Representation choice shapes the interpretation of protein conformational dynamics

TL;DR

This paper demonstrates that the choice of representation significantly influences the interpretation of protein conformational dynamics in molecular simulations, introducing new methods and tools for analysis.

Contribution

It introduces Orientation features, a new rotation-aware encoding, and ManiProt, a library for comparing multiple protein representations.

Findings

Different representations highlight complementary conformational aspects.

No single representation captures all dynamics.

Orientation features improve analysis of backbone conformations.

Abstract

Molecular dynamics simulations provide detailed trajectories at the atomic level, but extracting interpretable and robust insights from these high-dimensional data remains challenging. In practice, analyses typically rely on a single representation. Here, we show that representation choice is not neutral: it fundamentally shapes the conformational organization, similarity relationships, and apparent transitions inferred from identical simulation data. To complement existing representations, we introduce Orientation features, a geometrically grounded, rotation-aware encoding of protein backbone. We compare it against common descriptions across three dynamical regimes: fast-folding proteins, large-scale domain motions, and protein-protein association. Across these systems, we find that different representations emphasize complementary aspects of conformational space, and that no single representation provides a complete picture of the underlying dynamics. To facilitate systematic comparison, we developed ManiProt, a library for efficient computation and analysis of multiple protein representations. Our results motivate a comparative, representation-aware framework for the interpretation of molecular dynamics simulations.