Cooperative Conformational Transitions Underpin the Activation Heat Capacity in the Temperature Dependence of Enzyme Catalysis.

Many enzymes display non-Arrhenius behavior with curved Arrhenius plots in the absence of denaturation. There has been significant debate about the origin of this behavior and recently the role of the activation heat capacity (ΔCP⧧) has been widely discussed. If enzyme-catalyzed reactions occur with appreciable negative values of ΔCP⧧ (arising from narrowing of the conformational space along the reaction coordinate), then curved Arrhenius plots are a consequence. To investigate these phenomena in detail, we have collected high precision temperature-rate data over a wide temperature interval for a model glycosidase enzyme MalL, and a series of mutants that change the temperature-dependence of the enzyme-catalyzed rate. We use these data to test a range of models including macromolecular rate theory (MMRT) and an equilibrium model. In addition, we have performed extensive molecular dynamics (MD) simulations to characterize the conformational landscape traversed by MalL in the enzyme-substrate complex and an enzyme-transition state complex. We have crystallized the enzyme in a transition state-like conformation in the absence of a ligand and determined an X-ray crystal structure at very high resolution (1.10 Å). We show (using simulation) that this enzyme-transition state conformation has a more restricted conformational landscape than the wildtype enzyme. We coin the term "transition state-like conformation (TLC)" to apply to this state of the enzyme. Together, these results imply a cooperative conformational transition between an enzyme-substrate conformation (ES) and a transition-state-like conformation (TLC) that precedes the chemical step. We present a two-state model as an extension of MMRT (MMRT-2S) that describes the data along with a convenient approximation with linear temperature dependence of the activation heat capacity (MMRT-1L) that can be used where fewer data points are available. Our model rationalizes disparate behavior seen for MalL and previous results for a thermophilic alcohol dehydrogenase and is consistent with a raft of data for other enzymes. Our model can be used to characterize the conformational changes required for enzyme catalysis and provides insights into the role of cooperative conformational changes in transition state stabilization that are accompanied by changes in heat capacity for the system along the reaction coordinate. TLCs are likely to be of wide importance in understanding the temperature dependence of enzyme activity and other aspects of enzyme catalysis.

Synthetic cannabinoid use in an adult male prison in the UK.

INTRODUCTION: Synthetic cannabinoids (i.e. Spice) are a major public health problem in UK prisons, however, research in this area is limited. Here we aimed to draw comparisons between people with and without experience of using synthetic cannabinoids in prison, to characterise the features of, and motivations for use within this setting and evaluate support for different treatment interventions. METHOD: Questionnaires were administered to 122 people in a category-B prison for adult males in England between July 2022 and March 2023. Participants were asked questions related to their sociodemographic and custodial characteristics, use of synthetic cannabinoids (and other drugs) inside and outside of prison and psychological distress was measured via the Brief Symptom Inventory (BSI-18). Those that had ever used synthetic cannabinoids in prison completed additional questions related to features of use, motivations for use and support for various interventions. RESULTS: In total 46.7 % (n = 57) of participants reported use of synthetic cannabinoids in prison and this group experienced significantly greater levels of psychological distress compared to those reporting no use (mean (± standard deviation) BSI-18 scores = 23.7 (±16.7) vs 12.8 (±13.6), p < 0.001). Participants mostly reported using paper-based preparations (77.4 %) and use via e-cigarettes (75.9 %). The most strongly endorsed motivations for use included to alleviate boredom (91.1 % strongly agree/agree), to make the sentence pass faster (89.3 % strongly agree/agree) and to cope with stress (80.4 % strongly agree/agree). The interventions that received most support were strategies to better manage time and medication to manage withdrawal. CONCLUSIONS: The use of synthetic cannabinoids in UK prisons typically involves the use of paper-based preparations via e-cigarettes, and use is associated with greater levels of psychological distress. Motivations for use were mostly pragmatic (e.g. to alleviate boredom or cope with stress) and interventions should prioritise increasing the time individuals spend out of cells and in meaningful activity.

Instant Detection of Synthetic Cannabinoids on Physical Matrices, Implemented on a Low-Cost, Ultraportable Device.

Synthetic cannabinoids (SCs) make up a class of novel psychoactive substances (NPS), used predominantly in prisons and homeless communities in the U.K. SCs can have severe side effects, including psychosis, stroke, and seizures, with numerous reported deaths associated with their use. The chemical diversity of SCs presents the major challenge to their detection since approaches relying on specific molecular recognition become outdated almost immediately. Ideally one would have a generic approach to detecting SCs in portable settings. The problem of SC detection is more challenging still because the majority of SCs enter the prison estate adsorbed onto physical matrices such as paper, fabric, or herb materials. That is, regardless of the detection modality used, the necessary extraction step reduces the effectiveness and ability to rapidly screen materials on-site. Herein, we demonstrate a truly instant generic test for SCs, tested against real-world drug seizures. The test is based on two advances. First, we identify a spectrally silent region in the emission spectrum of most physical matrices. Second, the finding that background signals (including from autofluorescence) can be accurately predicted is based on tracking the fraction of absorbed light from the irradiation source. Finally, we demonstrate that the intrinsic fluorescence of a large range of physical substrates can be leveraged to track the presence of other drugs of interest, including the most recent iterations of benzodiazepines and opioids. We demonstrate the implementation of our presumptive test in a portable, pocket-sized device that will find immediate utility in prisons and law enforcement agencies around the world.

Glycosylation increases active site rigidity leading to improved enzyme stability and turnover.

Glycosylation is the most prevalent protein post-translational modification, with a quarter of glycosylated proteins having enzymatic properties. Yet, the full impact of glycosylation on the protein structure-function relationship, especially in enzymes, is still limited. Here, we show that glycosylation rigidifies the important commercial enzyme horseradish peroxidase (HRP), which in turn increases its turnover and stability. Circular dichroism spectroscopy revealed that glycosylation increased holo-HRP's thermal stability and promoted significant helical structure in the absence of haem (apo-HRP). Glycosylation also resulted in a 10-fold increase in enzymatic turnover towards o-phenylenediamine dihydrochloride when compared to its nonglycosylated form. Utilising a naturally occurring site-specific probe of active site flexibility (Trp117) in combination with red-edge excitation shift fluorescence spectroscopy, we found that glycosylation significantly rigidified the enzyme. In silico simulations confirmed that glycosylation largely decreased protein backbone flexibility, especially in regions close to the active site and the substrate access channel. Thus, our data show that glycosylation does not just have a passive effect on HRP stability but can exert long-range effects that mediate the 'native' enzyme's activity and stability through changes in inherent dynamics.

Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection.

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group, which makes rapid detection challenging. We have previously shown that fluorescence spectral fingerprinting (FSF) has the potential to provide rapid assessment of SCRA presence directly from street material with minimal processing and in saliva. Enhancing the sensitivity and discriminatory ability of this approach has high potential to accelerate the delivery of a point-of-care technology that can be used confidently by a range of stakeholders, from medical to prison staff. We demonstrate that a range of structurally distinct SCRAs are photochemically active and give rise to distinct FSFs after irradiation. To explore this in detail, we have synthesized a model series of compounds which mimic specific structural features of AM-694. Our data show that FSFs are sensitive to chemically conservative changes, with evidence that this relates to shifts in the electronic structure and cross-conjugation. Crucially, we find that the photochemical degradation rate is sensitive to individual structures and gives rise to a specific major product, the mechanism and identification of which we elucidate through density-functional theory (DFT) and time-dependent DFT. We test the potential of our hybrid "photochemical fingerprinting" approach to discriminate SCRAs by demonstrating SCRA detection from a simulated smoking apparatus in saliva. Our study shows the potential of tracking photochemical reactivity via FSFs for enhanced discrimination of SCRAs, with successful integration into a portable device.

Synthetic cannabinoid receptor agonists are monoamine oxidase-A selective inhibitors.

Synthetic cannabinoid receptor agonists (SCRAs) are one of the fastest growing classes of recreational drugs. Despite their growth in use, their vast chemical diversity and rapidly changing landscape of structures make understanding their effects challenging. In particular, the side effects for SCRA use are extremely diverse, but notably include severe outcomes such as cardiac arrest. These side effects appear at odds with the main putative mode of action, as full agonists of cannabinoid receptors. We have hypothesized that SCRAs may act as MAO inhibitors, owing to their structural similarity to known monoamine oxidase inhibitors (MAOI's) as well as matching clinical outcomes (hypertensive crisis) of 'monoaminergic toxicity' for users of MAOIs and some SCRA use. We have studied the potential for SCRA-mediated inhibition of MAO-A and MAO-B via a range of SCRAs used commonly in the UK, as well as structural analogues to prove the atomistic determinants of inhibition. By combining in silico and experimental kinetic studies we demonstrate that SCRAs are MAO-A-specific inhibitors and their affinity can vary significantly between SCRAs, most notably affected by the nature of the SCRA 'head' group. Our data allow us to posit a putative mechanism of inhibition. Crucially our data demonstrate that SCRA activity is not limited to just cannabinoid receptor agonism and that alternative interactions might account for some of the diversity of the observed side effects and that these effects can be SCRA-specific.

Trends in hospital presentations following analytically confirmed synthetic cannabinoid receptor agonist exposure before and after implementation of the 2016 UK Psychoactive Substances Act.

BACKGROUND AND AIMS: The United Kingdom (UK) Psychoactive Substances Act (PSA), implemented on the 26th  May 2016, made the production, supply and sale of all non-exempted psychoactive substances illegal. The aim of this study was to measure trends in hospital presentations for severe toxicity following analytically confirmed synthetic cannabinoid receptor agonist (SCRA) exposure before and after implementation of the PSA. DESIGN: Observational study. SETTING: Thirty-four hospitals across the UK participating in the Identification of Novel Psychoactive Substances (IONA) study. PARTICIPANTS: A total of 627 (79.9% male) consenting individuals who presented to participating hospitals between July 2015 and December 2019 with severe acute toxicity and suspected novel psychoactive substances exposure. MEASUREMENTS: Toxicological analyses of patient samples were conducted using liquid-chromatography tandem mass-spectrometry. Time-series analysis was conducted on the monthly number of patients with and without analytically confirmed SCRA exposure using Poisson segmented regression. FINDINGS: SCRAs were detected in 35.7% (n = 224) of patients. After adjusting for seasonality and the number of active sites, models showed no clear evidence of an upward or downward trend in the number of SCRA exposure cases in the period before (incidence rate ratio [IRR], 1.12; 95% CI, 0.99-1.26; P = 0.068) or after (IRR, 0.97; 95% CI, 0.94-1.01; P = 0.202) the implementation of the PSA. There was also no clear evidence of an upward or downward trend in non-SCRA exposure cases before (IRR, 1.12; 95% CI, 0.98-1.27; P = 0.105) or after (IRR, 1.01; 95% CI, 0.98-1.04; P = 0.478) implementation of the PSA. CONCLUSIONS: There is no clear evidence of an upward or downward trend in the number of patients presenting to UK hospitals with severe acute toxicity following analytically confirmed synthetic cannabinoid receptor agonist exposure since the implementation of the Psychoactive Substances Act.

Reliable In Silico Ranking of Engineered Therapeutic TCR Binding Affinities with MMPB/GBSA.

Accurate and efficient in silico ranking of protein-protein binding affinities is useful for protein design with applications in biological therapeutics. One popular approach to rank binding affinities is to apply the molecular mechanics Poisson-Boltzmann/generalized Born surface area (MMPB/GBSA) method to molecular dynamics (MD) trajectories. Here, we identify protocols that enable the reliable evaluation of T-cell receptor (TCR) variants binding to their target, peptide-human leukocyte antigens (pHLAs). We suggest different protocols for variant sets with a few (≤4) or many mutations, with entropy corrections important for the latter. We demonstrate how potential outliers could be identified in advance and that just 5-10 replicas of short (4 ns) MD simulations may be sufficient for the reproducible and accurate ranking of TCR variants. The protocols developed here can be applied toward in silico screening during the optimization of therapeutic TCRs, potentially reducing both the cost and time taken for biologic development.

Structure and in silico simulations of a cold-active esterase reveals its prime cold-adaptation mechanism.

Here we determined the structure of a cold active family IV esterase (EstN7) cloned from Bacillus cohnii strain N1. EstN7 is a dimer with a classical α/ß hydrolase fold. It has an acidic surface that is thought to play a role in cold-adaption by retaining solvation under changed water solvent entropy at lower temperatures. The conformation of the functionally important cap region is significantly different to EstN7's closest relatives, forming a bridge-like structure with reduced helical content providing greater access to the active site through more than one substrate access tunnel. However, dynamics do not appear to play a major role in cold adaption. Molecular dynamics at different temperatures, rigidity analysis, normal mode analysis and geometric simulations of motion confirm the flexibility of the cap region but suggest that the rest of the protein is largely rigid. Rigidity analysis indicates the distribution of hydrophobic tethers is appropriate to colder conditions, where the hydrophobic effect is weaker than in mesophilic conditions due to reduced water entropy. Thus, it is likely that increased substrate accessibility and tolerance to changes in water entropy are important for of EstN7's cold adaptation rather than changes in dynamics.

Chemical Mapping Exposes the Importance of Active Site Interactions in Governing the Temperature Dependence of Enzyme Turnover.

Uncovering the role of global protein dynamics in enzyme turnover is needed to fully understand enzyme catalysis. Recently, we have demonstrated that the heat capacity of catalysis, ΔC P ‡, can reveal links between the protein free energy landscape, global protein dynamics, and enzyme turnover, suggesting that subtle changes in molecular interactions at the active site can affect long-range protein dynamics and link to enzyme temperature activity. Here, we use a model promiscuous enzyme (glucose dehydrogenase from Sulfolobus solfataricus) to chemically map how individual substrate interactions affect the temperature dependence of enzyme activity and the network of motions throughout the protein. Utilizing a combination of kinetics, red edge excitation shift (REES) spectroscopy, and computational simulation, we explore the complex relationship between enzyme-substrate interactions and the global dynamics of the protein. We find that changes in ΔC P ‡ and protein dynamics can be mapped to specific substrate-enzyme interactions. Our study reveals how subtle changes in substrate binding affect global changes in motion and flexibility extending throughout the protein.

Rigidifying a De Novo Enzyme Increases Activity and Induces a Negative Activation Heat Capacity.

Conformational sampling profoundly impacts the overall activity and temperature dependence of enzymes. Peroxidases have emerged as versatile platforms for high-value biocatalysis owing to their broad palette of potential biotransformations. Here, we explore the role of conformational sampling in mediating activity in the de novo peroxidase C45. We demonstrate that 2,2,2-triflouoroethanol (TFE) affects the equilibrium of enzyme conformational states, tending toward a more globally rigid structure. This is correlated with increases in both stability and activity. Notably, these effects are concomitant with the emergence of curvature in the temperature-activity profile, trading off activity gains at ambient temperature with losses at high temperatures. We apply macromolecular rate theory (MMRT) to understand enzyme temperature dependence data. These data point to an increase in protein rigidity associated with a difference in the distribution of protein dynamics between the ground and transition states. We compare the thermodynamics of the de novo enzyme activity to those of a natural peroxidase, horseradish peroxidase. We find that the native enzyme resembles the rigidified de novo enzyme in terms of the thermodynamics of enzyme catalysis and the putative distribution of protein dynamics between the ground and transition states. The addition of TFE apparently causes C45 to behave more like the natural enzyme. Our data suggest robust, generic strategies for improving biocatalytic activity by manipulating protein rigidity; for functional de novo protein catalysts in particular, this can provide more enzyme-like catalysts without further rational engineering, computational redesign, or directed evolution.

Sensing Enzyme Activation Heat Capacity at the Single-Molecule Level Using Gold-Nanorod-Based Optical Whispering Gallery Modes.

Here, we report a label-free gold nanoparticle-based single-molecule optical platform to study the immobilization, activity, and thermodynamics of single enzymes. The sensor uses plasmonic gold nanoparticles coupled to optical whispering gallery modes (WGMs) to probe enzyme conformational dynamics during turnover at a microsecond time resolution. Using a glucosidase enzyme as the model system, we explore the temperature dependence of the enzyme turnover at the single-molecule (SM) level. A recent physical model for understanding enzyme temperature dependencies (macromolecular rate theory; MMRT) has emerged as a powerful tool to study the relationship between enzyme turnover and thermodynamics. Using WGMs, SM enzyme measurements enable us to accurately track turnover as a function of conformational changes and therefore to quantitatively probe the key feature of the MMRT model, the activation heat capacity, at the ultimate level of SM. Our data shows that WGMs are extraordinarily sensitive to protein conformational change and can discern both multiple steps with turnover as well as microscopic conformational substates within those steps. The temperature dependence studies show that the MMRT model can be applied to a range of steps within turnover at the SM scale that is associated with conformational change. Our study validates the notion that MMRT captures differences in dynamics between states. The WGM sensors provide a platform for the quantitative analysis of SM activation heat capacity, applying MMRT to the label-free sensing of microsecond substates of active enzymes.

Conformation control of the histidine kinase BceS of Bacillus subtilis by its cognate ABC-transporter facilitates need-based activation of antibiotic resistance.

Bacteria closely control gene expression to ensure optimal physiological responses to their environment. Such careful gene expression can minimize the fitness cost associated with antibiotic resistance. We previously described a novel regulatory logic in Bacillus subtilis enabling the cell to directly monitor its need for detoxification. This cost-effective strategy is achieved via a two-component regulatory system (BceRS) working in a sensory complex with an ABC-transporter (BceAB), together acting as a flux-sensor where signaling is proportional to transport activity. How this is realized at the molecular level has remained unknown. Using experimentation and computation we here show that the histidine kinase is activated by piston-like displacements in the membrane, which are converted to helical rotations in the catalytic core via an intervening HAMP-like domain. Intriguingly, the transporter was not only required for kinase activation, but also to actively maintain the kinase in its inactive state in the absence of antibiotics. Such coupling of kinase activity to that of the transporter ensures the complete control required for transport flux-dependent signaling. Moreover, we show that the transporter likely conserves energy by signaling with sub-maximal sensitivity. These results provide the first mechanistic insights into transport flux-dependent signaling, a unique strategy for energy-efficient decision making.

Monoclonal antibody stability can be usefully monitored using the excitation-energy-dependent fluorescence edge-shift.

Among the major challenges in the development of biopharmaceuticals are structural heterogeneity and aggregation. The development of a successful therapeutic monoclonal antibody (mAb) requires both a highly active and also stable molecule. Whilst a range of experimental (biophysical) approaches exist to track changes in stability of proteins, routine prediction of stability remains challenging. The fluorescence red edge excitation shift (REES) phenomenon is sensitive to a range of changes in protein structure. Based on recent work, we have found that quantifying the REES effect is extremely sensitive to changes in protein conformational state and dynamics. Given the extreme sensitivity, potentially this tool could provide a 'fingerprint' of the structure and stability of a protein. Such a tool would be useful in the discovery and development of biopharamceuticals and so we have explored our hypothesis with a panel of therapeutic mAbs. We demonstrate that the quantified REES data show remarkable sensitivity, being able to discern between structurally identical antibodies and showing sensitivity to unfolding and aggregation. The approach works across a broad concentration range (µg-mg/ml) and is highly consistent. We show that the approach can be applied alongside traditional characterisation testing within the context of a forced degradation study (FDS). Most importantly, we demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The quantified REES data will find immediate use in the biopharmaceutical industry in quality assurance, formulation and development. The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.

Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy.

Immuno-oncology approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Additionally, we performed molecular dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiological binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addition of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive analysis of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.

Enzyme evolution and the temperature dependence of enzyme catalysis.

Experiments and biomolecular simulations are revealing new and unexpected details of how enzymes are adapted to specific temperatures. These findings are elucidating enzyme evolutionary trajectories and offer great promise for design and engineering of natural and artificial enzymes. They also have implications for understanding responses of larger scale biological temperature dependence, relevant for understanding the effects of climate change on ecosystems. We review recent work on the temperature dependence of enzyme-catalysed reaction rates and the implications for enzyme evolution. Evidence from kinetic isotope effects, temperature dependent reaction rates, molecular dynamics simulations and thermodynamics provides new insights into enzyme thermoadaptation and evolution.

Peptide cargo tunes a network of correlated motions in human leucocyte antigens.

Most biomolecular interactions are typically thought to increase the (local) rigidity of a complex, for example, in drug-target binding. However, detailed analysis of specific biomolecular complexes can reveal a more subtle interplay between binding and rigidity. Here, we focussed on the human leucocyte antigen (HLA), which plays a crucial role in the adaptive immune system by presenting peptides for recognition by the αß T-cell receptor (TCR). The role that the peptide plays in tuning HLA flexibility during TCR recognition is potentially crucial in determining the functional outcome of an immune response, with obvious relevance to the growing list of immunotherapies that target the T-cell compartment. We have applied high-pressure/temperature perturbation experiments, combined with molecular dynamics simulations, to explore the drivers that affect molecular flexibility for a series of different peptide-HLA complexes. We find that different peptide sequences affect peptide-HLA flexibility in different ways, with the peptide cargo tuning a network of correlated motions throughout the pHLA complex, including in areas remote from the peptide-binding interface, in a manner that could influence T-cell antigen discrimination.

Switching protein metalloporphyrin binding specificity by design from iron to fluorogenic zinc.

Metalloporphyrins play important roles in areas ranging from biology to nanoscience. Using computational design, we converted metalloporphyrin specificity of cytochrome b562 from iron to fluorogenic zinc. The new variant had a near total preference for zinc representing a switch in specificity, which greatly enhanced the negligible aqueous fluorescence of free ZnPP in vitro and in vivo.

Synthetic Cannabinoid Receptor Agonists Detection Using Fluorescence Spectral Fingerprinting.

Synthetic cannabinoid receptor agonists (SCRAs), termed "Spice" or "K2", are molecules that emulate the effects of the active ingredient of marijuana, and they have gained enormous popularity over the past decade. SCRAs are Schedule 1 drugs that are highly prevalent in the U.K. prison system and among homeless populations. SCRAs are highly potent and addictive. With no way to determine the dose/amount at the point-of care, they pose severe health risks to users, including psychosis, stroke, epileptic seizures, and they can kill. SCRAs are chemically diverse, with over a hundred compounds used as recreational drugs. The chemical diversity of SCRA structures presents a challenge in developing detection modalities. Typically, GC-MS is used for chemical identification; however, this cannot be in place in most settings where detection is critical, e.g., in hospital Emergency Departments, in custody suites/prisons, or among homeless communities. Ideally, real time, point-of-care identification of SCRAs is desirable to direct the care pathway of overdoses and provide information for informed consent. Herein, we show that fluorescence spectral fingerprinting can be used to identify the likely presence of SCRAs, as well as provide more specific information on structural class and concentration (∼1 µg mL-1). We demonstrate that that fluorescence spectral fingerprints, combined with numerical modeling, can detect both parent and combusted material, and such fingerprinting is also practical for detecting them in oral fluids. Our proof-of-concept study suggests that, with development, the approach could be useful in a range of capacities, notably in harm reduction for users of Spice/K2.

Exposing the Interplay Between Enzyme Turnover, Protein Dynamics, and the Membrane Environment in Monoamine Oxidase B.

There is an increasing realization that structure-based drug design may show improved success by understanding the ensemble of conformations accessible to an enzyme and how the environment affects this ensemble. Human monoamine oxidase B (MAO-B) catalyzes the oxidation of amines and is inhibited for the treatment of both Parkinson's disease and depression. Despite its clinical importance, its catalytic mechanism remains unclear, and routes to drugging this target would be valuable. Evidence of a radical in either the transition state or the resting state of MAO-B is present throughout the literature and is suggested to be a flavin semiquinone, a tyrosyl radical, or both. Here we see evidence of a resting-state flavin semiquinone, via absorption redox studies and electron paramagnetic resonance, suggesting that the anionic semiquinone is biologically relevant. On the basis of enzyme kinetic studies, enzyme variants, and molecular dynamics simulations, we find evidence for the importance of the membrane environment in mediating the activity of MAO-B and that this mediation is related to the protein dynamics of MAO-B. Further, our MD simulations identify a hitherto undescribed entrance for substrate binding, membrane modulated substrate access, and indications for half-site reactivity: only one active site is accessible to binding at a time. Our study combines both experimental and computational evidence to illustrate the subtle interplay between enzyme activity and protein dynamics and the immediate membrane environment. Understanding key biomedical enzymes to this level of detail will be crucial to inform strategies (and binding sites) for rational drug design for these targets.