which are the “doors” of the lateral gate. Hence, they are likely to hamper the gate function, keeping it open upon binding. Therefore, we postulated that ES1 and ES24 can be potential “gate blockers” which promote Ca2+ leakage via Sec61α. These findings are consistent with the results from calcium imaging experiments which were conducted by our colleagues.In den vergangenen Jahren haben sich rechnerische Technologien sowie die Entwicklung von anspruchsvollen Algorithmen und Software schnell entwickelt. Diese technologischen Fortschritte spielen einen entscheidende Rolle fĂŒr die bioinformatische Forschung, da die biologischen Daten in Bezug auf QuantitĂ€t, QualitĂ€t und KomplexitĂ€t exponentiell zunehmen. In dieser Arbeit haben wir in drei Projekten, die auf die Charakterisierung von funktionellen Eigenschaften von Membrantransportsystemen sowie deren Wechselwirkungen mit Substraten und Nicht-Substraten abzielen, Bioinformatik-Werkzeuge/-Techniken entwickelt, umgesetzt und angewendet. Membrantransporter sind eine sehr wichtige Klasse von integralen Transmembranproteinen, die fĂŒr den Materialaustausch zwischen Zellen und deren Umgebungen verantwortlich sind. Aufgrund der starken Beziehung mit verschiedenen Krankheiten und abnormen medizinischen Bedingungen wurde und wird die Wechselwirkung von Transportern mit kleinen ArzneimittelmolekĂŒlen intensiv untersucht. Im ersten Projekt haben wir eine neuartige Methode fĂŒr die MdfA-Substratklassifizierung entwickelt. MdfA ist ein Multidrug-Membrantransporter von E. coli, der fĂŒr die Erkennung und den Transport eines breiten Spektrums von Substraten mit nicht verwandten Eigenschaften verantwortlich ist. Im Gegensatz zu anderen herkömmlichen Verfahren, die allgemeine Merkmale wie aus den sequenzen abgeleitete Informationen, molekulare Deskriptoren usw. verwenden, umfasst das neue Verfahren Protein- Ligand-Struktur-Wechselwirkungen und potentielle Energieinformationen, die aus molekulardynamischen Simulationen abgeleitet sind. Allerdings stieß das Verfahren immer noch auf Schwierigkeiten mit dem strukturellen Ähnlichkeitsproblem zwischen Substraten und Nichtsubstraten. Die neue Methode erreichte eine zufriedenstellende Genauigkeit mit 73,12% Klassifizierungsgenauigkeit. Es ist die erste Methode, die Protein-Ligand-Wechselwirkungen bei einem Klassifizierungsproblem fĂŒr Membrantransport berĂŒcksichtigt. Im nÄchsten Projekt analysierten wir Proteomikdaten aus Sec61α und TRAP-Stummschaltungsexperimenten, um TRAP-Substrate zu identifizieren und zu charakterisieren. TRAP ist eine assistierende Komponente des Translocon-Komplexes, der fĂŒr die Protein-Translokation verantwortlich ist. Wir identifizierten erfolgreich einen Satz von TRAP-abhÄngigen Proteinen aus Massenspektrometrie-Proteomik-Daten. DarĂŒber hinaus zeigte unsere Analyse, dass die Signalpeptide von TRAP-Substraten eine geringe Hydrophobie-Tendenz sowie einen signifikant erhöhten Glycin- und Prolin-Gehalt aufwiesen. Wir schlugen vor, dass TRAP dafĂŒr verantwortlich sein VII kann, diejenigen Proteine bei der Migration durch den Sec61α-Kanal zu unterstĂŒtzen, die Signalpeptide mit hohem Glycin-Prolin-Gehalt und geringer HydrophobizitÄt haben. Im letzten Projekt haben wir die molekulare Docking-Technik angewendet, um die Bindungsmodi von mehreren Eeyarestatin-Verbindungen (ES1, ES24, ES35 und ES47) mit einem Homologiemodell von humanem Sec61α Protein zu untersuchen. Der Sec61α-Kanal ist nicht nur fĂŒr die Proteintranslokation verantwortlich, sondern fördert auch Ca2+ Leckage. Die Docking-Ergebnisse ergaben, dass sich die energetisch gĂŒnstigste Bindungsposition von ES1 und ES24 zwischen den H2- und H7- Helices befindet, die die \TĂŒren" des lateralen Tores sind. Daher ist es wahrscheinlich, dass sie die Tor-Funktion behindern können und nach der Bindung den Kanal offen halten. Daher haben wir postuliert, dass ES1 und ES24 die potentiellen \Gate Blocker" sein können, die Ca2+ Leckage durch Sec61α fördern. Diese Ergebnisse stimmen mit den Ergebnissen der Calcium-Imaging-Experimente ĂŒberein, die von unseren Kollegen durchgefĂŒhrt wurden. In dieser Arbeit haben wir verschiedene Rechentechniken eingesetzt, um neue mechanistische Einblicke in Transmembran-Transporter zu gewinnen und wichtige Informationen aus der Analyse von Proteomik-Daten zu erhalten. Wir hoffen, dass unsere Arbeit nĂŒtzliche mikroskopische Details und mögliche Mechanismen fĂŒr die experimentellen Biologen, die an transmembranen Proteinen arbeiten, zur VerfĂŒgung stellt.SFB 1027, GRK127
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