50 research outputs found
SuperLigands – a database of ligand structures derived from the Protein Data Bank
BACKGROUND: Currently, the PDB contains approximately 29,000 protein structures comprising over 70,000 experimentally determined three-dimensional structures of over 5,000 different low molecular weight compounds. Information about these PDB ligands can be very helpful in the field of molecular modelling and prediction, particularly for the prediction of protein binding sites and function. DESCRIPTION: Here we present an Internet accessible database delivering PDB ligands in the MDL Mol file format which, in contrast to the PDB format, includes information about bond types. Structural similarity of the compounds can be detected by calculation of Tanimoto coefficients and by three-dimensional superposition. Topological similarity of PDB ligands to known drugs can be assessed via Tanimoto coefficients. CONCLUSION: SuperLigands supplements the set of existing resources of information about small molecules bound to PDB structures. Allowing for three-dimensional comparison of the compounds as a novel feature, this database represents a valuable means of analysis and prediction in the field of biological and medical research
SuperNatural: a searchable database of available natural compounds
Although tremendous effort has been put into synthetic libraries, most drugs on the market are still natural compounds or derivatives thereof. There are encyclopaedias of natural compounds, but the availability of these compounds is often unclear and catalogues from numerous suppliers have to be checked. To overcome these problems we have compiled a database of ∼50 000 natural compounds from different suppliers. To enable efficient identification of the desired compounds, we have implemented substructure searches with typical templates. Starting points for in silico screenings are about 2500 well-known and classified natural compounds from a compendium that we have added. Possible medical applications can be ascertained via automatic searches for similar drugs in a free conformational drug database containing WHO indications. Furthermore, we have computed about three million conformers, which are deployed to account for the flexibilities of the compounds when the 3D superposition algorithm that we have developed is used. The SuperNatural Database is publicly available at . Viewing requires the free Chime-plugin from MDL (Chime) or Java2 Runtime Environment (MView), which is also necessary for using Marvin application for chemical drawing
CancerResource - updated database of cancer-relevant proteins, mutations and interacting drugs
Here, we present an updated version of CancerResource, freely available
without registration at http://bioinformatics.charite.de/care. With upcoming
information on target expression and mutations in patients’ tumors, the need
for systems supporting decisions on individual therapy is growing. This
knowledge is based on numerous, experimentally validated drug-target
interactions and supporting analyses such as measuring changes in gene
expression using microarrays and HTS-efforts on cell lines. To enable a better
overview about similar drug-target data and supporting information, a series
of novel information connections are established and made available as
described in the following. CancerResource contains about 91 000 drug-target
relations, more than 2000 cancer cell lines and drug sensitivity data for
about 50 000 drugs. CancerResource enables the capability of uploading
external expression and mutation data and comparing them to the database's
cell lines. Target genes and compounds are projected onto cancer-related
pathways to get a better overview about how drug-target interactions benefit
the treatment of cancer. Features like cellular fingerprints comprising of
mutations, expression values and drug-sensitivity data can promote the
understanding of genotype to drug sensitivity associations. Ultimately, these
profiles can also be used to determine the most effective drug treatment for a
cancer cell line most similar to a patient's tumor cells
Super Natural II - a database of natural products
Natural products play a significant role in drug discovery and development.
Many topological pharmacophore patterns are common between natural products
and commercial drugs. A better understanding of the specific physicochemical
and structural features of natural products is important for corresponding
drug development. Several encyclopedias of natural compounds have been
composed, but the information remains scattered or not freely available. The
first version of the Supernatural database containing ∼50 000 compounds was
published in 2006 to face these challenges. Here we present a new, updated and
expanded version of natural product database, Super Natural II
(http://bioinformatics.charite.de/supernatural), comprising ∼326 000
molecules. It provides all corresponding 2D structures, the most important
structural and physicochemical properties, the predicted toxicity class for
∼170 000 compounds and the vendor information for the vast majority of
compounds. The new version allows a template-based search for similar
compounds as well as a search for compound names, vendors, specific physical
properties or any substructures. Super Natural II also provides information
about the pathways associated with synthesis and degradation of the natural
products, as well as their mechanism of action with respect to structurally
similar drugs and their target proteins
a web-based interactive knowledge-sharing platform for sex- and gender- specific medical education
Background Sex and Gender Medicine is a novel discipline that provides
equitable medical care for society and improves outcomes for both male and
female patients. The integration of sex- and gender-specific knowledge into
medical curricula is limited due to adequate learning material, systematic
teacher training and an innovative communication strategy. We aimed at
initiating an e-learning and knowledge-sharing platform for Sex and Gender
Medicine, the eGender platform (http://egender.charite.de), to ensure that
future doctors and health professionals will have adequate knowledge and
communication skills on sex and gender differences in order to make informed
decisions for their patients. Methods The web-based eGender knowledge-sharing
platform was designed to support the blended learning pedagogical teaching
concept and follows the didactic concept of constructivism. Learning materials
developed by Sex and Gender Medicine experts of seven universities have been
used as the basis for the new learning tools. The content of these tools is
patient-centered and provides add-on information on gender-sensitive aspects
of diseases. The structural part of eGender was designed and developed using
the open source e-learning platform Moodle. The eGender platform comprises an
English and a German version of e-learning modules: one focusing on basic
knowledge and seven on specific medical disciplines. Each module consists of
several courses corresponding to a disease or symptom complex. Self-organized
learning has to be managed by using different learning tools, e.g., texts and
audiovisual material, tools for online communication and collaborative work.
Results More than 90 users from Europe registered for the eGender Medicine
learning modules. The most frequently accessed module was “Gender
Medicine—Basics” and the users favored discussion forums. These e-learning
modules fulfill the quality criteria for higher education and are used within
the elective Master Module “Gender Medicine—Basics” implemented into the
accredited Master of Public Health at Charité—Berlin. Conclusions The eGender
platform is a flexible and user-friendly electronical knowledge-sharing
platform providing evidence-based high-quality learning material used by a
growing number of registered users. The eGender Medicine learning modules
could be key in the reform of medical curricula to integrate Sex and Gender
Medicine into the education of health professionals
SuperTarget and Matador: resources for exploring drug-target relationships
The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use 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 the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.d
Identity development and forgivingness: tests of basic relations and mediational pathways
Adaptive identity development leads to increases in personality traits that allow for social well-being. The current study tested this claim with respect to forgivingness, a dispositional tendency to forgive others. In a sample of university undergraduates (N = 214), we examined the relations between forgivingness and two indicators of identity development: commitment and exploration. Forgivingness uniquely positively related with both identity variables, controlling for the other. Next, we tested mediational models to examine the mechanisms underlying these relationships. Our results suggest that, in part, the association between identity development and forgivingness is mediated by levels of agreeableness and neuroticism, as measured by the Big Five Inventory
CancerResource: a comprehensive database of cancer-relevant proteins and compound interactions supported by experimental knowledge
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/
SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions
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