Literature DB >> 32692571

DIA-DB: A Database and Web Server for the Prediction of Diabetes Drugs.

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/.

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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


  5 in total

1.  Computational Study of Asian Propolis Compounds as Potential Anti-Type 2 Diabetes Mellitus Agents by Using Inverse Virtual Screening with the DIA-DB Web Server, Tanimoto Similarity Analysis, and Molecular Dynamic Simulation.

Authors:  Putri Hawa Syaifie; Azza Hanif Harisna; Mochammad Arfin Fardiansyah Nasution; Adzani Gaisani Arda; Dwi Wahyu Nugroho; Muhammad Miftah Jauhar; Etik Mardliyati; Nurwenda Novan Maulana; Nurul Taufiqu Rochman; Alfian Noviyanto; Antonio J Banegas-Luna; Horacio Pérez-Sánchez
Journal:  Molecules       Date:  2022-06-21       Impact factor: 4.927

Review 2.  Advanced Bioinformatics Tools in the Pharmacokinetic Profiles of Natural and Synthetic Compounds with Anti-Diabetic Activity.

Authors:  Ana Maria Udrea; Gratiela Gradisteanu Pircalabioru; Anca Andreea Boboc; Catalina Mares; Andra Dinache; Maria Mernea; Speranta Avram
Journal:  Biomolecules       Date:  2021-11-14

3.  DiaNat-DB: a molecular database of antidiabetic compounds from medicinal plants.

Authors:  Abraham Madariaga-Mazón; José J Naveja; José L Medina-Franco; Karla O Noriega-Colima; Karina Martinez-Mayorga
Journal:  RSC Adv       Date:  2021-01-28       Impact factor: 3.361

4.  Computation Screening of Multi-Target Antidiabetic Properties of Phytochemicals in Common Edible Mediterranean Plants.

Authors:  Vlasios Goulas; Antonio J Banegas-Luna; Athena Constantinou; Horacio Pérez-Sánchez; Alexandra Barbouti
Journal:  Plants (Basel)       Date:  2022-06-21

5.  Calycosin-loaded nanoliposomes as potential nanoplatforms for treatment of diabetic nephropathy through regulation of mitochondrial respiratory function.

Authors:  Chunrong Huang; Lian-Fang Xue; Bo Hu; Huan-Huan Liu; Si-Bo Huang; Suliman Khan; Yu Meng
Journal:  J Nanobiotechnology       Date:  2021-06-13       Impact factor: 10.435

  5 in total

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