Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Wednesday, September 26 4:00 p.m. - SWIG Boardroom (CIT 241) Daniel Udwary Assistant Professor of Pharmacognosy Department of Biomedical & Pharmaceutical Sciences University of Rhode Island "SMOR: A database and web analysis tool to identify bacterial secondary metabolism and enable drug discovery" Many species of bacteria, fungi and plants produce specialized biologically active small molecules used in their natural environment for chemical defense, communication, pigmentation and metal binding, and these so-called natural products, or secondary metabolites, are often collected and utilized by man as pharmaceuticals (commonly antimicrobials and anticancer agents), as dyes, in agriculture, or as inspiration or starting materials for complex chemical syntheses. By virtue of evolutionary pre-selection by the producing organism, naturally derived compounds should be a rich source of bioactive starting materials for drug discovery. Because the carbon or peptide skeletons of natural product molecules are often biosynthesized by one of a relatively small number of enzyme families, the genes responsible can be readily identified in the exponentially increasing number of microbial genomes being sequenced, and in many cases partial chemical structures of the products of these pathways can be predicted. Unfortunately, secondary metabolism genes are very often overlooked or incorrectly annotated by automated genetic analysis tools because of their evolutionary relationships to primary metabolic genes. Currently there is no specialized storehouse for secondary metabolic gene cluster information, nor is there a dedicated online site for discussion and critical analysis. To aid our drug discovery efforts, we have constructed SMOR, a Secondary Metabolism Online Repository. The SMOR analysis software routinely searches for secondary metabolism gene clusters within newly deposited genomes in NCBI's RefSeq resource, re-annotates genes and domains, and stores the information in an easily-searchable MySQL database. Users may examine, comment on, and discuss data through a user-friendly web interface. It is the intention that by enabling community-wide involvement in analysis of microbial secondary metabolism, SMOR will become a useful resource for early-stage drug discovery and biochemical investigations. Database URL: http://www.secondarymetabolism.com Hosted by Sorin Istrail