Deterministic Protein Folding from Coherence Fields

This paper presents a deterministic, geometry-based model of protein folding within the Coherence Geometry (CG) framework. Residues are modeled as local multi-phase agents embedded in a spatial field, each carrying internal phase biases that reflect simplified chemical identities. The chain folds through local alignment dynamics, long-range field interactions, collapse pressure, identity-driven directionality, and ripple-like correction events. The paper studies folding in one-dimensional chains of 50 to 200 residues and reports the emergence of compact protein-like structures, modular substructure, stable hydrophobic cores, residue-order sensitivity, phase-channel effects, single-point mutation sensitivity, identity-shuffle behavior, curvature/ripple activity, long-chain dynamics, and residue-class differentiation. The model treats folding as a coherence-driven formation process in which geometry, residue identity, phase alignment, local tension, long-range interaction, and correction events jointly guide the chain toward compact organized structures. The paper should be read as a simulation-driven CG study of folding principles and coherent core formation. Broader all-atom modeling, quantitative biochemical calibration, native-structure prediction, and full protein-engineering applications are left to future work. This paper is released in its original May 2025 form and belongs to the early simulation-driven biological phase of the CG corpus. The paper defines the folding model internally, including residue representation, multi-phase alignment, ripple events, long-range interactions, and update rules. Later canon records and Foundations texts provide the current public reference layer for the underlying CG framework. The Zenodo record includes a Jupyter notebook used to generate the protein-folding images, videos, and plots associated with the paper. The notebook is provided as a research artifact for inspection, experimentation, and reproducibility support, not as maintained software. Internal reference: CGI-RSR-000026.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-19
DOI
https://doi.org/10.5281/zenodo.20285351
Primary Topic
Protein Structure and Dynamics
Type
preprint
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preprint

Deterministic Protein Folding from Coherence Fields

B. Petersen
Zenodo (CERN European Organization for Nuclear Research)
Protein Structure and Dynamics
preprint

Deterministic Protein Folding from Coherence Fields

B. Petersen
preprint en

Abstract

This paper presents a deterministic, geometry-based model of protein folding within the Coherence Geometry (CG) framework. Residues are modeled as local multi-phase agents embedded in a spatial field, each carrying internal phase biases that reflect simplified chemical identities. The chain folds through local alignment dynamics, long-range field interactions, collapse pressure, identity-driven directionality, and ripple-like correction events. The paper studies folding in one-dimensional chains of 50 to 200 residues and reports the emergence of compact protein-like structures, modular substructure, stable hydrophobic cores, residue-order sensitivity, phase-channel effects, single-point mutation sensitivity, identity-shuffle behavior, curvature/ripple activity, long-chain dynamics, and residue-class differentiation. The model treats folding as a coherence-driven formation process in which geometry, residue identity, phase alignment, local tension, long-range interaction, and correction events jointly guide the chain toward compact organized structures. The paper should be read as a simulation-driven CG study of folding principles and coherent core formation. Broader all-atom modeling, quantitative biochemical calibration, native-structure prediction, and full protein-engineering applications are left to future work. This paper is released in its original May 2025 form and belongs to the early simulation-driven biological phase of the CG corpus. The paper defines the folding model internally, including residue representation, multi-phase alignment, ripple events, long-range interactions, and update rules. Later canon records and Foundations texts provide the current public reference layer for the underlying CG framework. The Zenodo record includes a Jupyter notebook used to generate the protein-folding images, videos, and plots associated with the paper. The notebook is provided as a research artifact for inspection, experimentation, and reproducibility support, not as maintained software. Internal reference: CGI-RSR-000026.

Zenodo (CERN European Organization for Nuclear Research)
Geomechanica (Canada) (CA)
Protein Structure and Dynamics
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