Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity.
There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget.
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/.
During the development of methods for cancer diagnosis and treatment, a vast amount of information is generated. Novel cancer target proteins have been identified and many compounds that activate or inhibit cancer-relevant target genes have been developed. This knowledge is based on an immense number of experimentally validated compound–target interactions in the literature, and excerpts from literature text mining are spread over numerous data sources. Our own analysis shows that the overlap between important existing repositories such as Comparative Toxicogenomics Database (CTD), Therapeutic Target Database (TTD), Pharmacogenomics Knowledge Base (PharmGKB) and DrugBank as well as between our own literature mining for cancer-annotated entries is surprisingly small. In order to provide an easy overview of interaction data, it is essential to integrate this information into a single, comprehensive data repository. Here, we present CancerResource, a database that integrates cancer-relevant relationships of compounds and targets from (i) our own literature mining and (ii) external resources complemented with (iii) essential experimental and supporting information on genes and cellular effects. In order to facilitate an overview of existing and supporting information, a series of novel information connections have been established. CancerResource addresses the spectrum of research on compound–target interactions in natural sciences as well as in individualized medicine; CancerResource is available at: http://bioinformatics.charite.de/cancerresource/.
Functional effects of surgical interventions in sleep-disordered breathing should be considered in addition to mechanistic concepts alone.
The application of 600 J at 85 degrees C leads to optimal lesion sizes. Higher amounts of energy will not lead to a relevant increase in tissue necrosis. With regard to the time needed for application, 600 J appears to be the ideal adjustment for energy delivery in the treatment of the human tongue.
Introduction: The aim of this study was to evaluate the primary and secondary therapeutic successes of different therapy schemes for the treatment of synechia of the labia in pre-pubertal girls. Materials and Methods: The treatment courses of 47 pre-pubertal girls who were treated between February 2007 and February 2013 in the special outpatient clinic for paediatric gynaecology of a department for gynaecology at a German university hospital and for whom information on the course of the disease was available for at least the six months following end of the treatment. 23 of these children were treated with a topical estriol therapy (treatment group A). For 24 of the girls a manual separation of the adhering labia minora was undertaken (treatment group B). Statistical evaluation was performed using the ?2 test, Fischer?s exact test and the Mann-Whitney U test. Results: For 18 of the 23 (80?%) girls in treatment group A topical estriol therapy alone led to a resolution of the synechia. Five of these 23 children (20?%) required a secondary manual separation. All girls for whom treatment was not successful were under 5 years of age. For all 24 girls (100?%) of treatment group B the primary manual separation was performed with success. The recurrence rates after ??6 months in cases with identical after-care did not differ between the two treatment groups (treatment group A: 34?%, treatment group B: 33?%, ?2 test: p?=?0.853). 16 of the 17 recurrences occurred ??3 months after the end of the therapy. Conclusion: Our results show that for children 5 years of age a 4-week topical therapy with estriol is a promising therapy option for synechia of the labia that is less of a burden for the family situation. Especially for girls ??5 years of age, primary therapy fails in up to 20?% of the cases. Primary manual separation represents a more effective therapeutic option. Irrespective of the treatment applied, a recurrence after ??3 must be expected in one-third of the treated girls.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.