Electric-field-stimulated protein mechanics

Synechism 2.0: Contours of a new theory of continuity in bioengineering

The methodological principle of synechism, the all-pervading continuity first proposed by Charles Peirce in 1892, is reinvigorated in the present paper to prompt a comprehensive reevaluation of the integrated concepts of life, machines, agency, and intelligence. The evidence comes from the intersections of synthetic bioengineering, developmental biology, and cognitive and computational sciences. As a regulative principle, synechism, "that continuity governs the whole domain of experience in every element of it", has been shown to infiltrate fundamental issues of contemporary biology, including cognition in different substrates, embodied agency, collectives (swarm and nested), intelligence on multiple scales, and developmental bioelectricity in morphogenesis. In the present paper, we make explicit modern biology's turn to this fundamental feature of science in its rejection of conceptual binaries, preference for collectives over individuals, quantitative over qualitative, and multiscale applicability of the emerging hypotheses about the integration of the first principles of the diversity of life. Specifically, synechism presents itself as the bedrock for research encompassing biological machines, chimaeras, organoids, and Xenobots. We then review a synechistic framework that embeds functionalist, information-theoretic, pragmaticist and inferentialist approaches to springboard to continuum-driven biosystemic behaviour.

On-the-fly resolution enhancement in X-ray protein crystallography using electric field

X-ray crystallography has tremendously served structural biology by routinely providing high-resolution 3D structures of macromolecules. The extent of information encoded in the X-ray crystallography is proportional to which resolution the crystals diffract and the structure can be refined to. Therefore, there is a continuous effort to obtain high-quality crystals, especially for those proteins, which are considered difficult to crystallize into high-quality protein crystals of suitable sizes for X-ray crystallography. Efforts in enhancing the resolution in X-ray crystallography have also been made by optimizing crystallization protocols using external stimuli such as an electric field and magnetic field during the crystallization. Here, we present the feasibility of on-the-fly post-crystallization resolution enhancement of the protein crystal diffraction by applying a high-voltage electric field. The electric field between 2 and 11 kV/cm, which was applied after mounting the crystals in the beamline, resulted in the enhancement of the resolution. The crystal diffraction quality improved progressively with the exposure time. Moreover, we also find that upto defined electric field threshold, the protein structure remains largely unperturbed, a conclusion further supported by molecular dynamics simulations.

Direct visualization of electric-field-stimulated ion conduction in a potassium channel

Understanding protein function would be facilitated by direct, real-time observation of chemical kinetics in the atomic structure. The selectivity filter (SF) of the K+ channel provides an ideal model, catalyzing the dehydration and transport of K+ ions across the cell membrane through a narrow pore. We used a "pump-probe" method called electric-field-stimulated time-resolved X-ray crystallography (EFX) to initiate and observe K+ conduction in the NaK2K channel in both directions on the timescale of the transport process. We observe both known and potentially new features in the high-energy conformations visited along the conduction pathway, including the associated dynamics of protein residues that control selectivity and conduction rate. A single time series of one channel in action shows the orderly appearance of features observed in diverse homologs with diverse methods, arguing for deep conservation of the dynamics underlying the reaction coordinate in this protein family.

Effect of Electric Fields on the Mechanical Mechanism of Regorafenib-VEGFR2 Interaction to Enhance Inhibition of Hepatocellular Carcinoma

The interaction between molecular targeted therapy drugs and target proteins is crucial with regard to the drugs' anti-tumor effects. Electric fields can change the structure of proteins, which determines the interaction between drugs and proteins. However, the regulation of the interaction between drugs and target proteins and the anti-tumor effects of electric fields have not been studied thoroughly. Here, we explored how electric fields enhance the inhibition of regorafenib with regard to the activity, invasion, and metastasis of hepatocellular carcinoma cells. We found that electric fields lead to an increase in the normal (adhesion) and transverse (friction) interaction forces between regorafenib and VEGFR2. In single molecule pair interactions, there are changes in specific and nonspecific forces. Hydrogen bonds, hydrophobic interactions, and van der Waals forces are the main influencing factors. Importantly, the increase in the adhesion force and friction force between regorafenib and VEGFR2 caused by electric fields is related to the activity and migration ability of hepatocellular carcinoma cells. The morphological changes in VEGFR2 prove that electric fields regulate protein conformation. Overall, our work proves the drug-protein mechanical mechanism by which electric fields enhance the anti-tumor effect of regorafenib and provides insights into the application of electric fields in clinical tumor treatment.

Soft Modes as a Predictive Framework for Low Dimensional Biological Systems across Scales

All biological systems are subject to perturbations: due to thermal fluctuations, external environments, or mutations. Yet, while biological systems are composed of thousands of interacting components, recent high-throughput experiments show that their response to perturbations is surprisingly low-dimensional: confined to only a few stereotyped changes out of the many possible. Here, we explore a unifying dynamical systems framework - soft modes - to explain and analyze low-dimensionality in biology, from molecules to eco-systems. We argue that this one framework of soft modes makes non-trivial predictions that generalize classic ideas from developmental biology to disparate systems, namely: phenocopying, dual buffering, and global epistasis. While some of these predictions have been borne out in experiments, we discuss how soft modes allow for a surprisingly far-reaching and unifying framework in which to analyze data from protein biophysics to microbial ecology.

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

Multiplexing methods in dynamic protein crystallography

Time-resolved X-ray crystallography experiments were first performed in the 1980s, yet they remained a niche technique for decades. With the recent advent of X-ray free electron laser (XFEL) sources and serial crystallographic techniques, time-resolved crystallography has received renewed interest and has become more accessible to a wider user base. Despite this, time-resolved structures represent < 1 % of models deposited in the world-wide Protein Data Bank, indicating that the tools and techniques currently available require further development before such experiments can become truly routine. In this chapter, we demonstrate how applying data multiplexing to time-resolved crystallography can enhance the achievable time resolution at moderately intense monochromatic X-ray sources, ranging from synchrotrons to bench-top sources. We discuss the principles of multiplexing, where this technique may be advantageous, potential pitfalls, and experimental design considerations.

ResiDEM: Analytical Tool for Isomorphous Difference Electron Density Maps Utilizing Dynamic Residue Identification via Density Clustering

Time-resolved serial femtosecond crystallography (TR-SFX) of biological molecules captures the time-evolved dynamics of the residual motions across crystal structures, enabling the visualization of structural changes in response to chemical and physical stimuli to elucidate the relationship between the structure and function of the system under study. However, interpretations of residual motions can be complex to deconvolute because of various factors such as the system's size, temporal and spatial complexity, and allosteric behavior away from active sites. Relying solely on electron density map visualization can also pose a challenge in differentiating between useful and irrelevant data. In order to accurately identify residues and determine their respective contributions to the reaction dynamics, new tools are needed. We developed a new tool, ResiDEM, which employs a clustering-based approach to group difference electron densities and associate them with proximal residues. It can identify and rank residues with significant motions. Network representation can be used to delineate the interrelations between the residues in motion. With these features, ResiDEM helps to interpret residual motions in TR-SFX data, identify key residues, and elucidate their roles in dynamic processes.

Insights into VDAC Gating: Room-Temperature X-ray Crystal Structure of mVDAC-1

The voltage-dependent anion channel (VDAC) is a crucial mitochondrial protein that facilitates ion and metabolite exchange between mitochondria and the cytosol. Initially characterized over three decades ago, the structure of VDAC-1 was resolved in 2008, revealing a novel β-barrel protein architecture. This study presents the first room-temperature crystal structure of mouse VDAC-1 (mVDAC-1), which is a significant step toward understanding the channel's gating mechanism. The new structure, obtained at a 3.3 Å resolution, demonstrates notable differences from the previously determined cryogenic structure, particularly in the loop regions, which may be critical for the transition between the 'open' and 'closed' states of VDAC-1. Comparative analysis of the root-mean-square deviation (R.M.S.D.) and B-factors between the cryogenic and room-temperature structures suggests that these conformational differences, although subtle, are important for VDAC's functional transitions. The application of electric field-stimulated X-ray crystallography (EF-X) is proposed as a future direction to resolve the 'closed' state of VDAC-1 by inducing voltage-driven conformational changes in order to elucidate the dynamic gating mechanism of VDAC-1. Our findings have profound implications for understanding the molecular basis of VDAC's role in mitochondrial function and its regulation under physiological conditions.

Laue-DIALS: Open-source software for polychromatic x-ray diffraction data

Most x-ray sources are inherently polychromatic. Polychromatic ("pink") x-rays provide an efficient way to conduct diffraction experiments as many more photons can be used and large regions of reciprocal space can be probed without sample rotation during exposure-ideal conditions for time-resolved applications. Analysis of such data is complicated, however, causing most x-ray facilities to discard >99% of x-ray photons to obtain monochromatic data. Key challenges in analyzing polychromatic diffraction data include lattice searching, indexing and wavelength assignment, correction of measured intensities for wavelength-dependent effects, and deconvolution of harmonics. We recently described an algorithm, Careless, that can perform harmonic deconvolution and correct measured intensities for variation in wavelength when presented with integrated diffraction intensities and assigned wavelengths. Here, we present Laue-DIALS, an open-source software pipeline that indexes and integrates polychromatic diffraction data. Laue-DIALS is based on the dxtbx toolbox, which supports the DIALS software commonly used to process monochromatic data. As such, Laue-DIALS provides many of the same advantages: an open-source, modular, and extensible architecture, providing a robust basis for future development. We present benchmark results showing that Laue-DIALS, together with Careless, provides a suitable approach to the analysis of polychromatic diffraction data, including for time-resolved applications.

Piezoelectric Analgesia Blocks Cancer-Induced Bone Pain

The manipulation of cell surface receptors' activity will open a new frontier for drug development and disease treatment. However, limited by the desensitization of drugs, effective physical intervention strategy remains challenging. Here, the controllable internalization of transient receptor potential vanilloid 1 (TRPV1) on neural cells by local piezoelectric field is reported. Single-cell-level local electric field is construct by synthesizing piezoelectric BiOIO3 nanosheets (BIONSs). Upon a mild ultrasound of 0.08 W cm-2, an electric field of 15.29 µV is generated on the surface of BIONSs, further inducing TRPV1 internalization in 5 min. The as-downregulated TRPV1 expression results in the reduction of Ca2+ signal in a spinal neuron and the inhibition of the activity of wide range dynamic neurons, therefore effectively preventing the transmission of cancer-induced bone pain (CIBP). This strategy not only charts a new course for CIBP alleviation, but also introduces a promising nanotechnology for regulating cell surface receptors, showing significant potential in neuropathological and receptor-related diseases.

Innovative Strategies in X-ray Crystallography for Exploring Structural Dynamics and Reaction Mechanisms in Metabolic Disorders

Enzymes are crucial in metabolic processes, and their dysfunction can lead to severe metabolic disorders. Structural biology, particularly X-ray crystallography, has advanced our understanding of these diseases by providing 3D structures of pathological enzymes. However, traditional X-ray crystallography faces limitations, such as difficulties in obtaining suitable protein crystals and studying protein dynamics. X-ray free-electron lasers (XFELs) have revolutionized this field with their bright and brief X-ray pulses, providing high-resolution structures of radiation-sensitive and hard-to-crystallize proteins. XFELs also enable the study of protein dynamics through room temperature structures and time-resolved serial femtosecond crystallography, offering comprehensive insights into the molecular mechanisms of metabolic diseases. Understanding these dynamics is vital for developing effective therapies. This review highlights the contributions of protein dynamics studies using XFELs and synchrotrons to metabolic disorder research and their application in designing better therapies. It also discusses G protein-coupled receptors (GPCRs), which, though not enzymes, play key roles in regulating physiological systems and are implicated in many metabolic disorders.

Tubulin Vibration Modes Are in the Subterahertz Range, and Their Electromagnetic Absorption Is Affected by Water

Many proteins are thought to coordinate distant sites in their structures through a concerted action of global structural vibrations. However, the direct experimental spectroscopic detection of these vibration modes is rather elusive. We used normal-mode analysis to explore the dominant vibration modes of an all-atom model of the tubulin protein and described their characteristics using a large ensemble of tubulin structures. We quantified the frequency range of the normal vibrational modes to be in the subterahertz band, specifically between ∼40 and ∼160 GHz. Adding water layers to the model increases the frequencies of the low-frequency modes and narrows the frequency variations of the modes among the protein ensemble. We also showed how the electromagnetic absorption of tubulin vibration modes is affected by vibrational damping. These results contribute to our understanding of tubulin's vibrational and electromagnetic properties and provide a foundation for future attempts to control protein behavior via external electromagnetic fields.

An Infrared Nanospectroscopy Technique for the Study of Electric-Field-Induced Molecular Dynamics

Static electric fields play a considerable role in a variety of molecular nanosystems as diverse as single-molecule junctions, molecules supporting electrostatic catalysis, and biological cell membranes incorporating proteins. External electric fields can be applied to nanoscale samples with a conductive atomic force microscopy (AFM) probe in contact mode, but typically, no structural information is retrieved. Here we combine photothermal expansion infrared (IR) nanospectroscopy with electrostatic AFM probes to measure nanometric volumes where the IR field enhancement and the static electric field overlap spatially. We leverage the vibrational Stark effect in the polymer poly(methyl methacrylate) for calibrating the local electric field strength. In the relevant case of membrane protein bacteriorhodopsin, we observe electric-field-induced changes of the protein backbone conformation and residue protonation state. The proposed technique also has the potential to measure DC currents and IR spectra simultaneously, insofar enabling the monitoring of the possible interplay between charge transport and other effects.

No observable non-thermal effect of microwave radiation on the growth of microtubules

Despite widespread public interest in the health impact of exposure to microwave radiation, studies of the influence of microwave radiation on biological samples are often inconclusive or contradictory. Here we examine the influence of microwave radiation of frequencies 3.5 GHz, 20 GHz and 29 GHz on the growth of microtubules, which are biological nanotubes that perform diverse functions in eukaryotic cells. Since microtubules are highly polar and can extend several micrometres in length, they are predicted to be sensitive to non-ionizing radiation. Moreover, it has been speculated that tubulin dimers within microtubules might rapidly toggle between different conformations, potentially participating in computational or other cooperative processes. Our data show that exposure to microwave radiation yields a microtubule growth curve that is distorted relative to control studies utilizing a homogeneous temperature jump. However, this apparent effect of non-ionizing radiation is reproduced by control experiments using an infrared laser or hot air to heat the sample and thereby mimic the thermal history of samples exposed to microwaves. As such, no non-thermal effects of microwave radiation on microtubule growth can be assigned. Our results highlight the need for appropriate control experiments in biophysical studies that may impact on the sphere of public interest.

Scaling and Merging Time-Resolved Laue Data with Variational Inference

Time-resolved X-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

Laue-DIALS: open-source software for polychromatic X-ray diffraction data

Most X-ray sources are inherently polychromatic. Polychromatic ("pink") X-rays provide an efficient way to conduct diffraction experiments as many more photons can be used and large regions of reciprocal space can be probed without sample rotation during exposure-ideal conditions for time-resolved applications. Analysis of such data is complicated, however, causing most X-ray facilities to discard >99% of X-ray photons to obtain monochromatic data. Key challenges in analyzing polychromatic diffraction data include lattice searching, indexing and wavelength assignment, correction of measured intensities for wavelength-dependent effects, and deconvolution of harmonics. We recently described an algorithm, Careless, that can perform harmonic deconvolution and correct measured intensities for variation in wavelength when presented with integrated diffraction intensities and assigned wavelengths. Here, we present Laue-DIALS, an open-source software pipeline that indexes and integrates polychromatic diffraction data. Laue-DIALS is based on the dxtbx toolbox, which supports the DIALS software commonly used to process monochromatic data. As such, Laue-DIALS provides many of the same advantages: an open-source, modular, and extensible architecture, providing a robust basis for future development. We present benchmark results showing that Laue-DIALS, together with Careless, provides a suitable approach to the analysis of polychromatic diffraction data, including for time-resolved applications.

Sensitive Detection of Structural Differences using a Statistical Framework for Comparative Crystallography

Chemical and conformational changes underlie the functional cycles of proteins. Comparative crystallography can reveal these changes over time, over ligands, and over chemical and physical perturbations in atomic detail. A key difficulty, however, is that the resulting observations must be placed on the same scale by correcting for experimental factors. We recently introduced a Bayesian framework for correcting (scaling) X-ray diffraction data by combining deep learning with statistical priors informed by crystallographic theory. To scale comparative crystallography data, we here combine this framework with a multivariate statistical theory of comparative crystallography. By doing so, we find strong improvements in the detection of protein dynamics, element-specific anomalous signal, and the binding of drug fragments.

Unraveling the binding mechanisms of transglutaminase and substrate subjected to microwaves: Molecular docking and molecular dynamic simulations

Previous studies showed that transglutaminase (TGase) and microwaves acted synergistically to improve the functional properties of proteins. The mechanism behind this has yet to be elucidated. In this study, the phenomenon of microwaves enhancing TGase activity was experimentally validated. Molecular docking and molecular dynamics simulations revealed that moderate microwaves (105 and 108 V/m) increased the structural flexibility of TGase and promoted the orientation of the side chain carboxylate anion group on Asp255, driving the reaction forward. Also, TGase underwent partial transformation from α-helix to turns or coils at 105 and 108 V/m, exposing more residues in the active site and facilitating the binding of the substrate (CBZ-Gln-Gly) to TGase. However, 109 V/m microwaves completely destroyed the TGase structure, inactivating the enzyme. This study provides insights into the molecular mechanisms underlying the interactions between TGase and substrate subjected to microwaves, promoting the future applications of TGase and microwaves in food processing.

Confined liquid crystallization governed by electric field for API crystal polymorphism screening and massive preparation

Active pharmaceutical ingredients (APIs) crystal preparation is a significant issue for the pharmaceutical development attributed to the effect on anti-inflammatory, anti-bacteria, and anti-viral, etc. While, the massive preparation of API crystal with high polymorphism selectivity is still a pendent challenge. Here, we firstly proposed a criterion according to the molecular aggregation, molecular orientation, and hydrogen bond energy between INA molecules from molecular dynamics (MD) simulations, which predicted the hydrogen bond architecture in crystal under different electric fields, hinting the recognition of crystal polymorphism. Then, an electric field governing confined liquid crystallization was constructed to achieve the INA crystal polymorphism screening relying on the criterion. Further, magnifying confined liquid volume by 5000 times from 1.0 μL to 5.0 mL realized the massive preparation of INA crystal with high polymorphic purity (>98.4%), giving a unique pathway for crystal engineering and pharmaceutical industry on the development of innovative and generic API based drugs.

Design and fabrication of 3D-printed in situ crystallization plates for probing microcrystals in an external electric field

X-ray crystallography is an established tool to probe the structure of macromolecules with atomic resolution. Compared with alternative techniques such as single-particle cryo-electron microscopy and micro-electron diffraction, X-ray crystallography is uniquely suited to room-temperature studies and for obtaining a detailed picture of macromolecules subjected to an external electric field (EEF). The impact of an EEF on proteins has been extensively explored through single-crystal X-ray crystallography, which works well with larger high-quality protein crystals. This article introduces a novel design for a 3D-printed in situ crystallization plate that serves a dual purpose: fostering crystal growth and allowing the concurrent examination of the effects of an EEF on crystals of varying sizes. The plate's compatibility with established X-ray crystallography techniques is evaluated.

MatchMaps: non-isomorphous difference maps for X-ray crystallography

Conformational change mediates the biological functions of macromolecules. Crystallographic measurements can map these changes with extraordinary sensitivity as a function of mutations, ligands and time. A popular method for detecting structural differences between crystallographic data sets is the isomorphous difference map. These maps combine the phases of a chosen reference state with the observed changes in structure factor amplitudes to yield a map of changes in electron density. Such maps are much more sensitive to conformational change than structure refinement is, and are unbiased in the sense that observed differences do not depend on refinement of the perturbed state. However, even modest changes in unit-cell properties can render isomorphous difference maps useless. This is unnecessary. Described here is a generalized procedure for calculating observed difference maps that retains the high sensitivity to conformational change and avoids structure refinement of the perturbed state. This procedure is implemented in an open-source Python package, MatchMaps, that can be run in any software environment supporting PHENIX [Liebschner et al. (2019). Acta Cryst. D75, 861-877] and CCP4 [Agirre et al. (2023). Acta Cryst. D79, 449-461]. Worked examples show that MatchMaps 'rescues' observed difference electron-density maps for poorly isomorphous crystals, corrects artifacts in nominally isomorphous difference maps, and extends to detecting differences across copies within the asymmetric unit or across altogether different crystal forms.

Structural biology in the age of X-ray free-electron lasers and exascale computing

Serial femtosecond X-ray crystallography has emerged as a powerful method for investigating biomolecular structure and dynamics. With the new generation of X-ray free-electron lasers, which generate ultrabright X-ray pulses at megahertz repetition rates, we can now rapidly probe ultrafast conformational changes and charge movement in biomolecules. Over the last year, another innovation has been the deployment of Frontier, the world's first exascale supercomputer. Synergizing extremely high repetition rate X-ray light sources and exascale computing has the potential to accelerate discovery in biomolecular sciences. Here we outline our perspective on each of these remarkable innovations individually, and the opportunities and challenges in yoking them within an integrated research infrastructure.

Functional protein dynamics in a crystal

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.

Changes in an enzyme ensemble during catalysis observed by high-resolution XFEL crystallography

Enzymes populate ensembles of structures necessary for catalysis that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography at an x-ray free electron laser to observe catalysis in a designed mutant isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations, and formation of the thioimidate intermediate selects for catalytically competent substates. The influence of cysteine ionization on the ICH ensemble is validated by determining structures of the enzyme at multiple pH values. Large molecular dynamics simulations in crystallo and time-resolved electron density maps show that Asp17 ionizes during catalysis and causes conformational changes that propagate across the dimer, permitting water to enter the active site for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Functional Protein Dynamics in a Crystal

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.

The time revolution in macromolecular crystallography

Macromolecular crystallography has historically provided the atomic structures of proteins fundamental to cellular functions. However, the advent of cryo-electron microscopy for structure determination of large and increasingly smaller and flexible proteins signaled a paradigm shift in structural biology. The extensive structural and sequence data from crystallography and advanced sequencing techniques have been pivotal for training computational models for accurate structure prediction, unveiling the general fold of most proteins. Here, we present a perspective on the rise of time-resolved crystallography as the new frontier of macromolecular structure determination. We trace the evolution from the pioneering time-resolved crystallography methods to modern serial crystallography, highlighting the synergy between rapid detection technologies and state-of-the-art x-ray sources. These innovations are redefining our exploration of protein dynamics, with high-resolution crystallography uniquely positioned to elucidate rapid dynamic processes at ambient temperatures, thus deepening our understanding of protein functionality. We propose that the integration of dynamic structural data with machine learning advancements will unlock predictive capabilities for protein kinetics, revolutionizing dynamics like macromolecular crystallography revolutionized structural biology.

Perturbative diffraction methods resolve a conformational switch that facilitates a two-step enzymatic mechanism

Enzymes catalyze biochemical reactions through precise positioning of substrates, cofactors, and amino acids to modulate the transition-state free energy. However, the role of conformational dynamics remains poorly understood due to poor experimental access. This shortcoming is evident with Escherichia coli dihydrofolate reductase (DHFR), a model system for the role of protein dynamics in catalysis, for which it is unknown how the enzyme regulates the different active site environments required to facilitate proton and hydride transfer. Here, we describe ligand-, temperature-, and electric-field-based perturbations during X-ray diffraction experiments to map the conformational dynamics of the Michaelis complex of DHFR. We resolve coupled global and local motions and find that these motions are engaged by the protonated substrate to promote efficient catalysis. This result suggests a fundamental design principle for multistep enzymes in which pre-existing dynamics enable intermediates to drive rapid electrostatic reorganization to facilitate subsequent chemical steps.

From femtoseconds to minutes: time-resolved macromolecular crystallography at XFELs and synchrotrons

Over the last decade, the development of time-resolved serial crystallography (TR-SX) at X-ray free-electron lasers (XFELs) and synchrotrons has allowed researchers to study phenomena occurring in proteins on the femtosecond-to-minute timescale, taking advantage of many technical and methodological breakthroughs. Protein crystals of various sizes are presented to the X-ray beam in either a static or a moving medium. Photoactive proteins were naturally the initial systems to be studied in TR-SX experiments using pump-probe schemes, where the pump is a pulse of visible light. Other reaction initiations through small-molecule diffusion are gaining momentum. Here, selected examples of XFEL and synchrotron time-resolved crystallography studies will be used to highlight the specificities of the various instruments and methods with respect to time resolution, and are compared with cryo-trapping studies.

MatchMaps: Non-isomorphous difference maps for X-ray crystallography

Conformational change mediates the biological functions of macromolecules. Crystallographic measurements can map these changes with extraordinary sensitivity as a function of mutations, ligands, and time. The isomorphous difference map remains the gold standard for detecting structural differences between datasets. Isomorphous difference maps combine the phases of a chosen reference state with the observed changes in structure factor amplitudes to yield a map of changes in electron density. Such maps are much more sensitive to conformational change than structure refinement is, and are unbiased in the sense that observed differences do not depend on refinement of the perturbed state. However, even minute changes in unit cell properties can render isomorphous difference maps useless. This is unnecessary. Here we describe a generalized procedure for calculating observed difference maps that retains the high sensitivity to conformational change and avoids structure refinement of the perturbed state. We have implemented this procedure in an open-source python package, MatchMaps, that can be run in any software environment supporting PHENIX and CCP4. Through examples, we show that MatchMaps "rescues" observed difference electron density maps for poorly-isomorphous crystals, corrects artifacts in nominally isomorphous difference maps, and extends to detecting differences across copies within the asymmetric unit, or across altogether different crystal forms.

BioCARS: Synchrotron facility for probing structural dynamics of biological macromolecules

A major goal in biomedical science is to move beyond static images of proteins and other biological macromolecules to the internal dynamics underlying their function. This level of study is necessary to understand how these molecules work and to engineer new functions and modulators of function. Stemming from a visionary commitment to this problem by Keith Moffat decades ago, a community of structural biologists has now enabled a set of x-ray scattering technologies for observing intramolecular dynamics in biological macromolecules at atomic resolution and over the broad range of timescales over which motions are functionally relevant. Many of these techniques are provided by BioCARS, a cutting-edge synchrotron radiation facility built under Moffat leadership and located at the Advanced Photon Source at Argonne National Laboratory. BioCARS enables experimental studies of molecular dynamics with time resolutions spanning from 100 ps to seconds and provides both time-resolved x-ray crystallography and small- and wide-angle x-ray scattering. Structural changes can be initiated by several methods-UV/Vis pumping with tunable picosecond and nanosecond laser pulses, substrate diffusion, and global perturbations, such as electric field and temperature jumps. Studies of dynamics typically involve subtle perturbations to molecular structures, requiring specialized computational techniques for data processing and interpretation. In this review, we present the challenges in experimental macromolecular dynamics and describe the current state of experimental capabilities at this facility. As Moffat imagined years ago, BioCARS is now positioned to catalyze the scientific community to make fundamental advances in understanding proteins and other complex biological macromolecules.

Dramatic Differences between the Structural Susceptibility of the S1 Pre- and S2 Postfusion States of the SARS-CoV-2 Spike Protein to External Electric Fields Revealed by Molecular Dynamics Simulations

In its prefusion state, the SARS-CoV-2 spike protein (similarly to other class I viral fusion proteins) is metastable, which is considered to be an important feature for optimizing or regulating its functions. After the binding process of its S1 subunit (S1) with ACE2, the spike protein (S) undergoes a dramatic conformational change where S1 splits from the S2 subunit, which then penetrates the membrane of the host cell, promoting the fusion of the viral and cell membranes. This results in the infection of the host cell. In a previous work, we showed-using large-scale molecular dynamics simulations-that the application of external electric fields (EFs) induces drastic changes and damage in the receptor-binding domain (RBD) of the wild-type spike protein, as well of the Alpha, Beta, and Gamma variants, leaving a structure which cannot be recognized anymore by ACE2. In this work, we first extend the study to the Delta and Omicron variants and confirm the high sensitivity and extreme vulnerability of the RBD of the prefusion state of S to moderate EF (as weak as 104 V/m), but, more importantly, we also show that, in contrast, the S2 subunit of the postfusion state of the spike protein does not suffer structural damage even if electric field intensities four orders of magnitude higher are applied. These results provide a solid scientific basis to confirm the connection between the prefusion-state metastability of the SARS-CoV-2 spike protein and its susceptibility to be damaged by EF. After the virus docks to the ACE2 receptor, the stable and robust postfusion conformation develops, which exhibits a similar resistance to EF (damage threshold higher than 108 V/m) like most globular proteins.

Modulating SARS-CoV-2 Spike Protein Reactivity through Moderate Electric Fields: A Pathway to Innovative Therapies

In the quest for effective COVID-19 treatments and vaccines, traditional biochemical methods have been paramount, yet the challenge of accommodating diverse viral mutants persists. Recent simulations propose an innovative physical strategy involving an external electric field applied to the SARS-CoV-2 spike protein, demonstrating a reduced viral binding potential. However, limited empirical knowledge exists regarding the characteristics of the spike protein after E-field treatment. Our study addresses this gap by employing diverse analytical techniques to elucidate the impact of low/moderate E-field intensity on the binding of the SARS-CoV-2 spike protein to the ACE2 receptor. Through comprehensive analysis, we unveil a substantial reduction in the spike protein binding capacity validated via enzyme-linked immunosorbent assay and quartz crystal microbalance experiments. Remarkably, the E-field exposure induces significant protein structure rearrangement, leading to an enhanced negative surface zeta potential confirmed by dynamic light scattering. Circular dichroism spectroscopy corroborates these structural changes, showing alterations in the secondary protein structures. This study provides insights into SARS-CoV-2 spike protein modification under an E-field pulse, potentially paving the way for nonbiochemical strategies to mitigate viral reactivity and opening avenues for innovative therapeutic and preventive approaches against COVID-19 and its evolving variants.

Mapping protein dynamics at high spatial resolution with temperature-jump X-ray crystallography

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

Electrochemistry in sensing of molecular interactions of proteins and their behavior in an electric field

Electrochemical methods can be used not only for the sensitive analysis of proteins but also for deeper research into their structure, transport functions (transfer of electrons and protons), and sensing their interactions with soft and solid surfaces. Last but not least, electrochemical tools are useful for investigating the effect of an electric field on protein structure, the direct application of electrochemical methods for controlling protein function, or the micromanipulation of supramolecular protein structures. There are many experimental arrangements (modalities), from the classic configuration that works with an electrochemical cell to miniaturized electrochemical sensors and microchip platforms. The support of computational chemistry methods which appropriately complement the interpretation framework of experimental results is also important. This text describes recent directions in electrochemical methods for the determination of proteins and briefly summarizes available methodologies for the selective labeling of proteins using redox-active probes. Attention is also paid to the theoretical aspects of electron transport and the effect of an external electric field on the structure of selected proteins. Instead of providing a comprehensive overview, we aim to highlight areas of interest that have not been summarized recently, but, at the same time, represent current trends in the field.

Correcting systematic errors in diffraction data with modern scaling algorithms

X-ray diffraction enables the routine determination of the atomic structure of materials. Key to its success are data-processing algorithms that allow experimenters to determine the electron density of a sample from its diffraction pattern. Scaling, the estimation and correction of systematic errors in diffraction intensities, is an essential step in this process. These errors arise from sample heterogeneity, radiation damage, instrument limitations and other aspects of the experiment. New X-ray sources and sample-delivery methods, along with new experiments focused on changes in structure as a function of perturbations, have led to new demands on scaling algorithms. Classically, scaling algorithms use least-squares optimization to fit a model of common error sources to the observed diffraction intensities to force these intensities onto the same empirical scale. Recently, an alternative approach has been demonstrated which uses a Bayesian optimization method, variational inference, to simultaneously infer merged data along with corrections, or scale factors, for the systematic errors. Owing to its flexibility, this approach proves to be advantageous in certain scenarios. This perspective briefly reviews the history of scaling algorithms and contrasts them with variational inference. Finally, appropriate use cases are identified for the first such algorithm, Careless, guidance is offered on its use and some speculations are made about future variational scaling methods.

Conformational Fluctuations and Induced Orientation of a Protein, Its Solvation Shell, and Bulk Water in Weak Non-Unfolding External Electric Fields

Extreme external electric fields have been reported to disrupt the tertiary structure of stably folded proteins; however, the effects of weaker electric fields on many biomolecules, especially net-uncharged proteins, and on the surrounding aqueous environment have been rarely discussed. To explore these effects at the atomic level, here, we have used molecular dynamics simulations to estimate rotational motion and induced structural fluctuations in the model protein ubiquitin and its hydration layer due to applied non-unfolding electrostatic fields. When exposed to weak electric fields of up to 0.2 V nm-1, ubiquitin displayed competition between internal structure-maintaining molecular interactions and the external orienting force, which disrupted the local structure in certain regions of the protein. Moreover, relative to hydration water, bulk water showed a greater tendency to align with the electric field, indicating that the presence of protein caused hydration water to acquire rotational mobility different from that in a pure-water system. The differential influence of the applied electric field on the hydration and bulk water surrounding ubiquitin will be common to almost all (nonmembrane) biomacromolecules. Our findings highlight the importance of local dipoles and their electric polarizability even in net-uncharged biomolecules.

Protection of high-frequency low-intensity pulsed electric fields and brain-derived neurotrophic factor for SH-SY5Y cells against hydrogen peroxide-induced cell damage

Neurodegenerative diseases (NDDs) pose a significant global health threat. In particular, Alzheimer disease, the most common type causing dementia, remains an incurable disease. Alzheimer disease is thought to be associated with an imbalance of reactive oxygen species (ROS) in neurons, and scientists considered ROS modulation as a promising strategy for novel remedies. In the study, human neural cell line SH-SY5Y was used in probing the effect of combining noninvasive high-frequency low-intensity pulsed electric field (H-LIPEF) and brain-derived neurotrophic factor (BDNF) in protection against hydrogen peroxide (H2O2)-induced neuron damage. Our result finds that the combination approach has intensified the neuroprotective effect significantly, perhaps due to H-LIPEF and BDNF synergistically increasing the expression level of the phosphorylated epidermal growth factor receptor (p-EGFR), which induces the survival-related mitogen-activated protein kinases (MAPK) proteins. The study confirmed the activation of extracellular signal-regulated kinase (ERK) and the downstream pro-survival and antioxidant proteins as the mechanism underlying neuron protection. These findings highlighted the potential of H-LIPEF combined with BDNF in the treatment of NDDs. Furthermore, BDNF-mimetic drugs combining with noninvasive H-LIPEF to patients is a promising approach worthy of further research. This points to strategies for selecting drugs to cooperate with electric fields in treating neurodegenerative disorders.

LAWS: Local alignment for water sites-Tracking ordered water in simulations

Accurate modeling of protein-water interactions in molecular dynamics (MD) simulations is important for understanding the molecular basis of protein function. Data from x-ray crystallography can be useful in assessing the accuracy of MD simulations, in particular, the locations of crystallographic water sites (CWS) coordinated by the protein. Such a comparison requires special methodological considerations that take into account the dynamic nature of proteins. However, existing methods for analyzing CWS in MD simulations rely on global alignment of the protein onto the crystal structure, which introduces substantial errors in the case of significant structural deviations. Here, we propose a method called local alignment for water sites (LAWS), which is based on multilateration-an algorithm widely used in GPS tracking. LAWS considers the contacts formed by CWS and protein atoms in the crystal structure and uses these interaction distances to track CWS in a simulation. We apply our method to simulations of a protein crystal and to simulations of the same protein in solution. Compared with existing methods, LAWS defines CWS characterized by more prominent water density peaks and a less-perturbed protein environment. In the crystal, we find that all high-confidence crystallographic waters are preserved. Using LAWS, we demonstrate the importance of crystal packing for the stability of CWS in the unit cell. Simulations of the protein in solution and in the crystal share a common set of preserved CWS that are located in pockets and coordinated by residues of the same domain, which suggests that the LAWS algorithm will also be useful in studying ordered waters and water networks in general.

Stimuli-Induced Subconformation Transformation of the PSI-LHCI Protein at Single-Molecule Resolution

Photosynthesis is a very important process for the current biosphere which can maintain such a subtle and stable circulatory ecosystem on earth through the transformation of energy and substance. Even though been widely studied in various aspects, the physiological activities, such as intrinsic structural vibration and self-regulation process to stress of photosynthetic proteins, are still not in-depth resolved in real-time. Herein, utilizing silicon nanowire biosensors with ultrasensitive temporal and spatial resolution, real-time responses of a single photosystem I-light harvesting complex I (PSI-LHCI) supercomplex of Pisum sativum to various conditions, including gradient variations in temperature, illumination, and electric field, are recorded. Under different temperatures, there is a bi-state switch process associated with the intrinsic thermal vibration behavior. When the variations of illumination and the bias voltage are applied, two additional shoulder states, probably derived from the self-conformational adjustment, are observed. Based on real-time monitoring of the dynamic processes of the PSI-LHCI supercomplex under various conditions, it is successively testified to promising nanotechnology for protein profiling and biological functional integration in photosynthesis studies.

Resolving conformational changes that mediate a two-step catalytic mechanism in a model enzyme

Enzymes catalyze biochemical reactions through precise positioning of substrates, cofactors, and amino acids to modulate the transition-state free energy. However, the role of conformational dynamics remains poorly understood due to lack of experimental access. This shortcoming is evident with E. coli dihydrofolate reductase (DHFR), a model system for the role of protein dynamics in catalysis, for which it is unknown how the enzyme regulates the different active site environments required to facilitate proton and hydride transfer. Here, we present ligand-, temperature-, and electric-field-based perturbations during X-ray diffraction experiments that enable identification of coupled conformational changes in DHFR. We identify a global hinge motion and local networks of structural rearrangements that are engaged by substrate protonation to regulate solvent access and promote efficient catalysis. The resulting mechanism shows that DHFR's two-step catalytic mechanism is guided by a dynamic free energy landscape responsive to the state of the substrate.

Emerging Time-Resolved X-Ray Diffraction Approaches for Protein Dynamics

Proteins guide the flows of information, energy, and matter that make life possible by accelerating transport and chemical reactions, by allosterically modulating these reactions, and by forming dynamic supramolecular assemblies. In these roles, conformational change underlies functional transitions. Time-resolved X-ray diffraction methods characterize these transitions either by directly triggering sequences of functionally important motions or, more broadly, by capturing the motions of which proteins are capable. To date, most successful have been experiments in which conformational change is triggered in light-dependent proteins. In this review, I emphasize emerging techniques that probe the dynamic basis of function in proteins lacking natively light-dependent transitions and speculate about extensions and further possibilities. In addition, I review how the weaker and more distributed signals in these data push the limits of the capabilities of analytical methods. Taken together, these new methods are beginning to establish a powerful paradigm for the study of the physics of protein function.

Electrically stimulated gene expression under exogenously applied electric fields

Introduction: Electrical stimulation, the application of an electric field to cells and tissues grown in culture to accelerate growth and tight junction formation among endothelial cells, could be impactful in cardiovascular tissue engineering, allotransplantation, and wound healing. Methods: Using Electrical Cell Stimulation And Recording Apparatus (ECSARA), the exploration of the stimulatory influences of electric fields of different magnitude and frequencies on growth and proliferation, trans endothelial electrical resistance (TEER) and gene expression of human endothelia cells (HUVECs) were explored. Results: Within the range of endogenous electrical pulses studied, frequency was found to be more significant (p = 0.05) than voltage in influencing HUVEC gene expression. Localization of Yes Associated Protein (YAP) and expression of CD-144 are shown to be consistent with temporal manifestations of TEER. Discussion: This work introduces the field of electromics, the study of cellular gene expression profiles and their implications under the influence of exogenously applied electric fields. Homology of electrobiology and mechanobiology suggests use of such exogenous cues in tissue and regenerative engineering.

Capturing the Polarization Response of Solvated Proteins under Constant Electric Fields in Molecular Dynamics Simulations

We capture and compare the polarization response of a solvated globular protein ubiquitin to static electric (E-fields) using atomistic molecular dynamics simulations. We collectively follow E-field induced changes, electrical and structural, occurring across multiple trajectories using the magnitude of the protein dipole vector (P_p ). E-fields antiparallel to P_p induce faster structural changes and more facile protein unfolding relative to parallel fields of the same strength. While weak E-fields (0.1-0.5 V/nm) do not unfold ubiquitin and produce a reversible polarization, strong E-fields (1-2 V/nm) unfold the protein through a pathway wherein the helix:β-strand interactions rupture before those for the β1-β5 clamp. Independent of E-field direction, high E-field induced structural changes are also reversible if the field is switched off before P_p exceeds 2 times its equilibrium value. We critically examine the dependence of water properties, protein rotational diffusion and E-field induced protein unfolding pathways on the thermostat/barostat parameters used in our simulations.

Electro-detachment of kinesin motor domain from microtubule in silico

Kinesin is a motor protein essential in cellular functions, such as intracellular transport and cell-division, as well as for enabling nanoscopic transport in bio-nanotechnology. Therefore, for effective control of function for nanotechnological applications, it is important to be able to modify the function of kinesin. To circumvent the limitations of chemical modifications, here we identify another potential approach for kinesin control: the use of electric forces. Using full-atom molecular dynamics simulations (247,358 atoms, total time ∼ 4.4 μs), we demonstrate, for the first time, that the kinesin-1 motor domain can be detached from a microtubule by an intense electric field within the nanosecond timescale. We show that this effect is field-direction dependent and field-strength dependent. A detailed analysis of the electric forces and the work carried out by electric field acting on the microtubule-kinesin system shows that it is the combined action of the electric field pulling on the β-tubulin C-terminus and the electric-field-induced torque on the kinesin dipole moment that causes kinesin detachment from the microtubule. It is shown, for the first time in a mechanistic manner, that an electric field can dramatically affect molecular interactions in a heterologous functional protein assembly. Our results contribute to understanding of electromagnetic field-biomatter interactions on a molecular level, with potential biomedical and bio-nanotechnological applications for harnessing control of protein nanomotors.

High sensitivity CIP2A detection for oral cancer using a rapid transistor-based biosensor module

Oral squamous cell carcinoma (OSCC) is one of the most common lip and oral cavity cancer types. It requires early detection via various medical technologies to improve the survival rate. While most detection techniques for OSCC require testing in a centralized lab to confirm cancer type, a point of care detection technique is preferred for on-site use and quick result readout. The modular biological sensor utilizing transistor-based technology has been leveraged for testing CIP2A, and optimal transistor gate voltage and load resistance for sensing setup was investigated. Sensitivities of 1 × 10-15 g/ml have been obtained for both detections of pure CIP2A protein and HeLa cell lysate using identical test conditions via serial dilution. The superior time-saving and high accuracy testing provides opportunities for rapid clinical diagnosis in the medical space.

A unifying Bayesian framework for merging X-ray diffraction data

Novel X-ray methods are transforming the study of the functional dynamics of biomolecules. Key to this revolution is detection of often subtle conformational changes from diffraction data. Diffraction data contain patterns of bright spots known as reflections. To compute the electron density of a molecule, the intensity of each reflection must be estimated, and redundant observations reduced to consensus intensities. Systematic effects, however, lead to the measurement of equivalent reflections on different scales, corrupting observation of changes in electron density. Here, we present a modern Bayesian solution to this problem, which uses deep learning and variational inference to simultaneously rescale and merge reflection observations. We successfully apply this method to monochromatic and polychromatic single-crystal diffraction data, as well as serial femtosecond crystallography data. We find that this approach is applicable to the analysis of many types of diffraction experiments, while accurately and sensitively detecting subtle dynamics and anomalous scattering.

Light-induced reversible reorganizations in closed Type II reaction centre complexes: physiological roles and physical mechanisms

The purpose of this review is to outline our understanding of the nature, mechanism and physiological significance of light-induced reversible reorganizations in closed Type II reaction centre (RC) complexes. In the so-called 'closed' state, purple bacterial RC (bRC) and photosystem II (PSII) RC complexes are incapable of generating additional stable charge separation. Yet, upon continued excitation they display well-discernible changes in their photophysical and photochemical parameters. Substantial stabilization of their charge-separated states has been thoroughly documented-uncovering light-induced reorganizations in closed RCs and revealing their physiological importance in gradually optimizing the operation of the photosynthetic machinery during the dark-to-light transition. A range of subtle light-induced conformational changes has indeed been detected experimentally in different laboratories using different bRC and PSII-containing preparations. In general, the presently available data strongly suggest similar structural dynamics of closed bRC and PSII RC complexes, and similar physical mechanisms, in which dielectric relaxation processes and structural memory effects of proteins are proposed to play important roles.