Parsing contributions of physical phenomena to smFRET statistical inhomogeneity via multiparameter stochastic simulations

Abstract

Single-molecule Förster resonance energy transfer (smFRET) affords access to nanometer-scale structural and kinetic information for individual biomolecular species. Conventional analyses presuppose a strict separation of the underlying dynamical processes into distinct timescales—an assumption that is frequently violated and seldom verifiable a posteriori. To address this limitation, we present an integrated Brownian dynamics/stochastic simulation framework that treats the three principal dynamic contributors to smFRET observables—(i) diffusion of the molecule’s center of mass, (ii) photophysical state-cycling, and (iii) intramolecular diffusion—in a fully time-resolved manner. Each contribution can be selectively activated, deactivated, and parametrically adjusted, thereby providing a controlled computational testbed for determining the extent to which distinct dynamical contributions alter smFRET data. By systematically varying these contributions, the individual and collective impact of specific physical processes on smFRET measurements can be delineated and, therefore, the biologically relevant information (iii) can be more precisely estimated.