dc.contributor.author |
Perez-Sanchez, Horacio
|
|
dc.contributor.author |
Den-Haan, Helena
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|
dc.contributor.author |
Pena-Garcia, Jorge
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|
dc.contributor.author |
Lozano-Sanchez, Jesus
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|
dc.contributor.author |
Moreno, María Encarnacion Martínez
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|
dc.contributor.author |
Sanchez-Perez, Antonia
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dc.contributor.author |
Munoz, Andres
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dc.contributor.author |
Ruiz-Espinosa, Pedro
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|
dc.contributor.author |
Pereira, Andreia S.P.
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dc.contributor.author |
Katsikoudi, Antigoni
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|
dc.contributor.author |
Hernandez, Jose Antonio Gabaldon
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|
dc.contributor.author |
Stojanovic, Ivana
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|
dc.contributor.author |
Carretero, Antonio Segura
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|
dc.contributor.author |
Tzakos, Andreas G.
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dc.date.accessioned |
2021-09-28T11:56:55Z |
|
dc.date.available |
2021-09-28T11:56:55Z |
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dc.date.issued |
2020-07 |
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dc.description.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/. |
en_ZA |
dc.description.department |
Biochemistry |
en_ZA |
dc.description.department |
Genetics |
en_ZA |
dc.description.department |
Microbiology and Plant Pathology |
en_ZA |
dc.description.librarian |
hj2021 |
en_ZA |
dc.description.uri |
http://pubs.acs.org/journal/jcics1/about.html |
en_ZA |
dc.identifier.citation |
Perez-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. |
en_ZA |
dc.identifier.issn |
1549-9596 (print) |
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dc.identifier.issn |
1549-960X (online) |
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dc.identifier.other |
10.1021/acs.jcim.0c00107 |
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dc.identifier.uri |
http://hdl.handle.net/2263/81973 |
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dc.language.iso |
en |
en_ZA |
dc.publisher |
American Chemical Society |
en_ZA |
dc.rights |
© 2020 American Chemical Society |
en_ZA |
dc.subject |
Web server |
en_ZA |
dc.subject |
Prediction |
en_ZA |
dc.subject |
Diabetes drugs |
en_ZA |
dc.title |
DIA-DB : a database and web server for the prediction of diabetes drugs |
en_ZA |
dc.type |
Postprint Article |
en_ZA |