Single-molecule FRET (smFRET) has become an established tool to study biomolecular structure and dynamics in vitro and in live cells. We performed a worldwide blind study involving 19 labs to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems that undergo distinct conformational changes, we obtained an uncertainty of the FRET efficiency of less than 0.06, corresponding to an interdye distance precision of less than 0.2 nm and accuracy of less than 0.5 nm. We further discuss the limits for detecting distance fluctuations with sensitivity down to less than 10% of the Foerster distance and provide guidelines on how to detect potential dye perturbations. The ability of smFRET experiments to simultaneously measure distances and avoid averaging of conformational dynamics slower than the fluorescence lifetime is unique for dynamic structural biology.
Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.
Understanding the basic chemistry between highly reactive free radicals and dopamine is an important step in characterizing the antioxidative activity of catecholamine neurotrasmitters. In this work, we simulated the reactions between dopamine and hydroxyl, peroxyl and methoxy radicals in aqueous solution by employing first principle molecular dynamics based on density functional theory and the BLYP functional. The simulations provide mechanistic insight into the reaction mechanisms but underestimate reaction timescales. The failure of the BLYP functional to address the formal hydrogen atom transfer barriers between dopamine and free radicals is attributed to the self-interaction error.
Maximum entropy methods (MEMs) determine posterior distributions by combining experimental data with prior information. MEMs are frequently used to reconstruct conformational ensembles of molecular systems for experimental information and initial molecular ensembles. We performed time-resolved Forster resonance energy transfer (FRET) experiments to probe the interdye distance distributions of the lipase-specific foldase Lif in the apo state, which likely has highly flexible, disordered, and/or ordered structural elements. Distance distributions estimated from ensembles of molecular dynamics (MD) simulations serve as prior information, and FRET experiments, analyzed within a Bayesian framework to recover distance distributions, are used for optimization. We tested priors obtained by MD with different force fields (FFs) tailored to ordered (FF99SB, FF14SB, and FF19SB) and disordered proteins (IDPSFF and FF99SBdisp). We obtained five substantially different posterior ensembles. As in our FRET experiments the noise is characterized by photon counting statistics, for a validated dye model, MEM can quantify consistencies between experiment and prior or posterior ensembles. However, posterior populations of conformations are uncorrelated to structural similarities for individual structures selected from different prior ensembles. Therefore, we assessed MEM simulating varying priors in synthetic experiments with known target ensembles. We found that (i) the prior and experimental information must be carefully balanced for optimal posterior ensembles to minimize perturbations of populations by overfitting and (ii) only ensemble-integrated quantities like inter-residue distance distributions or density maps can be reliably obtained but not ensembles of atomistic structures. This is because MEM optimizes ensembles but not individual structures. This result for a highly flexible system suggests that structurally varying priors calculated from varying prior ensembles, e.g., generated with different FFs, may serve as an ad hoc estimate for MEM reconstruction robustness.
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