We’ve been working with largish data sets and testing for protein-protein interactions using AF2, AF3 and Boltz. For many of these tests we’ve run the prediction programs locally on our supercomputer. We’ve also done a good amount of primary testing and double-checking using web-based interfaces available for CoLab(AF2) and AF3. I just recently started using Boltz2 through the ChimeraX interface.

What I’ve noticed so far is a pattern where the Boltz prediction through ChimeraX is giving much lower interaction scores, based on ipTM and PAEs, than Boltz through our supercomputer as well as AF2 and AF3 through our super computer or via the web. I’ve tried running multiple models, seeds, and increasing recycles to 3 as well as checking the two different boxes (Use steering potential vs. Use MSA cache). The commands I’ve run might look like: boltz predict #1/A #1/B recycle 3 seed 4 samples 5. In any case, I’m puzzled as to why the scores are consistently lower.

I recognize that I may be doing something wrong. For example, I seem to need to start out by running a first round of Boltz using the interaction window. Then once I get the first prediction, I can next invoke the “boltz predict” as above using different parameters on the command line. (These parameters are not part of the menus in the Boltz window that I can find.) The different runs, seeds, and models, I’m getting do give slightly different results, but they all seem to be under predicting what we know to be are quite strong interactions. I should say that we also see some differences between local and web-based AF3 and AF2 results, but they aren’t as extreme as what we’re seeing from Boltz from what we can tell.

Any thoughts? Thanks greatly in advance!

David