revealing This paper analyses the free energy foundations of inverse folding models for protein stability prediction, revealing limitations in current practice and proposing simple improvements for better zero-shot prediction.

We derive brain-like inference as natural gradient descent on free energy (FOND). The resulting spiking network (iP-VAE) outperforms amortized VAEs in reconstruction-sparsity trade-offs and out-of-distribution generalization.