Protein Conformational Dynamics Probed by Single-Molecule Electron Transfer

A role for conformational changes in enzyme catalysis

The role played by conformational changes in enzyme catalysis is controversial. In addition to examining specific enzymes, studying formal models can help identify the conditions under which conformational changes promote catalysis. Here, we present a model demonstrating how conformational changes can break a generic trade-off due to the conflicting requirements of successive steps in catalytic cycles, namely high specificity for the transition state to accelerate the chemical transformation and low affinity for the products to favor their release. The mechanism by which the trade-off is broken is a transition between conformations with different affinities for the substrate. The role of the effector that induces the transition is played by a substrate "handle," a part of the substrate that is not chemically transformed but whose interaction with the enzyme is nevertheless essential to rapidly complete the catalytic cycle. A key element of the model is the formalization of the constraints causing the trade-off that the presence of multiple states breaks, which we attribute to the strong chemical similarity between successive reaction states-substrates, transition states, and products. For the sake of clarity, we present our model for irreversible one-step unimolecular reactions. In this context, we demonstrate how the different forms that chemical similarities between reaction states can take impose limits on the overall catalytic turnover. We first analyze catalysts without internal degrees of freedom and then show how two-state catalysts can overcome their limitations. Our results recapitulate previous proposals concerning the role of conformational changes and substrate handles in a formalism that makes explicit the constraints that elicit these features. In addition, our approach establishes links with studies in the field of heterogeneous catalysis, where the same trade-offs are observed and where overcoming them is a well-recognized challenge.

A practical guide to time-resolved fluorescence microscopy and spectroscopy

Time-correlated single photon counting (TCSPC) coupled with confocal microscopy is a versatile biophysical tool that enables real-time monitoring of biomolecular dynamics across many timescales. With TCSPC, Fluorescence correlation spectroscopy (FCS) and pulsed interleaved excitation-Förster resonance energy transfer (PIE-FRET) are collected simultaneously on diffusing molecules to extract diffusion characteristics and proximity information. This article is a guide to calibrating FCS and PIE-FRET measurements with several biological samples including liposomes, streptavidin-coated quantum dots, proteins, and nucleic acids for reliable determination of diffusion coefficients and FRET efficiency. The FRET efficiency results are also compared to surface-attached single molecules using fluorescence lifetime imaging microscopy (FLIM-FRET). Combining the methods is a powerful approach to revealing mechanistic details of biological processes and pathways.

Main role of fractal-like nature of conformational space in subdiffusion in proteins

Protein dynamics involves a myriad of mechanical movements happening at different time and space scales, which make it highly complex. One of the less understood features of protein dynamics is subdiffusivity, defined as sublinear dependence between displacement and time. Here, we use all-atoms molecular dynamics (MD) simulations to directly interrogate an already well-established theory and demonstrate that subdiffusivity arises from the fractal nature of the network of metastable conformations over which the dynamics, thought of as a diffusion process, takes place.

Fractional Extended Diffusion Theory to capture anomalous relaxation from biased/accelerated molecular simulations

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586-599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head-tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes.

Convergence and equilibrium in molecular dynamics simulations

Molecular dynamics is a powerful tool that has been long used for the simulation of biomolecules. It complements experiments, by providing detailed information about individual atomic motions. But there is an essential and often overlooked assumption that, left unchecked, could invalidate any results from it: is the simulated trajectory long enough, so that the system has reached thermodynamic equilibrium, and the measured properties are converged? Previous studies showed mixed results in relation to this assumption. This has profound implications, as the resulting simulated trajectories may not be reliable in predicting equilibrium properties. Yet, this is precisely what most molecular dynamics studies do. So the question arises: are these studies even valid?Here, we present a thorough analysis of up to a hundred microseconds long trajectories, of several system with varying size, to probe the convergence of different structural, dynamical and cumulative properties, and elaborate on the relevance of the concept of equilibrium, and its physical and biological meaning. The results show that properties with the most biological interest tend to converge in multi-microsecond trajectories, although other properties-like transition rates to low probability conformations-may require more time.

Conformational Dynamics in Proteins: Entangled Slow Fluctuations and Nonequilibrium Reaction Events

Proteins exhibit conformational fluctuations and changes over various time scales, ranging from rapid picosecond-scale local atomic motions to slower microsecond-scale global conformational transformations. In the presence of these intricate fluctuations, chemical reactions occur and functions emerge. These conformational fluctuations of proteins are not merely stochastic random motions but possess distinct spatiotemporal characteristics. Moreover, chemical reactions do not always proceed along a single reaction coordinate in a quasi-equilibrium manner. Therefore, it is essential to understand spatiotemporal conformational fluctuations of proteins and the conformational change processes associated with reactions. In this Perspective, we shed light on the complex dynamics of proteins and their role in enzyme catalysis by presenting recent results regarding dynamic couplings and disorder in the conformational dynamics of proteins and rare but rapid enzymatic reaction events obtained from molecular dynamics simulations.

Impacts of QM region sizes and conformation numbers on modelling enzyme reactions: a case study of polyethylene terephthalate hydrolase

A quantum mechanics/molecular mechanics (QM/MM) approach is a broadly used tool in computational enzymology. Treating the QM region with a high-level DFT method is one of the important branches. Here, taking leaf-branch compost cutinase-catalyzed polyethylene terephthalate depolymerization as an example, the convergence behavior of energy barriers as well as key structural and charge features with respect to the size of the QM region (up to 1000 atoms) is systematically investigated. BP86/6-31G(d)//CHARMM and M06-2X/6-311G(d,p)//CHARMM level of theories were applied for geometry optimizations and single-point energy calculations, respectively. Six independent enzyme conformations for all the four catalytic steps (steps (i)-(iv)) were considered. Most of the twenty-four cases show that at least 500 QM atoms are needed while only two rare cases show that ∼100 QM atoms are sufficient for convergence when only a single conformation was considered. This explains why most previous studies showed that 500 or more QM atoms are required while a few others showed that ∼100 QM atoms are sufficient for DFT/MM calculations. More importantly, average energy barriers and key structural/charge features from six conformations show an accelerated convergence than that in a single conformation. For instance, to reach energy barrier convergence (within 2.0 kcal mol-1) for step (ii), only ∼100 QM atoms are required if six conformations are considered while 500 or more QM atoms are needed with a single conformation. The convergence is accelerated to be more rapid if hundreds and thousands of conformations were considered, which aligns with previous findings that only several dozens of QM atoms are required for convergence with semi-empirical QM/MM MD simulations.

Probing conformational kinetics of catalase with and without magnetic field by single-entity collision electrochemistry

The conformational motions of enzymes are crucial for their catalytic activities, but these fluctuations are usually spontaneous and unsynchronized and thus difficult to obtain from ensemble-averaged measurements. Here, we employ label-free single-entity electrochemical measurements to monitor in real time the fluctuating enzymatic behavior of single catalase molecules toward the degradation of hydrogen peroxide. By probing the electrochemical signals of single catalase molecules at a carbon nanoelectrode, we were able to observe three distinct current traces that could be attributed to conformational changes on the sub-millisecond timescale. Whereas, nearly uniform single long peaks were observed for single catalase molecules under a moderate magnetic field due to the restricted conformational changes of catalase. By combining high-resolution current signals with a multiphysics simulation model, we studied the catalytic kinetics of catalase with and without a magnetic field, and further estimated the maximum catalytic rate and conformational transition rate. This work introduces a new complementary approach to existing single-molecule enzymology, giving further insight into the enzymatic reaction mechanism.

Probing Single-molecule Interfacial Electron Transfer Inside a Single Lipid Vesicle

Inhomogeneity in single molecule electron transfer at the surface of lipid in a single vesicle has been explored by single molecule spectroscopic technique. In our study we took Di-methyl aniline (DMA), as the electron donor (D) and three different organic dyes as acceptor. These dyes are C153, C480 and C152 and they reside in different regions in the vesicle depending upon their preference of residence. For each probe, we found fluctuations in the single-molecule fluorescence decay, which are attributed to the variation in the reactivity of interfacial electron transfer. We found a non-exponential auto-correlation fluctuation of the intensity of the probe, which is ascribed to the kinetic disorder in the rate of electron transfer. We have also shown the power law distribution of the dark state (off time), which obeys the levy's statistics. We found a shift in lifetime distribution for the probe (C153) from 3.9 ns to 3.5 ns. This observed quenching is due to the dynamic electron transfer. We observed the kinetic disorderness in the electron transfer reaction for each dye. This source of fluctuation in electron transfer rate may be ascribed to the inherent fluctuation, occurring on the time scale of ~ 1.1 ms (for C153) of the vesicle, containing lipids.

Parameter estimation of the fractional Ornstein-Uhlenbeck process based on quadratic variation

Modern experiments routinely produce extensive data of the diffusive dynamics of tracer particles in a large range of systems. Often, the measured diffusion turns out to deviate from the laws of Brownian motion, i.e., it is anomalous. Considerable effort has been put in conceiving methods to extract the exact parameters underlying the diffusive dynamics. Mostly, this has been done for unconfined motion of the tracer particle. Here, we consider the case when the particle is confined by an external harmonic potential, e.g., in an optical trap. The anomalous particle dynamics is described by the fractional Ornstein-Uhlenbeck process, for which we establish new estimators for the parameters. Specifically, by calculating the empirical quadratic variation of a single trajectory, we are able to recover the subordination process governing the particle motion and use it as a basis for the parameter estimation. The statistical properties of the estimators are evaluated from simulations.

Control of charge transport in electronically active systems towards integrated biomolecular circuits (IbC)

The miniaturization of traditional silicon-based electronics will soon reach its limitation as quantum tunneling and heat become serious problems at the several-nanometer scale. Crafting integrated circuits via self-assembly of electronically active molecules using a "bottom-up" paradigm provides a potential solution to these technological challenges. In particular, integrated biomolecular circuits (IbC) offer promising advantages to achieve this goal, as nature offers countless examples of functionalities entailed by self-assembly and examples of controlling charge transport at the molecular level within the self-assembled structures. To this end, the review summarizes the progress in understanding how charge transport is regulated in biosystems and the key redox-active amino acids that enable the charge transport. In addition, charge transport mechanisms at different length scales are also reviewed, offering key insights for controlling charge transport in IbC in the future.

Ballistic Brownian Motion of Nanoconfined DNA

Theoretical treatments of polymer dynamics in liquid generally start with the basic assumption that motion at the smallest scale is heavily overdamped; therefore, inertia can be neglected. We report on the Brownian motion of tethered DNA under nanoconfinement, which was analyzed by molecular dynamics simulation and nanoelectrochemistry-based single-electron shuttle experiments. Our results show a transition into the ballistic Brownian motion regime for short DNA in sub-5 nm gaps, with quality coefficients as high as 2 for double-stranded DNA, an effect mainly attributed to a drastic increase in stiffness. The possibility for DNA to enter the underdamped regime could have profound implications on our understanding of the energetics of biomolecular engines such as the replication machinery, which operates in nanocavities that are a few nanometers wide.

Transcending Markov: non-Markovian rate processes of thermosensitive TRP ion channels

The Markov state model (MSM) is a popular theoretical tool for describing the hierarchy of time scales involved in the function of many proteins especially ion channel gating. An MSM is a particular case of the general non-Markovian model, where the rate of transition from one state to another does not depend on the history of state occupancy within the system, i.e. it only includes reversible, non-dissipative processes. However, an MSM requires knowledge of the precise conformational state of the protein and is not predictive when those details are not known. In the case of ion channels, this simple description fails in real (non-equilibrium) situations, for example when local temperature changes, or when energy losses occur during channel gating. Here, we show it is possible to use non-Markovian equations (i.e. offer a general description that includes the MSM as a particular case) to develop a relatively simple analytical model that describes the non-equilibrium behaviour of the temperature-sensitive transient receptor potential (TRP) ion channels, TRPV1 and TRPM8. This model accurately predicts asymmetrical opening and closing rates, infinite processes and the creation of new states, as well as the effect of temperature changes throughout the process. This approach therefore overcomes the limitations of the MSM and allows us to go beyond a mere phenomenological description of the dynamics of ion channel gating towards a better understanding of the physics underlying these processes.

CASPI: collaborative photon processing for active single-photon imaging

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

Dynamic Heterogeneity in the Optical Signals from Single Nano-Objects

In contrast to ensemble-averaged measurements, single-molecule experiments directly display the heterogeneity of molecular properties in space and time. In many complex systems, spatial heterogeneity is regularly accompanied by temporal or dynamic heterogeneity; if a property differs from molecule to molecule, it will often vary in time for one and the same molecule. In this short paper, we discuss a few examples of complex systems where dynamical heterogeneity was observed in single-molecule or single-particle optical signals. For single biomolecules, the first demonstration of dynamic heterogeneity in a single enzyme was provided by Xie and colleagues. Other examples are found in glassy systems, and very recently in the magnetic relaxation of single superparamagnetic nanoparticles. The ubiquity of this phenomenon suggests that, rather than an exception, dynamic heterogeneity is the rule in complex systems with multiple degrees of freedom.

How synonymous mutations alter enzyme structure and function over long timescales

The specific activity of enzymes can be altered over long timescales in cells by synonymous mutations that alter a messenger RNA molecule's sequence but not the encoded protein's primary structure. How this happens at the molecular level is unknown. Here, we use multiscale modelling of three Escherichia coli enzymes (type III chloramphenicol acetyltransferase, D-alanine-D-alanine ligase B and dihydrofolate reductase) to understand experimentally measured changes in specific activity due to synonymous mutations. The modelling involves coarse-grained simulations of protein synthesis and post-translational behaviour, all-atom simulations to test robustness and quantum mechanics/molecular mechanics calculations to characterize enzymatic function. We show that changes in codon translation rates induced by synonymous mutations cause shifts in co-translational and post-translational folding pathways that kinetically partition molecules into subpopulations that very slowly interconvert to the native, functional state. Structurally, these states resemble the native state, with localized misfolding near the active sites of the enzymes. These long-lived states exhibit reduced catalytic activity, as shown by their increased activation energies for the reactions they catalyse.

Reaction Dynamics in the Chrimson Channelrhodopsin: Observation of Product-State Evolution and Slow Diffusive Protein Motions

Chrimson is a red-light absorbing channelrhodopsin useful for deep-tissue optogenetics applications. Here, we present the Chrimson reaction dynamics from femtoseconds to seconds, analyzed with target analysis methods to disentangle spectrally and temporally overlapping excited- and product-state dynamics. We found multiple phases ranging from ≈100 fs to ≈20 ps in the excited-state decay, where spectral features overlapping with stimulated emission components were assigned to early dynamics of K-like species on a 10 ps time scale. Selective excitation at the maximum or the blue edge of the absorption spectrum resulted in spectrally distinct but kinetically similar excited-state and product-state species, which gradually became indistinguishable on the μs to 100 μs time scales. Hence, by removing specific protein conformations within an inhomogeneously broadened ensemble, we resolved slow protein backbone and amino acid side-chain motions in the dark that underlie inhomogeneous broadening, demonstrating that the latter represents a dynamic interconversion between protein substates.

Resolving Molecular Heterogeneity with Single-Molecule Centrifugation

For many classes of biomolecules, population-level heterogeneity is an essential aspect of biological function─from antibodies produced by the immune system to post-translationally modified proteins that regulate cellular processes. However, heterogeneity is difficult to fully characterize for multiple reasons: (i) single-molecule approaches are needed to avoid information lost by ensemble-level averaging, (ii) sufficient statistics must be gathered on both a per-molecule and per-population level, and (iii) a suitable analysis framework is required to make sense of a potentially limited number of intrinsically noisy measurements. Here, we introduce an approach that overcomes these difficulties by combining three techniques: a DNA nanoswitch construct to repeatedly interrogate the same molecule, a benchtop centrifuge force microscope (CFM) to obtain thousands of statistics in a highly parallel manner, and a Bayesian nonparametric (BNP) inference method to resolve separate subpopulations with distinct kinetics. We apply this approach to characterize commercially available antibodies and find that polyclonal antibody from rabbit serum is well-modeled by a mixture of three subpopulations. Our results show how combining a spatially and temporally multiplexed nanoswitch-CFM assay with BNP analysis can help resolve complex biomolecular interactions in heterogeneous samples.

Genetic Perturbation Alters Functional Substates in Alkaline Phosphatase

Enzymes inherently exhibit molecule-to-molecule heterogeneity in their conformational and functional states, which is considered to be a key to the evolution of new functions. Single-molecule enzyme assays enable us to directly observe such multiple functional states or functional substates. Here, we quantitatively analyzed functional substates in the wild-type and 69 single-point mutants of Escherichia coli alkaline phosphatase by employing a high-throughput single-molecule assay with a femtoliter reactor array device. Interestingly, many mutant enzymes exhibited significantly heterogeneous functional substates with various types, while the wild-type enzyme showed a highly homogeneous substate. We identified a correlation between the degree of functional substates and the level of improvement in promiscuous activities. Our work provides much comprehensive evidence that the functional substates can be easily altered by mutations, and the evolution toward a new catalytic activity may involve the modulation of the functional substates.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Explicit analytical form for memory kernel in the generalized Langevin equation for end-to-end vector of Rouse chains

The generalized Langevin equation (GLE) provides an attractive theoretical framework for investigating the dynamics of conformational fluctuations of polymeric systems. While the memory kernel is a central function in the GLE, explicit analytical forms for this function have been challenging to obtain, even for the simple models of polymer dynamics. Here, we achieve an explicit analytical expression for the memory kernel in the GLE for the end-to-end vector of Rouse chains in the overdamped limit. Our derivation takes advantage of the finding that the dynamics of the end-to-end vector of Rouse chains with both free ends are equivalent to those of Rouse chains with one free end and the other fixed. For the latter model, we first show that the equations of motion of the Rouse modes as well as their statistical properties can be obtained under the boundary conditions where the free end is held fixed temporarily. We then analytically solve the terms associated with intrachain interactions in the GLE. By formally comparing these terms with the GLE based on the Rouse modes, we obtain an explicit expression for the memory kernel, along with analytical forms for the potential field and the random colored noise force. Our analytical memory kernel is confirmed by numerical calculations in the Laplace space and is shown to yield asymptotic behaviors that are consistent with previous studies. Finally, we utilize our analytical result to simulate the cyclization dynamics of Rouse chains and discuss the scaling of the cyclization time with chain length.

Cyclic transitions of DNA origami dimers driven by thermal cycling

It is widely observed that life activities are regulated through conformational transitions of biological macromolecules, which inspires the construction of environmental responsive nanomachines in recent years. Here we present a thermal responsive DNA origami dimers system, whose conformations can be cyclically switched by thermal cycling. In our strategy, origami dimers are assembled at high temperatures and disassembled at low temperatures, which is different from the conventional strategy of breaking nanostructures using high temperatures. The advantage of this strategy is that the dimers system can be repeatedly operated without significant performance degradation, compared to traditional strategies such as conformational transitions via i-motif and G-quadruplexes, whose performance degrades with sample dilution due to repeated addition of trigger solutions. The cyclic conformational transitions of the dimers system are verified by fluorescence curves and AFM images. This research offered a new way to construct cyclic transformational nanodevices, such as reusable nanomedicine delivery systems or nanorobots with long service lifetimes.

Substituent derivatives of benzothiazole-based fluorescence probes for hydrazine with conspicuous luminescence properties: A theoretical study

In the present work, four probe molecules for detecting hydrazine have been designed based on the 2-(4-Acetoxy-3-benzothiazole-2-yl-phenyl)-4-methyl-thiazole- 5-carboxylic acid ethyl ester (HP1) to investigate the influence of the amino and cyano groups on the excited-state intramolecular proton transfer (ESIPT) behavior and photophysical properties. The changes in hydrogen bond strength indicate that the intramolecular hydrogen bond of all probe products is enhanced upon photoexcitation. Frontier molecular orbitals (FMOs) and natural bond orbital (NBO) reveal the driving force of ESIPT. In addition, the potential energy curves and transition state theory explain the reason for the single fluorescence phenomenon in the experiment. The simulated absorption and fluorescence spectra of HP1 and its product (HPP1) are completely consistent with the experimental results, which also verify the viewpoint. Meanwhile the cyano derivative HPP4 exhibits a larger Stokes-shift (201 nm) than that of HPP1 (145 nm) and has the same low energy barrier as HPP1. These excellent properties allow HPP4 to be a fluorescent probe with superior performance than the original molecule. In conclusion, this work can provide a theoretical basis for the design and synthesis of more sensitive fluorescent probes for the detection of hydrazine.

Everlasting impact of initial perturbations on first-passage times of non-Markovian random walks

Persistence, defined as the probability that a signal has not reached a threshold up to a given observation time, plays a crucial role in the theory of random processes. Often, persistence decays algebraically with time with non trivial exponents. However, general analytical methods to calculate persistence exponents cannot be applied to the ubiquitous case of non-Markovian systems relaxing transiently after an imposed initial perturbation. Here, we introduce a theoretical framework that enables the non-perturbative determination of persistence exponents of Gaussian non-Markovian processes with non stationary dynamics relaxing to a steady state after an initial perturbation. Two situations are analyzed: either the system is subjected to a temperature quench at initial time, or its past trajectory is assumed to have been observed and thus known. Our theory covers the case of spatial dimension higher than one, opening the way to characterize non-trivial reaction kinetics for complex systems with non-equilibrium initial conditions.

Endocrine-disrupting metabolic activation of 2-nitrofluorene catalyzed by human cytochrome P450 1A1: A QM/MM approach

Nitropolycyclic aromatic hydrocarbons (NPAHs) present one of the most important airborne pollutants. Recent studies have shown that one of the most abundant NPAHs, 2-Nitrofluorene (NF), was supposed to be converted to endocrine-disrupting metabolites by cytochrome P450 1A1 (CYP1A1) in human cells. However, the mechanism is still largely unexplored. Here the metabolic activation and transformation mechanism of NF catalyzed by CYP1A1 were systematically studied with the aid of Molecular Dynamics, Density Functional Theory and Quantum Mechanics/Molecular Mechanics techniques. We evidence that CYP1A1 can activate NF through two elementary processes: (i) electrophilic addition (12.4 kcal·mol-1) or hydrogen abstraction (38.2 kcal·mol-1) and (ii) epoxidation (5.9 and 8.7 kcal·mol-1) or NIH shift (12.5 and 14.9 kcal·mol-1) or proton shuttle (12.1 kcal·mol-1). Electrophilic addition was found to be the rate-determining step while epoxidation rather than NIH shift or proton shuttle is the more feasible pathway after electrophilic addition. Metabolites 6,7-epoxide-2-nitrofluorene and 7,8-epoxide-2-nitrofluorene were identified as the major epoxidation products. Epoxides are unstable and easy to react with hydrated hydrogen ions and hydroxyls to produce endocrine disrupter 7-hydroxy-2-nitrofluorene. Toxic analysis shows that some of the metabolites are more toxic to model aquatic organisms (e.g. Green algea) than NF. Binding affinity analysis to human sex hormone binding globulin reveals that NF metabolites all have endocrine-disrupting potential. This study provides a comprehensive understanding on the biotransformation process of NF and may aid future studies on various NPAHs activation catalyzed by human P450 enzyme.

Molecular Insights into the Intrinsic Dynamics and Their Roles During Catalysis in Pin1 Peptidyl-prolyl Isomerase

Proteins are intrinsically dynamic and change conformations over a wide range of time scales. While the conformational dynamics have been realized to be important for protein functions, e.g., in activity-stability trade-offs, how they play a role during enzyme catalysis has been of debate over decades. By studying Pin1 peptidyl-prolyl isomerase using extensive molecular dynamics simulations, here we discuss how the slow intrinsic dynamics of Pin1 observed in the NMR relaxation dispersion experiment occur and couple to isomerization reactions in molecular detail. In particular, we analyze the angular correlation functions of the backbone N-H bonds and find that slow conformational transitions occur at about the 3₁₀ helix in the apo state. These events at the helical region further affect the residues at about the ligand binding site. Unfolding of this helix leads to a tight hydrogen bond between the helical region and the ligand binding loop, thus forming a stable coiled structure. The helical and coiled structures are found to be characteristic of the Pin1-ligand complex with the ligand in the trans and cis states, respectively. These results indicate that the changes in the slow dynamics of Pin1 by the isomerization reaction occur via the shift in populations of the helical and coiled states, where the balance is dependent on the ligand isomerization states.

Role of ergodicity, aging, and Gaussianity in resolving the origins of biomolecule subdiffusion

The internal motions of biomolecules are essential to their function. Although biological macromolecules conventionally show subdiffusive dynamics, only recently has subdiffusion been associated with non-ergodicity. These findings have stimulated new questions in biophysics and statistical mechanics. Is non-ergodic subdiffusion a general strategy shared by biomolecules? What underlying mechanisms are responsible for it? Here, we performed extensive molecular dynamics (MD) simulations to characterize the internal dynamics of six different biomolecules, ranging from single or double-stranded DNA, a single domain protein (KRAS), two globular proteins (PGK and SHP2), to an intrinsically disordered protein (SNAP-25). We found that the subdiffusive behavior of these biomolecules falls into two classes. The internal motion of the first three cases is ergodic subdiffusion and can be interpreted by fractional Brownian motion (FBM), while the latter three cases involve non-ergodic subdiffusion and can be modeled by mixed origins of continuous-time random walk (CTRW) and FBM.

Ultrasensitive detection of local acoustic vibrations at room temperature by plasmon-enhanced single-molecule fluorescence

Sensitive detection of local acoustic vibrations at the nanometer scale has promising potential applications involving miniaturized devices in many areas, such as geological exploration, military reconnaissance, and ultrasound imaging. However, sensitive detection of weak acoustic signals with high spatial resolution at room temperature has become a major challenge. Here, we report a nanometer-scale system for acoustic detection with a single molecule as a probe based on minute variations of its distance to the surface of a plasmonic gold nanorod. This system can extract the frequency and amplitude of acoustic vibrations with experimental and theoretical sensitivities of 10 pm Hz^−1/2 and 10 fm Hz^−1/2, respectively. This approach provides a strategy for the optical detection of acoustic waves based on molecular spectroscopy without electromagnetic interference. Moreover, such a small nano-acoustic detector with 40-nm size can be employed to monitor acoustic vibrations or read out the quantum states of nanomechanical devices.

.Sensitive detection of weak acoustic signals at nanometer scale is challenging. Here, the authors present an acoustic detection system based on a single molecule as a probe, where frequency and amplitude of acoustic vibrations can be extracted from its minute variations in distance to the surface of a plasmonic gold nanorod.

Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks

Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structure of the conformers that are involved. However, analysis of the NMR data that report on exchanging macromolecules often hinges on complex least-squares fitting procedures as well as human experience and intuition, which, in some cases, limits the widespread use of the methods. The applications of deep neural networks (DNNs) and artificial intelligence have increased significantly in the sciences, and recently, specifically, within the field of biomolecular NMR, where DNNs are now available for tasks such as the reconstruction of sparsely sampled spectra, peak picking, and virtual decoupling. Here we present a DNN for the analysis of chemical exchange saturation transfer (CEST) data reporting on two- or three-site chemical exchange involving sparse state lifetimes of between approximately 3-60 ms, the range most frequently observed via experiment. The work presented here focuses on the ¹H CEST class of methods that are further complicated, in relation to applications to other nuclei, by anti-phase features. The developed DNNs accurately predict the chemical shifts of nuclei in the exchanging species directly from anti-phase ¹H^N CEST profiles, along with an uncertainty associated with the predictions. The performance of the DNN was quantitatively assessed using both synthetic and experimental anti-phase CEST profiles. The assessments show that the DNN accurately determines chemical shifts and their associated uncertainties. The DNNs developed here do not contain any parameters for the end-user to adjust and the method therefore allows for autonomous analysis of complex NMR data that report on conformational exchange.

Progress and perspectives in single-molecule optical spectroscopy

We review some of the progress of single-molecule optical experiments in the past 20 years and propose some perspectives for the coming years. We particularly focus on methodological advances in fluorescence, super-resolution, photothermal contrast, and interferometric scattering and briefly discuss a few of the applications. These advances have enabled the exploration of new emitters and quantum optics; the chemistry and biology of complex heterogeneous systems, nanoparticles, and plasmonics; and the detection and study of non-fluorescing and non-absorbing nano-objects. We conclude by proposing some ideas for future experiments. The field will move toward more and better signals of a broader variety of objects and toward a sharper view of the surprising complexity of the nanoscale world of single (bio-)molecules, nanoparticles, and their nano-environments.

Flavoprotein Photochemistry: Fundamental Processes and Photocatalytic Perspectives

Flavins are highly versatile redox-active and colored cofactors in a large variety of proteins. These do include photoenzymes and photoreceptors, although the vast majority performs non-light-driven physiological functions. Nevertheless, electron transfer between flavins and specific nearby amino acid residues (in particular tyrosine, tryptophan, and presumably histidine and arginine) takes place upon excitation of flavin in many flavoproteins. For oxidized flavoproteins these reactions potentially have a photoprotective role. In this Perspective, we outline work on the characterization of early reaction intermediates not only in the relatively well-studied resting oxidized forms but also in the fully reduced and the intrinsically unstable semireduced forms, where ultrafast photooxidation of flavin was recently demonstrated. Along different lines, flavoprotein-based novel photocatalysts for biotechnological applications are presently emerging, employing both substrate photooxidation and photoreduction strategies. Deep insight into the fundamental flavin photochemical reactions may help in guiding and optimizing their development and in the exploration of novel photocatalytic approaches.

Computational biotransformation of polyethylene terephthalate by depolymerase: A QM/MM approach

Despite increasing environmental concerns on ever-lasting Polyethylene Terephthalate (PET), its global production is continuously growing. Effective strategies that can completely remove PET from environment are urgently desired. Here biotransformation processes of PET by one of the most effective enzymes, leaf-branch compost cutinase (LCC), were systematically explored with Molecular Dynamics and Quantum Mechanics/Molecular Mechanics approaches. We found that four concerted steps are required to complete the whole catalytic cycle. The last concerted step, deacylation, was determined as the rate-determining step with Boltzmann-weighted average barrier of 13.6 kcal/mol and arithmetic average of 16.1 ± 2.9 kcal/mol. Interestingly, unprecedented fluctuations of hydrogen bond length during LCC catalyzed transformation process toward PET were found. This fluctuation was also observed in enzyme IsPETase, indicating that it may widely exist in other catalytic triad (Ser-His-Asp) containing enzymes as well. In addition, possible features (bond, angle, dihedral angle and charge) that influence the catalytic reaction were identified and correlations between activation energies and key features were established. Our results present new insights into catalytic mechanism of hydrolases and shed light on the efficient recycling of the ever-lasting PET.

Multiscale relaxation dynamics and diffusion of myelin basic protein in solution studied by quasielastic neutron scattering

We report an analysis of high-resolution quasielastic neutron scattering spectra from Myelin Basic Protein (MBP) in solution, comparing the spectra at three different temperatures (283, 303, and 323 K) for a pure D₂O buffer and a mixture of D₂O buffer with 30% of deuterated trifluoroethanol (TFE). Accompanying experiments with dynamic light scattering and Circular Dichroism (CD) spectroscopy have been performed to obtain, respectively, the global diffusion constant and the secondary structure content of the molecule for both buffers as a function of temperature. Modeling the decay of the neutron intermediate scattering function by the Mittag-Leffler relaxation function, ϕ(t) = E_α(-(t/τ)^α) (0 < α < 1), we find that trifluoroethanol slows down the relaxation dynamics of the protein at 283 K and leads to a broader relaxation rate spectrum. This effect vanishes with increasing temperature, and at 323 K, its relaxation dynamics is identical in both solvents. These results are coherent with the data from dynamic light scattering, which show that the hydrodynamic radius of MBP in TFE-enriched solutions does not depend on temperature and is only slightly smaller compared to the pure D₂O buffer, except for 283 K, where it is much reduced. In accordance with these observations, the CD spectra reveal that TFE induces essentially a partial transition from β-strands to α-helices, but only a weak increase in the total secondary structure content, leaving about 50% of the protein unfolded. The results show that MBP is for all temperatures and in both buffers an intrinsically disordered protein and that TFE essentially induces a reduction in its hydrodynamic radius and its relaxation dynamics at low temperatures.

Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.

Sub-millisecond Translational and Orientational Dynamics of a Freely Moving Single Nanoprobe

This paper presents a new experiment with which we are able to measure the 3D translational motion of a single particle at 10 μs time resolution and with ∼10 nm spatial resolution while at the same time determining the 3D orientation of the same single particle with 250 μs time resolution. These high time resolutions are ∼40 times greater than previous simultaneous measurements of 3D position and 3D orientation. Detailed numerical simulations and experiments are used to demonstrate that the technique can measure 3D orientation at the shot-noise limit. The microscope is also able to simultaneously measure the length or width (with the other assumed) of the plasmonic nanorods used here in situ and nondestructively, which should yield a greater understanding of the underlying dynamics. This technique should be applicable to a broad range of problems where environments which change in space and time may perturb physical and chemical dynamics.

Single-molecule conformational dynamics of a transcription factor reveals a continuum of binding modes controlling association and dissociation

Binding and unbinding of transcription factors to DNA are kinetically controlled to regulate the transcriptional outcome. Control of the release of the transcription factor NF-κB from DNA is achieved through accelerated dissociation by the inhibitor protein IκBα. Using single-molecule FRET, we observed a continuum of conformations of NF-κB in free and DNA-bound states interconverting on the subseconds to minutes timescale, comparable to in vivo binding on the seconds timescale, suggesting that structural dynamics directly control binding kinetics. Much of the DNA-bound NF-κB is partially bound, allowing IκBα invasion to facilitate DNA dissociation. IκBα induces a locked conformation where the DNA-binding domains of NF-κB are too far apart to bind DNA, whereas a loss-of-function IκBα mutant retains the NF-κB conformational ensemble. Overall, our results suggest a novel mechanism with a continuum of binding modes for controlling association and dissociation of transcription factors.

Aging power spectrum of membrane protein transport and other subordinated random walks

Single-particle tracking offers detailed information about the motion of molecules in complex environments such as those encountered in live cells, but the interpretation of experimental data is challenging. One of the most powerful tools in the characterization of random processes is the power spectral density. However, because anomalous diffusion processes in complex systems are usually not stationary, the traditional Wiener-Khinchin theorem for the analysis of power spectral densities is invalid. Here, we employ a recently developed tool named aging Wiener-Khinchin theorem to derive the power spectral density of fractional Brownian motion coexisting with a scale-free continuous time random walk, the two most typical anomalous diffusion processes. Using this analysis, we characterize the motion of voltage-gated sodium channels on the surface of hippocampal neurons. Our results show aging where the power spectral density can either increase or decrease with observation time depending on the specific parameters of both underlying processes.

Fast and robust two-dimensional inverse Laplace transformation of single-molecule fluorescence lifetime data

Fluorescence spectroscopy at the single-molecule scale has been indispensable for studying conformational dynamics and rare states of biological macromolecules. Single-molecule two-dimensional (2D) fluorescence lifetime correlation spectroscopy is an emerging technique that holds promise for the study of protein and nucleic acid dynamics, as the technique is 1) capable of resolving conformational dynamics using a single chromophore, 2) resolves forward and reverse transitions independently, and 3) has a dynamic window ranging from microseconds to seconds. However, the calculation of a 2D fluorescence relaxation spectrum requires an inverse Laplace transform (ILT), which is an ill-conditioned inversion that must be estimated numerically through a regularized minimization. Current methods for performing ILTs of fluorescence relaxation can be computationally inefficient, sensitive to noise corruption, and difficult to implement. Here, we adopt an approach developed for NMR spectroscopy (T1-T2 relaxometry) to perform one-dimensional (1D) and 2D-ILTs on single-molecule fluorescence spectroscopy data using singular-valued decomposition and Tikhonov regularization. This approach provides fast, robust, and easy to implement Laplace inversions of single-molecule fluorescence data. We compare this approach to the widely used maximal entropy method.

Ultrafast dynamics of fully reduced flavin in catalytic structures of thymidylate synthase ThyX

Thymidylate is a vital DNA precursor synthesized by thymidylate synthases. ThyX is a flavin-dependent thymidylate synthase found in several human pathogens and absent in humans, which makes it a potential target for antimicrobial drugs. This enzyme methylates the 2'-deoxyuridine 5'-monophosphate (dUMP) to 2'-deoxythymidine 5'-monophosphate (dTMP) using a reduced flavin adenine dinucleotide (FADH^-) as prosthetic group and (6R)-N₅,N₁₀-methylene-5,6,7,8-tetrahydrofolate (CH₂THF) as a methylene donor. Recently, it was shown that ThyX-catalyzed reaction is a complex process wherein FADH^- promotes both methylene transfer and reduction of the transferred methylene into a methyl group. Here, we studied the dynamic and photophysics of FADH^- bound to ThyX, in several substrate-binding states (no substrate, in the presence of dUMP or folate or both) by femtosecond transient absorption spectroscopy. This methodology provides valuable information about the ground-state configuration of the isoalloxazine moiety of FADH^- and the rigidity of its local environment, through spectra shape and excited-state lifetime parameters. In the absence of substrate, the environment of FADH^- in ThyX is only mildly more constrained than that of free FADH^- in solution. The addition of dUMP however narrows the distribution of ground-state configurations and increases the constraints on the butterfly bending motion in the excited state. Folate binding results in the selection of new ground-state configurations, presumably located at a greater distance from the conical intersection where excited-state decay occurs. When both substrates are present, the ground-state configuration appears on the contrary rather limited to a geometry close to the conical intersection, which explains the relatively fast excited-state decay (100 ps on the average), even if the environment of the isoalloxazine is densely packed. Hence, although the environment of the flavin is dramatically constrained, FADH^- retains a dynamic necessary to shuttle carbon from folate to dUMP. Our study demonstrates the high sensitivity of FADH^- photophysics to the constraints exerted by its immediate surroundings.

Red-Emitting Fluorophores as Local Water-Sensing Probes

Fluorescent probes are known for their ability to sense changes in their direct environment. We introduce here the idea that common red-emitting fluorophores recommended for biological labeling and typically used for simple visualization of biomolecules can also act as reporters of the water content in their first solvent sphere by a simple measurement of their fluorescence lifetime. Using fluorescence spectroscopy, we investigated the excited-state dynamics of seven commercially available fluorophores emitting between 650 and 800 nm that are efficiently quenched by H₂O. The amount of H₂O in their direct surrounding was modulated in homogeneous H₂O-D₂O mixtures or, in heterogeneous systems, by confining them into reverse micelles, by encapsulating them into host-guest complexes with cyclodextrins, or by attaching them to peptides and proteins. We found that their fluorescence properties can be rationalized in terms of the amount of H₂O in their direct surroundings, which provides a general mechanism for protein-induced fluorescence enhancements of red-emitting dyes and opens perspectives for directly counting water molecules in key biological environments or in polymers.

Time-squeezing and time-expanding transformations in harmonic force fields

A variety of real life phenomena exhibit complex time-inhomogeneous nonlinear diffusive motion in the presence of an external harmonic force. In capturing the characteristics of such dynamics, the class of Ornstein-Uhlenbeck processes, with its physical time appropriately modulated, has long been regarded as the most relevant model on the basis of its mean reversion property. In this paper, we contrast two similar, yet definitely different, time-changing mechanisms in harmonic force fields by systematically deriving and presenting a variety of key properties all at once, that is, whether or not and how those time-changing mechanisms affect the characteristics of mean-reverting diffusion through sample path properties, the marginal probability density function, the asymptotic degeneracy of increments, the stationary law, the second-order structure, and the ensemble- and time-averaged mean square displacements. Some of those properties turn out rather counter-intuitive due to, or irrespective of, possible degeneracy of time-changing mechanisms in the long run. In light of those illustrative comparisons, we examine whether such time-changing operations are worth the additional operational cost, relative to physically relevant characteristics induced, and deduce practical implications and precautions from modeling and inference perspectives, for instance, on the experimental setup involving those anomalous diffusion processes, such as the observation start time and stepsize when measuring mean square displacements, so as to preclude potentially misleading results and paradoxical interpretations.

Factors underlying asymmetric pore dynamics of disaggregase and microtubule-severing AAA+ machines

Disaggregation and microtubule-severing nanomachines from the AAA+ (ATPases associated with various cellular activities) superfamily assemble into ring-shaped hexamers that enable protein remodeling by coupling large-scale conformational changes with application of mechanical forces within a central pore by loops protruding within the pore. We probed the asymmetric pore motions and intraring interactions that support them by performing extensive molecular dynamics simulations of single-ring severing proteins and the double-ring disaggregase ClpB. Simulations reveal that dynamic stability of hexameric pores of severing proteins and of the nucleotide-binding domain 1 (NBD1) ring of ClpB, which belong to the same clade, involves a network of salt bridges that connect conserved motifs of central pore loops. Clustering analysis of ClpB highlights correlated motions of domains of neighboring protomers supporting strong interprotomer collaboration. Severing proteins have weaker interprotomer coupling and stronger intraprotomer stabilization through salt bridges involving pore loops. Distinct mechanisms are identified in the NBD2 ring of ClpB involving weaker interprotomer coupling through salt bridges formed by noncanonical loops and stronger intraprotomer coupling. Analysis of collective motions of PL1 loops indicates that the largest amplitude motions in the spiral complex of spastin and ClpB involve axial excursions of the loops, whereas for katanin they involve opening and closing of the central pore. All three motors execute primarily axial excursions in the ring complex. These results suggest distinct substrate processing mechanisms of remodeling and translocation by ClpB and spastin compared to katanin, thus providing dynamic support for the differential action of the two severing proteins. Relaxation dynamics of the distance between the PL1 loops and the center of mass of protomers reveals observation-time-dependent dynamics, leading to predicted relaxation times of tens to hundreds of microseconds on millisecond experimental timescales. For ClpB, the predicted relaxation time is in excellent agreement with the extracted time from smFRET experiments.