Processing, analyzing and querying databases is a major challenge for today’s research scientists

One of the major challenges in a complex multi-disciplinary project like the Virtual Liver Network is to understand and process data from a variety of data sources. Simply having access to data isn't enough.

  • Researchers need to be able to integrate many seemingly simple bits of data together to be able to answer more complex questions. Therefore, the group of Rebecca Wade at the Heidelberg Institute for Theoretical Studies developed a webserver LigDig. LigDig helps to solve a variety of tasks that are linked by the need to answer questions about proteins. Such questions are based on searching for the compounds that can bind to proteins.
  • LigDig can simplify complex tasks such as converting a chemical compound name from English into a computer based representation of this compound. This representation can be used to search compound databases. This might sound like a trivial task, but for example in the case of fructose 1,6-bisphosphate, a compound involved in regulating central energy metabolism, you can find the compound with different names in different databases: fructose 1,6-diphosphate, fructose bisphosphate, or even FBP.
  • In another example, researchers might be interested to know which proteins in a signaling or metabolic network will be inhibited by a selected inhibitor compound. LigDig allows researchers to search the ChEMBL database of protein-compound binding affinities, a measure of how tightly a protein and compound can bind to each other, and identify the proteins of interest, or to select a more specific inhibitor compound. It can be used, when researchers are modeling a signaling or metabolic network. They can find out this information and choose to add it to their mathematical model. Then they can see whether there is an observable effect on their results, based on their choice of inhibitor compound.
  • LigDig can also be used to compare the 3D structure of two or more binding sites on a protein. Knowing that one protein can bind to a particular compound, e.g. fructose 1,6-bisphosphate, a researcher can compare the known binding site for this protein to a binding site in another protein where it isn't known if fructose 1,6-bisphosphate can bind. If the two binding sites are similar then there is a good chance that the second protein can also bind fructose 1,6-bisphosphate.
  • In the picture, we show how the researcher who is interested in the human protein ERK1 (Uniprot P27361) can use LigDig. The tool identifies a compound Tamatinib. We see that at the moment two protein 3D structures containing this compound are available. Graph-based visualizations can show that Tamatinib can also bind to the protein FLT3, a tyrosine protein kinase receptor. Since there is currently no 3D structure of Tamatinib bound to protein FLT3, superposition of Tamatinib to another compound and protein, whose 3D structure is known gives a suggestion for how Tamatinib might bind to the protein FLT3.
  • Author: Jonathan C. Fuller

  • Further reading and figure reference: Fuller, Jonathan C, Martinez, Michael, Henrich, Stefan, Stank, Antonia, Richter, Stefan, Wade, Rebecca C LigDig: a web server for querying ligand-protein interactions Bioinformatics 2014 Oxford University Press.
  • LigDig is available at: http://mcm.h-its.org/ligdig
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