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Improved Free‐Energy Landscape Quantification Illustrated with a Computationally Designed Protein–Ligand Interaction
Author(s) -
Van Patten William J.,
Walder Robert,
Adhikari Ayush,
Okoniewski Stephen R.,
Ravichandran Rashmi,
Tinberg Christine E.,
Baker David,
Perkins Thomas T.
Publication year - 2018
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/cphc.201701147
Subject(s) - energy landscape , chemistry , ligand (biochemistry) , energy (signal processing) , protein ligand , computational chemistry , biological system , nanotechnology , chemical physics , computer science , materials science , physics , biochemistry , biology , receptor , quantum mechanics
Quantifying the energy landscape underlying protein–ligand interactions leads to an enhanced understanding of molecular recognition. A powerful yet accessible single‐molecule technique is atomic force microscopy (AFM)‐based force spectroscopy, which generally yields the zero‐force dissociation rate constant ( k off ) and the distance to the transition state (Δ x ≠ ). Here, we introduce an enhanced AFM assay and apply it to probe the computationally designed protein DIG10.3 binding to its target ligand, digoxigenin. Enhanced data quality enabled an analysis that yielded the height of the transition state (Δ G ≠ =6.3±0.2 kcal mol −1 ) and the shape of the energy barrier at the transition state (linear‐cubic) in addition to the traditional parameters [ k off (=4±0.1×10 −4 s −1 ) and Δ x ≠ (=8.3±0.1 Å)]. We expect this automated and relatively rapid assay to provide a more complete energy landscape description of protein–ligand interactions and, more broadly, the diverse systems studied by AFM‐based force spectroscopy.