اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدInvolvement of Surfactant Protein D in Ebola Virus Infection Enhancement via Glycoprotein Interaction
103
0
0.0
(
0
)
تأليف
Anne-Laure Favier
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Since the largest 2014-2016 Ebola virus disease outbreak in West Africa, understanding of Ebola virus infection has improved, notably the involvement of innate immune mediators. Amongst them, collectins are important players in the antiviral innate immune defense. A screening of Ebola glycoprotein (GP)-collectins interactions revealed the specific interaction of human surfactant protein D (hSP-D), a lectin expressed in lung and liver, two compartments where Ebola was found in vivo. Further analyses have demonstrated an involvement of hSP-D in the enhancement of virus infection in several in vitro models. Similar effects were observed for porcine SP-D (pSP-D). In addition, both hSP-D and pSP-D interacted with Reston virus (RESTV) GP and enhanced pseudoviral infection in pulmonary cells. Thus, our study reveals a novel partner of Ebola GP that may participate to enhance viral spread.
قيم البحث
اقرأ أيضاً
Heparin has been found to have antiviral activity against SARS-CoV-2. Here, by means of sliding window docking, molecular dynamics simulations and biochemical assays, we investigate the binding mode of heparin to the virus spike glycoprotein and the
molecular basis for its antiviral activity. The simulations show that heparin binds at long, mostly positively charged patches on the spike, thereby masking the basic residues of the receptor binding domain and of the S1/S2 site. Experiments corroborated the simulation results by showing that heparin inhibits the cleavage of spike by furin by binding to the basic S1/S2 site. Our results indicate that heparin exerts its antiviral activity by both direct and allosteric mechanisms. Furthermore, the simulations provide insights into how heparan sulfate proteoglycans on the host cell can facilitate viral infection. Our results will aid the rational optimization of heparin derivatives for SARS-CoV-2 antiviral therapy.
Mathematical modelling has successfully been used to provide quantitative descriptions of many viral infections, but for the Ebola virus, which requires biosafety level 4 facilities for experimentation, modelling can play a crucial role. Ebola modell
ing efforts have primarily focused on in vivo virus kinetics, e.g., in animal models, to aid the development of antivirals and vaccines. But, thus far, these studies have not yielded a detailed specification of the infection cycle, which could provide a foundational description of the virus kinetics and thus a deeper understanding of their clinical manifestation. Here, we obtain a diverse experimental data set of the Ebola infection in vitro, and then make use of Bayesian inference methods to fully identify parameters in a mathematical model of the infection. Our results provide insights into the distribution of time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity. We suggest how these results can be used in future models to describe co-infection with defective interfering particles, which are an emerging alternative therapeutic.
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major worldwide public health emergency that has infected over $1.5$ million people. The partially open state of S1 subunit in spike glycoprotein is considered vital for its
infection with host cell and is represented as a key target for neutralizing antibodies. However, the mechanism elucidating the transition from the closed state to the partially open state still remains unclear. Here, we applied a combination of Markov state model, transition path theory and random forest to analyze the S1 motion. Our results explored a promising complete conformational movement of receptor-binding domain, from buried, partially open, to detached states. We also numerically confirmed the transition probability between those states. Based on the asymmetry in both the dynamics behavior and backbone C$alpha$ importance, we further suggested a relation between chains in the trimer spike protein, which may help in the vaccine design and antibody neutralization.
In the present work, we review the fundamental methods which have been developed in the last few years for classifying into families and clans the distribution of amino acids in protein databases. This is done through functions of random variables, t
he Entropy Measures of probabilities of occurrence of the amino acids. An intensive study of the Pfam databases is presented with restrictions to families which could be represented by rectangular arrays of amino acids with m rows (protein domains) and n columns (amino acids). This work is also an invitation to scientific research groups worldwide to undertake the statistical analysis with different numbers of rows and columns since we believe in the mathematical characterization of the distribution of amino acids as a fundamental insight on the determination of protein structure and evolution.
The protein-protein interactions (PPIs) of 14-3-3 proteins are a model system for studying PPI stabilization. The complex natural product Fusicoccin A stabilizes many 14-3-3 PPIs but is not amenable for use in SAR studies, motivating the search for m
ore drug-like chemical matter. However, drug-like 14-3-3 PPI stabilizers enabling such study have remained elusive. An X-ray crystal structure of a PPI in complex with an extremely low potency stabilizer uncovered an unexpected non-protein interacting, ligand-chelated Mg 2+ leading to the discovery of metal ion-dependent 14-3-3 PPI stabilization potency. This originates from a novel chelation-controlled bioactive conformation stabilization effect. Metal chelation has been associated with pan-assay interference compounds (PAINS) and frequent hitter behavior, but chelation can evidently also lead to true potency gains and find use as a medicinal chemistry strategy to guide compound optimization. To demonstrate this, we exploited the effect to design the first potent, selective and drug-like 14-3-3 PPI stabilizers.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
