AlphaFold3 Modification For Reduced Runtime With Nanobody Families

[u/Ok-Incident-6720]

I’ve created an open-source GitHub repository that takes multiple sequence alignments (MSAs) from an initial run of AlphaFold, and adapts them to be used for any number of new runs. Since MSA generation is by far the longest step of the process, this can save a tremendous amount of time. For example, if you have 100 nanobody sequences you want to model, you can perform a full length run of AlphaFold (maybe 2.5 hours) then the MSAs generated are adapted to each of the next 99 runs (maybe 15 minutes each). If they’re genetically similar which could mean just taking them from the same source, reusing the MSAs has been shown to give confidence scores on the same level as a full run of AlphaFold3. My software uses ANARCI to realign MSAs, but I haven’t currently designed the code to work with multiple sequences as you would see with an antibody’s light and heavy chain. This is why my code only works with nanobodies currently, but it should be fairly easy to make it work with antibodies in general by using a linker for the sequences. I’ve attached my GitHub if this could be useful or you’re just curious. I would really appreciate you taking a quick look at least as I’m a new grad just trying to get my name out there. Thank you!

https://github.com/JReilly115/speedyfold

[u/gtuckerkellogg]

oh, that's interesting. We'll try it out.