Chaos of Protein Folding

TL;DR

This paper investigates the chaotic nature of protein folding in a simplified 2D model, challenging the assumption of predictability and highlighting implications for biological structure prediction.

Contribution

It mathematically proves that protein folding in a 2D HP lattice model is chaotic, providing a new perspective on the complexity of folding processes.

Findings

Protein folding in the 2D HP model is chaotic as per Devaney's definition.

Chaos in folding suggests limits to predictability in biological systems.

Implications for structure prediction and biological understanding are discussed.

Abstract

As protein folding is a NP-complete problem, artificial intelligence tools like neural networks and genetic algorithms are used to attempt to predict the 3D shape of an amino acids sequence. Underlying these attempts, it is supposed that this folding process is predictable. However, to the best of our knowledge, this important assumption has been neither proven, nor studied. In this paper the topological dynamic of protein folding is evaluated. It is mathematically established that protein folding in 2D hydrophobic-hydrophilic (HP) square lattice model is chaotic as defined by Devaney. Consequences for both structure prediction and biology are then outlined.