Current BioData\'s new databases for the Business Of Biology
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Literature Analytics & Alerts provides daily curated literature on proteins, genes and their relationships to diseases. It offers powerful filters to identify high-impact articles. Over 120,000 protein-disease links have been identified and classified. Scientists can save time by applying these filters. The system also includes protein and disease reports summarizing curated information. The Partner Discovery System provides a target-centric view of biology research. It identifies over 17,000 research centers working on targets/biomarkers and classifies institutions. Users can find partnering opportunities and centers of excellence by filtering by factors like diseases, targets, locations, and article recommendations. Institution reports provide quantitative and qualitative summaries of research.
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Neglected infectious diseases such as tuberculosis (TB) and malaria kill millions of people annually and the oral drugs used are subject to resistance requiring the urgent development of new therapeutics. Several groups, including pharmaceutical companies, have made large sets of antimalarial screening hit compounds and the associated bioassay data available for the community to learn from and potentially optimize. We have examined both intrinsic and predicted molecular properties across these datasets and compared them with large libraries of compounds screened against Mycobacterium tuberculosis in order to identify any obvious patterns, trends or relationships. One set of antimalarial hits provided by GlaxoSmithKline appears less optimal for lead optimization compared with two other sets of screening hits we examined. Active compounds against both diseases were identified to have larger molecular weight ([similar]350–400) and logP values of [similar]4.0, values that are, in general, distinct from the less active compounds. The antimalarial hits were also filtered with computational rules to identify potentially undesirable substructures. We were surprised that approximately 75–85% of these compounds failed one of the sets of filters that we applied during this work. The level of filter failure was much higher than for FDA approved drugs or a subset of antimalarial drugs. Both antimalarial and antituberculosis drug discovery should likely use simple available approaches to ensure that the hits derived from large scale screening are worth optimizing and do not clearly represent reactive compounds with a higher probability of toxicity in vivo.Meta analysis of molecular property patterns and filtering of public datasets...
Meta analysis of molecular property patterns and filtering of public datasets...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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Neglected infectious diseases such as tuberculosis (TB) and malaria kill millions of people annually and the oral drugs used are subject to resistance requiring the urgent development of new therapeutics. Several groups, including pharmaceutical companies, have made large sets of antimalarial screening hit compounds and the associated bioassay data available for the community to learn from and potentially optimize. We have examined both intrinsic and predicted molecular properties across these datasets and compared them with large libraries of compounds screened against Mycobacterium tuberculosis in order to identify any obvious patterns, trends or relationships. One set of antimalarial hits provided by GlaxoSmithKline appears less optimal for lead optimization compared with two other sets of screening hits we examined. Active compounds against both diseases were identified to have larger molecular weight ([similar]350–400) and logP values of [similar]4.0, values that are, in general, distinct from the less active compounds. The antimalarial hits were also filtered with computational rules to identify potentially undesirable substructures. We were surprised that approximately 75–85% of these compounds failed one of the sets of filters that we applied during this work. The level of filter failure was much higher than for FDA approved drugs or a subset of antimalarial drugs. Both antimalarial and antituberculosis drug discovery should likely use simple available approaches to ensure that the hits derived from large scale screening are worth optimizing and do not clearly represent reactive compounds with a higher probability of toxicity in vivo.Meta analysis of molecular property patterns and filtering of public datasets...
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Current BioData\'s new databases for the Business Of Biology
- 1. The 3 rd Generation of Target Intelligence: Literature Analytics & Alerts Jim Jacketti Current BioData Ltd
- 22. For more information please contact: Jim Jacketti [email_address] (215) 453-3161 (direct)