Out-of-equilibrium selection pressure enhances inference from protein sequence data

Nicola Dietler; Cyril Malbranke; Anne-Florence Bitbol

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arXiv · 2602.11427

Out-of-equilibrium selection pressure enhances inference from protein sequence data

Nicola Dietler·Cyril Malbranke·Anne-Florence Bitbol

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Abstract

Homologous proteins have similar three-dimensional structures and biological functions that shape their sequences. The resulting coevolution-driven correlations underlie methods from Potts models to AlphaFold, which infer protein structure and function from sequences. Using a minimal model, we show that fluctuating selection strength and the onset of new selection pressures improve coevolution-based inference of structural contacts. Our conclusions extend to realistic synthetic data and to the inference of interaction partners. Out-of-equilibrium noise arising from ubiquitous variations in natural selection thus enhances, rather than hinders, the success of inference from protein sequences.

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Nicola Dietler, Cyril Malbranke, Anne-Florence Bitbol. 2026-02-11. Out-of-equilibrium selection pressure enhances inference from protein sequence data. https://arxiv.org/abs/2602.11427

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