Environmental and structural factors associated with bacterial diversity in household dust across the Arizona-Sonora border.

We previously reported that asthma prevalence was higher in the United States (US) compared to Mexico (MX) (25.8% vs. 8.4%). This investigation assessed differences in microbial dust composition in relation to demographic and housing characteristics on both sides of the US-MX Border. Forty homes were recruited in the US and MX. Home visits collected floor dust and documented occupants' demographics, asthma prevalence, housing structure, and use characteristics. US households were more likely to have inhabitants who reported asthma when compared with MX households (30% vs. 5%) and had significantly different flooring types. The percentage of households on paved roads, with flushing toilets, with piped water and with air conditioning was higher in the US, while dust load was higher in MX. Significant differences exist between countries in the microbial composition of the floor dust. Dust from Mexican homes was enriched with Alishewanella, Paracoccus, Rheinheimera genera and Intrasporangiaceae family. A predictive metagenomics analysis identified 68 significantly differentially abundant functional pathways between US and MX. This study documented multiple structural, environmental, and demographic differences between homes in the US and MX that may contribute to significantly different microbial composition of dust observed in these two countries.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana.

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

An in silico pipeline for the discovery of multitarget ligands: A case study for epi-polypharmacology based on DNMT1/HDAC2 inhibition.

The search for novel therapeutic compounds remains an overwhelming task owing to the time-consuming and expensive nature of the drug development process and low success rates. Traditional methodologies that rely on the one drug-one target paradigm have proven insufficient for the treatment of multifactorial diseases, leading to a shift to multitarget approaches. In this emerging paradigm, molecules with off-target and promiscuous interactions may result in preferred therapies. In this study, we developed a general pipeline combining machine learning algorithms and a deep generator network to train a dual inhibitor classifier capable of identifying putative pharmacophoric traits. As a case study, we focused on dual inhibitors targeting DNA methyltransferase 1 (DNMT) and histone deacetylase 2 (HDAC2), two enzymes that play a central role in epigenetic regulation. We used this approach to identify dual inhibitors from a novel large natural product database in the public domain. We used docking and atomistic simulations as complementary approaches to establish the ligand-interaction profiles between the best hits and DNMT1/HDAC2. By using the combined ligand- and structure-based approaches, we discovered two promising novel scaffolds that can be used to simultaneously target both DNMT1 and HDAC2. We conclude that the flexibility and adaptability of the proposed pipeline has predictive capabilities of similar or derivative methods and is readily applicable to the discovery of small molecules targeting many other therapeutically relevant proteins.

Expanding the Structural Diversity of DNA Methyltransferase Inhibitors.

Inhibitors of DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug discovery. They are also chemical tools to understand the biochemistry of epigenetic processes. Herein, we report five distinct inhibitors of DNMT1 characterized in enzymatic inhibition assays that did not show activity with DNMT3B. It was concluded that the dietary component theaflavin is an inhibitor of DNMT1. Two additional novel inhibitors of DNMT1 are the approved drugs glyburide and panobinostat. The DNMT1 enzymatic inhibitory activity of panobinostat, a known pan inhibitor of histone deacetylases, agrees with experimental reports of its ability to reduce DNMT1 activity in liver cancer cell lines. Molecular docking of the active compounds with DNMT1, and re-scoring with the recently developed extended connectivity interaction features approach, led to an excellent agreement between the experimental IC50 values and docking scores.

Current advances on the development of BET inhibitors: insights from computational methods.

Epigenetics was coined almost 70 years ago for the description of heritable phenotype without altering DNA sequences. Research on the field has uncovered significant roles of such mechanisms, that account for the biogenesis of several diseases. Further studies have led the way for drug development which targets epi-enzymes, mainly for cancer treatment. Of the numerous epi-targets involved with histone acetylation, bromodomains have captured the spotlight of drug discovery focused on novel therapies. However, due to high sequence identity, the development of potent and selective inhibitors poses a significant challenge. Herein, we discuss recent computational developments on BET inhibitors and other methods that may be applied for drug discovery in general. As a proof-of-concept, we discuss a virtual screening to identify novel BET inhibitors based on coumarin derivatives. From public data, we identified putative structure-activity relationships of coumarin scaffold and propose R-group modifications for BET selectivity. Results showed that the optimization and design of novel coumarins could be further explored.

In silico tools to study molecular targets of neglected diseases: inhibition of TcSir2rp3, an epigenetic enzyme of Trypanosoma cruzi.

There is a growing interest to study and address neglected tropical diseases (NTD). To this end, in silico methods can serve as the bridge that connects academy and industry, encouraging the development of future treatments against these diseases. This chapter discusses current challenges in the development of new therapies, available computational methods and successful cases in computer-aided design with particular focus on human trypanosomiasis. Novel targets are also discussed. As a case study, we identify amentoflavone as a potential inhibitor of TcSir2rp3 (sirtuine) from Trypanosoma cruzi (20.03 µM) with a workflow that integrates chemoinformatic approaches, molecular modeling, and theoretical affinity calculations, as well as in vitro assays.

Cheminformatics Explorations of Natural Products.

The chemistry of natural products is fascinating and has continuously attracted the attention of the scientific community for many reasons including, but not limited to, biosynthesis pathways, chemical diversity, the source of bioactive compounds and their marked impact on drug discovery. There is a broad range of experimental and computational techniques (molecular modeling and cheminformatics) that have evolved over the years and have assisted the investigation of natural products. Herein, we discuss cheminformatics strategies to explore the chemistry and applications of natural products. Since the potential synergisms between cheminformatics and natural products are vast, we will focus on three major aspects: (1) exploration of the chemical space of natural products to identify bioactive compounds, with emphasis on drug discovery; (2) assessment of the toxicity profile of natural products; and (3) diversity analysis of natural product collections and the design of chemical collections inspired by natural sources.

Predicting Asthma Using Clinical Indexes.

Asthma is no longer considered a single disease, but a common label for a set of heterogeneous conditions with shared clinical symptoms but associated with different cellular and molecular mechanisms. Several wheezing phenotypes coexist at preschool age but not all preschoolers with recurrent wheezing develop asthma at school-age; and since at the present no accurate single screening test using genetic or biochemical markers has been developed to determine which preschooler with recurrent wheezing will have asthma at school age, the asthma diagnosis still needs to be based on clinical predicted models or scores. The purpose of this review is to summarize the existing and most frequently used asthma predicting models, to discuss their advantages/disadvantages, and their accomplishment on all the necessary consecutive steps for any predictive model. Seven most popular asthma predictive models were reviewed (original API, Isle of Wight, PIAMA, modified API, ucAPI, APT Leicestersher, and ademAPI). Among these, the original API has a good positive LR~7.4 (increases the probability of a prediction of asthma by 2-7 times), and it is also simple: it only requires four clinical parameters and a peripheral blood sample for eosinophil count. It is thus an easy model to use in any rural or urban health care system. However, because its negative LR is not good, it cannot be used to rule out the development of asthma.

A thermostable laccase from Thermus sp. 2.9 and its potential for delignification of Eucalyptus biomass.

Laccases are multicopper oxidases that are being studied for their potential application in pretreatment strategies of lignocellulosic feedstocks for bioethanol production. Here, we report the expression and characterization of a predicted laccase (LAC_2.9) from the thermophilic bacterial strain Thermus sp. 2.9 and investigate its capacity to delignify lignocellulosic biomass. The purified enzyme displayed a blue color typical of laccases, showed strict copper dependence and retained 80% of its activity after 16 h at 70 °C. At 60 °C, the enzyme oxidized 2,2'-azino-di-(3-ethylbenzthiazoline sulfonate) (ABTS) and 2,6-dimethoxyphenol (DMP) at optimal pH of 5 and 6, respectively. LAC_2.9 had higher substrate specificity (kcat/KM) for DMP with a calculated value that accounts for one of the highest reported for laccases. Further, the enzyme oxidized a phenolic lignin model dimer. The incubation of steam-exploded eucalyptus biomass with LAC_2.9 and 1-hydroxybenzotriazole (HBT) as mediator changed the structural properties of the lignocellulose as evidenced by Fourier transform infrared (FTIR) spectroscopy and thermo-gravimetric analysis (TGA). However, this did not increase the yield of sugars released by enzymatic saccharification. In conclusion, LAC_2.9 is a thermostable laccase with potential application in the delignification of lignocellulosic biomass.

Activity Landscape and Molecular Modeling to Explore the SAR of Dual Epigenetic Inhibitors: A Focus on G9a and DNMT1.

In this work we discuss the insights from activity landscape, docking and molecular dynamics towards the understanding of the structure-activity relationships of dual inhibitors of major epigenetic targets: lysine methyltransferase (G9a) and DNA methyltranferase 1 (DNMT1). The study was based on a novel data set of 50 published compounds with reported experimental activity for both targets. The activity landscape analysis revealed the presence of activity cliffs, e.g., pairs of compounds with high structure similarity but large activity differences. Activity cliffs were further rationalized at the molecular level by means of molecular docking and dynamics simulations that led to the identification of interactions with key residues involved in the dual activity or selectivity with the epigenetic targets.

Flavonoids as Putative Epi-Modulators: Insight into Their Binding Mode with BRD4 Bromodomains Using Molecular Docking and Dynamics.

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative, and antineoplastic activities. Recently, different studies showed that flavonoids have the potential to inhibit bromodomain and extraterminal (BET) bromodomains. Previous reports suggested that flavonoids bind between the Z and A loops of the bromodomain (ZA channel) due to their orientation and interactions with P86, V87, L92, L94, and N140. Herein, a comprehensive characterization of the binding modes of fisetin and the biflavonoid, amentoflavone, is discussed. To this end, both compounds were docked with BET bromodomain 4 (BRD4) using four docking programs. The results were post-processed with protein⁻ligand interaction fingerprints. To gain further insight into the binding mode of the two natural products, the docking results were further analyzed with molecular dynamics simulations. The results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was experimentally tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as the basis for scaffold optimization and the further characterization of flavonoids as BET inhibitors.

Prevalence of Asthma in School Children on the Arizona-Sonora Border.

BACKGROUND: Mexican-born children living in the United States have a lower prevalence of asthma than other US children. Although children of Mexican descent near the Arizona (AZ)-Sonora border are genetically similar, differences in environmental exposures might result in differences in asthma prevalence across this region. OBJECTIVE: The objective of this study was to determine if the prevalence of asthma and wheeze in these children varies across the AZ-Sonora border. METHODS: The International Study of Asthma and Allergy in Children written and video questionnaires were administered to 1753 adolescents from 5 middle schools: Tucson (school A), Nogales, AZ (schools B, C), and Nogales, Sonora, Mexico (schools D, E). The prevalence of asthma and symptoms was compared, with analyses in the AZ schools limited to self-identified Mexican American students. RESULTS: Compared with the Sonoran reference school E, the adjusted odds ratio (OR) for asthma was significantly higher in US schools A (OR 4.89, 95% confidence interval [CI] 2.72-8.80), B (OR 3.47, 95% CI 1.88-6.42), and C (OR 4.12, 95% CI 1.78-9.60). The adjusted OR for wheeze in the past year was significantly higher in schools A (OR 2.19, 95% CI 1.20-4.01) and B (OR 2.67, 95% CI 1.42-5.01) on the written questionnaire and significantly higher in A (OR 2.13, 95% CI 1.22-3.75), B (OR 1.95, 95% CI 1.07-3.53), and Sonoran school D (OR 2.34, 95% CI 1.28-4.30) on the video questionnaire compared with school E. CONCLUSIONS: Asthma and wheeze prevalence differed significantly between schools and was higher in the United States. Environmental factors that may account for these differences could provide insight into mechanisms of protection from asthma.

Consensus Diversity Plots: a global diversity analysis of chemical libraries.

BACKGROUND: Measuring the structural diversity of compound databases is relevant in drug discovery and many other areas of chemistry. Since molecular diversity depends on molecular representation, comprehensive chemoinformatic analysis of the diversity of libraries uses multiple criteria. For instance, the diversity of the molecular libraries is typically evaluated employing molecular scaffolds, structural fingerprints, and physicochemical properties. However, the assessment with each criterion is analyzed independently and it is not straightforward to provide an evaluation of the "global diversity". RESULTS: Herein the Consensus Diversity Plot (CDP) is proposed as a novel method to represent in low dimensions the diversity of chemical libraries considering simultaneously multiple molecular representations. We illustrate the application of CDPs to classify eight compound data sets and two subsets with different sizes and compositions using molecular scaffolds, structural fingerprints, and physicochemical properties. CONCLUSIONS: CDPs are general data mining tools that represent in two-dimensions the global diversity of compound data sets using multiple metrics. These plots can be constructed using single or combined measures of diversity. An online version of the CDPs is freely available at: https://consensusdiversityplots-difacquim-unam.shinyapps.io/RscriptsCDPlots/.Graphical AbstractConsensus Diversity Plot is a novel data mining tool that represents in two-dimensions the global diversity of compound data sets using multiple metrics.

Stress and Bronchodilator Response in Children with Asthma.

RATIONALE: Stress is associated with asthma morbidity in Puerto Ricans (PRs), who have reduced bronchodilator response (BDR). OBJECTIVES: To examine whether stress and/or a gene regulating anxiety (ADCYAP1R1) is associated with BDR in PR and non-PR children with asthma. METHODS: This was a cross-sectional study of stress and BDR (percent change in FEV1 after BD) in 234 PRs ages 9-14 years with asthma. We assessed child stress using the Checklist of Children's Distress Symptoms, and maternal stress using the Perceived Stress Scale. Replication analyses were conducted in two cohorts. Polymorphisms in ADCYAP1R1 were genotyped in our study and six replication studies. Multivariable models of stress and BDR were adjusted for age, sex, income, environmental tobacco smoke, and use of inhaled corticosteroids. MEASUREMENTS AND MAIN RESULTS: High child stress was associated with reduced BDR in three cohorts. PR children who were highly stressed (upper quartile, Checklist of Children's Distress Symptoms) and whose mothers had high stress (upper quartile, Perceived Stress Scale) had a BDR that was 10.2% (95% confidence interval, 6.1-14.2%) lower than children who had neither high stress nor a highly stressed mother. A polymorphism in ADCYAP1R1 (rs34548976) was associated with reduced BDR. This single-nucleotide polymorphism is associated with reduced expression of the gene for the ß2-adrenergic receptor (ADRB2) in CD4(+) lymphocytes of subjects with asthma, and it affects brain connectivity of the amygdala and the insula (a biomarker of anxiety). CONCLUSIONS: High child stress and an ADCYAP1R1 single-nucleotide polymorphism are associated with reduced BDR in children with asthma. This is likely caused by down-regulation of ADRB2 in highly stressed children.

Exposición crónica a hidrocarburos y glomerulopatías en humanos: [revisión] / Chronic exposure to hydrocarbons and glomerular diseases in humans: [review]

Los hidrocarburos representan una gran variedad de compuestos que tienen en su estructura sólo carbono e hidrógeno y pueden ser considerados como las moléculas principales de las que derivan todos los demás compuestos orgánicos. Las exposiciones breves e incidentales pueden ser relativamente inocuas, sin embargo las exposiciones prolongadas pueden ser tóxicas. Neuquén es la provincia del país con la prevalencia más elevada de pacientes en diálisis (superior a 800 pacientes por millón de habitantes) y una alta incidencia de enfermedad renal crónica estadio 5 (mayor a 190 pacientes por millón de habitantes). Presenta además una prevalencia notablemente elevada de glomerulopatías primarias. En Neuquén se desarrolla una importante actividad hidrocarburífera, lo que nos lleva a cuestionarnos si existe asociación entre ambas condiciones. Revisamos la evidencia disponible en la literatura sobre la relación existente entre exposición crónica a hidrocarburos en el desarrollo y progresión de glomerulopatías en humanos.

Asthma phenotypes in childhood: lessons from an epidemiological approach.

Asthma is a heterogenous disease with variable signs and symptoms among patients. It also presents significant individual variability over time. Recently, some important population-based studies that followed children from birth or from early childhood into adulthood have shed new light on how we understand this syndrome. Three phenotypes have been identified in children with asthma: transient wheezing, non-atopic wheezing of the toddler and pre-school-aged child and IgE-mediated wheezing. Transient wheezing is associated with symptoms that are limited to the first 3-5 years of life, decreased lung function, maternal smoking during pregnancy and exposure to other siblings or children at daycare centres. There is no association between transient wheezing and family history of asthma or allergic sensitisation. Children wheezing with respiratory syncytial virus in the first years of life are more likely to be wheezing up to 13 years of age; this is independent of atopy (non-atopic wheezers) and is not related to atopic sensitisation. Wheezing associated with evidence of allergic sensitisation has been identified as the 'classic' asthma phenotype. Early allergic sensitisation is a major risk factor for persistent asthma.