Dual Lifetimes for Complexes between Glutathione-S-transferase (hGSTA1-1) and Product-like Ligands Detected by Single-Molecule Fluorescence Imaging

Measuring PETase enzyme kinetics by single-molecule microscopy

Polyethylene terephthalate (PET) is one of the most widely produced man-made polymers and is a significant contributor to microplastics pollution. The environmental and human health impacts of microplastics pollution have motivated a concerted effort to develop microbe- and enzyme-based strategies to degrade PET and similar plastics. A PETase derived from the bacteria Ideonella sakaiensis was previously shown to enzymatically degrade PET, triggering multidisciplinary efforts to improve the robustness and activity of this and other PETases. However, because these enzymes only erode the surface of the insoluble PET substrate, it is difficult to measure standard kinetic parameters, such as kon, koff and kcat, complicating interpretation of the activity of mutants using traditional enzyme kinetics frameworks. To address this challenge, we developed a single-molecule microscopy assay that quantifies the landing rate and binding duration of quantum dot-labeled PETase enzymes interacting with a surface-immobilized PET film. Wild-type PETase binding durations were well fit by a biexponential with a fast population having a 2.7 s time constant, interpreted as active binding events, and a slow population interpreted as non-specific binding interactions that last tens of seconds. A previously described hyperactive mutant, S238F/W159H had both a faster on-rate and a slower off-rate than wild-type PETase, potentially explaining its enhanced activity. Because this single-molecule approach provides a more detailed mechanistic picture of PETase enzymatic activity than standard bulk assays, it should aid future efforts to engineer more robust and active PETases to combat global microplastics pollution.

Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.

Direct observation of negative cooperativity in a detoxification enzyme at the atomic level by Electron Paramagnetic Resonance spectroscopy and simulation

The catalytic activity of human glutathione S-transferase A1-1 (hGSTA1-1), a homodimeric detoxification enzyme, is dependent on the conformational dynamics of a key C-terminal helix α9 in each monomer. However, the structural details of how the two monomers interact upon binding of substrates is not well understood and the structure of the ligand-free state of the hGSTA1-1 homodimer has not been resolved. Here, we used a combination of electron paramagnetic resonance (EPR) distance measurements and weighted ensemble (WE) simulations to characterize the conformational ensemble of the ligand-free state at the atomic level. EPR measurements reveal a broad distance distribution between a pair of Cu(II) labels in the ligand-free state that gradually shifts and narrows as a function of increasing ligand concentration. These shifts suggest changes in the relative positioning of the two α9 helices upon ligand binding. WE simulations generated unbiased pathways for the seconds-timescale transition between alternate states of the enzyme, leading to the generation of atomically detailed structures of the ligand-free state. Notably, the simulations provide direct observations of negative cooperativity between the monomers of hGSTA1-1, which involve the mutually exclusive docking of α9 in each monomer as a lid over the active site. We identify key interactions between residues that lead to this negative cooperativity. Negative cooperativity may be essential for interaction of hGSTA1-1 with a wide variety of toxic substrates and their subsequent neutralization. More broadly, this work demonstrates the power of integrating EPR distances with WE rare-events sampling strategy to gain mechanistic information on protein function at the atomic level.

ESR Resolves the C Terminus Structure of the Ligand-free Human Glutathione S-Transferase A1-1

Nitroxide- and Cu²⁺-based electron spin resonance (ESR) are combined to provide insight into the conformational states of the functionally important α-helix of the human glutathione S-transferase A1. Distance measurements on various spin-labeled dimeric human glutathione S-transferase A1-1 all result in bimodal distance distributions, indicating that the C-terminus exists in two distinct conformations in solution, one of which closely matches that found in the crystal structure of the ligand-bound enzyme. These measurements permit the generation of a model of the unliganded conformation. Room temperature ESR indicates that the second conformation has high mobility, potentially enabling the enzyme's high degree of substrate promiscuity. This model is then validated using computational modeling and further Cu²⁺-based ESR distance measurements. Cu²⁺-based ESR also provides evidence that the secondary structure of the second conformation is of helical nature. Addition of S-hexyl glutathione results in a shift in relative populations, favoring the state that is similar to the previously known structure of the ligand-bound enzyme.