Proto–neural networks from thermal proteins

Mougkogiannis, Panagiotis; Adamatzky, Andrew

Abstract

Proteinoids are synthetic polymers that have structural similarities to natural proteins, and their formation is achieved through the application of heat to amino acid combinations in a dehydrated environment. The thermal proteins, initially synthesised by Sidney Fox during the 1960s, has the ability to undergo self-assembly, resulting in the formation of microspheres that resemble cells. These microspheres have fascinating biomimetic characteristics. In recent studies, substantial advancements have been made in elucidating the electrical signalling phenomena shown by proteinoids, hence showcasing their promising prospects in the field of neuro-inspired computing. This study demonstrates the advancement of experimental prototypes that employ proteinoids in the construction of fundamental neural network structures. The article provides an overview of significant achievements in proteinoid systems, such as the demonstration of electrical excitability, emulation of synaptic functions, capabilities in pattern recognition, and adaptability of network structures. This study examines the similarities and differences between proteinoid networks and spontaneous neural computation. We examine the persistent challenges associated with deciphering the underlying mechanisms of emergent proteinoid-based intelligence. Additionally, we explore the potential for developing bio-inspired computing systems using synthetic thermal proteins in forthcoming times. The results of this study offer a theoretical foundation for the advancement of adaptive, self-assembling electronic systems that operate using artificial bio-neural principles. [Abstract copyright: Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.]

Citation

Mougkogiannis, P., & Adamatzky, A. (2024). Proto–neural networks from thermal proteins. Biochemical and Biophysical Research Communications, 709, Article 149725. https://doi.org/10.1016/j.bbrc.2024.149725

• Journal Article Type: Article
• Acceptance Date: Feb 25, 2024
• Online Publication Date: Mar 16, 2024
• Publication Date: May 21, 2024
• Deposit Date: Mar 18, 2024
• Publicly Available Date: Apr 12, 2024
• Journal: Biochemical and biophysical research communications
• Print ISSN: 0006-291X
• Electronic ISSN: 1090-2104
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 709
• Article Number: 149725
• DOI: https://doi.org/10.1016/j.bbrc.2024.149725
• Keywords: Memristive systems, Amino Acids, Hot Temperature, Unconventional computing, Neural Networks, Computer, Proteins - metabolism, Proteinoids, Bioinspired engineering, Prebiotic chemistry, Electrical spiking
• Public URL: https://uwe-repository.worktribe.com/output/11824434
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0006291X24002614?via%3Dihub
• Additional Information: This article is maintained by: Elsevier; Article Title: Proto–neural networks from thermal proteins; Journal Title: Biochemical and Biophysical Research Communications; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.bbrc.2024.149725; Content Type: article; Copyright: © 2024 The Author(s). Published by Elsevier Inc.