Frequency-Space Mechanics: A Sequence and Coordinate-Free Representation for Protein Function Prediction

TL;DR

This paper introduces frequency-space mechanics, a vibrational dynamics-based representation for proteins, enabling function prediction without sequence data, and demonstrates its effectiveness with graph neural networks and quantum-compatible operations.

Contribution

It presents a novel coordinate-free, sequence-independent protein representation using vibrational modes, advancing function prediction methods.

Findings

Vibrational physics alone predicts broad functional classes.

Entrainment improves prediction for function-dependent conformational dynamics.

Achieved 7.5-fold and 2.4-fold signal amplification in CLIC1 protein states.

Abstract

Protein function prediction is dominated by representations grounded in sequence and static structure, neither of which captures the collective vibrational dynamics through which proteins act. Here we introduce frequency-space mechanics, a representational framework in which a protein is encoded as a mechanical harmonics graph (MHG): nodes are vibrational modes derived from molecular dynamics, and edges are harmonic couplings weighted by octave alignment between mode frequencies. The representation is coordinate-free, sequence-independent, scale-invariant, and inhabits a latent mechanical space in which the original atomic coordinates have been projected out. The same construction applies to any system with a tractable eigendecomposition. Trained on 5,238 SwissProt proteins under a strict 30% sequence-identity split and using no sequence information, a graph neural network over static MHGs predicts GO molecular function terms across the ontology, demonstrating that vibrational physics alone encodes broad functional class. Kuramoto entrainment of the harmonic coupling graph, formally a Hamiltonian operation over mode frequencies and directly compatible with quantum annealing hardware, improves prediction for proteins whose function depends on collective conformational dynamics. On CLIC1, a fold- and function-switching chloride channel excluded from training, entrainment amplifies channel-activity signal 7.5-fold and antioxidant signal 2.4-fold, recovering both functional states from dynamics alone.