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Drug Search for Leishmaniasis Researchers Make Data Publicly Available
By: Dr. Carlos Muskus López
Coordinator, Molecular Biology and Computational Unit, PECET University of Antioquia
14 Nov 2016   

Summary
The Drug Search for Leishmaniasis research team has created an online database of the highest-scoring results from their research on World Community Grid. This database will help accelerate the work of other scientists who are conducting similar research.

Above is an illustration of how ligands (drugs) are predicted to bind to each of the DHODH protein conformations extracted from experiments simulated on World Community Grid. DHODH is one of the essential proteins associated with the survival of the parasite that causes leishmaniasis.

Background

The Drug Search for Leishmaniasis project was created to identify potential new treatments for leishmaniasis, a neglected tropical disease that infects more than two million people in 98 countries every year. The existing drug treatments for leishmaniasis can cause severe side effects, leading to an urgent need for new, safe, and inexpensive anti-leishmaniasis drug compounds.

With the help of massive computing power donated by more than 120,000 World Community Grid volunteers, they identified several drug compounds that may become improved treatments for this disease. The team has also created an open database of the project’s highest-scoring results, which is available to scientists and to the public.

New Database Links Proteins with Compounds

The project’s research team at PECET, University of Antioquia in Colombia used AutoDock VINA software to search the ZINC database of commercially available compounds for those which appeared to best bind to 50 selected target proteins involved in leishmaniasis.

You can access the database created by the Drug Search for Leishmaniasis team at:

http://ubmc-pecet.udea.edu.co/index.php/dsfl/

The database allows the selection of any protein studied in the virtual screening, based on its PDB (Protein Data Bank) ID or protein name. After selecting a protein, basic information about the protein appears together with a PDB link and a visualizer to explore the protein's structure without leaving the database. In the section beneath the protein information, the top 20 binding compounds for that protein are listed, with a link to each compound's details and the corresponding VINA docking score. At the bottom of the list, there is an option to download the data in CSV format.

Selecting one of the binding compounds from the list for a given protein target shows information about the molecule (its physicochemical properties), a picture of its 2D structure, and its link to the ZINC database. A list of other proteins with significant docking scores with this compound is provided. This can also be downloaded in CSV format.

The researchers hope this information will be valuable to other scientists investigating treatments for this neglected tropical disease. Please contact us (rodrigo.ochoa@udea.edu.co  or carlos.muskus@udea.edu.co) for information about lower-scoring compounds that are not listed in the database.

If you use information from this repository please cite: Ochoa, R, et al. "Drug search for leishmaniasis: a virtual screening approach by grid computing." Journal of Computer-Aided Molecular Design, 2016, 30(7):541-552.

Thank you to all World Community Grid volunteers who donated computing time to this project.