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Research PaperResearchia:202602.13086

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

Nicola Dietler

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 i...

Submitted: February 13, 2026Subjects: Biochemistry; Pharmaceutical Research

Description / Details

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.


Source: arXiv:2602.11427v1 - http://arxiv.org/abs/2602.11427v1 PDF: https://arxiv.org/pdf/2602.11427v1 Original Link: http://arxiv.org/abs/2602.11427v1

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Submission Info
Date:
Feb 13, 2026
Topic:
Pharmaceutical Research
Area:
Biochemistry
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