Kite-Shaped Molecules Block SARS-CoV-2 Cell Entry at a Post-Attachment Step

From MDPI via Jisc Publications RouterHistory: accepted 2021-11-15, pub-electronic 2021-11-19Publication status: PublishedAnti-viral small molecules are currently lacking for treating coronavirus infection. The long development timescales for such drugs are a major problem, but could be shortened by repurposing existing drugs. We therefore screened a small library of FDA-approved compounds for potential severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antivirals using a pseudovirus system that allows a sensitive read-out of infectivity. A group of structurally-related compounds, showing moderate inhibitory activity with IC50 values in the 2–5 μM range, were identified. Further studies demonstrated that these “kite-shaped” molecules were surprisingly specific for SARS-CoV-1 and SARS-CoV-2 and that they acted early in the entry steps of the viral infectious cycle, but did not affect virus attachment to the cells. Moreover, the compounds were able to prevent infection in both kidney- and lung-derived human cell lines. The structural homology of the hits allowed the production of a well-defined pharmacophore that was found to be highly accurate in predicting the anti-viral activity of the compounds in the screen. We discuss the prospects of repurposing these existing drugs for treating current and future coronavirus outbreaks

Structure of ABCB1/P-Glycoprotein in the Presence of the CFTR Potentiator Ivacaftor

From MDPI via Jisc Publications RouterHistory: accepted 2021-11-23, pub-electronic 2021-11-25Publication status: PublishedABCB1/P-glycoprotein is an ATP binding cassette transporter that is involved in the clearance of xenobiotics, and it affects the disposition of many drugs in the body. Conformational flexibility of the protein within the membrane is an intrinsic part of its mechanism of action, but this has made structural studies challenging. Here, we have studied different conformations of P-glycoprotein simultaneously in the presence of ivacaftor, a known competitive inhibitor. In order to conduct this, we used high contrast cryo-electron microscopy imaging with a Volta phase plate. We associate the presence of ivacaftor with the appearance of an additional density in one of the conformational states detected. The additional density is in the central aqueous cavity and is associated with a wider separation of the two halves of the transporter in the inward-facing state. Conformational changes to the nucleotide-binding domains are also observed and may help to explain the stimulation of ATPase activity that occurs when transported substrate is bound in many ATP binding cassette transporters

Structural conservation of insulin/IGF signalling axis at the insulin receptors level in Drosophila and humans

The insulin-related hormones regulate key life processes in Metazoa, from metabolism to growth, lifespan and aging, through an evolutionarily conserved insulin signalling axis (IIS). In humans the IIS axis is controlled by insulin, two insulin-like growth factors, two isoforms of the insulin receptor (hIR-A and -B), and its homologous IGF-1R. In Drosophila, this signalling engages seven insulin-like hormones (DILP1-7) and a single receptor (dmIR). This report describes the cryoEM structure of the dmIR ectodomain:DILP5 complex, revealing high structural homology between dmIR and hIR. The excess of DILP5 yields dmIR complex in an asymmetric 'T' conformation, similar to that observed in some complexes of human IRs. However, dmIR binds three DILP5 molecules in a distinct arrangement, showing also dmIR-specific features. This work adds structural support to evolutionary conservation of the IIS axis at the IR level, and also underpins a better understanding of an important model organism

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Hepatitis C virus in Pakistan: A systematic review of prevalence, genotypes and risk factors

In Pakistan more than 10 million people are living with Hepatitis C virus (HCV), with high morbidity and mortality. This article reviews the prevalence, genotypes and factors associated with HCV infection in the Pakistani population. A literature search was performed by using the keywords; HCV prevalence, genotypes and risk factors in a Pakistani population, in Pubmed, PakMediNet and Google scholar. Ninety-one different studies dating from 1994 to May 2009 were included in this study, and weighted mean and standard error of each population group was calculated. Percentage prevalence of HCV was 4.95% ± 0.53% in the general adult population, 1.72% ± 0.24% in the pediatric population and 3.64% ± 0.31% in a young population applying for recruitment, whereas a very high 57% ± 17.7% prevalence was observed in injecting drug users and 48.67% ± 1.75% in a multi-transfused population. Most prevalent genotype of HCV was 3a. HCV prevalence was moderate in the general population but very high in injecting drug users and multi-transfused populations. This data suggests that the major contributing factors towards increased HCV prevalence include unchecked blood transfusions and reuse of injection syringes. Awareness programs are required to decrease the future burden of HCV in the Pakistani population

A Four-Pronged Low Cost and Optimized Traffic Routing Solution

This paper proposes a novel four-pronged solution for estimating routes and total time required to travel in a transportation network. The proposed solution attempts to optimize the Google’s Map API request flow using open street map (OSM). As it is known that each request to Google Map API will incur some latency, since different computation are performed on Google server for each request. To avoid this latency, route estimations (distance and time) are calculated using a four-pronged approach based on Google map API, open street map (OSM), routing cache and logical grid of locations. The objective is to create a generalized routing system that tries to use Google services in optimized fashion. The proposed approach stores each requests/ response from Google Map API into an optimized data structure called cache. After passage of time, these cache records are moved to another data structure called random access memory (RAM) file. In scenarios where requests can’t be served via stored data, the proposed system attempts to give approximate estimations based on open street map (OSM) using an A* search for finding route. In addition to this, data that has been cached in proposed approach can be used for further analysis or applying machine learning algorithm for off-line route calculations later

A Four-Pronged Low Cost and Optimized Traffic Routing Solution

This paper proposes a novel four-pronged solution for estimating routes and total time required to travel in a transportation network. The proposed solution attempts to optimize the Google’s Map API request flow using open street map (OSM). As it is known that each request to Google Map API will incur some latency, since different computation are performed on Google server for each request. To avoid this latency, route estimations (distance and time) are calculated using a four-pronged approach based on Google map API, open street map (OSM), routing cache and logical grid of locations. The objective is to create a generalized routing system that tries to use Google services in optimized fashion. The proposed approach stores each requests/ response from Google Map API into an optimized data structure called cache. After passage of time, these cache records are moved to another data structure called random access memory (RAM) file. In scenarios where requests can’t be served via stored data, the proposed system attempts to give approximate estimations based on open street map (OSM) using an A* search for finding route. In addition to this, data that has been cached in proposed approach can be used for further analysis or applying machine learning algorithm for off-line route calculations later