140 research outputs found

    An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles

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    Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease.Peer reviewe

    A geometrical framework for thinking about proteins

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    We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre-sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity

    Computational Approaches to Generating Diverse Enzyme Panels

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    Ph. D. ThesisMotivation Enzymes are complex macromolecules crucial to life on earth. From bacteria to human beings, all organisms use enzymes to catalyse the many thousands of chemical reactions occurring in their cells. Enzyme functions are so diverse that the use of enzymes in industries like pharmaceuticals and agriculture has gained popularity over recent years as ”biocatalysts”. Unfortunately, the confident laboratory-based characterisation of enzyme function has lagged behind a massive increase in sequencing data, slowing down initiatives that look to use biocatalysts as part of their chemical processes. Computational methods for identifying biocatalysts do exist, but often falter due to the complexity of enzymes and sequence bias, leaving much of the catalytic space of enzymes and their families undiscovered. This thesis has two major themes: the development of in silico approaches for curating diverse panels of novel enzyme sequences for experimental characterisation, and of tooling that integrates in silico panel creation and in vitro enzyme characterisation into a unified and iterative framework. Contributions of this thesis The contributions of this thesis can be divided into the two larger themes, starting with the diverse panel selection of sequences from an enzyme family: • A novel type of protein network based on patterns of coevolving residues that can be used to identify functionally-interesting groupings in enzyme families. • The automatic sampling of functionally diverse subsets of enzyme sequences by solving the maximum diversity problem. - i - • A study into the viability of artificially increasing enzyme family diversity through neural networks-based generation of synthetic sequences. The second theme, which deals with built tools for bridging the gap between the in silico and in vitro side of enzyme family exploration: • A platform that integrates the panel selection process and resulting characterisation data to promote an iterative approach to exploring enzyme families. • A repository for storing the metadata generated by the major steps of characterisation assays in the lab.EPSRC and Prozomix Limite

    MOLECULAR DESIGN STRATEGIES AND IMAGING OF ELECTRONIC PEPTIDE NANOMATERIAL SCAFFOLDS

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    Peptide-pi conjugated materials represent a powerful class of supramolecular materials with the unique ability to bridge the traditionally disparate realms of electronics and biological settings. The modular nature of peptide synthesis has facilitated systematic investigations into the impacts of amino acid composition for material properties. This dissertation presents design strategies to achieve new conformations and electronic outcomes within these peptide materials, efforts to characterize mixed peptide assemblies on the nanoscale and attempts to employ them in biological settings. In chapter 1 the state of organic electronics and its extensions to bioelectronics is introduced. Previous efforts from our lab to control peptide-pi-peptide scaffolds through monomer design and assembly trigger are discussed. Then, the fundamentals of electron microscopy are reviewed along with electron specimen interactions and their use in characterizing nanomaterials. In chapter 2, constitutional isomerism brought about by swapping regimes of unique hydrophobicity and the influence on physical properties, morphology, and electronic communication among pi-cores is examined. The addition of a purely hydrophobic alkyl tail is also discussed wherein access to a range of nanoarchitectures without diluting the impacts of constitutional isomerism is demonstrated. Chapter 3 details efforts to use bromine and sulfur as elemental indicators of co-assembly or self-sorting and examine the nanoscopic details of mixed assemblies by way of STEM-EDS mapping. This characterization method is applied to statistically mixed co-assemblies, self-sorted structures based on exploiting subtle pKa differences as previously reported by our lab, and a novel self-sorting paradigm brought about by tailoring specific monomer-monomer interactions. In chapter 4, the field of diphenylalanine research and extensive efforts to effectuate control over the assembly of this unique dipeptide are discussed. iii Efforts to control the assembly of diphenylalanine by single fluorine substitution at the beta-carbon are explored wherein preliminary studies suggest that this relatively small change in structure can have dramatic impacts on assembly. Chapter 5 is concerned with biologically relevant nanomaterials and the promise of peptide-pi conjugates in 3D cell culture applications. Both failed and successful attempts to prepare a hydrogel scaffold containing attributes known to guide neuronal stem cells toward neuronal lineages are presented. Finally, promising efforts to translate peptide-pi-peptide nanomaterials to in vivo stroke recovery models are detailed

    The Role of PPARs in Disease

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    This reprint combines recent original manuscripts and reviews covering the multiple functions of peroxisome proliferator-activated receptors in physiology and pathophysiology. Potential applications and limitations of PPAR agonists and antagonists are discussed. All original contributions were published in Cells

    Multifunctional Hybrid Materials Based on Polymers: Design and Performance

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    Multifunctional hybrid materials based on polymers have already displayed excellent commitment in addressing and presenting solutions to existing demands in priority areas such as the environment, human health, and energy. These hybrid materials can lead to unique superior multifunction materials with a broad range of envisaged applications. However, their design, performance, and practical applications are still challenging. Thus, it is highly advantageous to provide a breakthrough in state-of-the-art manufacturing and scale-up technology to design and synthesize advanced multifunctional hybrid materials based on polymers with improved performance.The main objective of this interdisciplinary book is to bring together, at an international level, high-quality elegant collection of reviews and original research articles dealing with polymeric hybrid materials within different areas such as the following:- Biomaterials chemistry, physics, engineering, and processing;- Polymer chemistry, physics and engineering;- Organic chemistry;- Composites science;- Colloidal chemistry and physics;- Porous nanomaterials science;- Energy storage; and- Automotive and aerospace manufacturing

    Investigations toward the rational modulation of G protein-coupled receptor signalling pathways using in silico methods

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    G protein-coupled receptors (GPCRs) are one of the most important protein families and function as signal transducers located in the cell membrane. Currently, about one third of the marketed drugs target a GPCR, reflecting its importance in therapy and disease. Thus, it is not surprising that GPCRs and their signalling are of major interest for researchers. In this thesis, in silico methods were used to investigate the modulation of GPCR signalling pathways. The modulation of GPCR signalling can take place on different levels, e.g. at the level of GPCR ligands or in the downstream signalling pathways. Interactions of the receptor with small molecules can result either in its inactivation or activation. The latter can lead to the intracellular recruitment of various effector proteins to the receptor which can then induce different signalling pathways inside the cell. Certain ligands can induce a stronger recruitment of one effector protein compared to other effector proteins. On a structural basis it is still unclear why and how these ligands induce such bias. Furthermore, there are many different proteins involved in the downstream signalling of GPCRs. One protein family are the Regulators for G protein Signalling (RGS) which are involved in the deactivation of the G protein and, hence, GPCR signalling. Although the members of this protein family are known to be involved in a variety of processes and diseases –many of which are also related to GPCR signalling– they are still not well understood. GPCR signalling needs to be comprehended better on all of these levels to be able to modulate them rationally. In this thesis, two GPCRs –the β2-adrenergic receptor (β2AR) and the Cannabinoid receptor 2 (CB2)– and one member of the RGS protein family –the RGS7– were targeted with in silico techniques in five studies to investigate their signalling and its modulation. Two of the studies described in this thesis targeted the β2AR. More than 30 structures of this class A GPCR in different activation states are available, allowing for more exhaustive structural investigations. This fact was used and three different structures of the β2AR in different activation states were targeted with a molecular library using a comparative docking approach. The aim was to predict novel agonists for this receptor based on the assumption that these should rather result from docking calculations against active conformations of the receptor. The selected molecules were then characterised pharmacologically, showing that this approach was very successful. Furthermore, a retrospective analysis of the docking approach showed up the optimal way to increase the chances to discover novel agonists for this receptor or other class A GPCRs. The aim of the second study targeting the β2AR was to predict antagonists with novel structural scaffolds for this receptor using docking calculations. The project was conducted in collaboration with InterAx Biotech AG who also characterised the selected ligands pharmacologically. An antagonist for the β2AR with a previously undescribed structural scaffold was successfully predicted in this study and a structure-activity relationship investigation showed the general affinity of this structural scaffold for this receptor. The second studied GPCR was the CB2. In one study, molecular docking was applied to find structurally novel ligands for the CB2. For that, the docking setups were first optimised using a set known reference ligands. The prediction of water positions in the orthosteric binding pocket was shown to be a useful tool to achieve optimised docking results. These docking setups were then targeted by a large molecular library docking screen and several re-ranking and filtering steps were used to achieve better enrichment, similar to one of the approaches targeting the β2AR. The selected molecules were then tested by collaboration partners from the Veprintsev lab at the University of Nottingham and preliminary results suggest that this screen was successful. In the second study, Molecular Dynamics simulations were applied to the CB2 to investigate the structural basis of ligands inducing a certain recruitment bias. The results showed that it might be difficult to track recruitment bias with this method, however, indicators for receptor activation and deactivation could be observed. In the last study, the RGS7-Gβ5 complex was targeted using docking calculations. The overall goal is to find small molecules that can bind to this complex, thereby modulating its conformation and possibly its function. However, no binding sites of small molecules on this complex are known. Therefore, the main part of the study consisted of the prediction and evaluation of possible binding sites. Promising cavities were identified and will be targeted in docking screens to investigate whether they can serve the proposed function. This project was conducted in collaboration with the Martemyanov lab at the Scripps Research Institute in Florida. Overall, the described studies were able to (1) show up ideas on how to best employ in silico tools to obtain the desired results, (2) find potential small molecule binding sites for a quite unexplored but therapeutically interesting target, (3) give insights on dynamic processes and structural rearrangements of receptor-ligand interactions leading to (biased) signalling and (4) successfully predict several novel ligands with different properties for two different GPCR targets with hit rates of up to 37%

    Spontaneous dimensional reduction and novel ground state degeneracy in a simple chain model

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    Chain molecules play a key role in the polymer field and in living cells. Our focus is on a new homopolymer model of a linear chain molecule subject to an attractive self-interaction promoting compactness. We analyze the model using simple analytic arguments complemented by extensive computer simulations. We find several striking results: there is a first order transition from a high temperature random coil phase to a highly unusual low temperature phase; the modular ground states exhibit significant degeneracy; the ground state structures exhibit spontaneous dimensional reduction and have a two-layer structure; and the ground states are assembled from secondary motifs of helices and strands connected by tight loops. We discuss the similarities and notable differences between the ground state structures (we call these PoSSuM -- Planar Structures with Secondary Motifs) in the novel phase and protein native state structures.Comment: 14 pages, 5 figure

    Onco-Receptors Targeting in Lung Cancer via Application of Surface-Modified and Hybrid Nanoparticles: A Cross-Disciplinary Review

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    Lung cancer is among the most prevalent and leading causes of death worldwide. The major reason for high mortality is the late diagnosis of the disease, and in most cases, lung cancer is diagnosed at fourth stage in which the cancer has metastasized to almost all vital organs. The other reason for higher mortality is the uptake of the chemotherapeutic agents by the healthy cells, which in turn increases the chances of cytotoxicity to the healthy body cells. The complex pathophysiology of lung cancer provides various pathways to target the cancerous cells. In this regard, upregulated onco-receptors on the cell surface of tumor including epidermal growth factor receptor (EGFR), integrins, transferrin receptor (TFR), folate receptor (FR), cluster of differentiation 44 (CD44) receptor, etc. could be exploited for the inhibition of pathways and tumor-specific drug targeting. Further, cancer borne immunological targets like T-lymphocytes, myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), and dendritic cells could serve as a target site to modulate tumor activity through targeting various surface-expressed receptors or interfering with immune cell-specific pathways. Hence, novel approaches are required for both the diagnosis and treatment of lung cancers. In this context, several researchers have employed various targeted delivery approaches to overcome the problems allied with the conventional diagnosis of and therapy methods used against lung cancer. Nanoparticles are cell nonspecific in biological systems, and may cause unwanted deleterious effects in the body. Therefore, nanodrug delivery systems (NDDSs) need further advancement to overcome the problem of toxicity in the treatment of lung cancer. Moreover, the route of nanomedicines’ delivery to lungs plays a vital role in localizing the drug concentration to target the lung cancer. Surface-modified nanoparticles and hybrid nanoparticles have a wide range of applications in the field of theranostics. This cross-disciplinary review summarizes the current knowledge of the pathways implicated in the different classes of lung cancer with an emphasis on the clinical implications of the increasing number of actionable molecular targets. Furthermore, it focuses specifically on the significance and emerging role of surface functionalized and hybrid nanomaterials as drug delivery systems through citing recent examples targeted at lung cancer treatment.The APC was funded through PHOTO-EMULSION project. Financing entity: European Union H2020-MSCA-ITN-2017
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