We just stumbled upon this nice article from Alicja Gawalska et al. , where they report a suitable binding site and binding mode prediction for an antagonist of the TRPA1 ion channel.
The authors started looking for different pockets in the published structures of TRPA1 using different pocket detection software, including DeepSite, one of our drug discovery tools in PlayMolecule. One of the pockets predicted by DeepSite (the one with highest druggability score – 0.9997, named Deepsite-1 in Table 6, and pre-S1/S4/S5/TRP-like in Table 2), included the residue Asn-855, known to be critical. This pocket was also identified by some of the other methods, further increasing the confidence in the prediction.
This pocket and a few minor variants of it (see Figure 5 of the original publication) progressed to the next stage, on which the antagonist was docked to the different identified pockets. The best pose was selected for each pocket and a short molecular dynamics simulation was run on them to assess their stability. The pose that was generated for the Deepsite-1 pocket (named complex G in the paper) was the most stable and created long-lasting interactions with several residues, including an hydrogen bond with the key residue Asn-855.
The article reports that, after this docking exercise had taken place, a new structure for this ion channel was published (7JUP), containing a bound ligand. The main moiety of the antagonist in the G pose (methylxanthine) overlaps very well with a similar moiety (hypoxanthine) in 7JUP structure (see Figure 8B of the original publication), strongly suggesting that this is indeed the actual binding site for the antagonist.
We would like to congratulate the authors for their work. It is always great to see our tools being applied in real, prospective scenarios, as well as in-silico predictions getting verified with experimental evidence!
Finally, if you are interested in running a similar protocol in your target of choice (finding the binding site and binding mode of a ligand), feel free to drop us a message in the contact us page.
1. Gawalska, A.; Kołaczkowski, M.; Bucki, A. Structural Modeling of TRPA1 Ion Channel—Determination of the Binding Site for Antagonists. Molecules 2022, 27, 3077. https://doi.org/10.3390/molecules27103077