| Literature DB >> 32692571 |
Horacio Pérez-Sánchez1, Helena den-Haan1,2, Jorge Peña-García1, Jesús Lozano-Sánchez3,4, María Encarnación Martínez Moreno1, Antonia Sánchez-Pérez1, Andrés Muñoz1, Pedro Ruiz-Espinosa5, Andreia S P Pereira6, Antigoni Katsikoudi7, José Antonio Gabaldón Hernández1, Ivana Stojanovic8, Antonio Segura Carretero3,4, Andreas G Tzakos7.
Abstract
The 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/.Entities:
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Year: 2020 PMID: 32692571 DOI: 10.1021/acs.jcim.0c00107
Source DB: PubMed Journal: J Chem Inf Model ISSN: 1549-9596 Impact factor: 4.956