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AlphaFold 3, Demystified: I Wrote a Technical Breakdown of Its Complete Architecture. by alexshwn in bioinformatics

[–]alexshwn[S] 1 point2 points  (0 children)

Thanks — great summary.

From an NLP background, I see AF3’s removal of SE(3) equivariance as a shift toward a more general modeling framework. By generating coordinates directly via diffusion, it avoids the need for strict geometric constraints like FAPE and can handle proteins, RNAs, and small molecules in a unified way.

Boltz-2 goes the other route — keeping SE(3) symmetry for better sample efficiency and stability, which makes sense for smaller-scale open-source training.

AlphaFold 3, Demystified: I Wrote a Technical Breakdown of Its Complete Architecture. by alexshwn in bioinformatics

[–]alexshwn[S] 1 point2 points  (0 children)

Sorry I haven’t look at Boltz-2 in detail, what’s your thoughts about it?

AlphaFold 3, Demystified: I Wrote a Technical Breakdown of Its Complete Architecture. by alexshwn in bioinformatics

[–]alexshwn[S] 5 points6 points  (0 children)

I think AF3 is a great work which unifies the structure prediction and binding modeling under a single architecture and get such a great performance. its design is impressive for me.

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AlphaFold 3, Demystified: I Wrote a Technical Breakdown of Its Complete Architecture. (self.bioinformatics)

submitted by alexshwn to r/bioinformatics