Musicality in protein interaction dynamics informs the multi-scale evolution of prosocial behaviour

Area of Science:

• Biophysics
• Computational Biology
• Bioacoustics

Background:

• Non-verbal communication, like music and dance, fosters social connection.
• Proteins, particularly amyloids, form group structures with spatio-temporal correlations.
• Hypothesis: Amyloid vibrational frequencies may show musicality linked to prosocial behavior.

Purpose of the Study:

• To develop a data sonification method for molecular dynamics simulations.
• To analyze acoustic features of protein interactions for musicality.
• To investigate the relationship between amyloid structure, musicality, and prosocial behavior.

Main Methods:

• Developed a novel data sonification technique for simulated molecular dynamics.
• Applied auto-correlational and spectral cross-correlational analyses to sound data.
• Utilized machine learning to classify sounds based on 11 defined acoustic features.

Main Results:

• Amyloid protein interactions displayed more speech-like and musical acoustic features than less structured proteins.
• Significant shifts in memory (persistence) and autocorrelation characterized musicality in amyloids.
• Music showed less acoustic divergence from animal vocalizations compared to human speech.

Conclusions:

• Amyloid interactions possess inherent musicality, suggesting a link between biomolecular self-organization and prosocial behaviors.
• The acoustic properties of amyloid interactions provide a novel perspective on the evolution of communication.
• Music's acoustic proximity to animal vocalizations implies an ancient origin, potentially predating human language.