Narrow Results

Direct-acting antiviral agents (DAAs) are known to interfere with various intracellular stages of the hepatitis C virus (HCV) life cycle and have demonstrated efficacy in treating HCV infection. However, DAA monotherapy can lead to drug resistance due to mutations. This paper explores the impact of DAA therapy on HCV dynamics using a multiscale age-structured partial differential equation (PDE) model that incorporates intracellular viral RNA replication within infected cells and two strains of viruses representing a drug-sensitive strain and a drug-resistant mutant variant, respectively. We derived an equivalent ordinary differential equation (ODE) model from the PDE model to simplify mathematical analysis and numerical simulations. We studied the dynamics of the two virus strains before treatment and investigated the impact of mutations on the evolution kinetics of drug-sensitive and drug-resistant viruses, as well as the competition between the two strains during treatment. We also explored the role of DAAs in blocking HCV RNA replication and releasing new virus particles from cells. During treatment, mutations do not significantly influence the dynamics of various virus strains; however, they can generate low-level HCV that may be completely inhibited due to their poor fitness. The fitness of the mutant strain compared to the drug-sensitive strain determines which strain dominates the virus population. We also investigated the prevalence and drug resistance evolution of HCV variants during DAA treatment.

Entada africana (Ea) is a medicinal plant from the family of Fabaceae, used in Western and Central Africa regions to treat liver diseases. Antiviral properties of this plant were reported against Hepatitis B virus, while effects against Hepatitis C virus (HCV) remained unknown. This study reports for the first time, the effects of Ea crude extract and fractions on HCV replication. Furthermore, the effect of one Ea fraction on the transcriptional expression of two interferon-stimulated genes (ISGs) was also investigated. A methylene chloride–methanol (MCM) stem bark crude extract and different MCM fractions (EaF0, EaF5, EaF10, EaF25, and EaF100) were prepared and tested on LucUbiNeo-ET and Huh 5.15 cells lines used as genotype 1b (GT1b) replicon systems. The cells were incubated with crude extract and fractions at various concentrations. Then, the antiviral activity was assessed by luciferase reporter assay and the cell viability by MTT assay. Gene expression was also analyzed using quantitative real time RT-PCR. Results showed that the Ea crude extract dose-dependently inhibited HCV replication after 24 and 72 h of incubation. The MCM fraction (EaF10) exhibited the strongest anti-HCV properties with an IC₅₀ = 0.453 ± 0.00117 mg/ml and no reduction of cell viability at antiviral concentrations. This fraction also significantly induced the expression of heme oxygenase-1 (HO-1) (5.36-fold), and 2′-5′ oligoadenylate synthetase-3 (OAS-3) by 4.46-fold after 6 h and 2.31-fold after 24 h at the mRNA levels. Taken altogether, these results suggest that Ea may contain ingredients that indirectly regulate HCV replication.

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Ascletis gains exclusive China market rights from Presidio for clinical stage Hepatitis C virus inhibitor.

Irvine Pharmaceutical Services opens an analytical facility in Hangzhou, China.

Pioneering application of Google Glass by Renji Hospital.

WuXi PharmaTech launches representative office in Israel, forms strategic collaboration with Pontifax.

International Symposium on molecular biology of fruit trees held at Huazhong Agricultural University.

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UC Berkeley, Berkeley Lab Partner with China's Tsinghua on Clean Energy.

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Pollen Chains Associated with Secondary Pollen Presentation in a Wild Ginger Species.

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How Does HCV Escape From Immune Response?

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Crystal Structures of Human TIM Members: Ebolavirus Entry-enhancing Receptors.

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Agilent Technologies Array CGH Platform Assures Quality of Cancer Cell Lines Used in Biomedical Research.

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NCCS Awards Contract for Proton Beam Therapy System to Hitachi Asia Ltd.

Hitachi is Selected by National Cancer Centre Singapore for Southeast Asia’s First Proton Beam Therapy System.

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The interaction of virus proteins with host proteins plays a key role in viral infection and consequent pathogenesis. Many computational methods have been proposed to predict protein–protein interactions (PPIs), but most of the computational methods are intended for PPIs within a species rather than PPIs across different species such as virus–host PPIs. We developed a method that represents key features of virus and human proteins of variable length into a feature vector of fixed length. The key features include the relative frequency of amino acid triplets (RFAT), the frequency difference of amino acid triplets (FDAT) between virus and host proteins, and amino acid composition (AC). We constructed several support vector machine (SVM) models to evaluate our method and to compare our method with others on PPIs between human and two types of viruses: human papillomaviruses (HPV) and hepatitis C virus (HCV). Comparison of our method to others with same datasets of HPV–human PPIs and HCV–human PPIs showed that the performance of our method is significantly higher than others in all performance measures. Using the SVM model with gene ontology (GO) annotations of proteins, we predicted new HPV–human PPIs. We believe our approach will be useful in predicting heterogeneous PPIs.

In this paper, we investigate global dynamics for a distributed time delayed HCV infection model. Our model admits two possible equilibria, an uninfected equilibrium and infected equilibrium depending on the basic reproduction number. By employing the method of Lyapunov functional, we prove that the uninfected equilibrium is global asymptotically stable if the basic reproduction number is less than one, it is unstable and the infected equilibrium is global asymptotically stable if the basic reproduction number is larger than one. The simulations results are in good accordance with our analytic results.

In this paper, we consider a deterministic hepatitis C virus (HCV) model and study the impact of optimal control on the screening of immigrants and treatment of HCV on the transmission dynamics of the disease in a homogeneous population with constant immigration of susceptibles. First, we derived the condition in which disease-free equilibrium is locally asymptotically stable and established that a stable disease-free equilibrium can only be achieved in the absence of infective immigrants. Second, we investigated the impact of each control mechanism individually and the combinations of these strategies in the control of HCV. The costs associated with each of these strategies are also investigated by formulating the costs function problem as an optimal control problem, and we then use the Pontryagin's Maximum Principle to solve the optimal control problems. From the numerical simulations we found that the optimal combination of treatment of acute-infected and chronic-infected individuals control strategy produced the same results as the combination of the three strategies (combination of screening of immigrants, treatment of acute-infected and chronic-infected individuals). By our model and these results, we suggest the treatment of acute-infected and chronic-infected individuals control strategy should be optimized where resources are scarce, because the implementation of the three strategies (combination of screening of immigrants, treatment of acute-infected and chronic-infected individuals) would imply additional cost.

In this paper, the global properties of a mathematical modeling of hepatitis C virus (HCV) with distributed time delays is studied. Lyapunov functionals are constructed to establish the global asymptotic stability of the uninfected and infected steady states. It is shown that if the basic reproduction number $R_0$ is less than unity, then the uninfected steady state is globally asymptotically stable. If the basic reproduction number $R_0$ is larger than unity, then the infected steady state is globally asymptotically stable.

Piperazine/morpholine derivatives of quinoline substituted at positions C-3, C-6 and C-8 has been previously prepared by S_NAr reactions of 3,6,8-tribromoquinoline (1) under microwave or conventional heating reaction conditions. In this study, we evaluated binding interactions between the piperazine/morpholine substituted quinolines and its highly-likely receptor, Cyclin G associated kinase (GAK) involved in hepatitis C virus (HCV) entry into host cells, via docking, molecular dynamics (MD), thermodynamic and pharmacokinetics computations in order to select a possible lead compound, which may be used for lead-optimization in our future studies to develop novel drug candidates against HCV infections. 372 nsec MD simulations followed by MM-PBSA thermodynamic computations revealed that compound 23 ($K_d$= 0.08nM) possesses the greatest potential to inhibit GAK. Pharmacokinetics computations suggest that compound 23 is a drug-like molecule as it conforms to the Lipinski filter. We determined that compound 23 could be a lead-like molecule for peripheric and cerebral HCV infections.

Chronic diseases like rheumatoid arthritis (RA) and inflammatory bowel diseases (IBD), which include ulcerative colitis (UC) and Crohn’s disease (CD), are debilitating life-long morbid conditions caused by a dysregulated immune profile in the affected individuals. These conditions afflict millions of individuals throughout the world with symptoms that impair performance and quality of life. Considering IBD per se, the chronic nature of the immune disorders means that patients may require life-long medications often at high doses, but the currently available pharmacological preparations are aimed at reducing the symptoms or suppressing exacerbations, without a lasting effect on the underlying cause. Further, long-term drug therapy often leads to drug dependency and loss of response together with adverse side effects. Indeed, drug side effects become an additional morbidity factor in many patients on long-term medications…

The interaction of virus proteins with host proteins plays a key role in viral infection and consequent pathogenesis. Many computational methods have been proposed to predict protein–protein interactions (PPIs), but most of the computational methods are intended for PPIs within a species rather than PPIs across different species such as virus–host PPIs. We developed a method that represents key features of virus and human proteins of variable length into a feature vector of fixed length. The key features include the relative frequency of amino acid triplets (RFAT), the frequency difference of amino acid triplets (FDAT) between virus and host proteins, and amino acid composition (AC). We constructed several support vector machine (SVM) models to evaluate our method and to compare our method with others on PPIs between human and two types of viruses: human papillomaviruses (HPV) and hepatitis C virus (HCV). Comparison of our method to others with same datasets of HPV–human PPIs and HCV–human PPIs showed that the performance of our method is significantly higher than others in all performance measures. Using the SVM model with gene ontology (GO) annotations of proteins, we predicted new HPV–human PPIs. We believe our approach will be useful in predicting heterogeneous PPIs.