109 research outputs found
NeighborNet: improved algorithms and implementation
NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions
Development and characterisation of thermal responsive shape memory natural rubber
Compared to the last century, research and development of smart materials are receiving more attention due to their ability to change shape in response to specific environmental conditions. Although the development of shape memory natural rubber is motivated by the higher recovery strain, low trigger temperature leads to poor shape memory performance typically when the surrounding temperature is increased. A new shape memory natural rubber fabrication method, prevulcanisation is proposed to maintain the crystalline structure of the rubber molecule at elevated temperature. The low molar fatty acid which is palmitic acid involves in the prevulcanisation process to increase the trigger temperature of shape memory natural rubber. The prevulcanised rubber is fabricated with various amount of palmitic acid and sulphur to evaluate its shape memory capability under different temperature conditions (various programming temperatures and recovery temperatures). A custom-made stretching apparatus is developed to measure the shape memory parameters (shape fixity and shape recovery) under strain-control mode. The shape memory experimental settings (200% deformation strain for the shape memory natural rubber with less than 60% palmitic acid loading) are determined from the swollen shape memory natural rubber experiment. According to the shape memory experiment of prevulcanised rubber, the outstanding shape fixity and shape recovery are found when the temperature is closer to the melting temperature of the palmitic acid during the programming and recovery process. A similar trend is observed when palmitic acid content is increased. However, the sulphur content (>1.0pphr) has a reverse effect, causing the prevulcanised rubber to behave like elastic rubber and immediately recover its shape after unloading. Apart from the shape memory experiment, other material properties such as rubber strength and stress relaxation are also investigated. Furthermore, a shape memory behaviours prediction model is adopted to model the shape memory responses by using a standard linear solid model with Kelvin-Voigt element and a thermal strain model. The prediction model captured the shape memory behaviours appropriately and provided some insights on the stress-strain response of the respective segment phases for the shape memory process
Transposon mutagenesis in RT 078 Clostridioides difficile
Clostridioides difficile is a Gram-positive, spore-forming, anaerobic bacterium and a major cause of healthcare associated diarrhoea. Significant increases in the incidence of hypervirulent strains, such as those belonging to PCR ribotype (RT) 027, and increased antibiotic resistance have formed the focus of current C. difficile clinical research. Hypervirulent strains belonging to RT 078, in contrast, have received comparative less attention, despite the fact that they are widely recognized as being zoonotic, with a particular association with pigs. A greater understanding of RT 078 strains would benefit from the implementation of forward genetic approaches. Here we sought to implement Transposon directed insertion-site sequencing (TraDIS), a high throughput method able to define gene essentiality under niche-specific conditions, to elucidate physiological changes such as sporulation and germination in RT 078 strains. As effective DNA transfer is a prerequisite for TraDIS implementation, the most efficient strains as both donor and recipient in conjugation were identified. Applying next generation sequencing technologies on 10 clinical isolates and subsequent methylome analysis demonstrated that although the tested strains of RT 078 were genetically similar (up to 99.99%), they possess a variety of potential Restriction-Modification (R-M) barriers. One of these R-M systems was circumvented using the novel Escherichia coli donor strain, sExpress. Improved DNA transformability in C. difficile RT 078 strain CD9301 made it an optimal target for further genetic manipulations and subsequent TraDIS analysis. Subsequently, several transposon delivery systems were evaluated, based on their potential to mediate random transposon insertion and reliable plasmid loss, to prevent interference of the transposase during downstream experiments in C. difficile. The Tet-inducible transposon vector pRF215, performed best in CD9301. Based on this plasmid system, the novel vector pMTL-MtV10 was created, which was additionally equipped with I-SceI digestion sites, to achieve increased plasmid clearance during library preparation. Using both plasmids, genes essential for growth in rich media were determined. In total, 448 essential genes were predicted. The incorporation of I-SceI sites into pMtV-10 did not, however, improves plasmid loss during the TraDIS library preparation. A further 398 genes were predicted to be essential for sporulation. The number of genes identified is most likely an underestimate as the manual cut-off used to predict essentiality lacks sensitivity. The described findings lay the ground work necessary for determining essentiality in RT 078 and improving our understanding of this important ribotype
Computational and experimental studies of novel β-adrenoceptor ligands
With over 30% of available drugs targeting them, G protein-coupled receptors (GPCRs) are of significant pharmaceutical interest. Efforts to understand protein-ligand interactions among this group of proteins have been aided by the increase in available x-ray crystallography structures. β1-Adrenergic receptor (β1-AR) antagonists are used as treatment in patients with cardiovascular and airway conditions. However, current widely used medications are considerably prone to off-target side effects due to the lack of selectivity between the β1- and β2-AR subtypes. Therefore, a deeper understanding into the structural differences in characteristics is necessary to utilise them as a means of increasing ligand selectivity and therefore reducing the prevalence of off-target side effects. Here, two characteristics of the β1-AR are targeted as a means of increasing receptor selectivity. The first being receptor plasticity - recent research has shown that β-ARs contain a fissure between transmembrane helices 4 and 5 (TM4, TM5) (dubbed the ‘keyhole’) that differ slightly between β-AR subtypes that may accommodate for extended moieties or ligand entry and exit via the intramembrane space. The second characteristic being receptor dimerization. Receptor dimerization among GPCRs remains an active area of research, that so far has many pharmacological implications. Targeting receptor homodimerization has been proposed to be a method of improving receptor specificity within GPCRs. Research into β-AR dimers and findings from X-ray crystallography have shown that β1-AR homodimers may indeed align with a TM4/TM5 interface, aligning the ‘keyhole’. By combining and exploring both characteristics, we designed and computationally validated bivalent ligands capable of taking advantage of two unique β1-AR structural features as a means of improving ligand selectivity. Most current attempts at bivalent ligands in GPCRs explore using the extracellular space as a spacing route, leading to longer ligands, undesirably affecting molecular weight, lipophilicity, and viability. However, to validate our ligand design, we computationally demonstrate – by analyzing all-atom molecular dynamics (MD) simulations – that those ligands long enough to extend beyond the receptor via the keyhole can bind canonically and maintain key interactions that have previously been pharmacologically verified, as well as investigate structure activity relationships (SARs) of differing steric and electronic configurations of ligand components exposed to the intramembrane space. Bivalent ligand linkers were designed and computationally investigated within a GPCR dimer system to determine whether flexibility of the linker impacts the pharmacophores’ ability to maintain key canonical interactions. Long timescale coarse grained simulations of a membrane-bound β1-AR dimer showed the dimer interface to be stable, so shorter all-atom simulations could be used with confidence to aid bivalent ligand design. Bivalent ligands of the nature discussed in this work required at least one pharmacophore to enter/exit the receptor orthosteric binding site via the keyhole route. In house enhanced sampling computational methods were developed to study and validate the feasibility of this entry and exit route. Ligand exit pathways were generated by performing self-avoiding walk MD on protein-ligand complexes, then used to define starting and end points for weighted ensemble molecular dynamics (WEMD) to predict kinetic rate constants. These rate constants were then verified against pharmacologically derived β-AR kinetics data to validate the method, model, and ligand entry/exit pathway. The designed ligands would then lead to shorter and less hindering spacing between orthosteric sites
Solubility Prediction From First Principles
Solubility is a phenomenon of critical importance in countless areas of nature and industry. Solubility drives geological evolution through sedimentation and erosion. The solubility of pharmaceuticals and agrochemicals determines their efficacy and how they have to be formulated for the best efficiency of resources. Solubility determines the fate of artificial chemicals in nature. There are many areas of science where recreating the system in a lab environment is physically impossible or prohibitively expensive so the ability to simulate these systems is a high priority. This thesis is an exploration of methods to estimate solubilities from direct simulation of molecular systems and seeks to test their accuracy, precision and efficiency, and how they can be further improved. The first study seeks to recreate the solubility of urea in water using two different thermodynamic cycles (molecular and atomic routes) and two different sets of force fields (Özpınar and TIP3P versus Hölzl and TIP4P/2005) of significantly different ages. This project is a test of simulation software to see if the thermodynamic cycles produce the same results and a test of the force fields to see if the newer force fields give a better estimate of the solubility of urea in water than the older force fields. Neither set of force fields were actually tested in this way. The solubilities are also estimated using direct coexistence simulations to test the efficiency of this method with modern software and computing power. The newer Hölzl and TIP4P/2005 force fields are closer to reproducing the solubility of urea in water than the older Özpınar and TIP3P force fields according to direct coexistence method but the simulations take a very long time to equilibrate and a different solubility is obtained depending on whether the initial system is subsaturated or supersaturated. The Özpınar and TIP3P force fields failed to produce sensible chemical potential data. The chemical potentials derived from Hölzl and TIP4P/2005 through the molecular route agree with the direct coexistence results. The atomic route gives a too low estimate of the chemical potential difference between the crystal and solution. The second study seeks to recreate the temperature/solubility phase diagram of butanol and water with direct coexistence simulations and free energy calculations to construct the curves of free energy of mixing using the GAFF and TIP3P force fields. The thermodynamics of mutual solvation are complicated by the competing solvation processes between phases and requires a more thorough analysis than for the solvation of solids which potentially means that direct coexistence simulations are competitive. The direct coexistence simulations were much more efficient than anticipated and gave statistically rigorous estimates of the solubilities of butanol and water. Numerically, they were not accurate estimates but reproduced the qualitative behaviour of the phase diagram and the critical temperature of miscibility was closely reproduced at just above 100°C. The free energy calculations failed to produce chemical potential data with the precision required to create the curves of free energy of mixing at any temperature but the excess chemical potential calculations showed the correct behaviour of electrostatic interactions being more favourable in water than butanol and dispersion interactions being more favourable in butanol than water. The third study explores the phenomenon of polymorphism where a molecule can adopt multiple different crystal arrangements depending on temperature and pressure. The stability of polymorphs affects how soluble a molecule is in a particular solvent — higher stability means lower solubility. The drug molecule carbamazepine exists in four known polymorphs. The GAFF force field was tested on how well it can reproduce its polymorphs, judged on crystal unit cell parameters. The chemical potentials of carbamazepine in its four polymorphs and in water were calculated to then see how the solubilities of the four polymorphs compare with experimental data. The GAFF force field closely reproduced three of the four polymorphs with one having issues on a single crystal axis. The stability hierarchy of the four polymorphs was reproduced but the experimental solubility of carbamazepine was over an order of magnitude lower than experimental data. In conclusion, these studies show that there is still much progress required in general use force field development in order for solubility estimation to go mainstream. In some applications, direct coexistence simulations will give faster solubility estimates than free energy calculations but they can’t give the same thermodynamic insight. For free energy calculations, the thermodynamic cycle should be as simple as possible to avoid unnecessary errors — a thermodynamic adaptation of Occam’s Razor. Finally, there needs to be development of dedicated software for setting up free energy simulations. There were thousands of simulations in these studies and much time was dedicated to writing input files by hand and troubleshooting errors in them. Dedicated software that automates the process will reduce errors and open up free energy simulations to wider use
A whispering gallery mode based biosensor platform for single enzyme analysis
Enzymes catalyze most of the biochemical reactions in our cells. The functionality of enzymes depends on their dynamics starting from small bond vibrations in the fs timescale to large domain motions in the microsecond-millisecond timescale. Understanding the precise and rapid positioning of atoms within a catalytic site by an enzyme’s molecular movements is crucial for understanding biomolecular processes and for realizing synthetic biomolecular machines in the longer term. Hence, sensors capable of studying enzymes over a wide range of amplitudes and timescale and ideally one enzyme at a time are required. Many capable single-molecule techniques have been established in the past three decades, each with its pros and cons. This thesis presents the development of one such single-molecule sensor. The sensor is based on plasmonically enhanced whispering gallery mode resonators and is capable of studying enzyme kinetics and large-scale dynamics over the timescale of ns-seconds. Unlike fluorescence techniques which require labeling of the enzymes with dyes, the technique presented in this work detects single enzymes immobilized on the surface of plasmonic gold nanoparticles. A fast, low-noise, lock-in method is utilized to extract sensor signals in the microsecond timescale. Using a model enzyme, the ability of the sensor to detect conformational fluctuations of single enzymes is shown. Further, the thermodynamics of the enzyme is studied and the relevant thermodynamic parameters are extracted from the single-molecule data. Additionally, we extract the heat capacity changes associated with the enzyme using the single-molecule data. The sensor system presented in this thesis in the future could enable a fast, real-time, rapid throughput, lab-on-chip sensor system for studying single enzymes for both research and clinical use.Engineering and Physical Sciences Research Council (EPSRC)Engineering and Physical Sciences Research Council (EPSRC
Mapping three dimensional interactions between biomolecules and electric fields.
Electroporation is a technique that induces the formation of open pores in cell membranes by the application of an electric field. Electroporation is widely practiced in research and clinical work for transfection of genetic sequences and drug molecule transport through the membrane barrier. However, a full theoretical explanation of the molecular mechanisms and thermodynamics responsible for pore formation, structure, and longevity does not yet exist. Advances in molecular dynamics simulations have enabled theoretical studies of electroporation with previously unobtainable fidelity spanning biologically relevant timescales. All-atom simulations utilizing the recently developed method of computational electrophysiology demonstrate that pore size correlates to the magnitude of the applied electric flux. This insight suggests improvements to electroporation protocols and instrument design to increase treatment efficacy while simultaneously decreasing cell mortality. Data processing, that scales and centers each simulation frame, generates a pore-centric matrix of voxels representing the time-averaged charge density of the simulation volume. This processing enabled the calculation of the first high resolution, three-dimensional maps of the electric fields that act to create and stabilize the pore. Applying this capability to individual moieties gives additional insight to how electrostatic forces between biomolecules and membrane structures give cell membranes their remarkable properties. Complementary processing of atom types, instead of partial charges, produces a similarly scaled, stabilized, and time averaged matrix of moiety number densities. Plotted in three dimensions, these density data reveal additional membrane structure detail that have not previously been reported
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