Open vinbl opened 2 years ago
Hello @vinbl, thanks for raising an issue! Yep, DeeplyTough could be exactly what you're looking for. Apologies for the delay.
Obtaining the descriptors for each pocket is relatively straightforward, there are many strategies but I'll suggest the one with the fewest code changes.
pairs.csv
.custom_evaluation.py
the calculation of the entries
dictionary here involves calculating descriptors for each pocket so if you modify the code to save this dict somewhere you should be good to go. pairs.csv
would be to just duplicate your pocket entries (it will essentially be calculating the distance between pocket 1 and pocket 1 which should be 0. This allows you to loop over just the pockets you care about without needing to modify the current interface.p.s. I would suggest starting from our image on Dockerhub, or building the docker image yourself since this repo has a few stale dependencies now which can be a bit fiddly to install (docker pull joshuameyers/deeplytough
)
Hope this helps
Hello Josh,
I am thinking of the possibility of using DeeplyTough as an embedder for protein pockets, so that each pocket is mapped to a vector of descriptors. Could you provide some guidance on how these could be obtained?
Also, is it possible to process a custom pdb as the input containing only the pocket residues, instead of relying on the automated pocket detection?
Thank you very much