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March 25, 2026ChemBioChem3 citationsOpen Access

Fast and Slow Signal Propagation in Abiotic Polypeptide Assemblies

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PMPanagiotis MougkogiannisAAAndrew Adamatzky

Key Points

  • The aim is to quantify and analyze the electrical and structural dynamics of proteinoid microspheres.
  • Used multi-electrode differential recordings for electrical dynamics.
  • Performed high-resolution electron microscopy for structural analysis.
  • Characterized emergent dynamics using algorithmic complexity and graph theory.
  • Identified rapid voltage oscillations and long-timescale electrical drifts.
  • Found unique electrical properties correlated with microsphere composition.
  • Developed a new quantitative framework to assess electrical patterns.

Abstract

Proteinoid microspheres-abiotically synthesized by thermal polymerization of amino acids-exhibit spontaneous electrical potential fluctuations despite lacking genetic material, membranes, or ion channels. Here, we quantify the electrical and structural dynamics of five proteinoid compositions using multi-electrode differential recordings and high-resolution electron microscopy. The assemblies display rapid voltage oscillations (timescales ≪ 1 1 min), long-timescale drifts (hours to days), exponential relaxation, and correlated potential shifts across spatially separated electrode pairs (Pearson correlations 0. 147-0. 601, significantly above baseline noise levels, r 0. 05 r amp;amp;amp;amp;lt; 0. 05), suggesting composition-dependent patterns of electrical coupling. Optical stimulation induces reproducible voltage responses characterized by logarithmic drift and stimulus-specific stabilization, indicating that proteinoid networks can modulate electrical pathways in response to external perturbations. Morphological analysis reveals that single-amino-acid systems create uniform microspheres (2-3 μm). In contrast, mixed compositions lead to varied structures. These include hollow spheres, lamellar extensions, and crystalline aggregates that can reach 129 μm. Each structure shows unique electrical signatures. We develop a quantitative framework based on algorithmic complexity (Lempel-Ziv), spatial coherence (phase-locking value), and graph-theoretical metrics (global efficiency, clustering coefficient) to characterize emergent dynamics in these abiotic networks. These results show that proteinoid assemblies have unique electrical properties based on their composition. This may help us understand prebiotic organization and inspire new types of bioinspired computing materials.

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Cite This Study

Mougkogiannis et al. (2026) studied this question.

synapsesocial.com/papers/69c37bb3b34aaaeb1a67e4fchttps://doi.org/10.1002/cbic.202500943
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