The CARLSBAD database: a confederated database of chemical bioactivities.

Many bioactivity databases offer information regarding the biological activity of small molecules on protein targets. Information in these databases is often hard to resolve with certainty because of subsetting different data in a variety of formats; use of different bioactivity metrics; use of different identifiers for chemicals and proteins; and having to access different query interfaces, respectively. Given the multitude of data sources, interfaces and standards, it is challenging to gather relevant facts and make appropriate connections and decisions regarding chemical-protein associations. The CARLSBAD database has been developed as an integrated resource, focused on high-quality subsets from several bioactivity databases, which are aggregated and presented in a uniform manner, suitable for the study of the relationships between small molecules and targets. In contrast to data collection resources, CARLSBAD provides a single normalized activity value of a given type for each unique chemical-protein target pair. Two types of scaffold perception methods have been implemented and are available for datamining: HierS (hierarchical scaffolds) and MCES (maximum common edge subgraph). The 2012 release of CARLSBAD contains 439 985 unique chemical structures, mapped onto 1,420 889 unique bioactivities, and annotated with 277 140 HierS scaffolds and 54 135 MCES chemical patterns, respectively. Of the 890 323 unique structure-target pairs curated in CARLSBAD, 13.95% are aggregated from multiple structure-target values: 94 975 are aggregated from two bioactivities, 14 544 from three, 7 930 from four and 2214 have five bioactivities, respectively. CARLSBAD captures bioactivities and tags for 1435 unique chemical structures of active pharmaceutical ingredients (i.e. 'drugs'). CARLSBAD processing resulted in a net 17.3% data reduction for chemicals, 34.3% reduction for bioactivities, 23% reduction for HierS and 25% reduction for MCES, respectively. The CARLSBAD database supports a knowledge mining system that provides non-specialists with novel integrative ways of exploring chemical biology space to facilitate knowledge mining in drug discovery and repurposing. Database URL: http://carlsbad.health.unm.edu/carlsbad/.

Transcriptional analysis of Schistosoma mansoni treated with praziquantel in vitro.

Schistosomiasis is one of the foremost health problems in developing countries and has been estimated to account for the loss of up to 56 million annual disability-adjusted life years. Control of the disease relies almost exclusively on praziquantel (PZQ) but this drug does not kill juvenile worms during the early stages of infection or prevent post-treatment reinfection. As the use of PZQ continues to grow, there are fears that drug resistance may become problematic thus there is a need to develop a new generation of more broadly effective anti-schistosomal drugs, a task that will be made easier by having an understanding of why PZQ kills sexually mature worms but fails to kill juveniles. Here, we describe the exposure of mixed-sex juvenile and sexually mature male and female Schistosoma mansoni to 1 µg/mL PZQ in vitro and the use of microarrays to observe changes to the transcriptome associated with drug treatment. Although there was no significant difference in the total number of genes expressed by adult and juvenile schistosomes after treatment, juveniles differentially regulated a greater proportion of their genes. These included genes encoding multiple drug transporter as well as calcium regulatory, stress and apoptosis-related proteins. We propose that it is the greater transcriptomic flexibility of juvenile schistosomes that allows them to respond to and survive exposure to PZQ in vivo.