Metabolic capabilities of microorganisms include the production of secondary metabolites (e.g. antibiotics). The analysis of microbial volatile organic compounds (mVOCs) is an emerging research field with huge impact on medical, agricultural and biotechnical applied and basic science. The mVOC database (v1) has grown with microbiome research and integrated species information with data on emitted volatiles. Here, we present the mVOC 2.0 database with about 2000 compounds from almost 1000 species and new features to work with the database. The extended collection of compounds was augmented with data regarding mVOC-mediated effects on plants, fungi, bacteria and (in-)vertebrates. The mVOC database 2.0 now features a mass spectrum finder, which allows a quick mass spectrum comparison for compound identification and the generation of species-specific VOC signatures. Automatic updates, useful links and search for mVOC literature are also included. The mVOC database aggregates and refines available information regarding microbial volatiles, with the ultimate aim to provide a comprehensive and informative platform for scientists working in this research field. To address this need, we maintain a publicly available mVOC database at: http://bioinformatics.charite.de/mvoc.

The cytochrome P450 (CYP) enzymes are major players in drug metabolism. More than 2,000 mutations have been described, and certain single nucleotide polymorphisms (SNPs) have been shown to have a large impact on CYP activity. Therefore, CYPs play an important role in inter-individual drug response and their genetic variability should be factored into personalized medicine. To identify the most relevant polymorphisms in human CYPs, a text mining approach was used. We investigated their frequencies in different ethnic groups, the number of drugs that are metabolized by each CYP, the impact of CYP SNPs, as well as CYP expression patterns in different tissues. The most important polymorphic CYPs were found to be 1A2, 2D6, 2C9 and 2C19. Thirty-four common allele variants in Caucasians led to altered enzyme activity. To compare the relevant Caucasian SNPs with those of other ethnicities a search in 1,000 individual genomes was undertaken. We found 199 non-synonymous SNPs with frequencies over one percent in the 1,000 genomes, many of them not described so far. With knowledge of frequent mutations and their impact on CYP activities, it may be possible to predict patient response to certain drugs, as well as adverse side effects. With improved availability of genotyping, our data may provide a resource for an understanding of the effects of specific SNPs in CYPs, enabling the selection of a more personalized treatment regimen.

Much of the information on the Cytochrome P450 enzymes (CYPs) is spread across literature and the internet. Aggregating knowledge about CYPs into one database makes the search more efficient. Text mining on 57 CYPs and drugs led to a mass of papers, which were screened manually for facts about metabolism, SNPs and their effects on drug degradation. Information was put into a database, which enables the user not only to look up a particular CYP and all metabolized drugs, but also to check tolerability of drug-cocktails and to find alternative combinations, to use metabolic pathways more efficiently. The SuperCYP database contains 1170 drugs with more than 3800 interactions including references. Approximately 2000 SNPs and mutations are listed and ordered according to their effect on expression and/or activity. SuperCYP (http://bioinformatics.charite.de/supercyp) is a comprehensive resource focused on CYPs and drug metabolism. Homology-modeled structures of the CYPs can be downloaded in PDB format and related drugs are available as MOL-files. Within the resource, CYPs can be aligned with each other, drug-cocktails can be ‘mixed’, SNPs, protein point mutations, and their effects can be viewed and corresponding PubMed IDs are given. SuperCYP is meant to be a platform and a starting point for scientists and health professionals for furthering their research.

Background Given that an individual’s age and gender are strongly predictive of coronavirus disease 2019 (COVID-19) outcomes, do such factors imply anything about preferable therapeutic options? Methods An analysis of electronic health records for a large (68,466-case), international COVID-19 cohort, in 5-year age strata, revealed age-dependent sex differences. In particular, we surveyed the effects of systemic hormone administration in women. The primary outcome for estradiol therapy was death. Odds ratios (ORs) and Kaplan-Meier survival curves were analyzed for 37,086 COVID-19 women in two age groups: pre- (15–49 years) and peri-/post-menopausal (> 50 years). Results The incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is higher in women than men (by about + 15%) and, in contrast, the fatality rate is higher in men (about + 50%). Interestingly, the relationships between these quantities are linked to age: pre-adolescent girls and boys had the same risk of infection and fatality rate, while adult premenopausal women had a significantly higher risk of infection than men in the same 5-year age stratum (about 16,000 vs. 12,000 cases). This ratio changed again in peri- and postmenopausal women, with infection susceptibility converging with men. While fatality rates increased continuously with age for both sexes, at 50 years, there was a steeper increase for men. Thus far, these types of intricacies have been largely neglected. Because the hormone 17ß-estradiol influences expression of the human angiotensin-converting enzyme 2 (ACE2) protein, which plays a role in SARS-CoV-2 cellular entry, propensity score matching was performed for the women’s sub-cohort, comparing users vs. non-users of estradiol. This retrospective study of hormone therapy in female COVID-19 patients shows that the fatality risk for women > 50 years receiving estradiol therapy (user group) is reduced by more than 50%; the OR was 0.33, 95% CI [0.18, 0.62] and the hazard ratio (HR) was 0.29, 95% CI [0.11,0.76]. For younger, pre-menopausal women (15–49 years), the risk of COVID-19 fatality is the same irrespective of estradiol treatment, probably because of higher endogenous estradiol levels. Conclusions As of this writing, still no effective drug treatment is available for COVID-19; since estradiol shows such a strong improvement regarding fatality in COVID-19, we suggest prospective studies on the potentially more broadly protective roles of this naturally occurring hormone.

Immune dysregulation is characteristic of the more severe stages of SARS-CoV-2 infection. Understanding the mechanisms by which the immune system contributes to COVID-19 severity may open new avenues to treatment. Here we report that elevated interleukin-13 (IL-13) was associated with the need for mechanical ventilation in two independent patient cohorts.In addition, patients who acquired COVID-19 while prescribed Dupilumab, a mAb that blocks IL-13 and IL-4 signaling, had less severe disease. In SARS-CoV-2 infected mice, IL-13 neutralization reduced death and disease severity without affecting viral load, demonstrating an immunopathogenic role for this cytokine. Following anti-IL-13 treatment in infected mice, hyaluronan synthase 1 (Has1) was the most downregulated gene and accumulation of the hyaluronan polysaccharide was decreased in the lung. In patients with COVID-19, hyaluronan was increased in the lungs and plasma. Blockade of the hyaluronan receptor, CD44, reduced mortality in infected mice, supporting the importance of hyaluronan as a pathogenic mediator.Finally, hyaluronan was directly induced in the lungs of mice by administration of IL-13, indicating a new role for IL-13 in lung disease. Understanding the role of IL-13 and hyaluronan has important implications for therapy of COVID-19 and potentially other pulmonary diseases.Summary: IL-13 levels were elevated in patients with severe COVID-19. In a mouse model of disease, IL-13 neutralization reduced disease and decreased lung hyaluronan deposition.Administration of IL-13 induced hyaluronan in the lung. Blockade of the hyaluronan receptor CD44 prevented mortality, highlighting a novel mechanism for IL-13-mediated hyaluronan synthesis in pulmonary pathology.

Background: The development of ceramics during the last years was overwhelming. However, the focus was laid on the hardness and the strength of the restorative materials, resulting in high antagonistic tooth wear. This is critical for patients with bruxism. Objectives: The purpose of this study was to evaluate the clinical performance of the new double hybrid material for non-invasive treatment approaches.Material and Methods: The new approach of the material tested, was to modify ceramics to create a biomimetic material that has similar physical properties like dentin and enamel and is still as strong as conventional ceramics. Results: The produced crowns had a thickness ranging from 0.5 to 1.5 mm. To evaluate the clinical performance and durability of the crowns, the patient was examined half a year later. The crowns were still intact and soft tissues appeared healthy and this was achieved without any loss of tooth structure. Conclusions: The material can be milled to thin layers, but is still strong enough to prevent cracks which are stopped by the interpenetrating polymer within the network. Depending on the clinical situation, minimally- up to non-invasive restorations can be milled. Clinical Relevance: Dentistry aims in preservation of tooth structure. Patients suffering from loss of tooth structure (dental erosion, Amelogenesis imperfecta) or even young patients could benefit from minimally-invasive crowns. Due to a Vickers hardness between dentin and enamel, antagonistic tooth wear is very low. This might be interesting for treating patients with bruxism.

A vast number of sweet tasting molecules are known, encompassing small compounds, carbohydrates, d-amino acids and large proteins. Carbohydrates play a particularly big role in human diet. The replacement of sugars in food with artificial sweeteners is common and is a general approach to prevent cavities, obesity and associated diseases such as diabetes and hyperlipidemia. Knowledge about the molecular basis of taste may reveal new strategies to overcome diet-induced diseases. In this context, the design of safe, low-calorie sweeteners is particularly important. Here, we provide a comprehensive collection of carbohydrates, artificial sweeteners and other sweet tasting agents like proteins and peptides. Additionally, structural information and properties such as number of calories, therapeutic annotations and a sweetness-index are stored in SuperSweet. Currently, the database consists of more than 8000 sweet molecules. Moreover, the database provides a modeled 3D structure of the sweet taste receptor and binding poses of the small sweet molecules. These binding poses provide hints for the design of new sweeteners. A user-friendly graphical interface allows similarity searching, visualization of docked sweeteners into the receptor etc. A sweetener classification tree and browsing features allow quick requests to be made to the database. The database is freely available at: http://bioinformatics.charite.de/sweet/.

Regular monitoring of drug regulatory agency web sites and similar resources for information on new drug approvals and changes to legal status of marketed drugs is impractical. It requires navigation through several resources to find complete information about a drug as none of the publicly accessible drug databases provide all features essential to complement in silico drug discovery. Here, we propose SuperDRUG2 (http://cheminfo.charite.de/superdrug2) as a comprehensive knowledge-base of approved and marketed drugs. We provide the largest collection of drugs (containing 4587 active pharmaceutical ingredients) which include small molecules, biological products and other drugs. The database is intended to serve as a one-stop resource providing data on: chemical structures, regulatory details, indications, drug targets, side-effects, physicochemical properties, pharmacokinetics and drug–drug interactions. We provide a 3D-superposition feature that facilitates estimation of the fit of a drug in the active site of a target with a known ligand bound to it. Apart from multiple other search options, we introduced pharmacokinetics simulation as a unique feature that allows users to visualise the ‘plasma concentration versus time’ profile for a given dose of drug with few other adjustable parameters to simulate the kinetics in a healthy individual and poor or extensive metabolisers.