arXiv subjects

Emanuel Dorbath

Publications and source records attributed to Emanuel Dorbath.

4 recordsLinked to original sources

arXiv2026

Local molecular motions encode time-resolved infrared spectra of proteins

Time-resolved infrared spectroscopy probes protein dynamics over timescales spanning more than ten orders of magnitude, yet the molecular motions underlying the observed kinetic signatures have remained elusive. Here we combine transient infrared spectroscopy with nonequilibrium molecular dynamics simulations to establish a direct connection between experimental relaxation times and local structural motions. Studying single-domain allosteric proteins, we find that inter-residue contact distances provide the structural representation that most faithfully reproduces the experimental dynamics. Correlation analysis identifies localized networks of coordinated contacts that mediate communication between secondary-structure elements. The characteristic timescales of these contact networks quantitatively match the experimentally observed relaxation processes, enabling each kinetic step to be assigned to a specific molecular motion. Applied to allosteric signal propagation in PDZ3 and photoinduced ligand unbinding in PDZ2, this framework provides an atomistic picture of hierarchical protein relaxation and establishes a general framework for connecting transient infrared spectroscopy with the molecular mechanisms of protein dynamics.

cond-mat.soft↗

arXiv2025

Contact cluster modeling of allosteric communication in PDZ domains

Allostery, the intriguing phenomenon of long-range communication between distant sites in proteins, plays a central role in biomolecular regulation and signal transduction. While it is commonly attributed to conformational rearrangements, the underlying dynamical mechanisms remain poorly understood. The contact cluster model of allostery [J. Chem. Theory Comput. 2024, 20, 10731-10739] identifies localized groups of highly correlated contacts that mediate interactions between secondary structure elements. This framework proposes that allostery proceeds through a multistep process involving cooperative contact changes within clusters and communication between distant clusters, transmitted through rigid secondary structures. To demonstrate the validity and generality of the model, this Perspective employs extensive molecular dynamics simulations ($\sim1\,$ms total simulation time) of four different photoswitchable PDZ domains and studies how different domains, ligands, and perturbations influence both the contact clusters and their dynamical evolution. These analyses reveal several recurring clusters that represent shared flexible structural modules, such as loops connecting $\beta$-sheets, and show that the characteristic time scales of the nonequilibrium protein response can be directly associated with the motions of individual contact clusters. Thus, the dynamic decomposition of PDZ domains into contact clusters uncovers a modular, dynamics-based architecture that underlies and facilitates long-range allosteric communication.

physics.atm-clus↗

arXiv2024

Allosteric communication mediated by protein contact clusters: A dynamical model

Allostery refers to the puzzling phenomenon of long-range communication between distant sites in proteins. Despite its importance in biomolecular regulation and signal transduction, the underlying dynamical process is not well understood. This study introduces a dynamical model of allosteric communication based on "contact clusters"-localized groups of highly correlated contacts that facilitate interactions between secondary structures. The model shows that allostery involves a multi-step process with cooperative contact changes within clusters and communication between distant clusters mediated by rigid secondary structures. Considering time-dependent experiments on a photoswitchable PDZ3 domain, extensive (in total $\sim 500\,\mu$s) molecular dynamics simulations are conducted that directly monitor the photoinduced allosteric transition. The structural reorganization is illustrated by the time evolution of the contact clusters and the ligand, which affects the nonlocal coupling between distant clusters. A timescale analysis reveals dynamics from nano- to microseconds, which are in excellent agreement with the experimentally measured timescales.

physics.bio-ph↗

arXiv2023

Log-periodic oscillations as real-time signatures of hierarchical dynamics in proteins

The time-dependent relaxation of a dynamical system may exhibit a power-law behavior that is superimposed by log-periodic oscillations. Sornette [Phys. Rep. 297, 239 (1998)] showed that this behavior can be explained by a discrete scale invariance of the system, which is associated with discrete and equidistant timescales on a logarithmic scale. Examples include such diverse fields as financial crashes, random diffusion, and quantum topological materials. Recent time-resolved experiments and molecular dynamics simulations suggest that discrete scale invariance may also apply to hierarchical dynamics in proteins, where several fast local conformational changes are a prerequisite for a slow global transition to occur. Employing entropy-based timescale analysis and Markov state modeling to a simple one-dimensional hierarchical model and biomolecular simulation data, it is found that hierarchical systems quite generally give rise to logarithmically spaced discrete timescales. By introducing a one-dimensional reaction coordinate that collectively accounts for the hierarchically coupled degrees of freedom, the free energy landscape exhibits a characteristic staircase shape with two metastable end states, which causes the log-periodic time evolution of the system. The period of the log-oscillations reflects the effective roughness of the energy landscape, and can in simple cases be interpreted in terms of the barriers of the staircase landscape.

physics.bio-ph↗