588 research outputs found
The study of renal function and toxicity using zebrafish (Danio rerio) larvae as a vertebrate model
Zebrafish (Danio rerio) is a powerful model in biomedical and pharmaceutical sciences. The zebrafish model was introduced to toxicological sciences in 1960, followed by its use in biomedical sciences to investigate vertebrate gene functions. As a consequence of many research projects in this field, the study of human genetic diseases became instantly feasible. Consequently, zebrafish have been intensively used in developmental biology and associated disciplines. Due to the simple administration of medicines and the high number of offspring, zebrafish larvae became widely more popular in pharmacological studies in the following years. In the past decade, zebrafish larvae were further established as a vertebrate model in the field of pharmacokinetics and nanomedicines. In this PhD thesis, zebrafish larvae were investigated as an earlystage in vivo vertebrate model to study renal function, toxicity, and were applied in drug-targeting projects using nanomedicines.
The first part focused on the characterization of the renal function of three-to four-dayold zebrafish larvae. Non-renal elimination processes were additionally described. Moreover, injection techniques, imaging parameters, and post-image processing scripts were established to serve as a toolbox for follow-up projects.
The second part analyzed the impact of gentamicin (a nephrotoxin) on the morphology of the pronephros of zebrafish larvae. Imaging methodologies such as fluorescent-based laser scanning microscopy and X-ray-based microtomography were applied. A profound comparison study of specimens acquired with different laboratory X-ray-based microtomography devices and a radiation facility was done to promote the use of X-ray-based microtomography for broader biomedical applications.
In the third part, the toxicity of nephrotoxins on mitochondria in renal epithelial cells of proximal tubules was assessed using the zebrafish larva model. Findings were compared with other teleost models such as isolated renal tubules of killifish (Fundulus heteroclitus). In view of the usefulness and high predictability of the zebrafish model, it was applied to study the pharmacokinetics of novel nanoparticles in the fourth part. Various in vivo pharmacokinetic parameters such as drug release, transfection of mRNA/pDNA plasmids, macrophage clearance, and the characterization of novel drug carriers that were manipulated with ultrasound were assessed in multiple collaborative projects.
Altogether, the presented zebrafish model showed to be a reliable in vivo vertebrate model to assess renal function, toxicity, and pharmacokinetics of nanoparticles. The application of the presented model will hopefully encourage others to reduce animal experiments in preliminary studies by fostering the use of zebrafish larvae
Molecular modeling of drug delivery systems based on carbon nanostructures: structure, function, and potential applications for anticancer complexes of Pt(II)
The medication with Pt(II) drugs (cisplatin, carboplatin, and oxaliplatin) has been an effective
alternative for treating cancers due to their notable inhibition of cancer cells growth and the
prevention of metastasis. Nevertheless, the low selectivity of these metallodrugs for malignant
cells produces severe side effects, which limit this chemotherapy. In this context, carbon
nanohorns (CNHs) have been considered potential nanovectors for drugs, since they present
low toxicity, drug-loading capacity, biodegradation routes, and biocompatibility when
oxidized. However, there is still a lack of studies regarding the molecular behavior of these
nanocarriers on cell membranes. The present work aims to characterize the interactions between
inclusion complexes drug@CNH, which are formed by platinum drugs encapsulated in CNHs,
and plasma membranes by using molecular dynamics simulations. The results demonstrated
that the van der Waals contribution played a primary role (∼74%) for the complex stability,
which explain the confined dynamics of drugs inside the CNHs. The free energy profiles
revealed an endergonic character of the drug release processes from CNHs, in which the energy
barrier for oxaliplatin release (~24 kcal mol–1
) was ~30% larger than those for carboplatin and
cisplatin (~18 kcal mol-1
). The simulations also showed four stages of the interaction
mechanism CNH--membrane: approach, insertion, permeation, and internalization. Despite the
low structural disturbance of the membranes, the free energy barrier of ∼55 kcal mol-1 for the
CNHs translocation indicated that this transport is kinetically unfavorable by passive process.
The in silico experiments evidenced that the most likely mechanism of cisplatin delivery from
CNHs involve the approach and insertion stages, where the nanovector adheres on the surface
of cancer cells, as reported in in vitro studies. After this retention, the drug load may be slowly
released in the tumor site. Finally, simulations of the cellular uptake of Pt(II) drugs also pointed
out significant energy barriers (~30 kcal mol-1
) for this process, which reflects their low
permeability in membranes as discussed in experimental studies. In addition to reinforcing the
potential of CNH as nanovector of Pt(II) drugs, the results presented in this thesis may assist
and drive new experimental studies with CNHs, focusing on the development of less aggressive
formulations for cancer treatments.A medicação com fármacos a base de Pt(II) (cisplatina, carboplatina e oxaliplatina) tem sido
uma alternativa efetiva para tratar cânceres devido à sua notável inibição do crescimento de
células cancerosas e a prevenção de metástases. No entanto, a baixa seletividade dessas
metalodrogas por células cancerosas gera severos efeitos colaterais. Nesse contexto, nanohorns
de carbono (CNHs) têm sido considerados potenciais nanovetores de fármacos, devido a baixa
toxicidade, capacidade de carreamento de fármacos, rotas de biodegradação, e
biocompatibilidade quando oxidados. Porém, existe uma carência de estudos tratando o
comportamento desses nanocarreadores em biomembranas. Esse trabalho tem como objetivo
caracterizar as interações entre complexos de inclusão fármaco@CNH, formados por fármacos
de Pt(II) encapsulados em CNHs, e membranas usando simulações por dinâmica molecular. Os
resultados demonstraram que a contribuição de van der Waals teve um papel primário (∼74%)
na estabilidade dos complexos, o que explica a dinâmica confinada dos fármacos dentro dos
CNHs. Os perfis de energia livre revelaram o caráter endergônico da liberação dos fármacos a
partir de CNHs, nos quais a barreira de energia para a liberação da oxaliplatina (~24 kcal mol–
1
) é ~30% maior do que aquelas para carboplatina e cisplatina. As simulações mostraram quatro
estágios do mecanismo de interação CNH-membrana: aproximação, inserção, permeação e
internalização. Apesar do baixo distúrbio estrutural das membranas, a barreira de energia livre
de ∼55 kcal mol-1 para a translocação de CNHs indicou que esse transporte é desfavorável
cineticamente via o processo passivo. Os experimentos in silico evidenciam que o mecanismo
mais provável de entrega de cisplatina a partir de CNHs envolve a aproximação e inserção,
onde o nanovetor adere na superfície de células cancerosas, como reportado em estudos in vitro.
Após essa retenção, a carga de fármaco deve ser ligeiramente liberada no tumor. As simulações
de captação celular de fármacos de Pt(II) também apontaram barreiras de energia significativas
(∼30 kcal mol-1
) para esse processo, o que reflete a baixa permeabilidade deles em membranas
como discutido em estudos experimentais. Além de reforçar o potencial de CNHs como
nanovetores de fármacos de Pt(II), os resultados apresentados nessa tese podem auxiliar e
impulsionar novos estudos com CNHs, focando no desenvolvimento de formulações menos
agressivas para tratamentos de câncer.FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerai
Applications of Molecular Dynamics simulations for biomolecular systems and improvements to density-based clustering in the analysis
Molecular Dynamics simulations provide a powerful tool to study biomolecular systems with atomistic detail. The key to better understand the function and behaviour of these molecules can often be found in their structural variability. Simulations can help to expose this information that is otherwise experimentally hard or impossible to attain. This work covers two application examples for which a sampling and a characterisation of the conformational ensemble could reveal the structural basis to answer a topical research question. For the fungal toxin phalloidin—a small bicyclic peptide—observed product ratios in different cyclisation reactions could be rationalised by assessing the conformational pre-organisation of precursor fragments. For the C-type lectin receptor langerin, conformational changes induced by different side-chain protonations could deliver an explanation
of the pH-dependency in the protein’s calcium-binding. The investigations were accompanied by the continued development of a density-based clustering protocol into a respective software package, which is generally well applicable for the use case of extracting conformational states from Molecular Dynamics data
Applications of artificial intelligence to alchemical free energy calculations in contemporary drug design
The work presented in this thesis resides at the interface of alchemical free energy
methods (AFE) and machine-learning (ML) in the context of computer-aided drug
discovery (CADD). The majority of the work consists of explorations into regions
of synergy between the individual parts. The overarching hypothesis behind this
work is that although areas of high potential exist for standalone ML and AFE in
CADD, an additional source of value can be found in areas where ML and AFE are
combined in such a way that the new methodology profits from key strengths in
either part.
Physics-based AFE calculations have - over several decades - grown into precise
and accurate sub-kcal·mol−1
(in terms of mean absolute error versus experimental
measures) methods of predicting ligand-protein binding affinities which is the main
driver of its popularity in project support in drug design workflows. Data-driven
ML methods have seen a similar rapid development spurred by the exponential
growth in computational hardware capabilities, but are generally still lacking in
accuracy versus experimental measures of binding affinities to support drug design
work. Contrastingly, however, the first relies mainly on physical rules in the form
of statistical mechanics and the latter profits from interpolating signals within large
training domains of data.
After a historical and theoretical introduction into drug discovery, AFE calculations
and ML methods, the thesis will highlight several studies that reflect the above hypothesis along multiple key points in the AFE workflow. Firstly, a methodology that combines AFE with ML has been developed to compute accurate absolute hydration free energies. The hybrid AFE/ML methodology
was trained on a subset of the FreeSolv database, and retrospectively shown to
outperform most submissions from the SAMPL4 competition. Compared to pure
machine-learning approaches, AFE/ML yields more precise estimates of free energies
of hydration, and requires a fraction of the training set size to outperform standalone
AFE calculations. The ML-derived correction terms are further shown to be transferable to a range of related AFE simulation protocols. The approach may be used
to inexpensively improve the accuracy of AFE calculations, and to flag molecules
which will benefit the most from bespoke force field parameterisation efforts.
Secondly, early investigations into data-driven AFE network generators has been
performed. Because AFE calculations make use of alchemical transformations between ligands in congeneric series, practitioners are required to estimate an optimal
combination of transformations for each series. AFE networks constitute the collection of edges chosen such that all ligands (nodes) are included in the network and
where each edge is a AFE calculation. As there are a vast number of possible configurations for such networks this step in AFE setup suffers from several shortcomings
such as scalability and transferability between AFE softwares.
Although AFE network generation has been automated in the past, the algorithm
depends mostly on expert-driven estimation of AFE transformation reliabilities.
This work presents a first iteration of a data-driven alternative to the state-of-the-art using a graph siamese neural network architecture. A novel dataset, RBFE Space, is presented as a representative and transferable training domain for AFE
ML research. The workflow presented in this thesis matches state-of-the-art AFE
network generation performance with several key benefits. The workflow provides
full transferability of the network generator because RBFE-Space is open-sourced
and ready to be applied to other AFE softwares. Additionally, the deep learning
model represents the first robust ML predictor of transformation reliabilities in AFE
calculations. Finally, one major shortcoming of AFE calculations is its decreased reliability for
transformations that are larger than ∼5 heavy atoms. The work reported in this
thesis describes investigations into whether running charge, Van der Waals and bond
parameter transformations individually (with variable λ allocation per step) offers an
advantage to transforming all parameters in a single step, as is the current standard
in most AFE workflows. Initial results in this work qualitatively suggest that the
bound leg benefits from a MultiStep protocol over a onestep (”SoftCore”) protocol,
whereas the free leg does not show benefit. Further work was performed by Cresset
that showed no observable benefit of the MultiStep approach over the Softcore approach. Several key findings are reported in this work that illustrate the benefits of
dissecting an FEP approach and comparing the two approaches side-by-side
On the glass transition of bulk and confined polyamorphic liquids: A molecular dynamics simulations study
Supercooled liquids and the glass transition are not satisfactorily understood to date. The temperature dependence of dynamical properties eludes theoretical prediction. No model can be successfully applied to all liquids. One liquid is particularly complex in its supercooled regime - water. This seemingly simple liquid exhibits the most anomalies of any neat liquid, and most of these are thought to be related to the existence of two distinguishable liquid phases with different density in the supercooled regime, i.e., water exhibits polyamorphism. However, most of the relevant temperature range lies in the so-called no-man's land, a region of the phase diagram in which bulk water rapidly crystallizes and which is therefore experimentally inaccessible to the bulk liquid. Therefore, experimental studies often exploit the fact that crystallization of water is suppressed in nanoscopic confinements or water mixtures. The present work deals with both areas of research, water's polyamorphism and dynamics of supercooled liquids, confined and mixed, with the use of molecular dynamics simulations. They allow for detailed analysis and systematic variation of the liquid and enable easy supercooling.
Partial charges of the TIP4P/2005 and SPC/E water models were scaled which led to strong shifts of dynamics in temperature. These were reconciled by using the high-temperature activation energy as the relevant energy scale as long as structural properties were the same. For the TIP4P/2005 model and a set of reduced charges, isochore crossing in the phase diagram confirmed the existence of a liquid-liquid critical point (LLCP) in the supercooled regime at positive or negative pressures, depending on the molecular polarity. The two-structure equation of state (TSEOS) formalism was used to describe the data and determine the location of the LLCP. In addition, reduction of the partial charges accelerated dynamics at the LLCP and simulations with elongated boxes in the double metastable regime allowed for the coexistence of high-density (HDL) and low-density (LDL) liquid phases and the determination of their dynamics as a function of temperature. The results are in agreement with observations from isochoric and isobaric simulations and translational motion was observed for all state points. It was found that the temperature dependence of the dynamics at a constant fraction of the low-density state (LDS) is Arrhenius-like. Thus, the presumed fragile-to-strong transition (FST) of water is not caused by a transition from fragile HDL to strong LDL but by the fast transition between these liquid states when the system is cooled through the Widom line at constant pressure. This is consistent with experimental observations slightly above water's glass transition temperature Tg and reinforces the question of whether HDL or LDL on their own exhibit an FST. Models for the temperature dependence of reactive mixtures were tested but were unable to describe simulation results at the lowest studied temperatures.
A family of functional forms for the temperature dependence of dynamical properties of supercooled liquids was derived. These functions allow their description over the entire temperature range from the boiling point to the glass transition and with or without an FST. The second-order functions predict a high and low-temperature Arrhenius regime connected by an intermediate fragile regime. Knowledge of the path in the phase diagram of charge-scaled water-like systems, whether they cross the Widom line at increased charges or not, allowed for more rigorous testing of these functional forms. They are sensitive to deviations from Vogel-Fulcher-Tammann (VFT) behavior and apply well to data from charge-scaled water and silica simulations, which have a pronounced FST, as well as to real liquids. The possibility that supercooled liquids in general have a low-temperature Arrhenius regime and the characteristics of such FSTs were discussed.
Simulations of charge-scaled water models in chemically neutral pores were performed and static and dynamic length scales associated with changes of water's structure and dynamics near the pore wall were extracted. These correlation lengths were used to test theories of the glass transition and discussed in the context of water's two phases. Signs of crossing the Widom line could not be found in the temperature dependence of the correlation lengths within the moderately supercooled temperature range. The slowdown at the pore wall relative to the pore center was characterized using two empirical functions for additional activation energies caused by the liquid-confinement interface. Furthermore, the potential energy landscape (PEL) imprinted on the liquid was quantified using a novel approach based on Boltzmann statistics and predicted and measured mobility gradients are in agreement.
Lastly, the origin of slow solvent processes observed in dielectric spectroscopy studies of dynamically asymmetric binary mixtures was determined in simulations. For mixtures of picoline and poly-methylmethacrylate and of water and polylysine, fractions of slow solvent molecules were not found. Instead, the PEL imprinted by the slow polymer molecules causes preferred locations and orientations for the solvent molecules. A mechanism was proposed in which the solvent molecules exchange fast compared to the relaxation of the polymer molecules but have correlated orientations. This causes long-lived cross correlations that can be misinterpreted as slow solvent contributions in coherent measurements. Other sources of cross correlations were quantified and the dependency on measured molecular property and correlation function were discussed. The dynamical heterogeneity of solvent dynamics was traced back to the variation of the local solvent concentration and it is broad but unimodal. The same observations, slowly decaying cross correlations and absence of self correlation on these time scales, were made for other binary mixtures, suggesting that these effects are relevant to a wide range of systems
The role of dynamic hydrogen bond networks in protonation coupled dynamics of retinal proteins
Hydrogen bonds (H-bonds) are an essential interaction in membrane proteins. Embedded in complex hydrated lipid bilayers, intramolecular interactions through the means of hydrogen bonding networks are often crucial for the function of the protein. Internal water molecules that occupy stable sites inside the protein, or water molecules that visit transiently from the bulk, can play an important role in shaping local conformational dynamics forming complex networks that bridge regions of the protein via water-mediated hydrogen bonds that can function as wires for the transferring of protons as a part of the protein’s function. For example, the membrane-embedded channelrhodopsins which are found in archaea are proteins that couple light induced isomerization of a retinal chromophore with proton transfer reactions and passive flow of cations through their pore. I contributed to the development of a new algorithm package that features a unique approach to H-bond analyses. I performed analyses of long Molecular Dynamics (MD) trajectories of channelrhodopsin variants embedded in hydrated lipid membranes and large data sets of static structures, to detect and dissect dynamic hydrogen-bond networks. The photocycle of channelrhodopsins begins with absorption and isomerization of the retinal from an all-trans state to a 13-cis state and followed by the deprotonation of the Schiff base. Thus, the retinal is found in the epicenter of the analyses. Through the use of 2-dimensional graphs of the protein H-bond networks I identified protein groups potentially important for the proton transfer activity. Local dynamics are highly affected by point mutations of amino acids important for function. The interior of channelrhodopsin C1C2 hosts extensive networks of protein and H-bonded-water molecules, and a never reported before, network that can bridge transiently the two retinal chromophores in channelrhodopsin dimers.
In a recently identified inward proton pump, AntR, I applied centrality measures on MD trajectories of the homology model I generated, to assess the communication of the amino acid residues within the networks. I detected a frequently sampled long water chain that connects the retinal with a candidate proton acceptor, as well as a conserved serine in the vicinity of the retinal chromophore plays a significant role in the connectivity and communication of the H-bond networks upon isomerization. A similar water bridge is sampled in independent simulations of ChR2, where a participant for the proton donor group connects to the 13-cis,15-anti retinal. Proton transfer reactions often take place through certain amino acids, forming patterns. I analyzed H-bond patterns or motifs in large hand-curated datasets of static structures of α-transmembrane helix proteins, organized according to the superfamilies they belong, their function and an alternative classification method. The presence of motifs in TM proteins is tightly related to their families/superfamilies of the host protein and their position along the membrane normal.Wasserstoffbrücken (H-Brücke) sind eine wesentliche Wechselwirkung in Membranproteinen. Eingebettet in komplexe hydratisierte Lipiddoppelschichten sind intramolekulare Wechselwirkungen über Wasserstoffbrückenbindungsnetzwerke oft entscheidend für die Funktion des Proteins. Interne Wassermoleküle, die stabile Stellen im Inneren des Proteins besetzen, oder Wassermoleküle, die vorübergehend aus der Masse zu Besuch kommen, können eine wichtige Rolle bei der Gestaltung der lokalen Konformationsdynamik spielen, indem sie komplexe Netzwerke bilden, die Regionen des Proteins über wasservermittelte Wasserstoffbrückenbindungen überbrücken, die als Drähte für den Transfer von Protonen als Teil der Proteinfunktion funktionieren können. Die in Archaeen vorkommenden, in die Membran eingebetteten Kanalrhodopsine sind beispielsweise Proteine, die die lichtinduzierte Isomerisierung eines Retinachromophors mit Protonentransferreaktionen und dem passiven Fluss von Kationen durch ihre Pore verbinden. Ich habe an der Entwicklung eines neuen Algorithmuspakets mitgewirkt, das einen einzigartigen Ansatz für H-Bindungsanalysen bietet. Ich habe lange Molekulardynamik-Trajektorien von Kanalrhodopsine-Varianten, die in hydratisierte Lipidmembranen eingebettet sind, sowie große Datensätze statischer Strukturen analysiert, um dynamische Wasserstoffbrücken-bindungsnetzwerke zu erkennen und zu zerlegen. Der Photozyklus der Kanalrhodopsine beginnt mit der Absorption und Isomerisierung des Retinals von einem all-trans-Zustand zu einem 13-cis-Zustand, gefolgt von der Deprotonierung der Schiff-Base. Somit steht das Retinal im Mittelpunkt der Analysen. Durch die Verwendung von 2-dimensionalen Graphen der Protein- H-Brückenetzwerke identifizierte ich Proteingruppen, die für die Protonentransferaktivität wichtig sein könnten. Die lokale Dynamik wird durch Punktmutationen der für die Funktion wichtigen Aminosäuren stark beeinflusst. Das Innere von Kanalrhodopsine C1C2 beherbergt ausgedehnte Netzwerke von Protein- und H-Brücke-Wassermolekülen und ein bisher unbekanntes Netzwerk, das die beiden retinalen Chromophore in Kanalrhodopsine-Dimeren vorübergehend überbrücken kann.
In einer kürzlich identifizierten Protonenpumpe, AntR, wendete ich Zentralitätsmaße auf MD-Trajektorien des von mir erstellten Homologiemodells an, um die Kommunikation der Aminosäurereste innerhalb der Netzwerke zu bewerten. Ich fand, dass eine häufig gesampelte lange Wasserkette, die das Retinal mit einem Protonenakzeptor verbindet, sowie ein konserviertes Serin in der Nähe des Retinal-Chromophors eine wichtige Rolle bei der Konnektivität und Kommunikation der H-Brückesnetzwerke bei der Isomerisierung spielt. Eine ähnliche Wasserbrücke ist in unabhängigen Simulationen von Kanalrhodopsine-2 zu finden, wo ein Teilnehmer für die Protonendonorgruppe mit dem 13-cis,15-anti-Retinal verbunden ist. Protonenübertragungsreaktionen finden oft über bestimmte Aminosäuren statt und bilden Muster. Ich analysierte H-Brückemuster oder -motive in großen, von Hand kuratierten Datensätzen statischer Strukturen von α-Transmembranhelix-Proteinen, geordnet nach den Superfamilien, zu denen sie gehören, ihrer Funktion und einer alternativen Klassifizierungsmethode. Das Vorhandensein von Motiven in TM-Proteinen steht in engem Zusammenhang mit ihren Familien/Superfamilien des Wirtsproteins und ihrer Position entlang der Membrannormale
Estudios computacionales de mecanismos moleculares de la inmunidad innata
Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, leída el 20-12-2022Antimicrobial Resistance (AMR) is a worldwide health emergency. ESKAPE pathogens include the most relevant AMR bacterial families. In particular, Gram-negative bacteria stand out due to their cell envelope complexity, which exhibits strong resistance to antimicrobials. A key element for AMR is the chemical structure of bacterial lipopolysaccharide (LPS), and the phospholipid composition of the membrane, inflecting the membrane permeability to antibiotics. We have applied coarse-grained molecular dynamics simulations to capture the role of the phospholipid composition and lipid A structure in the membrane properties and morphology of ESKAPE Gram-negative bacterial vesicles. Moreover, the reported antimicrobial peptides Cecropin B1, JB95, and PTCDA1-kf were used to unveil their implications for membrane disruption. This study opens a promising starting point for understanding the molecular keys of bacterial membranes and promoting the discovery of new antimicrobials to overcome AMR...La resistencia a los antimicrobianos (AMR) es una emergencia sanitaria mundial. Los patógenos ESKAPE incluyen las familias bacterianas más resistentes a antibióticos y son altamente virulentas. En particular, las bacterias Gram negativas destacan por la complejidad de su pared celular, que presenta una fuerte resistencia frente a los antibióticos. Un elemento clave para la AMR es la estructura química del lipopolisacárido bacteriano (LPS) y la composición de los fosfolípidos de la membrana bacteriana, que influyen en su permeabilidad a los antibióticos. Se han empleado simulaciones de dinámica molecular de grano grueso para captar el papel de la composición de los fosfolípidos y la estructura del LPS en las propiedades y morfología de modelos de vesículas bacterianas Gram negativas ESKAPE. Además, se han empleado los péptidos antimicrobianos Cecropin B1, JB95 y PTCDA1-kf para desvelar su mecanismo disrupción de la membrana bacteriana. Este estudio abre un prometedor punto de partida para comprender las claves moleculares de la resistencia en membranas bacterianas y acelerar el descubrimiento de nuevos antibióticos para hacer frente a la AMR...Fac. de FarmaciaTRUEunpu
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Molecular modelling and biological implications of non-canonical structures in RNA viruses and long non-coding RNAs
Guanine quadruplexes folding in single-strand DNA have been extensively studied for some time. But far less attention has been paid to systems arising in duplex DNA or RNA. Furthermore, the literature shows an apparent absence of quadruplex systems generated exclusively by other nucleic acid bases. With guanine quadruplexes (G4s) as a benchmark, a comparison is made here with equivalent complexes folding in DNA and RNA when derived from cytosine, thymine and adenine. Molecular dynamics simulations determined cytosine and thymine models in DNA as relatively fragile systems, but all non-guanine RNA models were found to be stable into biologically relevant times. Uniquely biplanar or triplanar adenine quadruplexes (A4s) have ostensibly not been described. Adenine models constructed for this work were resolved in silico with stabilities comparable to known guanine equivalents. These complexes achieved further significance with the advent of SARS-CoV-2.
RNA viruses are characterised by a poly-adenylated structure capping the genomic terminus. This poly(A) tail is crucial to a cascade of viral replicative activity occurring both extra- and intra-cellular during infection. As a route to proposing potential chemotherapy, this study suggests simple biplanar A4s may fold in this poly-adenylated domain. Notably, mRNA configured as a biplanar A4, shows less dynamic activity than DNA equivalents. This observation may be especially relevant in a physiological context. In contrast to well-characterised guanine quadruplexes, co-ordination with cations appears not to impact on stability. These conclusions may apply to SARS-CoV-2, its variants and other pathogenic RNA viruses.
The thesis also infers models of potential interactions between small nucleolar RNAs and long non-coding RNAs may have biological relevance. Non-canonical base-pairing in some instances suggests a molecular mechanism for dysfunction in the development of the embryonic pre-frontal cortex
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