Dibenzodiazepinone-type mAChR ligands: radio- and fluorescence labeling enable unveiling of dualsteric M₂R binding and conjugation to short peptides as an avenue to highly selective M₂R ligands

In humans, the family of muscarinic acetylcholine receptors (mAChR, MRs) comprises five subtypes (M1R-M5R), which are members of the class A GPCR superfamily and mediate the action of the neurotransmitter acetylcholine in the central and peripheral nervous system. For instance, the M2R, which binds to Gi/o heterotrimeric G-proteins, acts as a presynaptic autoreceptor in the brain and in the periphery. Accordingly, selective M2R antagonism in the CNS results in an enhanced cholinergic transmission, representing a potential therapeutic approach to increase cholinergic function in Alzheimer patients. The development of high affinity and selective MR ligands has been hampered by the high conservation of the orthosteric (acetylcholine) binding site within the five MR subtypes. Therefore, highly selective molecular tools and therapeutic agents, acting at MRs, are lacking. MRs possess various accessory (allosteric) binding sites, which are less conserved. This prompted the design of numerous allosteric MR ligands. However, allosteric modulators with high MR affinity (Ki < 0.1 µM) are not described to date. The dualsteric ligand approach, that means, the design of ligands, which simultaneously bind to the orthosteric pocket and an allosteric site, was suggested as a promising strategy to develop high-affinity and highly selective MR ligands. In order to investigate the binding mode of dibenzodiazepinone-type MR antagonists at the M2R, three radiolabeled compounds, a monomeric ([3H]19) and two homodimeric ([3H]33, [3H]47) derivatives, were prepared. The results from various detailed experiments performed with [3H]19 and [3H]33, in particular saturation binding studies in the absence and in the presence of reported allosteric M2R ligands, strongly suggested that the studied type of M2R antagonists bind dualsterically to the M2R, interacting simultaneously with both, the orthosteric and the ‘common’ allosteric binding site. The results from molecuclar dynamics (MD) simulations, performed with the M2R (inactive state) bound to 19 or 33, were consistent with the conclusions drawn from radioligand binding studies. Interestingly, the homodimeric ligand 33, in contrast to the monomeric ligand 19, showed a long residence time at the M2R, which might be attributed, as also suggested by MD simulations, to additional contacts of 33 with amino acids constituting the allosteric vestibule. Moreover, five fluorescently labeled dibenzodiazepinone-type MR ligands (including two homodimeric and one heterodimeric derivative) were prepared using red-emitting cyanine dyes. Equilibrium competition binding studies with the orthosteric antagonist [3H]NMS revealed high M2R affinities for all fluorescent ligands (pKi = 8.85-9.59). Flow cytometric and high-content imaging-based binding experiments with a monomeric (62) and a homodimeric (64) fluorescent ligand in the presence of the reported allosteric modulator W84 (8) suggested that the fluorescent dibenzodiazepinone-type MR ligands bind dualsterically to the M2R, as also concluded for the tritium-labeled analogs [3H]19 and [3H]33. Confocal microscopy with 62 and 64 at CHO-hM2R cells revealed that binding of the fluorescent probes occurred mainly at the cell membrane, and an increase of intracellular fluorescence was not observed with increasing incubation time. Finally, aiming at MR ligands with improved M2R selectivity, the dibenzodiazepinone pharmacophore was conjugated to several di- and tripeptides via two different linkers yielding a series of non-peptide/peptide hybrid ligands (DIBA-peptide conjugates). The affinity and the selectivity profile of these compounds was assessed by radioligand competition binding at CHO-hMxR cells (x = 1-5) using [3H]NMS. The introduction of two basic amino acids (Arg, Lys) yielded the DIBA-peptide conjugates with the highest M2R selectivity (compound 96 (aliphatic linker, peptide sequence Lys-Arg): Ki M1R:M2R:M3R:M4R:M5R = 58:1:6900:99:300; compound 108 (basic linker, peptide sequence Lys-Ala-Arg): Ki M1R:M2R:M3R:M4R:M5R = 49:1:1800:70:3500). The DIBA-peptide conjugates 96 and 108 represent the most selective M2R antagonists reported to date with M2R binding constants in the low nanomolar (96, pKi = 9.00) and in the picomolar (108, pKi = 10.21) range. Thus, this new class of compounds represents a valuable basis for the development of high affinity and highly selective M2R antagonists. Taken together, the present work afforded new radio- and fluorescence labeled molecular tools, which bind with high affinity to the M2R. Moreover, the conjugation of the dibenzodiazepinone pharmacophore to short peptides yielded high affinity M2R ligands with improved M2R selectivity compared to previously reported M2 subtype preferring MR ligands

Role of Novel Immunoregulatory Long Noncoding RNAs in Airway Epithelial Pathophysiology and Chronic Pulmonary Disease

COPD is currently the third leading cause of death globally, accounting for approximately 6% of all deaths in 2019, and cigarette smoke (CS) is the primary risk factor for disease development. Transcriptomic analysis of a 3D in vitro model using differentiated human airway epithelial cells (AECs) identified a novel lncRNA on the antisense strand of ICAM-1 or LASI that showed increased expression upon CS exposure. The lncRNA was significantly upregulated in CS-induced Rhesus macaque airways and in human COPD airways that exhibited higher mucus expression and goblet cell hyperplasia, which was recapitulated in vitro. Blocking lncRNA expression in cell culture setting suppressed the smoke-induced and COPD-associated dysregulated mucoinflammatory response suggesting that this airway specific immunomodulatory lncRNA may represent a novel target to mitigate the smoke-mediated inflammation and mucus hyperexpression. Additionally, not much is known about contribution of airway lncRNAs in COVID-19. RNA-sequencing analysis of nasal samples from COVID-19 patients showed significantly higher expression of secretory mucin and inflammatory gene signatures compared to the uninfected controls. COVID-19 patients showed elevated expression of inflammatory factors, airway mucins and associated transcription factors. LASI was induced in COVID-19 patients with high viral-load. A SARS-CoV-2 infected 3D-airway model largely recapitulated these clinical findings. Molecular dynamic modeling further suggested a stable interaction between viral RNA and LASI lncRNA. Notably, blocking LASI lncRNA reduced SARS-CoV-2 viral load and suppressed MUC5AC mucin levels. LASI lncRNA represents an essential facilitator of SARS-CoV-2 infection and associated airway mucoinflammatory response. Altogether, LASI lncRNA may represent a novel target to control the smoke-mediated dysregulation in airway responses and COPD exacerbations, as well as in viral infection-related inflammatory responses

Exploring the Multifaceted Roles of Glycosaminoglycans (GAGs) - New Advances and Further Challenges

Glycosaminoglycans are linear, anionic polysaccharides (GAGs) consisting of repeating disaccharides. GAGs are ubiquitously localized throughout the extracellular matrix (ECM) and to the cell membranes of cells in all tissues. They are either conjugated to protein cores in the form of proteoglycans, e.g., chondroitin/dermatan sulfate (CS/DS), heparin/heparan sulfate (Hep/HS) and keratan sulfate (KS), as well as non-sulfated hyaluronan (HA). By modulating biological signaling GAGs participate in the regulation of homeostasis and also participate in disease progression. The book, entitled “Exploring the multifaceted roles of glycosaminoglycans (GAGs)—new advances and further challenges”, features original research and review articles. These articles cover several GAG-related timely topics in structural biology and imaging; morphogenesis, cancer, and other disease therapy and drug developments; tissue engineering; and metabolic engineering. This book also includes an article illustrating how metabolic engineering can be used to create the novel chondroitin-like polysaccharide.A prerequisite for communicating in any discipline and across disciplines is familiarity with the appropriate terminology. Several nomenclature rules exist in the field of biochemistry. The historical description of GAGs follows IUPAC and IUB nomenclature. New structural depictions such as the structural nomenclature for glycan and their translation into machine-readable formats have opened the route for cross-references with popular bioinformatics resources and further connections with other exciting “omics” fields

Computer-Generated Holography for Areal Additive Manufacture

With a market of approximately $10B, additive manufacture (AM) is an exciting next-generation technology with the promise of significant environmental and societal impact. AM promises to help reduce emissions and waste during manufacture while improving sustainability. Widely used in applications from hip implants to jet engines, AM remains the domain of experts due to the material and thermal challenges encountered. AM in metals is dominated by Laser Powder Based Fusion (L-PBF). Powder is spread in layers 10s of microns thick and selectively melted by scanning a small laser spot heat source over the bed. Traditional AM systems have limited ability to manage or compensate for heat generated. The rapidly moving heat source spot results in high thermal cycling and is a major influence on residual stress and distortion. Mechanical limitations in the galvoscanner mean that over or under-heating is common and can lead to voids, boiling and spatter. The scale difference between the part size and the spot size means that predictive modelling is beyond the scope of even today’s best computing clusters. These factors have led to frequent inability to ensure part quality without physical prototyping and destructive testing. This thesis sets out initial research into creating a radically new AM process that uses computer-generated holography (CGH) to produce complex light patterns in a single pulse. Projecting power to the whole layer at once will mean that the thermal properties of the powders before and after writing can be factored into the processed hologram and part design. It will also significantly reduce thermal gradients and melt-pool instability. The fields of additive manufacture and computer-generated holography are introduced in Chapter 1. Chapters 2 and 3 then provide more detail on CGH and AM modelling respectively. The first deliverable, a reusable software package capable of generating holograms, is presented in Chapter 4. Algorithms developed for the project are introduced in Chapter 4.3. The first project demonstrator, an AM machine capable of printing in resins using holographic projection is discussed in Section 6.2. This shows performance comparable to modern 3D printing machines and highlights the applicability of computer-generated holography to areal processes. Section 6.3 then discusses the ongoing development of a metal powder demonstrator. As this PhD forms the first stage of a larger project, only preliminary work on the powder demonstrator is discussed. Chapter 7 then draws conclusions and outlines the way forward for future research. The thesis appendices then discuss an in-depth discussion of algorithm performances in Appendices A and B. Appendices C and D then discuss digressions into the implementation. Appendices E and F present a laser induced damage threshold (LIDT) measurement system developed. Finally, Appendices G and H provide more detail on the software developed and Appendix I gives links to additional project resources.EP/T008369/1; EP/L016567/1; EP/V055003/

Sex-related responses of blue mussels to the plasticiser DEHP under climate change scenarios

Climate change and plastic pollution are both pressing environmental issues. Little is known, however, about the combined effect of climate change conditions (such as global warming and ocean acidification) and plastic contaminants (such as the additive di-2-ethylhexyl phthalate DEHP), and whether this effect differs by sex. In fact, sex and gametogenesis status of individuals can influence a vast array of biological responses of several species, including the commercially important blue mussel Mytilus spp.This thesis investigates the consequences of DEHP exposure at environmentally relevant concentrations, alone or in combination with end-of-the-century simulated climate change conditions. A general effect of DEHP on mussel reproductive traits was observed, which confirmed the endocrine disruptive nature of this plasticiser. Specifically, fertility outcomes and estrogen receptor-related pathways were affected by the exposure, especially in female individuals. Overall, when combined with increased temperature or lowered pH, DEHP affected histological, molecular, transcriptomic, metabolic and behavioural systems at various degrees. Furthermore, as it was previously noted for other endocrine disruptive chemicals, the additive DEHP seemed to display a non-monotonic dose-response curve, provoking a stronger effect at low concentrations than at higher levels. Climate change stressors were also noticed to elicit a response in exposed individuals, especially increased temperature on spawning events and lowered pH on valve behaviours. Finally, when analysing the gene expression outcomes, sex and gametogenesis stage were considered useful predictive factors for interpreting the molecular datasets

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog

In Silico Strategies for Prospective Drug Repositionings

The discovery of new drugs is one of pharmaceutical research's most exciting and challenging tasks. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address our clinical challenges (e.g., new antibiotics, new anticancer drugs, new antivirals).Within this framework, drug repositioning—finding new pharmacodynamic properties for already approved drugs—becomes a worthy drug discovery strategy.Recent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, drug–target and drug–drug interactions, advances in human biochemistry, and the latest molecular and cellular biology discoveries.Following this new and exciting trend, this book is a collection of papers introducing innovative computational methods to identify potential candidates for drug repositioning. Thus, the papers in the Special Issue In Silico Strategies for Prospective Drug Repositionings introduce a wide array of in silico strategies such as complex network analysis, big data, machine learning, molecular docking, molecular dynamics simulation, and QSAR; these strategies target diverse diseases and medical conditions: COVID-19 and post-COVID-19 pulmonary fibrosis, non-small lung cancer, multiple sclerosis, toxoplasmosis, psychiatric disorders, or skin conditions