Hi all,
I have been interested in screening compounds for their interactions with a particular family of receptors. What methodologies would help me to accomplish this? Does this fall within the realm of data science?
Kindest regards,
Mike
Hi Michael, I'm not familiar with programs to mine large compound sets. In case you have only a few chemicals, you can try to find ligands using ChEmbl though (https://www.ebi.ac.uk/chembl/).
Hi, Number of resources are available for virtual screening process. For example, in Binding database, we have an option "do Virtual Screening". In that, we have to upload our actives (the active ligand) as well as compounds in which the screening process to be done (i.e., data set compounds). It will give the result based on tanimoto similarity. This is ligand based virtual screening. Then we can go for docking analysis through which we can identify their interactions with particular target.
I would recommend to go for pharmmapper. You can provide your compound structure (from pubchem or any other database) and submit job. It will give you all possible top 300 receptors/proteins results with their fit score. If your receptor of interest are coming in these 300 list, you can perform docking for confirmation and later wet lab studies to prove your results.
http://59.78.96.61/pharmmapper/submit_file.php
In the sense of modelling new/unknown ligands for receptors that have structures, "docking" as it is called sometimes, I think programs like Rosetta Dock can do that.
If you are imagining more generally identifying if important amino acids have changed at conserved binding pocket positions, that type of annotation is provided for PFAM or NCBI CDD, with information like "active site" or "binding", insofar as anyone has the structure or other data from mutation studies.
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