TY - DATA T1 - Targeted Dereplication of Microbial Natural Products by High-Resolution MS and Predicted LC Retention Time PY - 2017/04/26 AU - Justine Chervin AU - Marc Stierhof AU - Ming Him Tong AU - Doe Peace AU - Kine Østnes Hansen AU - Dagmar Solveig Urgast AU - Jeanette Hammer Andersen AU - Yi Yu AU - Rainer Ebel AU - Kwaku Kyeremeh AU - Veronica Paget AU - Gabriela Cimpan AU - Albert Van Wyk AU - Hai Deng AU - Marcel Jaspars AU - Jioji N. Tabudravu UR - https://acs.figshare.com/articles/journal_contribution/Targeted_Dereplication_of_Microbial_Natural_Products_by_High-Resolution_MS_and_Predicted_LC_Retention_Time/4922906 DO - 10.1021/acs.jnatprod.6b01035.s001 L4 - https://ndownloader.figshare.com/files/8277215 KW - t R KW - LC retention times KW - compound KW - pipeline approach KW - Targeted Dereplication KW - identification KW - spectroscopic techniques KW - HRMS data KW - novel structures KW - Microbial Natural Products KW - NMR spectra KW - UV KW - structure elucidation KW - Streptomyces extracts KW - ACD KW - HRESIMS KW - Streptomyces albus KW - high-throughput LCMS data processing algorithm KW - DB KW - LC retention time KW - High-Resolution MS KW - Predicted LC Retention Time KW - MbcDB KW - 5098 structures N2 - A new strategy for the identification of known compounds in Streptomyces extracts that can be applied in the discovery of natural products is presented. The strategy incorporates screening a database of 5555 natural products including 5098 structures from Streptomyces sp., using a high-throughput LCMS data processing algorithm that utilizes HRMS data and predicted LC retention times (tR) as filters for rapid identification of known compounds in the natural product extract. The database, named StrepDB, contains for each compound the structure, molecular formula, molecular mass, and predicted LC retention time. All identified compounds are annotated and color coded for easier visualization. It is an indirect approach to quickly assess masses (which are not annotated) that may potentially lead to the discovery of new or novel structures. In addition, a spectral database named MbcDB was generated using the ACD/Spectrus DB Platform. MbcDB contains 665 natural products, each with structure, experimental HRESIMS, MS/MS, UV, and NMR spectra. StrepDB was used to screen a mutant Streptomyces albus extract, which led to the identification and isolation of two new compounds, legonmaleimides A and B, the structures of which were elucidated with the aid of MbcDB and spectroscopic techniques. The structures were confirmed by computer-assisted structure elucidation (CASE) methods using ACD/Structure Elucidator Suite. The developed methodology suggests a pipeline approach to the dereplication of extracts and discovery of novel natural products. ER -