PSC-db: A Structured and Searchable 3D-Database for Plant Secondary Compounds
Alejandro Valdés-Jiménez,
Carlos Peña-Varas,
Paola Borrego-Muñoz,
Lily Arrue,
Melissa Alegría-Arcos,
Hussam Nour-Eldin,
Ingo Dreyer,
Gabriel Nuñez-Vivanco,
David Ramírez
Affiliations
Alejandro Valdés-Jiménez
Center for Bioinformatics, Simulations, and Modeling (CBSM), Faculty of Engineering, University of Talca, Talca 3460000, Chile
Carlos Peña-Varas
Instituto de Ciencias Biomédicas, Universidad Autónoma de Chile, Santiago 8900000, Chile
Paola Borrego-Muñoz
Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Campus Nueva Granada, Universidad Militar Nueva Granada, Cajicá 250247, Colombia
Lily Arrue
Instituto de Ciencias Biomédicas, Universidad Autónoma de Chile, Santiago 8900000, Chile
Melissa Alegría-Arcos
Instituto de Ciencias Biomédicas, Universidad Autónoma de Chile, Santiago 8900000, Chile
Hussam Nour-Eldin
DynaMo Center, Department of Plant and Environmental Sciences, University of Copenhagen, 1017 Copenhagen, Denmark
Ingo Dreyer
Center for Bioinformatics, Simulations, and Modeling (CBSM), Faculty of Engineering, University of Talca, Talca 3460000, Chile
Gabriel Nuñez-Vivanco
Center for Bioinformatics, Simulations, and Modeling (CBSM), Faculty of Engineering, University of Talca, Talca 3460000, Chile
David Ramírez
Instituto de Ciencias Biomédicas, Universidad Autónoma de Chile, Santiago 8900000, Chile
Plants synthesize a large number of natural products, many of which are bioactive and have practical values as well as commercial potential. To explore this vast structural diversity, we present PSC-db, a unique plant metabolite database aimed to categorize the diverse phytochemical space by providing 3D-structural information along with physicochemical and pharmaceutical properties of the most relevant natural products. PSC-db may be utilized, for example, in qualitative estimation of biological activities (Quantitative Structure-Activity Relationship, QSAR) or massive docking campaigns to identify new bioactive compounds, as well as potential binding sites in target proteins. PSC-db has been implemented using the open-source PostgreSQL database platform where all compounds with their complementary and calculated information (classification, redundant names, unique IDs, physicochemical properties, etc.) were hierarchically organized. The source organism for each compound, as well as its biological activities against protein targets, cell lines and different organism were also included. PSC-db is freely available for public use and is hosted at the Universidad de Talca.