Abstract

AbstractMechanistic 'physics' models of protein folding fail to account for the observed spectrum of protein folding and aggregation disorders, suggesting that a cognitive paradigm for protein folding regulation will be needed for understanding the etiology, prevention, and treatment of these diseases.

Highlights

  • Mechanistic ‘physics’ models of protein folding fail to account for the observed spectrum of protein folding and aggregation disorders, suggesting that a more appropriately biological paradigm will be needed for understanding the etiology, prevention, and treatment of these diseases

  • The existence of ‘global’ protein folding and aggregation diseases, in conjunction with the elaborate cellular folding regulatory apparatus associated with the endoplasmic reticulum and other structures (e.g., Scheuner and Kaufman, 2008; Dobson, 2003), makes clear that simple physical ‘folding funnel’ free energy mechanisms are not fully adequate to describe the process, to understate the matter

  • It is based on standard material from statistical physics and information theory, using, respectively, average distortion and the rate distortion function itself, as temperature analogs to produce mirror image ‘energy’ and ‘development’ pictures of protein folding

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Summary

Introduction

Mechanistic ‘physics’ models of protein folding fail to account for the observed spectrum of protein folding and aggregation disorders, suggesting that a more appropriately biological paradigm will be needed for understanding the etiology, prevention, and treatment of these diseases. In the ‘energy’ picture, the average distortion between codon message and final protein structure, under constraints driven by evolutionary selection, serves as a temperature analog, so that low values limit the possible distribution of protein forms, producing the canonical folding funnel. A dual ‘developmental’ perspective sees the rate distortion function itself as the temperature analog, and permits incorporation of chaperones or external factors as catalysts, driving the system to different possible outcomes or affecting the rate of convergence. A nonequilibrium empirical Onsager treatment provides an adaptable statistical model for protein folding, in the same manner as a regression equation. This produces quasi-equilibrium ‘resilience’ states representing normal, corrected, eliminated, and pathological states of protein folding.

Protein folding disorders
The ‘standard model’ of protein folding
Spontaneous symmetry breaking
A little information theory
The energy picture
The developmental picture
Symmetry arguments
The first level
The second level
Folding speed and mechanism
Catalysis of protein folding
Extending the model
Toward a cognitive paradigm for protein folding
Onsager models
Discussion and conclusions
10.1 Basic ideas about groupoids
10.2 Global and local symmetry groupoids
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