Protein Allostery and Conformational Dynamics

RNA's Dynamic Conformational Selection and Entropic Allosteric Mechanism in Controlling Cascade Protein Binding Events

In the TAR RNA of immunodeficiency viruses, an allosteric communication exists between a distant loop and a bulge. The bulge interacts with the TAT protein vital for transactivating viral RNA, while the loop interacts with cyclin-T1, contingent on TAT binding. Through extensive atomistic and free energy simulations, we investigate TAR-TAT binding in nonpathogenic bovine immunodeficiency virus (BIV) and pathogenic human immunodeficiency virus (HIV). Thermodynamic analysis reveals enthalpically driven binding in BIV and entropically favored binding in HIV. The broader global basin in HIV is attributed to binding-induced loop fluctuation, corroborated by nuclear magnetic resonance (NMR), indicating classical entropic allostery onset. While this loop fluctuation affects the TAT binding affinity, it generates a binding-competent conformation that aids subsequent effector (cyclin-T1) binding. This study underscores how two structurally similar apo-RNA scaffolds adopt distinct conformational selection mechanisms to drive enthalpic and entropic allostery, influencing protein affinity in the signaling cascade.

Superb Silk Hydrogels with High Adaptability, Bioactivity, and Versatility Enabled by Photo-Cross-Linking

The exceptional biocompatibility and adaptability of hydrogels have garnered significant interest in the biomedical field for the fabrication of biomedical devices. However, conventional synthetic hydrogels still exhibit relatively weak and fragile properties. Drawing inspiration from the photosynthesis process, we developed a facile approach to achieve a harmonious combination of superior mechanical properties and efficient preparation of silk fibroin hydrogel through photo-cross-linking technology, accomplished within 60 s. The utilization of riboflavin and H2O2 enabled a sustainable cyclic photo-cross-linking reaction, facilitating the transformation from tyrosine to dityrosine and ultimately contributing to the formation of highly cross-linked hydrogels. These photo-cross-linking hydrogels exhibited excellent elasticity and restorability even after undergoing 1000 cycles of compression. Importantly, our findings presented that hydrogel-encapsulated adipose stem cells possess the ability to stimulate cell proliferation along with stem cell stemness. This was evidenced by the continuous high expression levels of OCT4 and SOX2 over 21 days. Additionally, the utilization of photo-cross-linking hydrogels can be extended to various material molding platforms, including microneedles, microcarriers, and bone screws. Consequently, this study offered a significant approach to fabricating biomedical hydrogels capable of facilitating real-time cell delivery, thereby introducing an innovative avenue for designing silk devices with exceptional machinability and adaptability in biomedical applications.

Comparison of methods for the NMR measurement of motionally averaged dipolar couplings

Motionally averaged dipolar couplings are an important tool for understanding the complex dynamics of catalysts, polymers, and biomolecules. While there is a plethora of solid-state NMR pulse sequences available for their measurement, in can be difficult to gauge the methods' strengths and weaknesses. In particular, there has not been a comprehensive comparison of their performance in natural abundance samples, where 1H homonuclear dipolar couplings are important and the use of large MAS rotors may be required for sensitivity reasons. In this work, we directly compared some of the more common methods for measuring C-H dipolar couplings in natural abundance samples using L-alanine (L-Ala) and the N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLF) tripeptide as model systems. We evaluated their performance in terms of accuracy, resolution, sensitivity, and ease of implementation. We found that, despite the presence of 1H homonuclear dipolar interactions, all methods, with the exception of REDOR, were able to yield the reasonable dipolar coupling strengths for both mobile and static moieties. Of these methods, PDLF provides the most convenient workflow and precision at the expense of low sensitivity. In low-sensitivity cases, MAS-PISEMA and DIPSHIFT appear to be the better options.

A parameterized two-domain thermodynamic model explains diverse mutational effects on protein allostery

New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multi-domain allosteric proteins.

Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network

Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states of TAK1, differing just by the presence or absence of its allosteric activator TAB1, from an ensemble mixture of conformations (obtained from 2.4 μs molecular dynamics (MD) simulations). The novelty, however, lies in understanding the deeper algorithmic potentials to systematically derive a diverse set of differential residue connectivity features that reconstruct the essential mechanistic architecture for TAK1-TAB1 allostery in such a close-to-active biochemical scenario. While the recursive, random forest-based workflow displays the potential of conducting discretized, hierarchical derivation of allosteric features, a multilayer perceptron-based approach gains considerable efficacy in revealing fluid connected patterns of features when hybridized with mutual information scoring. Interestingly, both pipelines benchmark similar directions of functional conformational changes for TAK1's activation. The findings significantly advance the depth of mechanistic understanding by highlighting crucial activation signatures along a directed C-lobe → activation loop → ATP pocket channel of information flow, including (1) the αF-αE biterminal alignments and (2) the "catalytic" drift of the activation loop toward kinase active site. Besides, some novel allosteric hotspots (K253, Y206, N189, etc.) are further recognized as TAB1 sensors, transducers, and responders, including a benchmark E70 mutation site, precisely mapping the important structural segments for sequential allosteric execution. Hence, our work demonstrates how to navigate through greater structural depths and dimensions of dynamic allosteric machineries just by leveraging standard ML methods in suitable streamlined workflows adaptive to the specific system and objectives.

Probing allosteric communication with combined molecular dynamics simulations and network analysis

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Cryo-EM and Molecular Dynamics Simulations Reveal Hidden Conformational Dynamics Controlling Ammonia Transport in Human Asparagine Synthetase

How motions in enzymes might be linked to catalytic function is of considerable general interest. Recent advances in X-ray crystallography and cryogenic electron microscopy offer the promise of elucidating functionally relevant motions in proteins that are not easily amenable to study by other biophysical methods. Here we use 3D variability analysis (3DVA) on cryo-EM maps for wild type (WT) human asparagine synthetase (ASNS) and the R142I ASNS variant to identify conformational changes in the Arg-142 side chain, which mediates the formation of a catalytically relevant intramolecular tunnel. Our 3DVA results for WT ASNS are consistent with independent molecular dynamics (MD) simulations on a model generated from the X-ray structure of human ASNS. Moreover, MD simulations of computational models for the ASNS/β-aspartyl-AMP/MgPPi and R142I/β-aspartyl-AMP/MgPPi ternary complexes, suggest that the structural integrity of the tunnel is impaired in the R142I variant when β-aspartyl-AMP is present in the synthetase active site. The kinetic properties of the R142I ASNS variant support the proposed function of Arg-142. These studies illustrate the power of cryo-EM to identify localized motions and dissect the conformational landscape of large proteins. When combined with MD simulations, 3DVA is a powerful approach to understanding how conformational dynamics might regulate function in multi-domain enzymes possessing multiple active sites.

Dynamics-driven allosteric stimulation of diguanylate cyclase activity in a red light-regulated phytochrome

Sensor-effector proteins integrate information from different stimuli and transform this into cellular responses. Some sensory domains, like red-light responsive bacteriophytochromes, show remarkable modularity regulating a variety of effectors. One effector domain is the GGDEF diguanylate cyclase catalyzing the formation of the bacterial second messenger cyclic-dimeric-guanosine monophosphate. While critical signal integration elements have been described for different phytochromes, a generalized understanding of signal processing and communication over large distances, roughly 100 Å in phytochrome diguanylate cyclases, is missing. Here we show that dynamics-driven allostery is key to understanding signal integration on a molecular level. We generated protein variants stabilized in their far-red-absorbing Pfr state and demonstrated by analysis of conformational dynamics using hydrogen-deuterium exchange coupled to mass spectrometry that single amino acid replacements are accompanied by altered dynamics of functional elements throughout the protein. We show that the conformational dynamics correlate with the enzymatic activity of these variants, explaining also the increased activity of a non-photochromic variant. In addition, we demonstrate the functional importance of mixed Pfr/intermediate state dimers using a fast-reverting variant that still enables wild-type-like fold-changes of enzymatic stimulation by red light. This supports the functional role of single protomer activation in phytochromes, a property that might correlate with the non-canonical mixed Pfr/intermediate-state spectra observed for many phytochrome systems. We anticipate our results to stimulate research in the direction of dynamics-driven allosteric regulation of different bacteriophytochrome-based sensor-effectors. This will eventually impact design strategies for the creation of novel sensor-effector systems for enriching the optogenetic toolbox.

Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins

An explicit analytic solution is given for the Langevin equation applied to the Gaussian Network Model of a protein subjected to both a random and a deterministic periodic force. Synchronous and asynchronous components of time correlation functions are derived and an expression for phase differences in the time correlations of residue pairs is obtained. The synchronous component enables the determination of dynamic communities within the protein structure. The asynchronous component reveals causality, where the time correlation function between residues i and j differs depending on whether i is observed before j or vice versa, resulting in directional information flow. Driver and driven residues in the allosteric process of cyclophilin A and human NAD-dependent isocitrate dehydrogenase are determined by a perturbation-scanning technique. Factors affecting phase differences between fluctuations of residues, such as network topology, connectivity, and residue centrality, are identified. Within the constraints of the isotropic Gaussian Network Model, our results show that asynchronicity increases with viscosity and distance between residues, decreases with increasing connectivity, and decreases with increasing levels of eigenvector centrality.

Aggregation Inducing Reversible Conformational Isomerization of Surface Staple in Au18SR14 Nanoclusters

The conformation of molecules and materials is crucial in determining their properties and applications. Here, this work explores the reversible transformation between two distinct conformational isomers in metal nanoclusters. This work demonstrates the successful manipulation of a controllable and reversible isomerization of Au18SR14 within an aqueous solution through two distinct methods: ethanol addition and pH adjustment. The initial driver is the alteration of the solution environment, leading to the aggregation of Au18SR14 protected by ligands with smaller steric hindrance. At the atomic level, the folding mode of the unique Au4SR5 staple underpins the observed structural transformation. The reversal of staple conformation leads to color shifting between green and orange-red, and tailors a second emission peak at 725 nm originating from charge transfer from the thiolate to the Au9 core. This work not only deepens the understanding of the surface structure and dual-emission of metal nanoparticles, but also enhances the comprehension of their isomerization.

Photoswitchable Cascades for Allosteric and Bidirectional Control over Covalent Bonds and Assemblies

Studies of complex systems and emerging properties to mimic biosystems are at the forefront of chemical research. Dynamic multistep cascades, especially those exhibiting allosteric regulation, are challenging. Herein, we demonstrate a versatile platform of photoswitchable covalent cascades toward remote and bidirectional control of reversible covalent bonds and ensuing assemblies. The relay of a photochromic switch, keto-enol equilibrium, and ring-chain equilibrium allows light-mediated reversible allosteric structural changes. The accompanying distinct reactivity further enables photoswitchable dynamic covalent bonding and release of substrates bidirectionally through alternating two wavelengths of light, essentially realizing light-mediated signaling cycles. The downfall of energy by covalent bond formation/scission upon photochemical reactions offers the driving force for the controlled direction of the cascade. To show the molecular diversity, photoswitchable on-demand assembly/disassembly of covalent polymers, including structurally reconfigurable polymers, was realized. This work achieves photoswitchable allosteric regulation of covalent architectures within dynamic multistep cascades, which has rarely been reported before. The results resemble allosteric control within biological signaling networks and should set the stage for many endeavors, such as dynamic assemblies, molecular motors, responsive polymers, and intelligent materials.

Four Parallel Pathways in T4 Ligase-Catalyzed Repair of Nicked DNA with Diverse Bending Angles

The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase-AMP complex and the ligase-AMP-DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase-AMP complex that persist in the ligase-AMP-DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Machine learning approaches in predicting allosteric sites

Allosteric regulation is a fundamental biological mechanism that can control critical cellular processes via allosteric modulator binding to protein distal functional sites. The advantages of allosteric modulators over orthosteric ones have sparked the development of numerous computational approaches, such as the identification of allosteric binding sites, to facilitate allosteric drug discovery. Building on the success of machine learning (ML) models for solving complex problems in biology and chemistry, several ML models for predicting allosteric sites have been developed. In this review, we provide an overview of these models and discuss future perspectives powered by the field of artificial intelligence such as protein language models.

ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

Comparative methods in molecular evolution and structural biology rely heavily upon the site-wise analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from nanoscale nonrandom machine-like motions induced by evolutionarily conserved molecular interactions. Comparisons of molecular dynamics (MD) simulations conducted between homologous sites representative of different functional or mutational states can potentially identify local effects on binding interaction and protein evolution. In addition, comparisons of different (i.e., nonhomologous) sites within MD simulations could be employed to identify functional shifts in local time-coordinated dynamics indicative of logic gating within proteins. However, comparative MD analysis is challenged by the large fraction of protein motion caused by random thermal noise in the surrounding solvent. Therefore, properly denoised MD comparisons could reveal functional sites involving these machine-like dynamics with good accuracy. Here, we introduce ATOMDANCE, a user-interfaced suite of comparative machine learning-based denoising tools designed for identifying functional sites and the patterns of coordinated motion they can create within MD simulations. ATOMDANCE-maxDemon4.0 employs Gaussian kernel functions to compute site-wise maximum mean discrepancy between learned features of motion, thereby assessing denoised differences in the nonrandom motions between functional or evolutionary states (e.g., ligand bound versus unbound, wild-type versus mutant). ATOMDANCE-maxDemon4.0 also employs maximum mean discrepancy to analyze potential random amino acid replacements allowing for a site-wise test of neutral versus nonneutral evolution on the divergence of dynamic function in protein homologs. Finally, ATOMDANCE-Choreograph2.0 employs mixed-model analysis of variance and graph network to detect regions where time-synchronized shifts in dynamics occur. Here, we demonstrate ATOMDANCE's utility for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small-molecule drugs, and virus-host recognition, as well as understanding shifts in global and local site coordination occurring during allosteric activation of a pathogenic protease.

High-fidelity, hyper-accurate, and evolved mutants rewire atomic-level communication in CRISPR-Cas9

The high-fidelity (HF1), hyper-accurate (Hypa), and evolved (Evo) variants of the CRISPR-associated protein 9 (Cas9) endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in recognition subdomain 3 (Rec3) mediate specificity in these variants are poorly understood. Here, solution nuclear magnetic resonance and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic His-Asn-His (HNH) domain. The variants remodel the communication sourcing from the Rec3 α helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

MD simulations indicate Omicron P132H of SARS-CoV-2 Mpro is a potential allosteric mutant involved in modulating the dynamics of catalytic site entry loop

The SARS-CoV-2 main protease Mpro, essential for viral replication is an important drug target. It plays a critical role in processing viral polyproteins necessary for viral replication assembly. One of the predominant SARS-CoV-2 Mpro mutations of Omicron variant is Pro132His. Structurally, this mutation site is located ∼22 Å away from the catalytic site. The solved crystal structure of this mutant in complex with inhibitors as well as its reported catalytic efficiency did not show any difference with respect to the wild type. Thus, the mutation was concluded to be non-allosteric. Based on microsecond long MD simulation of the Pro132His mutant and wild type, we show that Pro132His mutation affects the conformational equilibrium with more population of conformational substates having open catalytic site, modulated by the dynamics of the catalytic site entry loop, implying the allosteric nature of this mutation. The structural analysis indicates that rearrangement of hydrogen bonds between His132 and adjacent residues enhances the dynamics of the linker, which in turn is augmented by the inherent dynamic flexibility of the catalytic pocket entry site due to the presence of charged residues. The altered dynamics leading to loss of secondary structures corroborate well with the reported compromised thermal stability.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery

New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multidomain allosteric proteins.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

The shortest path method (SPM) webserver for computational enzyme design

SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme structure and dynamics. The server is built on top of the DynaComm.py code and enables the calculation and visualization of the SPM pathways. SPMweb is easy-to-use as it only requires three input files: the three-dimensional structure of the protein of interest, and the two matrices (distance and correlation) previously computed from a Molecular Dynamics simulation. We provide in this publication information on how to generate the files for SPM construction even for non-expert users and discuss the most relevant parameters that can be modified. The tool is extremely fast (it takes less than one minute per job), thus allowing the rapid identification of distal positions connected to the active site pocket of the enzyme. SPM applications expand from computational enzyme design, especially if combined with other tools to identify the preferred substitution at the identified position, but also to rationalizing allosteric regulation, and even cryptic pocket identification for drug discovery. The simple user interface and setup make the SPM tool accessible to the whole scientific community. SPMweb is freely available for academia at http://spmosuna.com/.

Unveiling the RNA-mediated allosteric activation discloses functional hotspots in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. It utilizes a CRISPR RNA (crRNA) to target RNA sequences and trigger a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) domains, cleaving any solvent-exposed RNA. In this system, an intriguing form of allosteric communication controls the RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory to decipher this intricate activation mechanism. We show that the binding of a target RNA acts as an allosteric effector, by amplifying the communication signals over the dynamical noise through interactions of the crRNA at the buried HEPN1-2 interface. By introducing a novel Signal-to-Noise Ratio (SNR) of communication efficiency, we reveal critical allosteric residues-R377, N378, and R973-that rearrange their interactions upon target RNA binding. Alanine mutation of these residues is shown to select target RNA over an extended complementary sequence beyond guide-target duplex for RNA cleavage, establishing the functional significance of these hotspots. Collectively our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of highly selective RNA-based cleavage and detection tools.

Transient Structural Dynamics of Glycogen Phosphorylase from Nonequilibrium Hydrogen/Deuterium-Exchange Mass Spectrometry

It remains a major challenge to ascertain the specific structurally dynamic changes that underpin protein functional switching. There is a growing need in molecular biology and drug discovery to complement structural models with the ability to determine the dynamic structural changes that occur as these proteins are regulated and function. The archetypal allosteric enzyme glycogen phosphorylase is a clinical target of great interest to treat type II diabetes and metastatic cancers. Here, we developed a time-resolved nonequilibrium millisecond hydrogen/deuterium-exchange mass spectrometry (HDX-MS) approach capable of precisely locating dynamic structural changes during allosteric activation and inhibition of glycogen phosphorylase. We resolved obligate transient changes in the localized structure that are absent when directly comparing active/inactive states of the enzyme and show that they are common to allosteric activation by AMP and inhibition by caffeine, operating at different sites. This indicates that opposing allosteric regulation by inhibitor and activator ligands is mediated by pathways that intersect with a common structurally dynamic motif. This mass spectrometry approach uniquely stands to discover local transient structural dynamics and could be used broadly to identify features that influence the structural transitions of proteins.

Understanding the intricacy of protein in hydrated deep eutectic solvent: Solvation dynamics, conformational fluctuation dynamics, and stability

Deep eutectic solvents (DESs) are potential biocatalytic media due to their easy preparation, fine-tuneability, biocompatibility, and most importantly, due to their ability to keep protein stable and active. However, there are many unanswered questions and gaps in our knowledge about how proteins behave in these alternate media. Herein, we investigated solvation dynamics, conformational fluctuation dynamics, and stability of human serum albumin (HSA) in 0.5 Acetamide/0.3 Urea/0.2 Sorbitol (0.5Ac/0.3Ur/0.2Sor) DES of varying concentrations to understand the intricacy of protein behaviour in DES. Our result revealed a gradual decrease in the side-chain flexibility and thermal stability of HSA beyond 30 % DES. On the other hand, the associated water dynamics around domain-I of HSA decelerate only marginally with increasing DES content, although viscosity rises considerably. We propose that even though macroscopic solvent properties are altered, a protein feels only an aqueous type of environment in the presence of DES. This is probably the first experimental study to delineate the role of the associated water structure of the enzyme for maintaining its stability inside DES. Although considerable effort is necessary to generalize such claims, it might serve as the basis for understanding why proteins remain stable and active in DES.

Stimulus-Induced Relief of Intentionally Incorporated Frustration Drives Refolding of a Water-Soluble Biomimetic Foldamer

Frustrated, or nonoptimal, interactions have been proposed to be essential to a protein's ability to display responsive behavior such as allostery, conformational signaling, and signal transduction. However, the intentional incorporation of frustrated noncovalent interactions has not been explored as a design element in the field of dynamic foldamers. Here, we report the design, synthesis, characterization, and molecular dynamics simulations of the first dynamic water-soluble foldamer that, in response to a stimulus, exploits relief of frustration in its noncovalent network to structurally rearrange from a pleated to an intercalated columnar structure. Thus, relief of frustration provides the energetic driving force for structural rearrangement. This work represents a previously unexplored design element for the development of stimulus-responsive systems that has potential application to materials chemistry, synthetic biology, and molecular machines.

Genetic switching by the Lac repressor is based on two-state Monod-Wyman-Changeux allostery

High-resolution NMR spectroscopy enabled us to characterize allosteric transitions between various functional states of the dimeric Escherichia coli Lac repressor. In the absence of ligands, the dimer exists in a dynamic equilibrium between DNA-bound and inducer-bound conformations. Binding of either effector shifts this equilibrium toward either bound state. Analysis of the ternary complex between repressor, operator DNA, and inducer shows how adding the inducer results in allosteric changes that disrupt the interdomain contacts between the inducer binding and DNA binding domains and how this in turn leads to destabilization of the hinge helices and release of the Lac repressor from the operator. Based on our data, the allosteric mechanism of the induction process is in full agreement with the well-known Monod-Wyman-Changeux model.

Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches

BACKGROUND

Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear.

RESULTS

This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin.

CONCLUSION

Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.

Exploring the "misfolding problem" by systematic discovery and analysis of functional-but-degraded proteins

In both health and disease, the ubiquitin-proteasome system (UPS) degrades point mutants that retain partial function but have decreased stability compared with their wild-type counterparts. This class of UPS substrate includes routine translational errors and numerous human disease alleles, such as the most common cause of cystic fibrosis, ΔF508-CFTR. Yet, there is no systematic way to discover novel examples of these "minimally misfolded" substrates. To address that shortcoming, we designed a genetic screen to isolate functional-but-degraded point mutants, and we used the screen to study soluble, monomeric proteins with known structures. These simple parent proteins yielded diverse substrates, allowing us to investigate the structural features, cytotoxicity, and small-molecule regulation of minimal misfolding. Our screen can support numerous lines of inquiry, and it provides broad access to a class of poorly understood but biomedically critical quality-control substrates.

All over or overall - Do we understand allostery?

Allostery is probably the most important concept in the regulation of cellular processes. Models to explain allostery are plenty. Each sheds light on different aspects but their entirety conveys an ambiguous feeling of comprehension and disappointment. Here, I discuss the most popular allostery models, their roots, similarities, and limitations. All of them are thermodynamic models. Naturally this bears a certain degree of redundancy, which forms the center of this review. After sixty years, many questions remain unanswered, mainly because our human longing for causality as base for understanding is not satisfied by thermodynamics alone. A description of allostery in terms of pathways, i.e., as a temporal chain of events, has been-, and still is-, a missing piece of the puzzle.

The impact of aggregation of AIE and ACQ moiety-integrating material on the excited state dynamics

The investigation of the properties of aggregate materials is highly interesting because the process of aggregation can result in the disappearance of original properties and the emergence of new ones. Here, a novel fluorescent material (TPEIP), which synergistically combines aggregation-induced emission (AIE) and aggregation caused quenching (ACQ) moieties, was first synthesized by the cyclization reaction of 2,3-diamino-phenazine with 4-tetraphenylenthenealdehyde. We controlled the degree of aggregation of TPEIP to shed light on the impact of the aggregation on the excited state dynamics. TPEIP aggregation realized control over the Intersystem Crossing (ISC) rates and, in turn, the suppression of triplet excited states in MeOH, EtOH or via the simple addition of water to TPEIP solutions in DMSO. From global target analysis, the time scale was 966.2 ps for ISC for TPEIP in DMSO, but it was 860 ps in the case of TPEIP solutions featuring 5% water. The dynamics of TPEIP excited states undergo significant changes as the degree of aggregation increases. Notably, the lifetime of singlet excited states decreases, and there was a gradual diminishment in triplet states.

Allosteric regulation of kinase activity in living cells

The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities, making it difficult to specifically target one kinase, and allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss the methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or 'sensors,' are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.

Conformational Switch of the 250s Loop Enables the Efficient Transglycosylation in GH Family 77

Amylomaltases (AMs) play important roles in glycogen and maltose metabolism. However, the molecular mechanism is elusive. Here, we investigated the conformational dynamics of the 250s loop and catalytic mechanism of Thermus aquaticus TaAM using path-metadynamics and QM/MM MD simulations. The results demonstrate that the transition of the 250s loop from an open to closed conformation promotes polysaccharide sliding, leading to the ideal positioning of the acid/base. Furthermore, the conformational dynamics can also modulate the selectivity of hydrolysis and transglycosylation. The closed conformation of the 250s loop enables the tight packing of the active site for transglycosylation, reducing the energy penalty and efficiently preventing the penetration of water into the active site. Conversely, the partially closed conformation for hydrolysis results in a loosely packed active site, destabilizing the transition state. These computational findings guide mutation experiments and enable the identification of mutants with an improved disproportionation/hydrolysis ratio. The present mechanism is in line with experimental data, highlighting the critical role of conformational dynamics in regulating the catalytic reactivity of GHs.

Allosteric regulation of kinase activity in living cells

The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities making it difficult to specifically target one kinase, allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or "sensors" are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.

Deciphering Evolutionary Trajectories of Lactate Dehydrogenases Provides New Insights into Allostery

Lactate dehydrogenase (LDH, EC.1.1.127) is an important enzyme engaged in the anaerobic metabolism of cells, catalyzing the conversion of pyruvate to lactate and NADH to NAD+. LDH is a relevant enzyme to investigate structure-function relationships. The present work provides the missing link in our understanding of the evolution of LDHs. This allows to explain (i) the various evolutionary origins of LDHs in eukaryotic cells and their further diversification and (ii) subtle phenotypic modifications with respect to their regulation capacity. We identified a group of cyanobacterial LDHs displaying eukaryotic-like LDH sequence features. The biochemical and structural characterization of Cyanobacterium aponinum LDH, taken as representative, unexpectedly revealed that it displays homotropic and heterotropic activation, typical of an allosteric enzyme, whereas it harbors a long N-terminal extension, a structural feature considered responsible for the lack of allosteric capacity in eukaryotic LDHs. Its crystallographic structure was solved in 2 different configurations typical of the R-active and T-inactive states encountered in allosteric LDHs. Structural comparisons coupled with our evolutionary analyses helped to identify 2 amino acid positions that could have had a major role in the attenuation and extinction of the allosteric activation in eukaryotic LDHs rather than the presence of the N-terminal extension. We tested this hypothesis by site-directed mutagenesis. The resulting C. aponinum LDH mutants displayed reduced allosteric capacity mimicking those encountered in plants and human LDHs. This study provides a new evolutionary scenario of LDHs that unifies descriptions of regulatory properties with structural and mutational patterns of these important enzymes.

Dynamic allosteric networks drive adenosine A1 receptor activation and G-protein coupling

G-protein coupled receptors (GPCRs) present specific activation pathways and signaling among receptor subtypes. Hence, an extensive knowledge of the structural dynamics of the receptor is critical for the development of therapeutics. Here, we target the adenosine A1 receptor (A1R), for which a negligible number of drugs have been approved. We combine molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection to decipher the activation pathway of A1R, decode the allosteric networks and identify transient pockets. The A1R activation pathway reveal hidden intermediate and pre-active states together with the inactive and fully-active states observed experimentally. The protein energy networks computed throughout these conformational states successfully unravel the extra and intracellular allosteric centers and the communication pathways that couples them. We observe that the allosteric networks are dynamic, being increased along activation and fine-tuned in presence of the trimeric G-proteins. Overlap of transient pockets and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. By an in-depth analysis of the bridge between activation pathway, energy networks and transient pockets, we provide a further understanding of A1R. This information can be useful to ease the design of allosteric modulators for A1R.

High-Fidelity, Hyper-Accurate, and Evolved Mutants Rewire Atomic Level Communication in CRISPR-Cas9

The Cas9-HF1, HypaCas9, and evoCas9 variants of the Cas9 endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in the Rec3 domain mediate specificity in these variants are poorly understood. Here, solution NMR and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and peculiar dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic HNH domain. The variants remodel the communication sourcing from the Rec3 α-helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Allosteric control of olefin isomerization kinetics via remote metal binding and its mechanochemical analysis

Allosteric control of reaction thermodynamics is well understood, but the mechanisms by which changes in local geometries of receptor sites lower activation reaction barriers in electronically uncoupled, remote reaction moieties remain relatively unexplored. Here we report a molecular scaffold in which the rate of thermal E-to-Z isomerization of an alkene increases by a factor of as much as 104 in response to fast binding of a metal ion to a remote receptor site. A mechanochemical model of the olefin coupled to a compressive harmonic spring reproduces the observed acceleration quantitatively, adding the studied isomerization to the very few reactions demonstrated to be sensitive to extrinsic compressive force. The work validates experimentally the generalization of mechanochemical kinetics to compressive loads and demonstrates that the formalism of force-coupled reactivity offers a productive framework for the quantitative analysis of the molecular basis of allosteric control of reaction kinetics. Important differences in the effects of compressive vs. tensile force on the kinetic stabilities of molecules are discussed.

Loop dynamics and the evolution of enzyme activity

In the early 2000s, Tawfik presented his 'New View' on enzyme evolution, highlighting the role of conformational plasticity in expanding the functional diversity of limited repertoires of sequences. This view is gaining increasing traction with increasing evidence of the importance of conformational dynamics in both natural and laboratory evolution of enzymes. The past years have seen several elegant examples of harnessing conformational (particularly loop) dynamics to successfully manipulate protein function. This Review revisits flexible loops as critical participants in regulating enzyme activity. We showcase several systems of particular interest: triosephosphate isomerase barrel proteins, protein tyrosine phosphatases and β-lactamases, while briefly discussing other systems in which loop dynamics are important for selectivity and turnover. We then discuss the implications for engineering, presenting examples of successful loop manipulation in either improving catalytic efficiency, or changing selectivity completely. Overall, it is becoming clearer that mimicking nature by manipulating the conformational dynamics of key protein loops is a powerful method of tailoring enzyme activity, without needing to target active-site residues.

RNA-mediated Allosteric Activation in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. The protein uses a CRISPR RNA (crRNA) to target RNA sequences, which are cleaved by a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) catalytic domains. In this system, an intriguing form of allosteric communication controls RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory and RNA cleavage assays to decipher this activation mechanism. We show that the binding of a target RNA acts as an allosteric effector of the spatially distant HEPN catalytic cleft, by amplifying the allosteric signals over the dynamical noise, that passes through the buried HEPN interface. Critical residues in this region - N378, R973, and R377 - rearrange their interactions upon target RNA binding, and alter allosteric signalling. Alanine mutation of these residues is experimentally shown to select target RNA over an extended complementary sequence beyond guide-target duplex, for RNA cleavage. Altogether, our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of more selective RNA-based cleavage and detection tools.

Insight into the Nucleotide Based Modulation of the Grp94 Molecular Chaperone Using Multiscale Dynamics

Grp94, an ER-localized molecular chaperone, is required for the folding and activation of many membrane and secretory proteins. Client activation by Grp94 is mediated by nucleotide and conformational changes. In this work, we aim to understand how microscopic changes from nucleotide hydrolysis can potentiate large-scale conformational changes of Grp94. We performed all-atom molecular dynamics simulations on the ATP-hydrolysis competent state of the Grp94 dimer in four different nucleotide bound states. We found that Grp94 was the most rigid when ATP was bound. ATP hydrolysis or nucleotide removal enhanced mobility of the N-terminal domain and ATP lid, resulting in suppression of interdomain communication. In an asymmetric conformation with one hydrolyzed nucleotide, we identified a more compact state, similar to experimental observations. We also identified a potential regulatory role of the flexible linker, as it formed electrostatic interactions with the Grp94 M-domain helix near the region where BiP is known to bind. These studies were complemented with normal-mode analysis of an elastic network model to investigate Grp94's large-scale conformational changes. SPM analysis identified residues that are important in signaling conformational change, many of which have known functional relevance in ATP coordination and catalysis, client binding, and BiP binding. Our findings suggest that ATP hydrolysis in Grp94 alters allosteric wiring and facilitates conformational changes.

Disease mutations and phosphorylation alter the allosteric pathways involved in autoinhibition of protein phosphatase 2A

Mutations in protein phosphatase 2A (PP2A) are connected to intellectual disability and cancer. It has been hypothesized that these mutations might disrupt the autoinhibition and phosphorylation-induced activation of PP2A. Since they are located far from both the active and substrate binding sites, it is unclear how they exert their effect. We performed allosteric pathway analysis based on molecular dynamics simulations and combined it with biochemical experiments to investigate the autoinhibition of PP2A. In the wild type (WT), the C-arm of the regulatory subunit B56δ obstructs the active and substrate binding sites exerting a dual autoinhibition effect. We find that the disease mutant, E198K, severely weakens the allosteric pathways that stabilize the C-arm in the WT. Instead, the strongest allosteric pathways in E198K take a different route that promotes exposure of the substrate binding site. To facilitate the allosteric pathway analysis, we introduce a path clustering algorithm for lumping pathways into channels. We reveal remarkable similarities between the allosteric channels of E198K and those in phosphorylation-activated WT, suggesting that the autoinhibition can be alleviated through a conserved mechanism. In contrast, we find that another disease mutant, E200K, which is in spatial proximity of E198, does not repartition the allosteric pathways leading to the substrate binding site; however, it may still induce exposure of the active site. This finding agrees with our biochemical data, allowing us to predict the activity of PP2A with the phosphorylated B56δ and provide insight into how disease mutations in spatial proximity alter the enzymatic activity in surprisingly different mechanisms.

Machine Learning Generation of Dynamic Protein Conformational Ensembles

Machine learning has achieved remarkable success across a broad range of scientific and engineering disciplines, particularly its use for predicting native protein structures from sequence information alone. However, biomolecules are inherently dynamic, and there is a pressing need for accurate predictions of dynamic structural ensembles across multiple functional levels. These problems range from the relatively well-defined task of predicting conformational dynamics around the native state of a protein, which traditional molecular dynamics (MD) simulations are particularly adept at handling, to generating large-scale conformational transitions connecting distinct functional states of structured proteins or numerous marginally stable states within the dynamic ensembles of intrinsically disordered proteins. Machine learning has been increasingly applied to learn low-dimensional representations of protein conformational spaces, which can then be used to drive additional MD sampling or directly generate novel conformations. These methods promise to greatly reduce the computational cost of generating dynamic protein ensembles, compared to traditional MD simulations. In this review, we examine recent progress in machine learning approaches towards generative modeling of dynamic protein ensembles and emphasize the crucial importance of integrating advances in machine learning, structural data, and physical principles to achieve these ambitious goals.

Mechanism of Reduced Glutathione Induced Lysozyme Defolding and Molecular Self-Assembly

The distinctive assembly behaviors of lysozyme (Lys) feature prominently in food, materials, biomedicine, and other fields and have intrigued many scholars. Although our previous work suggested that reduced glutathione (GSH) could induce lysozyme to form interfacial films at the air/water interface, the underlying mechanism is still obscure. In the present study, the effects of GSH on the disulfide bond and protein conformation of lysozyme were investigated by fluorescence spectroscopy, circular dichroism spectroscopy, and infrared spectroscopy. The findings demonstrated that GSH was able to break the disulfide bond in lysozyme molecules through the sulfhydryl/disulfide bond exchange reaction, thereby unraveling the lysozyme. The β-sheet structure of lysozyme expanded significantly, while the contents of α-helix and β-turn decreased. Furthermore, the interfacial tension and morphology analysis supported that the unfolded lysozyme tended to arrange macroscopic interfacial films at the air/water interface. It was found that pH and GSH concentrations had an impact on the aforementioned processes, with higher pH or GSH levels having a positive effect. This paper on the exploration of the mechanism of GSH-induced lysozyme interface assembly and the development of lysozyme-based green coatings has better instructive significance.

Steric Communication between Dynamic Components on DNA Nanodevices

Biomolecular nanotechnology has helped emulate basic robotic capabilities such as defined motion, sensing, and actuation in synthetic nanoscale systems. DNA origami is an attractive approach for nanorobotics, as it enables creation of devices with complex geometry, programmed motion, rapid actuation, force application, and various kinds of sensing modalities. Advanced robotic functions like feedback control, autonomy, or programmed routines also require the ability to transmit signals among subcomponents. Prior work in DNA nanotechnology has established approaches for signal transmission, for example through diffusing strands or structurally coupled motions. However, soluble communication is often slow and structural coupling of motions can limit the function of individual components, for example to respond to the environment. Here, we introduce an approach inspired by protein allostery to transmit signals between two distal dynamic components through steric interactions. These components undergo separate thermal fluctuations where certain conformations of one arm will sterically occlude conformations of the distal arm. We implement this approach in a DNA origami device consisting of two stiff arms each connected to a base platform via a flexible hinge joint. We demonstrate the ability for one arm to sterically regulate both the range of motion and the conformational state (latched or freely fluctuating) of the distal arm, results that are quantitatively captured by mesoscopic simulations using experimentally informed energy landscapes for hinge-angle fluctuations. We further demonstrate the ability to modulate signal transmission by mechanically tuning the range of thermal fluctuations and controlling the conformational states of the arms. Our results establish a communication mechanism well-suited to transmit signals between thermally fluctuating dynamic components and provide a path to transmitting signals where the input is a dynamic response to parameters like force or solution conditions.

Biochemical methods to map and quantify allosteric motions in human glucokinase

Allosteric regulation of protein function is ubiquitous in biology. Allostery originates from ligand-mediated alterations in polypeptide structure and/or dynamics, which produce a cooperative kinetic or thermodynamic response to changing ligand concentrations. Establishing a mechanistic description of individual allosteric events requires both mapping the relevant changes in protein structure and quantifying the rates of differential conformational dynamics in the absence and presence of effectors. In this chapter, we describe three biochemical approaches to understand the dynamic and structural signatures of protein allostery using the well-established cooperative enzyme glucokinase as a case study. The combined application of pulsed proteolysis, biomolecular nuclear magnetic resonance spectroscopy and hydrogen-deuterium exchange mass spectrometry offers complementary information that can used to establish molecular models for allosteric proteins, especially when differential protein dynamics are involved.

Multi-state Model-Based Identification of Cryptic Allosteric Sites on Human Serotonin Transporter

Serotonin transporter (SERT) plays a fundamental role in taking the synaptic cleft serotonin back to the presynaptic neuron. The discovery of allosteric SERT modulators represents the next-generation medication for psychiatric disorders such as depression. Here, based on the cryo-EM structures of ibogaine in complex with SERT in distinct conformations, the multiple functional structures of the transporter bound to serotonin, including outward-open (OO_holo), outward-occluded (OC_holo), and inward-open (IO_holo and IO_holo'), were carefully characterized by induced-fit docking Gaussian-accelerated molecular dynamics (IFD-GaMD) simulation and the free-energy landscape analysis. Further MM/GBSA binding free energy, per-residue contribution, and molecular interaction fingerprint calculations revealed the interaction variations of serotonin with SERT in functional structures, which confirmed the allostery of SERT during serotonin reuptake. Moreover, five unique cryptic allosteric sites, which are druggable and capable of targeting by small molecules, were identified on the characterized multistate structures. These results provide structural and energetic information for the molecular mechanism of serotonin reuptake and will provide opportunities for the development of novel therapeutics based on the identified new allosteric sites on SERT.

Allosteric Regulation of Glycogen Phosphorylase by Order/Disorder Transition of the 250' and 280s Loops

Allostery is a fundamental mechanism of protein activation, yet the precise dynamic changes that underlie functional regulation of allosteric enzymes, such as glycogen phosphorylase (GlyP), remain poorly understood. Despite being the first allosteric enzyme described, its structural regulation is still a challenging problem: the key regulatory loops of the GlyP active site (250' and 280s) are weakly stable and often missing density or have large b-factors in structural models. This led to the longstanding hypothesis that GlyP regulation is achieved through gating of the active site by (dis)order transitions, as first proposed by Barford and Johnson. However, testing this requires a quantitative measurement of weakly stable local structure which, to date, has been technically challenging in such a large protein. Hydrogen-deuterium-exchange mass spectrometry (HDX-MS) is a powerful tool for studying protein dynamics, and millisecond HDX-MS has the ability to measure site-localized stability differences in weakly stable structures, making it particularly valuable for investigating allosteric regulation in GlyP. Here, we used millisecond HDX-MS to measure the local structural perturbations of glycogen phosphorylase b (GlyPb), the phosphorylated active form (GlyPa), and the inhibited glucose-6 phosphate complex (GlyPb:G6P) at near-amino acid resolution. Our results support the Barford and Johnson hypothesis for GlyP regulation by providing insight into the dynamic changes of the key regulatory loops.

Apparatus for Automated Continuous Hydrogen Deuterium Exchange Mass Spectrometry Measurements from Milliseconds to Hours

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a rapidly growing technique for protein characterization in industry and academia, complementing the "static" picture provided by classical structural biology with information about the dynamic structural changes that accompany biological function. Conventional hydrogen deuterium exchange experiments, carried out on commercially available systems, typically collect 4-5 exchange timepoints on a timescale ranging from tens of seconds to hours using a workflow that can require 24 h or more of continuous data collection for triplicate measurements. A small number of groups have developed setups for millisecond timescale HDX, allowing for the characterization of dynamic shifts in weakly structured or disordered regions of proteins. This capability is particularly important given the central role that weakly ordered protein regions often play in protein function and pathogenesis. In this work, we introduce a new continuous flow injection setup for time-resolved HDX-MS (CFI-TRESI-HDX) that allows automated, continuous or discrete labeling time measurements from milliseconds to hours. The device is composed almost entirely of "off-the-shelf" LC components and can acquire an essentially unlimited number of timepoints with substantially reduced runtimes compared to conventional systems.

Noncanonical electromechanical coupling paths in cardiac hERG potassium channel

Voltage-gated potassium channels are involved in many physiological processes such as nerve impulse transmission, the heartbeat, and muscle contraction. However, for many of them the molecular determinants of the gating mechanism remain elusive. Here, using a combination of theoretical and experimental approaches, we address this problem focusing on the cardiac hERG potassium channel. Network analysis of molecular dynamics trajectories reveals the presence of a kinematic chain of residues that couples the voltage sensor domain to the pore domain and involves the S4/S1 and S1/S5 subunit interfaces. Mutagenesis experiments confirm the role of these residues and interfaces in the activation and inactivation mechanisms. Our findings demonstrate the presence of an electromechanical transduction path crucial for the non-domain-swapped hERG channel gating that resembles the noncanonical path identified in domain-swapped K+ channels.