Metals are essential nutrients that can also be toxic. Safe trafficking of metal ions is necessary inside cells, and specific metal transport pathways exist to deliver them to their destinations. 1,2 In human cells, the copper chaperone Hah1 and the Wilson disease protein (WDP) constitute a copper transport pathway-Hah1 is a single-domain cytoplasmic protein; WDP is a multidomain protein anchored on organelle membranes and has a cytosolic N-terminal region consisting of six homologous metal-binding domains (MBDs). All WDP MBDs and Hah1 contain a conserved CXXC motif that binds Cu 1+ , and Cu 1+ is transferred from Hah1 to a WDP MBD via direct and specific 3,4 Although the MBDs of WDP have different functional roles, 4,5 all of them, as well as Hah1, have similar Cu 1+ binding affinities. 3 This similarity indicates that the Hah1 to WDP Cu 1+ transfer is under kinetic control mediated by Hah1-WDP interactions, and that the functional differences among WDP MBDs are not defined by their Cu 1+ binding abilities but may be related to how each MBD interacts with Hah1. Very limited quantitative information is available, however, on the Hah1-WDP interaction dynamics. This is partly because the Hah1-WDP interactions are transient, and transient interactions are difficult to quantify in ensembleaveraged experiments.Here we report using nanovesicle trapping and single-molecule fluorescence resonance energy transfer (smFRET) measurements to probe the transient interactions between Hah1 and the fourth MBD (MBD4) of WDP in real time. We chose MBD4 as a representative WDP MBD because it is known to interact with Hah1 directly for Cu 1+ transfer. 4,6 Quantification of Hah1-MBD4 interaction dynamics will help understand how Hah1 and the full length WDP interact for Cu 1+ transfer.A primary obstacle in single-molecule experiments to probe transient protein interactions is the low concentrations (10 −12 -10 −9 M) commonly used to spatially separate molecules for detection, which limits the experiments to strong protein interactions. Weak protein interactions, including Hah1-WDP interactions, need to be studied at higher concentrations. Nonspecific protein-glass surface interactions during molecule immobilization present another challenge and must be minimized.To overcome these challenges, we adapted a nanovesicle trapping strategy (Figure 1), which was used to study protein and RNA folding and DNA-protein interactions at the singlemolecule level. 7 We trapped the two interacting molecules in a 100 nm diameter lipid vesicle. Because of the confined volume (∼5 × 10 −19 L), the effective concentration is ∼3 μM for each protein inside. Low concentrations of vesicles are then immobilized on a lipid bilayer or polymer-coated glass surface so protein-glass interactions are eliminated.To report Hah1-MBD4 interactions by smFRET, we introduced a C-terminal cysteine in both Hah1 and MBD4 and labeled this cysteine of Hah1 with Cy5 and that of MBD4 with Cy3. Cy3-Cy5 form a FRET pair with a Förster radius of ∼6 nm. The cysteines in the CXXC mot...
The distributions of the individual waiting times in Figure 2D were analyzed incorrectly. In the protein interaction scheme ( Figure 2C), each of the E FRET states (E 0 , E 1 , and E 2 ) branches directly to two other states. The decay constant from each of the six waiting time distributions (i.e., τ 0f1 , τ 0f2 , τ 1f0 , τ 1f2 , τ 2f0 , and τ 2f1 ) does not directly correspond to a particular kinetic constant in the interaction scheme, but instead is the sum of the rate constants of the two kinetic processes that branch from the same state (i.e., E 0 , E 1 , or E 2 ). The individual rate constants can subsequently be determined using the ratios of the number of transition events for each kinetic process. The relations between the decay constants of the waiting time distributions and the rate constants are given in the revised Figure 2D below; their derivations are in the additional Supporting Information. The decay constants of the τ 0f1 and τ 0f2 distributions should be the same, as should those of the τ 1f0 and τ 1f2 distributions and those of the τ 2f0 and τ 2f1 distributions. By omitting the first bin in each waiting time distribution, which is often inaccurate due to limited time resolution, all six waiting time distributions can be fitted consistently with single-exponential decay functions ( Figure 2D). The results give k 1 ) (1., and k -3 ) 0.7 ( 0.1 s -1. From these rate constants, we can also obtain the dissociation constants for the two interaction complexes with K 1 ) 5.6 ( 0.6 µM and K 2 ) 9 ( 1 µM (see also revised Figure S6 in the Supporting Information). Except for the quantitative values of the kinetic parameters listed here, this correction does not affect any other conclusions in our study. We thank Taekjip Ha for alerting us to the error. Supporting Information Available:Derivation of waiting time distribution for branching processes and revised Figure S6. This material is available free of charge via the Internet at http://pubs.acs.org.
Dynamic fluctuations in RNA structure enable conformational changes that are required for catalysis and recognition. In the hairpin ribozyme, the catalytically active structure is formed as an intricate tertiary interface between two RNA internal loops. Substantial alterations in the structure of each loop are observed upon interface formation, or docking. The very slow on-rate for this relatively tight interaction has led us to hypothesize a double conformational capture mechanism for RNA-RNA recognition. We used extensive molecular dynamics simulations to assess conformational sampling in the undocked form of the loop domain containing the scissile phosphate (loop A). We observed several major accessible conformations with distinctive patterns of hydrogen bonding and base stacking interactions in the active-site internal loop. Several important conformational features characteristic of the docked state were observed in well-populated substates, consistent with the kinetic sampling of docking-competent states by isolated loop A. Our observations suggest a hybrid or multistage binding mechanism, in which initial conformational selection of a docking-competent state is followed by induced-fit adjustment to an in-line, chemically reactive state only after formation of the initial complex with loop B.
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