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Single-molecule force spectroscopy is a powerful tool for studying protein folding. Over the last decade, a key question has emerged: how are changes in intrinsic biomolecular dynamics altered by attachment to μm-scale force probes via flexible linkers? Here, we studied the folding/unfolding of α3D using atomic force microscopy (AFM)–based force spectroscopy. α3D offers an unusual opportunity as a prior single-molecule fluorescence resonance energy transfer (smFRET) study showed α3D’s configurational diffusion constant within the context of Kramers theory varies with pH. The resulting pH dependence provides a test for AFM-based force spectroscopy’s ability to track intrinsic changes in protein folding dynamics. Experimentally, however, α3D is challenging. It unfolds at low force (<15 pN) and exhibits fast-folding kinetics. We therefore used focused ion beam–modified cantilevers that combine exceptional force precision, stability, and temporal resolution to detect state occupancies as brief as 1 ms. Notably, equilibrium and nonequilibrium force spectroscopy data recapitulated the pH dependence measured using smFRET, despite differences in destabilization mechanism. We reconstructed a one-dimensional free-energy landscape from dynamic data via an inverse Weierstrass transform. At both neutral and low pH, the resulting constant-force landscapes showed minimal differences (∼0.2 to 0.5kBT) in transition state height. These landscapes were essentially equal to the predicted entropic barrier and symmetric. In contrast, force-dependent rates showed that the distance to the unfolding transition state increased as pH decreased and thereby contributed to the accelerated kinetics at low pH. More broadly, this precise characterization of a fast-folding, mechanically labile protein enables future AFM-based studies of subtle transitions in mechanoresponsive proteins.
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Energetic driving force for LHCII clustering in plant membranes
Plants capture and convert solar energy in a complex network of membrane proteins. Under high light, the luminal pH drops and induces a reorganization of the protein network, particularly clustering of the major light-harvesting complex (LHCII). While the structures of the network have been resolved in exquisite detail, the thermodynamics that control the assembly and reorganization had not been determined, largely because the interaction energies of membrane proteins have been inaccessible. Here, we describe a method to quantify these energies and its application to LHCII. Using single-molecule measurements, LHCII proteoliposomes, and statistical thermodynamic modeling, we quantified the LHCII-LHCII interaction energy as ~−5kBTat neutral pH and at least −7kBTat acidic pH. These values revealed an enthalpic thermodynamic driving force behind LHCII clustering. Collectively, this work captures the interactions that drive the organization of membrane protein networks from the perspective of equilibrium statistical thermodynamics, which has a long and rich tradition in biology.
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- Award ID(s):
- 2130687
- PAR ID:
- 10485238
- Publisher / Repository:
- AAAS
- Date Published:
- Journal Name:
- Science Advances
- Volume:
- 9
- Issue:
- 51
- ISSN:
- 2375-2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/sciadv.adj0807
