Unbinding Rate Research Articles

Advances and Challenges in Milestoning Simulations for Drug-Target Kinetics.

Molecular dynamics simulations have become indispensable for exploring complex biological processes, yet their limitations in capturing rare events hinder our understanding of drug-target kinetics. In this Perspective, we investigate the domain of milestoning simulations to understand this challenge. The milestoning approach divides the phase space of the drug-target complex into discrete cells, offering extended time scale insights. This Perspective traces the history, applications, and future potential of milestoning simulations in the context of drug-target kinetics. It explores the fundamental principles of milestoning, highlighting the importance of probabilistic transitions and transition time independence. Markovian milestoning with Voronoi tessellations is revisited to address the traditional milestoning challenges. While observing the advancements in this field, this Perspective also addresses impending challenges in estimating drug-target unbinding rate constants through milestoning simulations, paving the way for more effective drug design strategies.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al. (J. Gen. Physiol., 2020, 152, e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al (J General Physiology 152 (2020), e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Arbidol, an antiviral drug, identified as a sodium channel blocker with anticonvulsant activity.

Sodium channel blockers (SCBs) have traditionally been utilized as anti-seizure medications by primarily targeting the inactivation process. In a drug discovery project aiming at finding potential anticonvulsants, we have identified arbidol, originally an antiviral drug, as a potent SCB. In order to evaluate its anticonvulsant potential, we have thoroughly examined its biophysical properties as well as its effects on animal seizure models. Patch clamp recording was used to investigate the electrophysiological properties of arbidol, as well as the binding and unbinding kinetics of arbidol, carbamazepine and lacosamide. Furthermore, we evaluated the anticonvulsant effects of arbidol using three different seizure models in male mice. Arbidol effectively suppressed neuronal epileptiform activity by blocking sodium channels. Arbidol demonstrated a distinct mode of action by interacting with both the fast and slow inactivation of Nav1.2 channels compared with carbamazepine and lacosamide. A kinetic study suggested that the binding and unbinding rates might be associated with the specific characteristics of these three drugs. Arbidol targeted the classical binding site of local anaesthetics, effectively inhibited the gain-of-function effects of Nav1.2 epileptic mutations and exhibited varying degrees of anticonvulsant effects in the maximal electroshock model and subcutaneous pentylenetetrazol model but had no effect in the pilocarpine-induced status epilepticus model. Arbidol shows promising potential as an anticonvulsant agent, providing a unique mode of action that sets it apart from existing SCBs.

Probing ligands to reaction centers to limit the photocycle in photosynthetic bacterium Rubrivivax gelatinosus

Light-induced electron flow between reaction center and cytochrome bc1 complexes is mediated by quinones and electron donors in purple photosynthetic bacteria. Upon high-intensity excitation, the contribution of the cytochrome bc1 complex is limited kinetically and the electron supply should be provided by the pool of reduced electron donors. The kinetic limitation of electron shuttle between reaction center and cytochrome bc1 complex and its consequences on the photocycle were studied by tracking the redox changes of the primary electron donor (BChl dimer) via absorption change and the opening of the closed reaction center via relaxation of the bacteriochlorophyll fluorescence in intact cells of wild type and pufC mutant strains of Rubrivivax gelatinosus. The results were simulated by a minimum model of reversible binding of different ligands (internal and external electron donors and inhibitors) to donor and acceptor sides of the reaction center. The calculated binding and kinetic parameters revealed that control of the rate of the photocycle is primarily due to 1) the light intensity, 2) the size and redox state of the donor pool, and 3) the unbinding rates of the oxidized donor and inhibitor from the reaction center. The similar kinetics of strains WT and pufC lacking the tetraheme cytochrome subunit attached to the reaction center raise the issue of the physiological importance of this subunit discussed from different points of view. SignificanceA crucial factor for the efficacy of electron donors in photosynthetic photocycle is not just the substantial size of the pool and large binding affinity (small dissociation constant KD = koff/kon) to the RC, but also the mean residence time (koff)−1 in the binding pocket. This is an important parameter that regulates the time of re-activation of the RC during multiple turnovers. The determination of koff has proven challenging and was performed by simulation of widespread experimental data on the kinetics of P+ and relaxation of fluorescence. This work is a step towards better understanding the complex pathways of electron transfer in proteins and simulation-based design of more effective electron transfer components in natural and artificial systems.

How negative feedback and the ambient environment limit the influence of recombination in common envelope evolution

ABSTRACT We perform 3D hydrodynamical simulations to study recombination and ionization during the common envelope (CE) phase of binary evolution, and develop techniques to track the ionic transitions in time and space. We simulate the interaction of a $2\, \mathrm{M_\odot }$ red giant branch primary and a $1\, \mathrm{M_\odot }$ companion modelled as a particle. We compare a run employing a tabulated equation of state (EOS) that accounts for ionization and recombination, with a run employing an ideal gas EOS. During the first half of the simulations, ∼15 per cent more mass is unbound in the tabulated EOS run due to the release of recombination energy, but by simulation end the difference has become negligible. We explain this as being a consequence of (i) the tabulated EOS run experiences a shallower inspiral and hence smaller orbital energy release at late times because recombination energy release expands the envelope and reduces drag, and (ii) collision and mixing between expanding envelope gas, ejecta and circumstellar ambient gas assists in unbinding the envelope, but does so less efficiently in the tabulated EOS run where some of the energy transferred to bound envelope gas is used for ionization. The rate of mass unbinding is approximately constant in the last half of the simulations and the orbital separation steadily decreases at late times. A simple linear extrapolation predicts a CE phase duration of ${\sim}2\, {\rm yr}$, after which the envelope would be unbound.

Theoretical analysis of cargo transport by catch bonded motors in optical trapping assays.

Dynein motors exhibit catch bonding, where the unbinding rate of the motors from microtubule filaments decreases with increasing opposing load. The implications of this catch bond on the transport properties of dynein-driven cargo are yet to be fully understood. In this context, optical trapping assays constitute an important means of accurately measuring the forces generated by molecular motor proteins. We investigate, using theory and stochastic simulations, the transport properties of cargo transported by catch bonded dynein molecular motors - both singly and in teams - in a harmonic potential, which mimics the variable force experienced by cargo in an optical trap. We estimate the biologically relevant measures of first passage time - the time during which the cargo remains bound to the microtubule and detachment force - the force at which the cargo unbinds from the microtubule, using both two-dimensional and one-dimensional force balance frameworks. Our results suggest that even for cargo transported by a single motor, catch bonding may play a role depending on the force scale which marks the onset of the catch bond. By comparing with experimental measurements on single dynein-driven transport, we estimate realistic bounds of this catch bond force scale. Generically, catch bonding results in increased persistent motion, and can also generate non-monotonic behaviour of first passage times. For cargo transported by multiple motors, emergent collective effects due to catch bonding can result in non-trivial re-entrant phenomena wherein average first passage times and detachment forces exhibit non-monotonic behaviour as a function of the stall force and the motor velocity.

A general model for the motion of multivalent cargo interacting with substrates.

Multivalent interactions are common in biology at many different length scales, and can result in the directional motion of multivalent cargo along substrates. Here, a general analytical model has been developed that can describe the directional motion of multivalent cargo as a response to position dependence in the binding and unbinding rates exhibited by their interaction sites. Cargo exhibit both an effective velocity, which acts in the direction of increasing cargo-substrate binding rate and decreasing cargo-substrate unbinding rate, and an effective diffusivity. This model can reproduce previously published experimental findings using only the binding and unbinding rate distributions of cargo interaction sites, and without any further parameter fitting. Extension of the cargo binding model to two dimensions reveals an effective velocity with the same properties as that derived for the one-dimensional case.

Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor.

Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.

Coarse-grained dynamics of transiently bound fast linkers.

Transient bonds between fast linkers and slower particles are widespread in physical and biological systems. Despite their diverse structure and function, a commonality is that the linkers diffuse on timescales much faster compared to the overall motion of the particles they bind to. This limits numerical and theoretical approaches that need to resolve these diverse timescales with high accuracy. Many models, therefore, resort to effective, yet ad hoc, dynamics, where linker motion is only accounted for when bound. This paper provides a mathematical justification for such coarse-grained dynamics that preserves detailed balance at equilibrium. Our derivation is based on multiscale averaging techniques and is broadly applicable. We verify our results with simulations on a minimal model of fast linker binding to a slow particle. We show how our framework can be applied to various systems, including those with multiple linkers, stiffening linkers upon binding, or slip bonds with force-dependent unbinding. Importantly, the preservation of detailed balance only sets the ratio of the binding to the unbinding rates, but it does not constrain the detailed expression of binding kinetics. We conclude by discussing how various choices of binding kinetics may affect macroscopic dynamics.

PRAX-628: A Novel Sodium Channel Blocker with Greater Potency and Activity Dependence Compared to Standard of Care (P8-9.012)

<h3>Objective:</h3> This study investigates the <i>in vitro</i> effects of PRAX-628 on sodium current (I_Na) expressed by hNa_V1.6. <h3>Background:</h3> Voltage-gated sodium channels (Na_V) are important therapeutic targets for anti-epileptic drugs (AEDs) due to their role in action potential initiation and propagation. Selective Na_V blockade during periods of hyperexcitability (activity dependence) has been proposed as a pharmacological target for reducing pathologic neuronal hyperactivity, while sparing peak I_Na is critical for normal neuronal function. <h3>Design/Methods:</h3> Persistent and peak I_Na inhibition was studied using automated patch clamp recordings of Na_V expressed in HEK cells (hNa_V1.6). Voltage protocols measured I_Na inhibition in multiple modes: persistent I_Na, tonic block (TB), voltage-dependent block (VDB), and activity/use-dependent block (UDB). PRAX-628 was compared to a panel of AEDs, non-AEDs, and investigational compounds. Binding kinetics were inferred from inhibition kinetics to calculate an apparent binding (K_ON) and unbinding (K_OFF) rate. <h3>Results:</h3> PRAX-628 exhibited potent activity dependence (UDB IC₅₀ 200nM, 44× preference to TB). PRAX-628 blocked hNa_V1.6 persistent I_Na with an IC₅₀ of 128nM (68× preference to TB); at least 550× more potent than other tested compounds. This profile differed from CBZ (persistent I_Na IC₅₀ 77,500nM, 30× preference to TB, no UDB observed) and cenobamate (persistent I_Na IC₅₀ of 71,690nM, 24× preference to TB, UDB 2.3× preference to TB). The preference for persistent I_Na exhibited by PRAX-628 was not retained versus activity in the more depolarized VDB assay (0.56× preference to VDB); contrasting with the preferential persistent I_Na inhibitor PRAX-562 (2.2× preference to VDB). The enhanced activity dependence of PRAX-628 derives from a rapid K_ON and moderate K_OFF. <h3>Conclusions:</h3> PRAX-628 is a next generation Na_V blocker with increased potency and activity dependence for peak I_Na, and greater potency for persistent I_Na. This profile may translate to efficacy in epilepsy and other indications caused by hyperexcitability, without tolerability issues caused by excessive block of peak I_Na. <b>Disclosure:</b> Dr. Kahlig has received personal compensation for serving as an employee of Praxis Precisoin Medicines. Dr. Kahlig has stock in Praxis Precision Medicines. Dr. Chapman has received personal compensation for serving as an employee of Ligand. Dr. Chapman has stock in Ligand. Steven Petrou has received personal compensation in the range of $100,000-$499,999 for serving as a Consultant for Praxis Precision Medicines. Steven Petrou has stock in Praxis Precision Medicines. The institution of Steven Petrou has received research support from Praxis Precision Medicines. The institution of Steven Petrou has received research support from Medical Research Future Fund. Steven Petrou has received intellectual property interests from a discovery or technology relating to health care. Steven Petrou has received intellectual property interests from a discovery or technology relating to health care.

Path separation of dissipation-corrected targeted molecular dynamics simulations of protein-ligand unbinding.

Protein-ligand (un)binding simulations are a recent focus of biased molecular dynamics simulations. Such binding and unbinding can occur via different pathways in and out of a binding site. Here, we present a theoretical framework on how to compute kinetics along separate paths and on how to combine the path-specific rates into global binding and unbinding rates for comparison with experimental results. Using dissipation-corrected targeted molecular dynamics in combination with temperature-boosted Langevin equation simulations [S. Wolf et al., Nat. Commun. 11, 2918 (2020)] applied to a two-dimensional model and the trypsin-benzamidine complex as test systems, we assess the robustness of the procedure and discuss the aspects of its practical applicability to predict multisecond kinetics of complex biomolecular systems.

Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment.

Reduction of the rapid delayed rectifier potassium current (I Kr) via drug binding to the human Ether-à-go-go-Related Gene (hERG) channel is a well recognised mechanism that can contribute to an increased risk of Torsades de Pointes. Mathematical models have been created to replicate the effects of channel blockers, such as reducing the ionic conductance of the channel. Here, we study the impact of including state-dependent drug binding in a mathematical model of hERG when translating hERG inhibition to action potential changes. We show that the difference in action potential predictions when modelling drug binding of hERG using a state-dependent model versus a conductance scaling model depends not only on the properties of the drug and whether the experiment achieves steady state, but also on the experimental protocols. Furthermore, through exploring the model parameter space, we demonstrate that the state-dependent model and the conductance scaling model generally predict different action potential prolongations and are not interchangeable, while at high binding and unbinding rates, the conductance scaling model tends to predict shorter action potential prolongations. Finally, we observe that the difference in simulated action potentials between the models is determined by the binding and unbinding rate, rather than the trapping mechanism. This study demonstrates the importance of modelling drug binding and highlights the need for improved understanding of drug trapping which can have implications for the uses in drug safety assessment.

Dissociation kinetics of small-molecule inhibitors in Escherichia coli is coupled to physiological state of cells

Bioactive small-molecule inhibitors represent a treasure chest for future drugs. In vitro high-throughput screening is a common approach to identify the small-molecule inhibitors that bind tightly to purified targets. Here, we investigate the inhibitor-target binding/unbinding kinetics in E. coli cells using a benzimidazole-derivative DNA inhibitor as a model system. We find that its unbinding rate is not constant but depends on cell growth rate. This dependence is mediated by the cellular activity, forming a feedback loop with the inhibitor’s activity. In accordance with this feedback, we find cell-to-cell heterogeneity in inhibitor-target interaction, leading to co-existence of two distinct subpopulations: actively growing cells that dissociate the inhibitors from the targets and non-growing cells that do not. We find similar heterogeneity for other clinical DNA inhibitors. Our studies reveal a mechanism that couples inhibitor-target kinetics to cell physiology and demonstrate the significant effect of this coupling on drug efficacy.

Quantifying binding kinetics with fluorescence microscopy.

Many processes crucial to life are regulated by the binding and unbinding of key molecules, such as target molecules to allosteric protein sites or transcription factors to gene loci. Capturing such binding events in living systems is often accomplished using fluorescence based methods. However, accurately determining assembly and disassembly rates from fluorescence data is challenging on account of the photophysical behavior of the fluorescent labels such as blinking and photobleaching. Here we present a Bayesian method that can simultaneously learn binding and unbinding rates while correcting for photophysical artifacts. We show that our method is robust across low light regimes relevant to in vivo experiments. We benchmark our method on both simulated and experimental data.

Measurements and simulations of light-activated matter.

Non-equilibrium active matter consumes energy to form self-organizing structures. For example, microtubules and motors assemble to form polar and nematic structures that facilitate cell division. Here, we investigate properties of varying aster geometries during and after contraction. Experiments, agent-based simulations, and field-based simulations provide insights into an in-vitro, light-activated system of microtubules (MTs) and kinesin motors. Using an agent-based simulation, we modeled the contraction process and computationally created radially symmetric aster structures; simulation results show asters contract faster at higher motor speeds and lower unbinding rates. Furthermore, the agent-based simulation captures 3D MT flux, potentially providing insight into field-based equations describing contraction. We aim to compare experimental contraction with a model from computational MT flux data, searching for mechanics that govern the formation and stabilization of aster structures.

Role of site-wise dynamic defects in a resource-constrained exclusion process

We study an exclusion process with site-wise dynamic disorder in a resource constrained environment. The dynamic defects that hinder the particle flux on the lattice stochastically appear and disappear throughout the lattice with a constrained binding rate and a constant unbinding rate, respectively. The effect of constrained resources on the stationary properties of the system has been comprehended in the form of the filling factor. The analytical results replicated by naive mean-field theory accord quite well with the Monte Carlo simulation for faster defects irrespective of the affected hopping rate and slower defects with a large affected hopping rate. For slower defects with a small affected hopping rate, some correlations are observed in the system, leading to the adoption of an enhanced mean-field approach which provides reasonably better approximations than the usual naive-mean field. These correlations slowly fade away with an increase in the affected hopping rate. Our theoretical calculations unify the parameters – the affected hopping rate, defect binding (unbinding) rate, and defect density – that control defect kinetics on the lattice into a single parameter known as the obstruction factor. The repercussions of the obstruction factor have been thoroughly examined by discussing its limiting cases. The phase boundaries that are yielded through different mean-field approaches are uniquely impacted by their corresponding obstruction factor.

Two dominant timescales of cytoskeletal crosslinking in the viscoelastic response of the cytoplasm

Cells precisely regulate their frequency-dependent viscoelastic properties in response to chemical and mechanical cues. We use optical trap-based active microrheology using intracellular probes to measure the cytoplasmic mechanical response of fibroblast and macrophage cells over a broad frequency range ($\ensuremath{\sim}0.02--350$ Hz). Both cell types show similar frequency-dependent behavior, suggesting that the mechanisms that control the cell's mechanical response are general to many cell types. At frequencies above 1 Hz, the cytoplasmic mechanical behavior shows a broad distribution of relaxation timescales consistent with power-law mechanics. At low frequencies ($&lt;1$ Hz), cells exhibit fluidlike behavior with distinct relaxation timescales, similar to that observed in reconstituted networks of transiently crosslinked actin filaments. The response across all frequencies can be captured by a mathematical model combining a power-law term with two crosslinker-unbinding terms. The two unbinding rates required to describe the low-frequency response suggest that the viscoelastic relaxation of the cytoplasm is governed either by multiple dominant crosslinkers or by a single crosslinker with multiple states.

Molecular crowders modulate ligand binding affinity to G-quadruplex DNA by decelerating ligand association

The study of kinetics of ligand binding to G-quadruplex DNA (GqDNA) structures is of paramount importance for comprehending (possible) ligand-induced anticancer activity involving GqDNA within cells. However, cellular environment is crowded with variety of small- and macro-molecules that occupy ∼30–40 % of cell-volume. While only few earlier studies dealt with deciphering the kinetics of ligands’ interactions with GqDNA in dilute solution, such studies in cell-like crowded milieu are absent. Here we investigate the effect of small and macro molecular crowders, glucose, sucrose and ficoll 70, on the kinetic steps of association and dissociation of a benzophenoxazine-ligand (Cresyl Violet: CV) with human telometic (hybrid) GqDNA structure using fluorescence correlation spectroscopy (FCS), aided by other methods. We find that the binding constants of the ligand to GqDNA change appreciably with nearly fivefold decrease in the presence of ficoll 70, compared to that in pure buffer solution. FCS measurements unfold that this decrease of binding constants is mainly modulated by the viscosity-induced deceleration of the association of the ligand to GqDNA in the crowded solution; however, the rate-determining dissociation rates remain nearly unchanged in the presence of all three crowders. These results have important implications in the context of ligand/GqDNA interactions within cellular environment, which indicate that even if the binding affinity of a ligand to GqDNA structures may be influenced by cellular crowders, they may not influence the unbinding rate of the ligand from a stable ligand/GqDNA complex formed by strong π-π stacking interactions.

Using transcription-based detectors to emulate the behavior of sequential probability ratio-based concentration detectors.

The sequential probability ratio test (SPRT) from statistics is known to have the least mean decision time compared to other sequential or fixed-time tests for given error rates. In some circumstances, cells need to make decisions accurately and quickly, therefore it has been suggested that the SPRT may be used to understand the speed-accuracy tradeoff in cellular decision-making. It is generally thought that in order for cells to make use of the SPRT, it is necessary to find biochemical circuits that can compute the log-likelihood ratio needed for the SPRT. However, this paper takes a different approach. We recognize that the high-level behavior of the SPRT is defined by its positive detection or hit rate, and the computation of the log-likelihood ratio is just one way to realize this behavior. In this paper, we will present a method in which a transcription-based detector is used to emulate the hit rate of the SPRT without computing the exact log-likelihood ratio. We consider the problem of using a promoter with multiple binding sites to accurately and quickly detect whether the concentration of a transcription factor is above a target level. We show that it is possible to find binding and unbinding rates of the transcription factor to the promoter's binding sites so that the probability that the amount of mRNA produced will be higher than a threshold is approximately equal to the hit rate of the SPRT detector. Moreover, we show that the average time that this transcription-based detector needs to make a positive detection is less than or equal to that of the SPRT for a wide range of concentrations. We remark that the last statement does not contradict Wald's optimality result because our transcription-based detector uses an open-ended test.