Zero-shot protein stability prediction by inverse folding models: a free energy interpretation

Jes Frellsen, Maher M. Kassem, Tone Bengtsen, Lars Olsen, Kresten Lindorff-Larsen +2 more
6/5/2025
cs.LGcs.AIq-bio.BM

No official code found. Best implementation: facebookresearch/esm (4,170 stars, MIT, last commit 2024-02-07). 1 more below.

Abstract

Inverse folding models have proven to be highly effective zero-shot predictors of protein stability. Despite this success, the link between the amino acid preferences of an inverse folding model and the free-energy considerations underlying thermodynamic stability remains incompletely understood. A better understanding would be of interest not only from a theoretical perspective, but also potentially provide the basis for stronger zero-shot stability prediction. In this paper, we take steps to clarify the free-energy foundations of inverse folding models. Our derivation reveals the standard practice of likelihood ratios as a simplistic approximation and suggests several paths towards better estimates of the relative stability. We empirically assess these approaches and demonstrate that considerable gains in zero-shot performance can be achieved with fairly simple means.

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Code Implementations(2)

MIT

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

4,170813Shell, PythonAug 31, 20202 years agoMIT
BSD-3-Clause

Code for the "Zero-shot protein stability prediction by inverse folding models: a free energy interpretation" paper.

20Python, Jupyter NotebookOct 14, 20259 months agoBSD-3-Clause

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Cite this paper

@article{frellsen2025zeroshot,
  title  = {Zero-shot protein stability prediction by inverse folding models: a free energy interpretation},
  author = {Jes Frellsen and Maher M. Kassem and Tone Bengtsen and Lars Olsen and Kresten Lindorff-Larsen and Jesper Ferkinghoff-Borg and Wouter Boomsma},
  year   = {2025},
  eprint = {2506.05596},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.05596v2}
}

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