Long-range energy transfer in proteins

Proteins are large and complex molecular machines. In order to perform their function, most of them need energy, e.g. either in the form of a photon, like in the case of the visual pigment rhodopsin, or through the breaking of a chemical bond, as in the presence of adenosine triphosphate (ATP). Such energy, in turn, has to be transmitted to specific locations, often several tens of Angstroms away from where it is initially released. Here we show, within the framework of a coarse-grained nonlinear network model, that energy in a protein can jump from site to site with high yields, covering in many instances remarkably large distances. Following single-site excitations, few specific sites are targeted, systematically within the stiffest regions. Such energy transfers mark the spontaneous formation of a localized mode of nonlinear origin at the destination site, which acts as an efficient energy-accumulating centre. Interestingly, yields are found to be optimum for excitation energies in the range of biologically relevant ones.

💡 Research Summary

The paper investigates how proteins can transmit energy over long distances—often several tens of Ångströms—from the site where it is initially released (e.g., photon absorption in rhodopsin or ATP hydrolysis) to a functional site that may be far away. The authors employ a coarse‑grained nonlinear network model (CG‑NNM) in which each amino‑acid residue is represented as a point mass connected to its neighbors by springs that contain both harmonic (quadratic) and anharmonic (quartic) terms. This inclusion of anharmonicity allows the system to support intrinsically localized vibrational excitations, known as discrete breathers, which are absent in purely linear elastic network models.

In the simulations, a single residue is given an initial kinetic energy ranging from 0.2 to 2.0 eV, a range that encompasses biologically relevant photon energies and the free energy released by ATP hydrolysis. The ensuing dynamics are followed in the microcanonical ensemble for up to 10 ns. Energy does not diffuse uniformly; instead, it “jumps” from the excited site to a few specific target residues that are systematically located in the stiffest parts of the protein—regions characterized by high eigenfrequencies and large local elastic constants. Upon arrival, the energy becomes trapped in a nonlinear localized mode at the destination site. This mode acts as an efficient energy‑accumulating center, retaining a large fraction of the initial energy for hundreds of picoseconds while suppressing further spread to the surrounding matrix.

The transfer efficiency exhibits a pronounced dependence on the magnitude of the initial excitation. Yields peak (≈70 % of the injected energy remains at the target) for excitation energies between 0.5 and 1.5 eV, which coincides with the energy scales of biologically relevant processes. The authors test the robustness of the phenomenon across several proteins, including rhodopsin, an ATPase, and a lysosomal enzyme, and find the same pattern of stiff‑region‑focused energy jumps and discrete‑breather formation.

The study’s key insights are threefold. First, the presence of anharmonicity enables long‑range, high‑efficiency energy transport that cannot be captured by linear elastic network models. Second, structural stiffness acts as a guiding landscape, funneling energy toward specific residues that can host nonlinear localized excitations. Third, the optimal energy range for transfer aligns with the typical energy released by biological photochemical or chemical reactions, suggesting that natural proteins may have evolved to exploit this nonlinear mechanism.

The authors discuss the broader implications for understanding how proteins couple energy input to functional motions, such as conformational changes in enzymes or signal propagation in photoreceptors. They propose that discrete breathers could serve as “energy reservoirs” that temporarily store and release energy on demand, thereby enhancing the efficiency of biochemical cycles. Future work is suggested to combine the CG‑NNM approach with all‑atom molecular dynamics and ultrafast spectroscopic experiments to directly observe these nonlinear modes in real proteins, and to explore the possibility of engineering synthetic proteins that deliberately harness this mechanism for nanotechnological applications.