Given the usefulness of chemical databases, many companies and researchers have taken it upon themselves to compile and put on web servers databases with diverse information. In an effort to classify these databases, Masoudi-Sobhanzadeh et al. distinguish five classes useful for drug repositioning based on data content, including: raw data (e.g. data from literature, in-house and clinical), target-based (include genes, proteins, pathways and side effects information), specific data (traditional medicine, disease-specific or geographical databases), drug design (containing the 3D structure of molecules, and molecular replacement information which are based on the resolved protein structures), and tool-based DB (tools and web servers). Other databases that are having a major current trend in drug discovery are virtual compound libraries and de novo designed libraries. Also, it is ongoing an effort to build and curate a compound database with metal-containing molecules in preclinical and clinical development, and approved for therapeutic use. Natural products have been sources of bioactive compounds that later have been used in the clinic or that have been used as starting points of drug candidates. The application of computational methods including chemoinformatic approaches and AI to further advance natural product research is a current trend. As early as 2012 there have been efforts to put together natural product databases in the public domain. The most recent large compound collection of natural products in the public domain is the Collection of Open Natural Products, COCONUT. In Latin America, there is an ongoing effort to put together and curate compound databases composed of natural products from the vast diversity contained in Latin American countries.