Perez-Sanchez, HoracioDen-Haan, HelenaPena-Garcia, JorgeLozano-Sanchez, JesusMoreno, María Encarnacion MartínezSanchez-Perez, AntoniaMunoz, AndresRuiz-Espinosa, PedroPereira, Andreia S.P.Katsikoudi, AntigoniHernandez, Jose Antonio GabaldonStojanovic, IvanaCarretero, Antonio SeguraTzakos, Andreas G.2021-09-282021-09-282020-07Perez-Sanchez, H., Den-Haan, H., Pena-Garcia, J. et al. 2020, 'DIA-DB: a database and web server for the prediction of diabetes drugs', Journal of Chemical Information and Modeling, vol. 60, no. 9, pp. 4124-4130.1549-9596 (print)1549-960X (online)10.1021/acs.jcim.0c00107http://hdl.handle.net/2263/81973The DIA-DB is a web server for the prediction of diabetes drugs that uses two different and complementary approaches: (a) comparison by shape similarity against a curated database of approved antidiabetic drugs and experimental small molecules and (b) inverse virtual screening of the input molecules chosen by the users against a set of therapeutic protein targets identified as key elements in diabetes. As a proof of concept DIA-DB was successfully applied in an integral workflow for the identification of the antidiabetic chemical profile in a complex crude plant extract. To this end, we conducted the extraction and LC-MS based chemical profile analysis of Sclerocarya birrea and subsequently utilized this data as input for our server. The server is open to all users, registration is not necessary, and a detailed report with the results of the prediction is sent to the user by email once calculations are completed. This is a novel public domain database and web server specific for diabetes drugs and can be accessed online through http://bio-hpc.eu/software/dia-db/.en© 2020 American Chemical SocietyWeb serverPredictionDiabetes drugsPostprint Article