Diabetes drugs prediction web server and database

 Blog #6

Hi everyone.

There is an extremely useful database called "DIA-DB: A Database and Web Server for the Prediction of Diabetes Drugs," which is recently reported in the American Chemical Society's Journal of Chemical Information and Modeling (JCIM).

This is the first and open access web server for the prediction of diabetes drugs. It does not require any registrations and the user receives an email with a comprehensive report containing the prediction results. 

It employs two distinct approaches:

a) 3D shape-based similarity approach for comparison of antidiabetic approved and experimental compounds.

b) inverse virtual screening of the input molecules chosen by users: It performs large-scale inverse docking (using Autodock Vina) on a collection of proteins involved in diabetes with the goal of identifying a query compound's possible target.

Researchers may also use the DIA-DB to find out whether any of the already-approved or experimental compounds are included in the database. It provides the most pertinent details about and compound's bioactivity. The following information is provided about the desired compounds: trade name, chemical name, chemical structure, SMILES code, notes (depending on the drug), type of diabetes it targets (T1D or T2D), ligand ID in DrugBank, PubChem, and ZINC databases, and protein target.

It provides users both Ligand- and Structure-based virtual screening features.

Tutorials are also provided for the users.

The link for the article: https://pubs.acs.org/doi/10.1021/acs.jcim.0c00107

The link for webserver: http://bio-hpc.ucam.edu/dia-db/web/Calculations/Calculations.php

In general, we believe that it makes a significant contribution to the scientific community, especially during this pandemic, where researchers can use this database and server to prepare diabetes-related research.



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