156 research outputs found
DNA-templated assembly of the bacterial flagellar motor's cytoplasmic ring
No full textThe bacterial flagellar motor is one of the most complex protein machines found in nature and how it self-assembles and produces force are very much open questions. In this thesis, I study the constituent parts of the motor in vitro, with the focus being primarily on FliG, a protein which helps to form the motorâs cytoplasmic ring. The experimental approach employs a DNA scaffold to direct the in vitro formation of the FliG ring, with the aim of determining both the number of proteins in the complex and the means by which they associate to form a circular structure. One leading theory states that the FliG proteins interact through a process of domain-swap oligomerization and the primary goal of this work is to search for evidence of this process with the aid of in vitro DNA templates.
To attach the FliG protein to the underlying DNA structures, I produced FliG-DNA conjugates through two different means. First, I bound both tris- and pentakis-NTA-modified DNA strands to the Histidine-tag of FliG and showed that these conjugates could be arranged on simple, linear DNA templates. In order for the proteins to be arranged with the spacing observed in the cytoplasmic ring however, a different conjugation strategy was required in which a maleimide-modified DNA strand was reacted with a single-cysteine FliG mutant. After issues relating to Histidine-tag-mediated FliG dimerization were resolved, these conjugates were able to be organized on both linear DNA strands and origami tiles with the desired spacing between the proteins. No interactions between either template-bound or free-floating FliG proteins could be observed however, meaning a new strategy was needed.
One model of cytoplasmic ring assembly predicts that binding of FliG to the C-terminal domain of the membrane-bound FliF protein induces a conformational change in both partners which then triggers interactions between neighbouring FliG proteins. To test this, I designed a peptide corresponding to the FliFC domain of Salmonella and E. coli FliF and incorporated it into my system. Several biophysical assays indicated that the FliFC peptide stably bound to purified wild-type Salmonella FliG and that binding to the peptide increased the overall stability of the protein. This constitutes the first confirmation that the cytoplasmic domain of FliF is sufficient for FliG binding in enteric bacteria. Following this discovery, a maleimide-modified DNA strand was then conjugated to a single-cysteine version of the peptide and the peptide-DNA conjugates organized with various stoichiometries and spacing on DNA templates to create an array of âbinding platformsâ for the FliG protein. FliG bound to the organized peptides in a one-to-one fashion but interactions between the organized FliG proteins were still not detected.
In a final effort to stimulate FliG-FliG binding, a radially-symmetric DNA nanostructure was designed with dimensions and a geometry which matched those found in the cytoplasmic rings of bacteria. Gels and AFM microscopy proved that the 12 designed strands assembled correctly into the desired structure and that FliFC-DNA conjugates with FliG proteins bound could be organized on the circular arrangement of binding sites around the structureâs outer rim. Even in such an arrangement, interactions between neighbouring proteins could not be observed, and though higher concentrations of FliFC and FliG were tested, issues with purification prevented accurate characterization of these complexes.
Thus, though the domain-swap model for FliG oligomerization was therefore neither confirmed or denied, the use of a DNA scaffold to organize protein molecules and study their interactions holds promise as a technique to investigate the proteins of other biological systems and will no doubt be employed to great effect in the coming years.</p
Guiding Biomolecular Interactions in Cells Using de Novo Protein - Protein Interfaces
No full textAn improved ability to direct and control biomolecular interactions in living cells would have an impact on synthetic biology. A key issue is the need to introduce interacting components that act orthogonally to endogenous proteomes and interactomes. Here, we show that low-complexity, de novo designed protein–protein interaction (PPI) domains can substitute for natural PPIs and guide engineered protein–DNA interactions in Escherichia coli. Specifically, we use de novo homo- and heterodimeric coiled coils to reconstitute a cytoplasmic split adenylate cyclase, recruit RNA polymerase to a promoter and activate gene expression, and oligomerize both natural and designed DNA-binding domains to repress transcription. Moreover, the stabilities of the heterodimeric coiled coils can be modulated by rational design and, thus, adjust the levels of gene activation and repression in vivo. These experiments demonstrate the possibilities for using designed proteins and interactions to control biomolecular systems such as enzyme cascades and circuits in cells
Coiled-Coil Design:Updated and Upgraded
No full textα-Helical coiled coils are ubiquitous protein-folding and protein-interaction domains in which two or more α-helical chains come together to form bundles. Through a combination of bioinformatics analysis of many thousands of natural coiled-coil sequences and structures, plus empirical protein engineering and design studies, there is now a deep understanding of the sequence-to-structure relationships for this class of protein architecture. This has led to considerable success in rational design and what might be termed in biro de novo design of simple coiled coils, which include homo- and hetero-meric parallel dimers, trimers and tetramers. In turn, these provide a toolkit for directing the assembly of both natural proteins and more-complex designs in protein engineering, materials science and synthetic biology. Moving on, the increased and improved use of computational design is allowing access to coiled-coil structures that are rare or even not observed in nature, for example α-helical barrels, which comprise five or more α-helices and have central channels into which different functions may be ported. This chapter reviews all of these advances, outlining improvements in our knowledge of the fundamentals of coiled-coil folding and assembly, and highlighting new coiled coil-based materials and applications that this new understanding is opening up. Despite considerable progress, however, challenges remain in coiled-coil design, and the next decade promises to be as productive and exciting as the last
De novo coiled-coil peptides as scaffolds for disrupting protein-protein interactions
No full textProtein-protein interactions (PPIs) play pivotal roles in the majority of biological processes. Therefore, improved approaches to target and disrupt PPIs would provide tools for chemical biology and leads for therapeutic development. PPIs with α-helical components are appealing targets given that the secondary structure is well understood and can be mimicked or stabilised to render small-molecule and constrained-peptide-based inhibitors. Here we present a strategy to target α-helix-mediated PPIs that exploits de novo coiled-coil assemblies and test this using the MCL-1/NOXA-B PPI. First, computational alanine scanning is used to identify key α-helical residues from NOXA-B that contribute to the interface. Next, these residues are grafted onto the exposed surfaces of de novo designed homodimeric or heterodimeric coiled-coil peptides. The resulting synthetic peptides selectively inhibit a cognate MCL-1/BID complex in the mid-nM range. Furthermore, the heterodimeric system affords control as inhibition occurs only when both the grafted peptide and its designed partner are present. This establishes proof of concept for exploiting peptides stabilised in de novo coiled coils as inhibitors of PPIs. This dependence on supramolecular assembly introduces new possibilities for regulation and control
Understanding a protein fold: the physics, chemistry, and biology of α-helical coiled coils
No full textProtein science is being transformed by powerful computational methods for structure prediction and design: AlphaFold2 can predict many natural protein structures from sequence, and other AI methods are enabling the de novo design of new structures. This raises a question: how much do we understand the underlying sequence-to-structure/function relationships being captured by these methods? This perspective presents our current understanding of one class of protein assembly, the α-helical coiled coils. At first sight, these are straightforward: sequence repeats of hydrophobic (h) and polar (p) residues, (hpphppp)n, direct the folding and assembly of amphipathic α helices into bundles. However, many different bundles are possible: they can have two or more helices (different oligomers); the helices can have parallel, antiparallel or mixed arrangements (different topologies); and the helical sequences can be the same (homomers) or different (heteromers). Thus, sequence-to-structure relationships must be present within the hpphppp repeats to distinguish these states. I discuss the current understanding of this problem at three levels: First, physics gives a parametric framework to generate the many possible coiled-coil backbone structures. Second, chemistry provides a means to explore and deliver sequence-to-structure relationships. Third, biology shows how coiled coils are adapted and functionalized in nature, inspiring applications of coiled coils in synthetic biology. I argue that the chemistry is largely understood; the physics is partly solved, though the considerable challenge of predicting even relative stabilities of different coiled-coil states remains; but there is much more to explore in the biology and synthetic biology of coiled coils
The de novo design of α-helical peptides for supramolecular self-assembly
No full textOne approach to designing de novo proteinaceous assemblies and materials is to develop simple, standardised building blocks and then to combine these symmetrically to construct more-complex higher-order structures. This has been done extensively using β-structured peptides to produce peptide fibres and hydrogels. Here, we focus on building with de novo α-helical peptides. Because of their self-contained, well-defined structures and clear sequence-to-structure relationships, α helices are highly programmable making them robust building blocks for biomolecular construction. The progress made with this approach over the past two decades is astonishing and has led to a variety of de novo assemblies, including discrete nanoscale objects, and fibrous, nanotube, sheet and colloidal materials. This body of work provides an exceptionally strong foundation for advancing the field beyond in vitro design and into in vivo applications including what we call protein design in cells.</p
Predicting 4D trajectories of aircraft using neural networks and gradient boosting machines: A data-driven aircraft trajectory prediction study
No full textData-driven trajectory prediction is one of the key pillars of the future ATM system. Recent research focuses on using novel data sources and machine learning algorithms to improve the performance of 4D trajectory prediction, enabling safer and more efficient routing of aircraft. In this paper a framework for data sourcing and preparation for such predictors is presented, as well as a comparison of three of the best performing prediction algorithms from literature to a baseline method. Currently such comparisons are lacking, making it hard to determine which techniques provide the best results. Using an ADS-B antenna and various online data sources a trajectory set of 40,000 trajectories is built. Two clustering methods are tested and it is found that clustering trajectories using Density Based Clus- tering for Applications with Noise (DBSCAN) performs poorly on our data set of arriving flights. Too many trajectories are classified as outliers while DBSCAN is not capable of separating the trajectories in distinct clusters. A clustering method based on the STARs of the airport is proposed, which performs better in terms of accuracy and efficiency. Finally, a baseline simulation using Aircraft Performance Models is compared to a deep neural network, a Long Short-Term Memory (LSTM) network and to Gradient Boosting Machines (GBM) for trajectory prediction. It is found that the latter outperforms the other methods overall, while it was expected that predictors based on LSTMs would provide more accurate results. It is concluded that long-term dependencies in trajectory data, on which LSTMs perform well, are less important than categorical indicators, on which GBMs perform better, in trajectory prediction.Aerospace Engineerin
The evolution and structure prediction of coiled coils across all genomes
No full textCoiled coils are α-helical interactions found in many natural proteins. Various sequence-based coiled-coil predictors are available, but key issues remain: oligomeric state and protein–protein interface prediction and extension to all genomes. We present SpiriCoil (http://supfam.org/SUPERFAMILY/spiricoil), which is based on a novel approach to the coiled-coil prediction problem for coiled coils that fall into known superfamilies: hundreds of hidden Markov models representing coiled-coil-containing domain families. Using whole domains gives the advantage that sequences flanking the coiled coils help. SpiriCoil performs at least as well as existing methods at detecting coiled coils and significantly advances the state of the art for oligomer state prediction. SpiriCoil has been run on over 16 million sequences, including all completely sequenced genomes (more than 1200), and a resulting Web interface supplies data downloads, alignments, scores, oligomeric state classifications, three-dimensional homology models and visualisation. This has allowed, for the first time, a genomewide analysis of coiled-coil evolution. We found that coiled coils have arisen independently de novo well over a hundred times, and these are observed in 16 different oligomeric states. Coiled coils in almost all oligomeric states were present in the last universal common ancestor of life. The vast majority of occasions that individual coiled coils have arisen de novo were before the last universal common ancestor of life; we do, however, observe scattered instances throughout subsequent evolutionary history, mostly in the formation of the eukaryote superkingdom. Coiled coils do not change their oligomeric state over evolution and did not evolve from the rearrangement of existing helices in proteins; coiled coils were forged in unison with the fold of the whole protein.Coiled coils are α-helical interactions found in many natural proteins. Various sequence-based coiled-coil predictors are available, but key issues remain: oligomeric state and protein–protein interface prediction and extension to all genomes. We present SpiriCoil (http://supfam.org/SUPERFAMILY/spiricoil), which is based on a novel approach to the coiled-coil prediction problem for coiled coils that fall into known superfamilies: hundreds of hidden Markov models representing coiled-coil-containing domain families. Using whole domains gives the advantage that sequences flanking the coiled coils help. SpiriCoil performs at least as well as existing methods at detecting coiled coils and significantly advances the state of the art for oligomer state prediction. SpiriCoil has been run on over 16 million sequences, including all completely sequenced genomes (more than 1200), and a resulting Web interface supplies data downloads, alignments, scores, oligomeric state classifications, three-dimensional homology models and visualisation. This has allowed, for the first time, a genomewide analysis of coiled-coil evolution. We found that coiled coils have arisen independently de novo well over a hundred times, and these are observed in 16 different oligomeric states. Coiled coils in almost all oligomeric states were present in the last universal common ancestor of life. The vast majority of occasions that individual coiled coils have arisen de novo were before the last universal common ancestor of life; we do, however, observe scattered instances throughout subsequent evolutionary history, mostly in the formation of the eukaryote superkingdom. Coiled coils do not change their oligomeric state over evolution and did not evolve from the rearrangement of existing helices in proteins; coiled coils were forged in unison with the fold of the whole protein
Haven in noord-west Suriname: Konstruktieve uitwerking van enige onderdelen van de Constantijnhaven
No full textUit de funktionele eisen van de meer- en overslagkonstruktie (van de stukgoedterminal) en de kritieke faktoren opgelegd door de gebiedsomstandigheden en de havenaktiviteiten is de hoogte van het dek en de te verwachten belastingen bepaald. Daarmee is er een programma van eisen voor de genoemde konstrukties opgesteld. Voor de overslagkonstruktie zijn de mogelijkheden bekeken aan de hand van een ontwerpboom. Op basis van voornamelijk konstruktieve overwegingen is gekozen voor een dek op palen. De draagkonstruktie (hoofdliggers) van het dek en de palen worden uitgevoerd in beton terwijl het bovendeel van het dek (rijvloer en langsliggers) in hout wordt uitgevoerd. Voor de meerkonstruktie is gekozen voor een 'berthing beam' (meerbalk) in kombinatie met fenders. Konklusies: 1. Bij de berekening van de overslagkonstruktie is getracht om de konstruktie geheel in hout uit te voeren. Vanwege de beperkte dimensies van hout is dit echter niet mogelijk. Er is evenwel getracht om daar waar mogelijk wel in hout uit te voeren. 2. De gekozen en berekende kadekonstruktie (dek op palen) is heel zwaar uitgevallen. Voor definitieve toepassing moeten enige andere konstrukties (o.a. een damwand) uitgerekend worden om daarmee 'een vergelijking te maken.Hydraulic EngineeringCivil Engineering and Geoscience
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