Nitrogen doping of carbon nanoelectrodes for enhanced control of DNA translocation dynamics

Controlling the dynamics of DNA translocation is a central issue in the emerging nanopore-based DNA sequencing. To address the potential of heteroatom doping of carbon nanostructures to achieve this goal, herein we carry out atomistic molecular dynamics simulations for single-stranded DNAs translocating between two pristine or doped carbon nanotube (CNT) electrodes. Specifically, we consider the substitutional nitrogen doping of capped CNT (capCNT) electrodes and perform two types of molecular dynamics simulations for the entrapped and translocating single-stranded DNAs. We find that the substitutional nitrogen doping of capCNTs stabilizes the edge-on nucleobase configurations rather than the original face-on ones and slows down the DNA translocation speed by establishing hydrogen bonds between the N dopant atoms and nucleobases. Due to the enhanced interactions between DNAs and N-doped capCNTs, the duration time of nucleobases within the nanogap was extended by up to ~ 290 % and the fluctuation of the nucleobases was reduced by up to ~ 70 %. Given the possibility to be combined with extrinsic light or gate voltage modulation methods, the current work demonstrates that the substitutional nitrogen doping is a promising direction for the control of DNA translocation dynamics through a nanopore or nanogap based of carbon nanomaterials.Comment: 11 pages, 4 figure

Water Pharmacophore: Designing Ligands using Molecular Dynamics Simulations with Water

In this study, we demonstrate a method to construct a water-based pharmacophore model which can be utilized in the absence of known ligands. This method utilizes waters found in the binding pocket, sampled through molecular dynamics. Screening of compound databases against this water-based pharmacophore model reveals that this approach can successfully identify known binders to a target protein. The method was tested by enrichment studies of 7 therapeutically important targets and compared favourably to screening-by-docking with Glide. Our results suggest that even without experimentally known binders, pharmacophore models can be generated using molecular dynamics with waters and used for virtual screening

Ivacaftor potentiation of multiple CFTR channels with gating mutations

AbstractBackgroundThe investigational CFTR potentiator ivacaftor (VX-770) increased CFTR channel activity and improved lung function in subjects with CF who have the G551D CFTR gating mutation. The aim of this in vitro study was to determine whether ivacaftor potentiates mutant CFTR with gating defects caused by other CFTR gating mutations.MethodsThe effects of ivacaftor on CFTR channel open probability and chloride transport were tested in electrophysiological studies using Fischer rat thyroid (FRT) cells expressing different CFTR gating mutations.ResultsIvacaftor potentiated multiple mutant CFTR forms with defects in CFTR channel gating. These included the G551D, G178R, S549N, S549R, G551S, G970R, G1244E, S1251N, S1255P and G1349D CFTR gating mutations.ConclusionThese in vitro data suggest that ivacaftor has a similar effect on all CFTR forms with gating defects and support investigation of the potential clinical benefit of ivacaftor in CF patients who have CFTR gating mutations beyond G551D

Disk Detective: Discovery of New Circumstellar Disk Candidates through Citizen Science

The Disk Detective citizen science project aims to find new stars with 22 micron excess emission from circumstellar dust using data from NASA's WISE mission. Initial cuts on the AllWISE catalog provide an input catalog of 277,686 sources. Volunteers then view images of each source online in 10 different bands to identify false-positives (galaxies, background stars, interstellar matter, image artifacts, etc.). Sources that survive this online vetting are followed up with spectroscopy on the FLWO Tillinghast telescope. This approach should allow us to unleash the full potential of WISE for finding new debris disks and protoplanetary disks. We announce a first list of 37 new disk candidates discovered by the project, and we describe our vetting and follow-up process. One of these systems appears to contain the first debris disk discovered around a star with a white dwarf companion: HD 74389. We also report four newly discovered classical Be stars (HD 6612, HD 7406, HD 164137, and HD 218546) and a new detection of 22 micron excess around a previously known debris disk host star, HD 22128.Comment: 50 pages, accepted for publication in the Astrophysical Journa

Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: Meeting new challenges

© 2014 Elsevier Ltd All rights reserved. Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems

Taking Multiple Infections of Cells and Recombination into Account Leads to Small Within-Host Effective-Population-Size Estimates of HIV-1

Whether HIV-1 evolution in infected individuals is dominated by deterministic or stochastic effects remains unclear because current estimates of the effective population size of HIV-1 in vivo, Ne, are widely varying. Models assuming HIV-1 evolution to be neutral estimate Ne∼102–104, smaller than the inverse mutation rate of HIV-1 (∼105), implying the predominance of stochastic forces. In contrast, a model that includes selection estimates Ne>105, suggesting that deterministic forces would hold sway. The consequent uncertainty in the nature of HIV-1 evolution compromises our ability to describe disease progression and outcomes of therapy. We perform detailed bit-string simulations of viral evolution that consider large genome lengths and incorporate the key evolutionary processes underlying the genomic diversification of HIV-1 in infected individuals, namely, mutation, multiple infections of cells, recombination, selection, and epistatic interactions between multiple loci. Our simulations describe quantitatively the evolution of HIV-1 diversity and divergence in patients. From comparisons of our simulations with patient data, we estimate Ne∼103–104, implying predominantly stochastic evolution. Interestingly, we find that Ne and the viral generation time are correlated with the disease progression time, presenting a route to a priori prediction of disease progression in patients. Further, we show that the previous estimate of Ne>105 reduces as the frequencies of multiple infections of cells and recombination assumed increase. Our simulations with Ne∼103–104 may be employed to estimate markers of disease progression and outcomes of therapy that depend on the evolution of viral diversity and divergence

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Exploring the Ligand Efficacy of Cannabinoid Receptor 1 (CB1) using Molecular Dynamics Simulations

Abstract Cannabinoid receptor 1 (CB1) is a promising therapeutic target for a variety of disorders. Distinct efficacy profiles showed different therapeutic effects on CB1 dependent on three classes of ligands: agonists, antagonists, and inverse agonists. To discriminate the distinct efficacy profiles of the ligands, we carried out molecular dynamics (MD) simulations to identify the dynamic behaviors of inactive and active conformations of CB1 structures with the ligands. In addition, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method was applied to analyze the binding free energy decompositions of the CB1-ligand complexes. With these two methods, we found the possibility that the three classes of ligands can be discriminated. Our findings shed light on the understanding of different efficacy profiles of ligands by analyzing the structural behaviors of intact CB1 structures and the binding energies of ligands, thereby yielding insights that are useful for the design of new potent CB1 drugs