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Physical Review. E Mar 2020Cofilin and ADF are cytoskeleton remodeling proteins that cooperatively bind and fragment actin filaments. Bound cofilin molecules do not directly interact with each...
Cofilin and ADF are cytoskeleton remodeling proteins that cooperatively bind and fragment actin filaments. Bound cofilin molecules do not directly interact with each other, indicating that cooperative binding of cofilin is mediated by the actin filament lattice. Cofilactin is therefore a model system for studying allosteric regulation of self-assembly. How cofilin binding changes structural and mechanical properties of actin filaments is well established. Less is known about the interaction energies and the thermodynamics of filament fragmentation, which describes the collective manner in which the cofilin concentration controls mean actin filament length. Here, we provide a general thermodynamic framework for allosteric regulation of self-assembly, and we use the theory to predict the interaction energies of experimental actin filament length distributions over a broad range of cofilin binding densities and for multiple cofilactin variants. We find that bound cofilin induces changes in nearby actin-actin interactions, and that these allosteric effects are propagated along the filament to affect up to four neighboring cofilin-binding sites (i.e., beyond nearest-neighbor allostery). The model also predicts that cofilin differentially stabilizes and destabilizes longitudinal versus lateral actin-actin interactions, and that the magnitude, range, asymmetry, and even the sign of these interaction energies can be altered using different actin and cofilin mutational variants. These results demonstrate that the theoretical framework presented here can provide quantitative thermodynamic information governing cooperative protein binding and filament length regulation, thus revealing nanometer length-scale interactions from micron length-scale "wet-lab" measurements.
Topics: Allosteric Regulation; Cytoskeletal Proteins; Models, Molecular; Thermodynamics
PubMed: 32290018
DOI: 10.1103/PhysRevE.101.032409 -
Physical Review. E May 2021A practical approach to the search for (quasi-) discrete breathers (DBs) in a triangular β-FPUT lattice (after Fermi, Pasta, Ulam, and Tsingou) is proposed. DBs are...
A practical approach to the search for (quasi-) discrete breathers (DBs) in a triangular β-FPUT lattice (after Fermi, Pasta, Ulam, and Tsingou) is proposed. DBs are obtained by superimposing localizing functions on delocalized nonlinear vibrational modes (DNVMs) having frequencies above the phonon spectrum of the lattice. Zero-dimensional and one-dimensional DBs are obtained. The former ones are localized in both spatial dimensions, and the latter ones are only in one dimension. Among the one-dimensional DBs, two families are considered: the first is based on the DNVMs of a triangular lattice, and the second is based on the DNVMs of a chain. We speculate that our systematic approach on the triangular β-FPUT lattice reveals all possible types of spatially localized oscillations with frequencies bifurcating from the upper edge of the phonon band as all DNVMs with frequencies above the phonon band are analyzed.
PubMed: 34134260
DOI: 10.1103/PhysRevE.103.052202 -
Journal of Infection and Public Health Oct 2021COVID-19 disease caused by SARS-CoV-2 is lacking efficient medication although certain medications are used to relief its symptoms.
BACKGROUND
COVID-19 disease caused by SARS-CoV-2 is lacking efficient medication although certain medications are used to relief its symptoms.
OBJECTIVES
We tested an FDA-approved antiviral medication namely rilpivirine to find a drug against SARS-CoV-2.
METHODS
The inhibition of rilpivirine against multiple SARS-CoV-2 therapeutic targets was studied using in silico method. The binding attraction of the protein-ligand complexes were calculated using molecular docking analysis.
RESULTS
Docking rilpivirine with main protease (Mpro), papin like protease (PLpro), sprike protein (Spro), human angiotensin converting enzyme-2 (ACE2), and RNA dependent-RNA polymerase (RdRp) yielded binding energies of -8.07, -8.40, -7.55, -9.11, and -8.69 kcal/mol, respectively. The electrostatic interaction is the key force in stabilizing the RdRp-rilpivirine complex, while van der Waals interaction dominates in the ACE2 rilpivirine case. Our findings suggest that rilpivirine can inhibit SARS-CoV-2 replication by targeting not only ACE2, but also RdRp and other targets, and therefore, it can be used to invoke altered mechanisms at the pre-entry and post-entry phases.
CONCLUSION
As a result of our in silico molecular docking study, we suggest that rilpivirine is a compound that could act as a powerful inhibitor against SARS-CoV-2 targets. Although in vitro and in vivo experiments are needed to verify this prediction we believe that this antiviral drug may be used in preclinical trials to fight against SARS coronavirus.
Topics: Antiviral Agents; COVID-19; Humans; Molecular Docking Simulation; Pharmaceutical Preparations; Rilpivirine; SARS-CoV-2
PubMed: 34326009
DOI: 10.1016/j.jiph.2021.07.012 -
Physical Review. E Nov 2021Sender-receiver games are simple models of information transmission that provide a formalism to study the evolution of honest signaling and deception between a sender...
Sender-receiver games are simple models of information transmission that provide a formalism to study the evolution of honest signaling and deception between a sender and a receiver. In many practical scenarios, lies often affect groups of receivers, which inevitably entangles the payoffs of individuals to the payoffs of other agents in their group, and this makes the formalism of pairwise sender-receiver games inapt for where it might be useful the most. We therefore introduce group interactions among receivers and study how their interconnectedness in higher-order social networks affects the evolution of lying. We observe a number of counterintuitive results that are rooted in the complexity of the underlying evolutionary dynamics, which has thus far remained hidden in the realm of pairwise interactions. We find conditions for honesty to persist even when there is a temptation to lie, and we observe the prevalence of moral strategy profiles even when lies favor the receiver at a cost to the sender. We confirm the robustness of our results by further performing simulations on hypergraphs created from real-world data using the SocioPatterns database. Altogether, our results provide persuasive evidence that moral behavior may evolve on higher-order social networks, at least as long as individuals interact in groups that are small compared to the size of the network.
PubMed: 34942761
DOI: 10.1103/PhysRevE.104.054308 -
Physical Review. E Jan 2022Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics...
Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics (or demographics) of an unsynchronized exponentially growing population, while the other captures cell-cycle dynamics, either by time-lapse imaging of full cell cycles or in bulk experiments on synchronized populations. In this paper, we study the subtle relationship between observations in these two distinct experimental approaches. We begin with an existing model: A single-cell deterministic description of cell-cycle dynamics where cell states (i.e., periods or phases) have precise lifetimes. We then generalize this description to a stochastic model in which the states have stochastic lifetimes, as described by arbitrary probability distribution functions. Our analyses of the demographics of an exponential culture reveal a simple and exact correspondence between the deterministic and stochastic models: The corresponding state ages in the deterministic model are equal to the exponential mean of the age in the stochastic model. An important implication is therefore that the demographics of an exponential culture will be well fit by a deterministic model even if the state timing is stochastic. Although we explore the implications of the models in the context of the Escherichia coli cell cycle, we expect both the models as well as the significance of the exponential-mean lifetimes to find many applications in the quantitative analysis of cell-cycle dynamics in other biological systems.
PubMed: 35193317
DOI: 10.1103/PhysRevE.105.014420 -
Research in Social & Administrative... Sep 2021Drug shortages have a negative impact on individual health outcomes for patients and health care systems more broadly. In recent years, regulatory bodies, such as the...
BACKGROUND
Drug shortages have a negative impact on individual health outcomes for patients and health care systems more broadly. In recent years, regulatory bodies, such as the Therapeutic Good Administration in Australia, have provided information about an increasing number of drug shortages. It is reported that 90% of medicines in Australia are imported; this leaves Australia vulnerable to international drug shortages. It has been suggested that Australia is heavily reliant on the US as its primary source of medicines.
OBJECTIVE(S)
To determine whether there are significant trends in the quantity, frequency, and nature of drug shortages between the US and Australia in a pre-pandemic and pandemic climate.
METHODS
This study mapped and analyzed drug shortages reported by both the United States Food and Drug Administration (FDA) and the Australian Therapeutic Goods Administration (TGA) in 2019 and 2020.
RESULTS
In 2019 (pre-COVID19), only 4% of US drug shortages were reported in Australia; this rose to 7% in 2020. Between 2019 and 2020, the number of US drug shortages increased by 37%, whilst the number of Australian drug shortages increased by 300%.
CONCLUSIONS
The Australian pharmaceuticals market is indeed more vulnerable to drug shortages, particularly in the event of a global pandemic such as COVID-19. However, these shortages are not significantly influenced by the US drug market.
Topics: Australia; COVID-19; Humans; Pandemics; Pharmaceutical Preparations; SARS-CoV-2; United States
PubMed: 33323334
DOI: 10.1016/j.sapharm.2020.12.001 -
Australasian Emergency Nursing Journal... May 2016There has been limited assessment of the impact that automated medication dispensing machines have on the medication administration process, particularly in Australian...
BACKGROUND
There has been limited assessment of the impact that automated medication dispensing machines have on the medication administration process, particularly in Australian emergency departments. The aim of this study is to examine the change in medication retrieval times, number of medications retrieved and staff perceptions before and after the installation of automated dispensing machines in an Australian emergency and trauma centre.
METHODS
A time and motion method recorded the time taken and number of medications retrieved from the medication room by emergency department staff, before and after the installation of two automated dispensing machines. Surveys were administered to staff members to elicit the perceived impact on clinical practice, utilising 5-point Likert scales.
RESULTS
A total of 954 medication retrievals (1030 medications) were recorded in the pre-implementation period and 842 (991 medications) in the post-implementation period. The mean time taken to retrieve any medication was significantly longer in the post-implementation period (+5.7s; p<0.01). For schedules 2, 3, 4 or unscheduled medications, the mean time increased by 26.9s (p<0.01), but decreased by 36.1s (p<0.01) for schedule 8 or 11 medications. The mean number of medications per retrieval increased slightly in the post implementation period (+0.10; p<0.01). Staff perceptions were that automated dispensing machines improve knowledge of medications on imprest (p=0.03) and reduced medication retrieval time (p<0.01).
CONCLUSIONS
This study found that the medication retrieval process was slower with automated dispensing machines for Schedules 2, 3, 4 and unscheduled medications, but quicker for Schedule 8 and 11 medications in an Australian emergency and trauma centre. Although retrieving medications took slightly longer overall, staff believed automated dispensing machines save time.
Topics: Attitude of Health Personnel; Emergency Service, Hospital; Humans; Medical Staff, Hospital; Medication Errors; Medication Systems, Hospital; Pharmaceutical Preparations; Pharmacy Service, Hospital; Practice Patterns, Physicians'; Time Factors; Victoria
PubMed: 26987705
DOI: 10.1016/j.aenj.2016.01.004 -
Drug Discovery Today Feb 2018Osteoarthritis (OA) is the most common form of joint disease. This presents the OA research community and pharmaceutical companies developing disease-modifying OA drugs... (Review)
Review
Osteoarthritis (OA) is the most common form of joint disease. This presents the OA research community and pharmaceutical companies developing disease-modifying OA drugs (DMOADs) with great opportunities. The different OA subtypes complicate the traditional approaches for developing new treatments. If we can identify new markers that can distinguish different subtypes this could greatly facilitate drug development from early discovery to late clinical development. Nevertheless, the current approaches result in poorly targeted treatments and the inability to recruit the right patients for clinical trials. Thus, there is an urgent medical need for objective biomarker tools for patient phenotyping.
Topics: Animals; Biomarkers; Clinical Trials as Topic; Drug Discovery; Humans; Osteoarthritis; Pharmaceutical Preparations
PubMed: 29038075
DOI: 10.1016/j.drudis.2017.10.008 -
Physical Review. E Apr 2016Hydrophobic thickness mismatch between integral membrane proteins and the surrounding lipid bilayer can produce lipid bilayer thickness deformations. Experiment and...
Hydrophobic thickness mismatch between integral membrane proteins and the surrounding lipid bilayer can produce lipid bilayer thickness deformations. Experiment and theory have shown that protein-induced lipid bilayer thickness deformations can yield energetically favorable bilayer-mediated interactions between integral membrane proteins, and large-scale organization of integral membrane proteins into protein clusters in cell membranes. Within the continuum elasticity theory of membranes, the energy cost of protein-induced bilayer thickness deformations can be captured by considering compression and expansion of the bilayer hydrophobic core, membrane tension, and bilayer bending, resulting in biharmonic equilibrium equations describing the shape of lipid bilayers for a given set of bilayer-protein boundary conditions. Here we develop a combined analytic and numerical methodology for the solution of the equilibrium elastic equations associated with protein-induced lipid bilayer deformations. Our methodology allows accurate prediction of thickness-mediated protein interactions for arbitrary protein symmetries at arbitrary protein separations and relative orientations. We provide exact analytic solutions for cylindrical integral membrane proteins with constant and varying hydrophobic thickness, and develop perturbative analytic solutions for noncylindrical protein shapes. We complement these analytic solutions, and assess their accuracy, by developing both finite element and finite difference numerical solution schemes. We provide error estimates of our numerical solution schemes and systematically assess their convergence properties. Taken together, the work presented here puts into place an analytic and numerical framework which allows calculation of bilayer-mediated elastic interactions between integral membrane proteins for the complicated protein shapes suggested by structural biology and at the small protein separations most relevant for the crowded membrane environments provided by living cells.
Topics: Finite Element Analysis; Lipid Bilayers; Membrane Proteins; Protein Binding
PubMed: 27176332
DOI: 10.1103/PhysRevE.93.042410 -
Physical Review. E Jul 2023A fundamental problem in the analysis of complex systems is getting a reliable estimate of the entropy of their probability distributions over the state space. This is...
A fundamental problem in the analysis of complex systems is getting a reliable estimate of the entropy of their probability distributions over the state space. This is difficult because unsampled states can contribute substantially to the entropy, while they do not contribute to the maximum likelihood estimator of entropy, which replaces probabilities by the observed frequencies. Bayesian estimators overcome this obstacle by introducing a model of the low-probability tail of the probability distribution. Which statistical features of the observed data determine the model of the tail, and hence the output of such estimators, remains unclear. Here we show that well-known entropy estimators for probability distributions on discrete state spaces model the structure of the low-probability tail based largely on a few statistics of the data: the sample size, the maximum likelihood estimate, the number of coincidences among the samples, and the dispersion of the coincidences. We derive approximate analytical entropy estimators for undersampled distributions based on these statistics, and we use the results to propose an intuitive understanding of how the Bayesian entropy estimators work.
PubMed: 37583218
DOI: 10.1103/PhysRevE.108.014101