Solution NMR Spectroscopy for the Study of Enzyme Allostery

Illuminating Protein Allostery by Chemically Accurate Contact Response Analysis (ChACRA)

Decoding allostery at the atomic level is essential for understanding the relationship between a protein's sequence, structure, and dynamics. Recently, we have shown that decomposing temperature responses of inter-residue contacts can reveal allosteric couplings and provide useful insight into the functional dynamics of proteins. The details of this Chemically Accurate Contact Response Analysis (ChACRA) are presented here along with its application to two well-known allosteric proteins. The first protein, IGPS, is a model of ensemble allostery that lacks clear structural differences between the active and inactive states. We show that the application of ChACRA reveals the experimentally identified allosteric coupling between effector and active sites of IGPS. The second protein, ATCase, is a classic example of allostery with distinct active and inactive structural states. Using ChACRA, we directly identify the most significant residue level interactions underlying the enzyme's cooperative behavior. Both test cases demonstrate the utility of ChACRA's unsupervised machine learning approach for dissecting allostery at the residue level.

Fusion of two homoleptic truncated tetrahedra into a heteroleptic truncated octahedron

The exploration of novel structures and structural transformation of supramolecular assemblies is of vital importance for their functions and applications. Herein, based on coordination-driven self-assembly, we prepare a neutral truncated tetrahedron and a heteroleptic truncated octahedron, whose structures are unambiguously confirmed by X-ray diffraction analysis. More importantly, the truncated tetrahedron is quantitatively transformed into the truncated octahedron through its fusion with another cationic truncated tetrahedron, as evidenced by fluorescence, mass and NMR spectroscopy. This study not only deepens our understanding of the process of supramolecular fusion but also opens up possibilities for the subsequent preparation of advanced supramolecular assemblies with complex structures and integrated functions.

NMR and Single-Molecule FRET Insights into Fast Protein Motions and Their Relation to Function

Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.

Validating the 15N-1H HSQC-ROESY experiment for detecting 1HN exchange broadening in proteated proteins

It is advantageous to investigate milli-to-micro-second conformational exchange data contained in the solution NMR protein relaxation data other than 15N nuclei. Not only does one search under another lamp post, one also looks at dynamics at other time scales. The HSQC-ROESY 1HN relaxation dispersion experiment for amide protons as introduced by Ishima, et al (1998). J. Am. Soc. 120, 10534-10542, is such an experiment, but has by the authors been advised to only be used for perdeuterated proteins to avoid complication with the 1H-1H multiple-spin effects. This is regretful, since not all proteins can be perdeuterated. Here we analyze in detail the 1HN relaxation terms for this experiment for a fully proteated protein. Indeed, the 1HN relaxation theory is in this case complex and includes dipolar-dipolar relaxation interference and TOCSY transfers. With simulate both of these effects and show that the interference can be exploited for detecting exchange broadening. The TOCSY effect is shown to minor, and when it is not, a solution is provided. We apply the HSQC-ROESY experiment, with a small modification to suppress ROESY crosspeaks, to a 7 kDa GB1 protein that is just 15N and 13C labeled. At 10 °C we cannot detect any conformational exchange broadening: the 1HN R2 relaxation rates with 1.357 kHz spinlock field not larger than those recorded with a 12.136 kHz spinlock field. This means that there is no exchange broadening that can be differentially suppressed with the applied fields. Either there is no broadening, or the broadening is effectively suppressed by all fields, or the broadening cannot be suppressed by either of the fields. While initially this seems to be a disappointing result, we feel that this work establishes that the HSQC-ROESY experiment is very robust. It can indeed be utilized for proteated proteins upto about 30 kDa. This could be opening the study the milli-microsecond conformational dynamics as reported by 1HN exchange broadening for many more proteins.

Protein Allostery Study in Cells Using NMR Spectroscopy

Protein allostery is commonly observed in vitro. But how protein allostery behaves in cells is unknown. In this work, a protein monomer-dimer equilibrium system was built with the allosteric effect on the binding characterized using NMR spectroscopy through mutations away from the dimer interface. A chemical shift linear fitting method was developed that enabled us to accurately determine the dissociation constant. A total of 28 allosteric mutations were prepared and grouped to negative allosteric, nonallosteric, and positive allosteric modulators. ∼ 50% of mutations displayed the allosteric-state changes when moving from a buffered solution into cells. For example, there were no positive allosteric modulators in the buffered solution but eight in cells. The change in protein allostery is correlated with the interactions between the protein and the cellular environment. These interactions presumably drive the surrounding macromolecules in cells to transiently bind to the monomer and dimer mutational sites and change the free energies of the two species differently which generate new allosteric effects. These surrounding macromolecules create a new protein allostery pathway that is only present in cells.

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.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.

Temperature as a modulator of allosteric motions and crosstalk in mesophilic and thermophilic enzymes

Mesophilic and thermophilic enzyme counterparts are often studied to understand how proteins function under harsh conditions. To function well outside of standard temperature ranges, thermophiles often tightly regulate their structural ensemble through intra-protein communication (via allostery) and altered interactions with ligands. It has also become apparent in recent years that the enhancement or diminution of allosteric crosstalk can be temperature-dependent and distinguish thermophilic enzymes from their mesophilic paralogs. Since most studies of allostery utilize chemical modifications from pH, mutations, or ligands, the impact of temperature on allosteric function is comparatively understudied. Here, we discuss the biophysical methods, as well as critical case studies, that dissect temperature-dependent function of mesophilic-thermophilic enzyme pairs and their allosteric regulation across a range of temperatures.

Connected Component Analysis of Dynamical Perturbation Contact Networks

Describing protein dynamical networks through amino acid contacts is a powerful way to analyze complex biomolecular systems. However, due to the size of the systems, identifying the relevant features of protein-weighted graphs can be a difficult task. To address this issue, we present the connected component analysis (CCA) approach that allows for fast, robust, and unbiased analysis of dynamical perturbation contact networks (DPCNs). We first illustrate the CCA method as applied to a prototypical allosteric enzyme, the imidazoleglycerol phosphate synthase (IGPS) enzyme from Thermotoga maritima bacteria. This approach was shown to outperform the clustering methods applied to DPCNs, which could not capture the propagation of the allosteric signal within the protein graph. On the other hand, CCA reduced the DPCN size, providing connected components that nicely describe the allosteric propagation of the signal from the effector to the active sites of the protein. By applying the CCA to the IGPS enzyme in different conditions, i.e., at high temperature and from another organism (yeast IGPS), and to a different enzyme, i.e., a protein kinase, we demonstrated how CCA of DPCNs is an effective and transferable tool that facilitates the analysis of protein-weighted networks.

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.

Introduction to diffuse scattering and data collection

A long-standing goal in X-ray crystallography has been to extract information about the collective motions of proteins from diffuse scattering: the weak, textured signal that is found in the background of diffraction images. In the past few years, the field of macromolecular diffuse scattering has seen dramatic progress, and many of the past challenges in measurement and interpretation are now considered tractable. However, the concept of diffuse scattering is still new to many researchers, and a general set of procedures needed to collect a high-quality dataset has never been described in detail. Here, we provide the first guidelines for performing diffuse scattering experiments, which can be performed at any macromolecular crystallography beamline that supports room-temperature studies with a direct detector. We begin with a brief introduction to the theory of diffuse scattering and then walk the reader through the decision-making processes involved in preparing for and conducting a successful diffuse scattering experiment. Finally, we define quality metrics and describe ways to assess data quality both at the beamline and at home. Data obtained in this way can be processed independently by crystallographic software and diffuse scattering software to produce both a crystal structure, which represents the average atomic coordinates, and a three-dimensional diffuse scattering map that can then be interpreted in terms of models for protein motions.

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

Structure Relaxation Approximation (SRA) for Elucidation of Protein Structures from Ion Mobility Measurements (II). Protein Complexes

Characterizing structures of protein complexes and their disease-related aberrations is essential to understanding molecular mechanisms of many biological processes. Electrospray ionization coupled with hybrid ion mobility/mass spectrometry (ESI-IM/MS) methods offer sufficient sensitivity, sample throughput, and dynamic range to enable systematic structural characterization of proteomes. However, because ESI-IM/MS characterizes ionized protein systems in the gas phase, it generally remains unclear to what extent the protein ions characterized by IM/MS have retained their solution structures. Here, we discuss the first application of our computational structure relaxation approximation [Bleiholder, C.; et al. J. Phys. Chem. B 2019, 123 (13), 2756-2769] to assign structures of protein complexes in the range from ∼16 to ∼60 kDa from their "native" IM/MS spectra. Our analysis shows that the computed IM/MS spectra agree with the experimental spectra within the errors of the methods. The structure relaxation approximation (SRA) indicates that native backbone contacts appear largely retained in the absence of solvent for the investigated protein complexes and charge states. Native contacts between polypeptide chains of the protein complex appear to be retained to a comparable extent as contacts within a folded polypeptide chain. Our computations also indicate that the hallmark "compaction" often observed for protein systems in native IM/MS measurements appears to be a poor indicator of the extent to which native residue-residue interactions are lost in the absence of solvent. Further, the SRA indicates that structural reorganization of the protein systems in IM/MS measurements appears driven largely by remodeling of the protein surface that increases its hydrophobic content by approximately 10%. For the systems studied here, this remodeling of the protein surface appears to occur mainly by structural reorganization of surface-associated hydrophilic amino acid residues not associated with β-strand secondary structure elements. Properties related to the internal protein structure, as assessed by void volume or packing density, appear unaffected by remodeling of the surface. Taken together, the structural reorganization of the protein surface appears to be generic in nature and to sufficiently stabilize protein structures to render them metastable on the time scale of IM/MS measurements.

Mapping N- to C-terminal allosteric coupling through disruption of a putative CD74 activation site in D-dopachrome tautomerase

The macrophage migration inhibitory factor (MIF) protein family consists of MIF and D-dopachrome tautomerase (also known as MIF-2). These homologs share 34% sequence identity while maintaining nearly indistinguishable tertiary and quaternary structure, which is likely a major contributor to their overlapping functions, including the binding and activation of the cluster of differentiation 74 (CD74) receptor to mediate inflammation. Previously, we investigated a novel allosteric site, Tyr99, that modulated N-terminal catalytic activity in MIF through a "pathway" of dynamically coupled residues. In a comparative study, we revealed an analogous allosteric pathway in MIF-2 despite its unique primary sequence. Disruptions of the MIF and MIF-2 N termini also diminished CD74 activation at the C terminus, though the receptor activation site is not fully defined in MIF-2. In this study, we use site-directed mutagenesis, NMR spectroscopy, molecular simulations, in vitro and in vivo biochemistry to explore the putative CD74 activation region of MIF-2 based on homology to MIF. We also confirm its reciprocal structural coupling to the MIF-2 allosteric site and N-terminal enzymatic site. Thus, we provide further insight into the CD74 activation site of MIF-2 and its allosteric coupling for immunoregulation.

Activation of xanthine oxidase by 1,4-naphthoquinones: A novel potential research topic for diet management and risk assessment

Oral intake of 1,4-naphthoquinones could be a potential risk factor for hyperuricemia and gout via activation of xanthine oxidase (XO). Herein, 1,4-naphthoquinones derived from food and food-borne pollutants were selected to investigate the structure and activity relationship (SAR) and the relative mechanism for activating XO in liver S9 fractions from humans (HLS9) and rats (RLS9). The SAR analysis showed that introduction of electron-donating substituents on the benzene ring or electron-withdrawing substituents on the quinone ring improved the XO-activating effect of 1,4-naphthoquinones. Different activation potential and kinetics behaviors were observed for activating XO by 1,4-naphthoquinones in HLS9/RLS9. Molecular docking simulation and density functional theory calculations showed a good correlation between -LogEC₅₀ and docking free energy or HOMO-LUMO energy gap. The risk of exposure to the 1,4-naphthoquinones was evaluated and discussed. Our findings are helpful to guide diet management in clinic and avoid adverse events attributable to exposure to food-derived 1,4-naphthoquinones.

From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.

An NMR portrait of functional and dysfunctional allosteric cooperativity in cAMP-dependent protein kinase A

The cAMP-dependent protein kinase A (PKA) is the archetypical eukaryotic kinase. The catalytic subunit (PKA-C) structure is highly conserved among the AGC-kinase family. PKA-C is a bilobal enzyme with a dynamic N-lobe, harbouring the Adenosine-5'-triphosphate (ATP) binding site and a more rigid helical C-lobe. The substrate-binding groove resides at the interface of the two lobes. A distinct feature of PKA-C is the positive binding cooperativity between nucleotide and substrate. Several PKA-C mutations lead to the development of adenocarcinomas, myxomas, and other rare forms of liver tumours. Nuclear magnetic resonance (NMR) spectroscopy shows that these mutations disrupt the allosteric communication between the two lobes, causing a drastic decrease in binding cooperativity. The loss of cooperativity correlates with changes in substrate fidelity and reduced kinase affinity for the endogenous protein kinase inhibitor (PKI). The similarity between PKI and the inhibitory sequence of the kinase regulatory subunits suggests that the overall mechanism of regulation of the kinase may be disrupted. We surmise that a reduced or obliterated cooperativity may constitute a common trait for both orthosteric and allosteric mutations of PKA-C that may lead to dysregulation and disease.

Engineering the Active Site Lid Dynamics to Improve the Catalytic Efficiency of Yeast Cytosine Deaminase

Conformational dynamics is important for enzyme catalysis. However, engineering dynamics to achieve a higher catalytic efficiency is still challenging. In this work, we develop a new strategy to improve the activity of yeast cytosine deaminase (yCD) by engineering its conformational dynamics. Specifically, we increase the dynamics of the yCD C-terminal helix, an active site lid that controls the product release. The C-terminal is extended by a dynamical single α-helix (SAH), which improves the product release rate by up to ~8-fold, and the overall catalytic rate kcat by up to ~2-fold. It is also shown that the kcat increase is due to the favorable activation entropy change. The NMR H/D exchange data indicate that the conformational dynamics of the transition state analog complex increases as the helix is extended, elucidating the origin of the enhanced catalytic entropy. This study highlights a novel dynamics engineering strategy that can accelerate the overall catalysis through the entropy-driven mechanism.

Allosteric Nucleic Acid Enzyme: A Versatile Stimuli-Responsive Tool for Molecular Computing and Biosensing Nanodevices

Allostery is a naturally occurring mechanism in which effector binding induces the modulation and fine control of a related biomolecule function. Deoxyribozyme (DNAzyme) with catalytic activity and substrate recognition ability is ideal to be regulated by allosteric strategies. However, the current regulations frequently confront various obstacles, such as severe activity decay, signal leakage, and limited effectors. In this work, a rational regulation strategy for developing versatile effectors-responsive allosteric nucleic acid enzyme (ANAzyme) by introducing an allosteric domain in response to diverse effectors is established. The enzyme-like activity of this re-engineered ANAzyme can be modulated in a more predictable and fine way compared with the previous DNAzyme regulation strategies. Based on the allosteric strategy, the construction of allosterically coregulatory nanodevices and a series of basic logic gates and logic circuits are achieved, demonstrating that the proposed ANAzyme-regulated strategy showed great potential in molecular computing. Given these facts, the rational design of ANAzyme with the allosteric domain presented here can expand the available toolbox to develop a variety of stimuli-responsive allosteric DNA materials, including molecular machines, computing systems, biosensing platforms, and gene-silencing tools.

Analysis of coordinated NMR chemical shifts to map allosteric regulatory networks in proteins

The exquisite sensitivity of the NMR chemical shift to local environment makes it an ideal probe to assess atomic level perturbations in proteins of all sizes and structural compositions. Recent advances in solution and solid-state NMR spectroscopy of biomolecules have leveraged the chemical shift to report on short- and long-range couplings between individual amino acids to establish "networks" of residues that form the basis of allosteric pathways that transmit chemical signals through the protein matrix to induce functional responses. The simple premise that thermodynamically and functionally coupled regions of a protein (i.e. active and allosteric sites) should be reciprocally sensitive to structural or dynamic perturbations has enabled NMR spectroscopy, the premier method for molecular resolution of protein structural fluctuations, to occupy a place at the forefront of investigations into protein allostery. Here, we detail several key methods of NMR chemical shift analysis to extract mechanistic information about long-range chemical signaling in a protein, focusing on practical methodological aspects and the circumstances under which a given approach would be relevant. We also detail some of the experimental considerations that should be made when applying these methods to specific protein systems.

Binding and Functional Folding (BFF): A Physiological Framework for Studying Biomolecular Interactions and Allostery

EF-hand Ca2+-binding proteins (CBPs), such as S100 proteins (S100s) and calmodulin (CaM), are signaling proteins that undergo conformational changes upon increasing intracellular Ca2+. Upon binding Ca2+, S100 proteins and CaM interact with protein targets and induce important biological responses. The Ca2+-binding affinity of CaM and most S100s in the absence of target is weak (CaKD > 1 μM). However, upon effector protein binding, the Ca2+ affinity of these proteins increases via heterotropic allostery (CaKD < 1 μM). Because of the high number and micromolar concentrations of EF-hand CBPs in a cell, at any given time, allostery is required physiologically, allowing for (i) proper Ca2+ homeostasis and (ii) strict maintenance of Ca2+-signaling within a narrow dynamic range of free Ca2+ ion concentrations, [Ca2+]free. In this review, mechanisms of allostery are coalesced into an empirical "binding and functional folding (BFF)" physiological framework. At the molecular level, folding (F), binding and folding (BF), and BFF events include all atoms in the biomolecular complex under study. The BFF framework is introduced with two straightforward BFF types for proteins (type 1, concerted; type 2, stepwise) and considers how homologous and nonhomologous amino acid residues of CBPs and their effector protein(s) evolved to provide allosteric tightening of Ca2+ and simultaneously determine how specific and relatively promiscuous CBP-target complexes form as both are needed for proper cellular function.

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct "enhanced network models", describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. "Ab-initio network models" combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.

MptpA Kinetics Enhanced by Allosteric Control of an Active Conformation

Understanding allostery in the Mycobacterium tuberculosis low molecular weight protein tyrosine phosphatase (MptpA) is a subject of great interest since MptpA is one of two protein tyrosine phosphatases (PTPs) from the pathogenic organism Mycobacterium tuberculosis expressed during host cell infection. Here, we combine computational modeling with solution NMR spectroscopy and we find that Q75 is an allosteric site. Removal of the polar side chain of Q75 by mutation to leucine results in a cascade of events that reposition the acid loop over the active site and relocates the catalytic aspartic acid (D126) at an optimal position for proton donation to the leaving aryl group of the substrate and for subsequent hydrolysis of the thiophosphoryl intermediate. The computational analysis is consistent with kinetic data, and NMR spectroscopy, showing that the Q75L mutant exhibits enhanced reaction kinetics with similar substrate binding affinity. We anticipate that our findings will motivate further studies on the possibility that MptpA remains passivated during the chronic state of infection and increases its activity as part of the pathogenic life cycle of M. tuberculosis possibly via allosteric means.

A New Model of Hemoglobin Oxygenation

The study of hemoglobin oxygenation, starting from the classical works of Hill, has laid the foundation for molecular biophysics. The cooperative nature of oxygen binding to hemoglobin has been variously described in different models. In the Adair model, which better fits the experimental data, the constants of oxygen binding at various stages differ. However, the physical meaning of the parameters in this model remains unclear. In this work, we applied Hill's approach, extending its interpretation; we obtained a good agreement between the theory and the experiment. The equation in which the Hill coefficient is modulated by the Lorentz distribution for oxygen partial pressure approximates the experimental data better than not only the classical Hill equation, but also the Adair equation.

M, Walker C, Kim J, Camilloni C, De Simone A, Vendruscolo M, Bernlohr DA, Taylor SS, Veglia G. ATP-competitive inhibitors modulate the substrate binding cooperativity of a kinase by altering its conformational entropy

ATP-competitive inhibitors are currently the largest class of clinically approved drugs for protein kinases. By targeting the ATP-binding pocket, these compounds block the catalytic activity, preventing substrate phosphorylation. A problem with these drugs, however, is that inhibited kinases may still recognize and bind downstream substrates, acting as scaffolds or binding hubs for signaling partners. Here, using protein kinase A as a model system, we show that chemically different ATP-competitive inhibitors modulate the substrate binding cooperativity by tuning the conformational entropy of the kinase and shifting the populations of its conformationally excited states. Since we found that binding cooperativity and conformational entropy of the enzyme are correlated, we propose a new paradigm for the discovery of ATP-competitive inhibitors, which is based on their ability to modulate the allosteric coupling between nucleotide and substrate-binding sites.

Molecular Dynamics Simulations Establish the Molecular Basis for the Broad Allostery Hotspot Distributions in the Tetracycline Repressor

It is imperative to identify the network of residues essential to the allosteric coupling for the purpose of rationally engineering allostery in proteins. Deep mutational scanning analysis has emerged as a function-centric approach for identifying such allostery hotspots in a comprehensive and unbiased fashion, leading to observations that challenge our understanding of allostery at the molecular level. Specifically, a recent deep mutational scanning study of the tetracycline repressor (TetR) revealed an unexpectedly broad distribution of allostery hotspots throughout the protein structure. Using extensive molecular dynamics simulations (up to 50 μs) and free energy computations, we establish the molecular and energetic basis for the strong anticooperativity between the ligand and DNA binding sites. The computed free energy landscapes in different ligation states illustrate that allostery in TetR is well described by a conformational selection model, in which the apo state samples a broad set of conformations, and specific ones are selectively stabilized by either ligand or DNA binding. By examining a range of structural and dynamic properties of residues at both local and global scales, we observe that various analyses capture different subsets of experimentally identified hotspots, suggesting that these residues modulate allostery in distinct ways. These results motivate the development of a thermodynamic model that qualitatively explains the broad distribution of hotspot residues and their distinct features in molecular dynamics simulations. The multifaceted strategy that we establish here for hotspot evaluations and our insights into their mechanistic contributions are useful for modulating protein allostery in mechanistic and engineering studies.

Distinct dissociation rates of murine and human norovirus P-domain dimers suggest a role of dimer stability in virus-host interactions

Norovirus capsids are icosahedral particles composed of 90 dimers of the major capsid protein VP1. The C-terminus of the VP1 proteins forms a protruding (P)-domain, mediating receptor attachment, and providing a target for neutralizing antibodies. NMR and native mass spectrometry directly detect P-domain monomers in solution for murine (MNV) but not for human norovirus (HuNoV). We report that the binding of glycochenodeoxycholic acid (GCDCA) stabilizes MNV-1 P-domain dimers (P-dimers) and induces long-range NMR chemical shift perturbations (CSPs) within loops involved in antibody and receptor binding, likely reflecting corresponding conformational changes. Global line shape analysis of monomer and dimer cross-peaks in concentration-dependent methyl TROSY NMR spectra yields a dissociation rate constant k_off of about 1 s⁻¹ for MNV-1 P-dimers. For structurally closely related HuNoV GII.4 Saga P-dimers a value of about 10⁻⁶s⁻¹ is obtained from ion-exchange chromatography, suggesting essential differences in the role of GCDCA as a cofactor for MNV and HuNoV infection.

NMR and native mass spectrometry reveal that the major capsid VP1 protein from murine and human norovirus exhibit distinct behaviors and are differentially regulated by the binding of glycochenodeoxycholic acid.

Identification of Core Allosteric Sites through Temperature- and Nucleus-Invariant Chemical Shift Covariance

Allosteric regulation is essential to control biological function. In addition, allosteric sites offer a promising venue for selective drug targeting. However, accurate mapping of allosteric sites remains challenging since allostery relies on often subtle, yet functionally relevant, structural and dynamical changes. A viable approach proposed to overcome such challenge is the chemical shift covariance analysis (CHESCA). Although CHESCA offers an exhaustive map of allosteric networks, it is critical to define the core allosteric sites to be prioritized in subsequent functional studies or the design of allosteric drugs. Here we propose two new CHESCA-based methodologies, called temperature CHESCA (T-CHESCA) and CLASS-CHESCA, aimed at narrowing down allosteric maps to the core allosteric residues. Both T- and CLASS-CHESCAs rely on the invariance of core inter-residue correlations to changes in the chemical shifts of the active and inactive conformations interconverting in fast exchange. In the T-CHESCA the chemical shifts of such states are modulated through temperature changes, while in the CLASS-CHESCA through variations in the spin-active nuclei involved in pairwise correlations. The T- and CLASS-CHESCAs as well as complete-linkage CHESCA were applied to the cAMP-binding domain of the exchange protein directly activated by cAMP (EPAC), which serves as a prototypical allosteric switch. Residues consistently identified by the three CHESCA methods were found in previously identified EPAC allosteric core sites. Hence, the T-, CLASS- and CL-CHESCA provide a toolset to establish allosteric site hierarchy and triage allosteric sites to be further analyzed by mutations and functional assays. Furthermore, the core allosteric networks selectively revealed through T- and CLASS-CHESCA are expected to facilitate the mechanistic understanding of disease-related mutations and the design of selective allosteric modulators.

Enzymology and Dynamics by Cryogenic Electron Microscopy

Cryogenic electron microscopy (cryo-EM) has revolutionized the field of structural biology, particularly in solving the structures of large protein complexes or cellular machineries that play important biological functions. This review focuses on the contribution and future potential of cryo-EM in related emerging applications-enzymatic mechanisms and dynamic processes. Work on these subjects can benefit greatly from the capability of cryo-EM to solve the structures of specific protein complexes in multiple conditions, including variations in the buffer condition, ligands, and temperature, and to capture multiple conformational states, conformational change intermediates, and reaction intermediates. These studies can expand the structural landscape of specific proteins or protein complexes in multiple dimensions and drive new advances in the fields of enzymology and dynamic processes. The advantages and complementarity of cryo-EM relative to X-ray crystallography and nuclear magnetic resonance with regard to these applications are also addressed. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Enhanced specificity mutations perturb allosteric signaling in CRISPR-Cas9

CRISPR-Cas9 (clustered regularly interspaced short palindromic repeat and associated Cas9 protein) is a molecular tool with transformative genome editing capabilities. At the molecular level, an intricate allosteric signaling is critical for DNA cleavage, but its role in the specificity enhancement of the Cas9 endonuclease is poorly understood. Here, multi-microsecond molecular dynamics is combined with solution NMR and graph theory-derived models to probe the allosteric role of key specificity-enhancing mutations. We show that mutations responsible for increasing the specificity of Cas9 alter the allosteric structure of the catalytic HNH domain, impacting the signal transmission from the DNA recognition region to the catalytic sites for cleavage. Specifically, the K855A mutation strongly disrupts the allosteric connectivity of the HNH domain, exerting the highest perturbation on the signaling transfer, while K810A and K848A result in more moderate effects on the allosteric communication. This differential perturbation of the allosteric signal correlates to the order of specificity enhancement (K855A > K848A ~ K810A) observed in biochemical studies, with the mutation achieving the highest specificity most strongly perturbing the signaling transfer. These findings suggest that alterations of the allosteric communication from DNA recognition to cleavage are critical to increasing the specificity of Cas9 and that allosteric hotspots can be targeted through mutational studies for improving the system's function.

Chloride Ions Stabilize Human Adult Hemoglobin in the T-State, Competing with Allosteric Interaction of Oxygen Molecules

In the context of a molecular-level understanding of the allostery mechanisms, human adult hemoglobin (HbA) has been extensively studied for over half a century. Chloride ions (Cl^-) have been known as one of HbA allosteric effectors, which stabilizes the T-state preferable to release oxygen molecules. The functional mechanisms were individually proposed by Ueno and Perutz several decades ago. Ueno considered that the site-specific Cl^- binding is essential, while Perutz proposed the non-site-specific interaction between HbA and Cl^-. Each speculation explains the mechanism plausibly since each was tightly associated with its reasonable experimental observation. However, both mechanisms themselves still seem to make their speculations controversial. In the present study, we have theoretically reconsidered these apart from their approaches. Our atomistic molecular dynamics simulations then showed that the increase of Cl^- concentration suppresses the conformational conversion from the T-state. Interestingly, chloride ions loosely interact with the amino acid residues inside the HbA central cavity, suggesting that both Perutz's and Ueno's speculations are involved in understanding the microscopic roles of Cl^-. In conclusion, we theoretically certified that the effect of Cl^- competes against that of solvated O₂, i.e., the destabilization of T-state through the non-site-specific interaction, implying the concerted regulation of HbA under physiological conditions.

Molecular Level Insights Into the Structural and Dynamic Factors Driving Cytokine Function

Cytokines are key mediators of cellular communication and regulators of biological advents. The timing, quantity and localization of cytokines are key features in producing specific biological outcomes, and thus have been thoroughly studied and reviewed while continuing to be a focus of the cytokine biology community. Due to the complexity of cellular signaling and multitude of factors that can affect signaling outcomes, systemic level studies of cytokines are ongoing. Despite their small size, cytokines can exhibit structurally promiscuous and dynamic behavior that plays an equally important role in biological activity. In this review using case studies, we highlight the recent insight gained from observing cytokines through a molecular lens and how this may complement a system-level understanding of cytokine biology, explain diversity of downstream signaling events, and inform therapeutic and experimental development.

Measuring radiofrequency fields in NMR spectroscopy using offset-dependent nutation profiles

The application of NMR spectroscopy for studying molecular and reaction dynamics relies crucially on the measurement of the magnitude of radiofrequency (RF) fields that are used to nutate or lock the nuclear magnetization. Here, we report a method for measuring RF field amplitudes that leverages the intrinsic modulations observed in offset-dependent NMR nutation profiles of small molecules. Such nutation profiles are exquisitely sensitive to the magnitude of the RF field, and B₁ values ranging from 1 to 2000 Hz, as well the inhomogeneity in B₁ distributions, can be determined with high accuracy and precision using this approach. In order to measure B₁ fields associated with NMR experiments carried out on protein or nucleic acids, where these modulations are obscured by the large transverse relaxation rate constants of the analyte, our approach can be used in conjunction with a suitable external small molecule standard, expanding the scope of the method for large biomolecules.

Dissecting the role of interprotomer cooperativity in the activation of oligomeric high-temperature requirement A2 protein

The human high-temperature requirement A2 (HtrA2) mitochondrial protease is critical for cellular proteostasis, with mutations in this enzyme closely associated with the onset of neurodegenerative disorders. HtrA2 forms a homotrimeric structure, with each subunit composed of protease and PDZ (PSD-95, DLG, ZO-1) domains. Although we had previously shown that successive ligand binding occurs with increasing affinity, and it has been suggested that allostery plays a role in regulating catalysis, the molecular details of how this occurs have not been established. Here, we use cysteine-based chemistry to generate subunits in different conformational states along with a protomer mixing strategy, biochemical assays, and methyl-transverse relaxation optimized spectroscopy-based NMR studies to understand the role of interprotomer allostery in regulating HtrA2 function. We show that substrate binding to a PDZ domain of one protomer increases millisecond-to-microsecond timescale dynamics in neighboring subunits that prime them for binding substrate molecules. Only when all three PDZ-binding sites are substrate bound can the enzyme transition into an active conformation that involves significant structural rearrangements of the protease domains. Our results thus explain why when one (or more) of the protomers is fixed in a ligand-binding-incompetent conformation or contains the inactivating S276C mutation that is causative for a neurodegenerative phenotype in mouse models of Parkinson's disease, transition to an active state cannot be formed. In this manner, wild-type HtrA2 is only active when substrate concentrations are high and therefore toxic and unregulated proteolysis of nonsubstrate proteins can be suppressed.

Coordination of Di-Acetylated Histone Ligands by the ATAD2 Bromodomain

The ATPase Family, AAA domain-containing protein 2 (ATAD2) bromodomain (BRD) has a canonical bromodomain structure consisting of four α-helices. ATAD2 functions as a co-activator of the androgen and estrogen receptors as well as the MYC and E2F transcription factors. ATAD2 also functions during DNA replication, recognizing newly synthesized histones. In addition, ATAD2 is shown to be up-regulated in multiple forms of cancer including breast, lung, gastric, endometrial, renal, and prostate. Furthermore, up-regulation of ATAD2 is strongly correlated with poor prognosis in many types of cancer, making the ATAD2 bromodomain an innovative target for cancer therapeutics. In this study, we describe the recognition of histone acetyllysine modifications by the ATAD2 bromodomain. Residue-specific information on the complex formed between the histone tail and the ATAD2 bromodomain, obtained through nuclear magnetic resonance spectroscopy (NMR) and X-ray crystallography, illustrates key residues lining the binding pocket, which are involved in coordination of di-acetylated histone tails. Analytical ultracentrifugation, NMR relaxation data, and isothermal titration calorimetry further confirm the monomeric state of the functionally active ATAD2 bromodomain in complex with di-acetylated histone ligands. Overall, we describe histone tail recognition by ATAD2 BRD and illustrate that one acetyllysine group is primarily engaged by the conserved asparagine (N1064), the "RVF" shelf residues, and the flexible ZA loop. Coordination of a second acetyllysine group also occurs within the same binding pocket but is essentially governed by unique hydrophobic and electrostatic interactions making the di-acetyllysine histone coordination more specific than previously presumed.

Making the invisible visible: Toward structural characterization of allosteric states, interaction networks, and allosteric regulatory mechanisms in protein kinases

Despite the established view of protein kinases as dynamic and versatile allosteric regulatory machines, our knowledge of allosteric functional states, allosteric interaction networks, and the intrinsic folding energy landscapes is surprisingly limited. We discuss the latest developments in structural characterization of allosteric molecular events underlying protein kinase dynamics and functions using structural, biophysical, and computational biology approaches. The recent studies highlighted progress in making the invisible aspects of protein kinase 'life' visible, including the determination of hidden allosteric states and mapping of allosteric energy landscapes, discovery of new mechanisms underlying ligand-induced modulation of allosteric activity, evolutionary adaptation of kinase allostery, and characterization of allosteric interaction networks as the intrinsic driver of kinase adaptability and signal transmission in the regulatory assemblies.

Cryo-EM to visualize the structural organization of viruses

It is intriguing to think that over millions of years, groups of nucleic acids got the chance to hold together with groups of proteins to build up what today is called a virus. Their only goal is to guarantee a successful replication inside a host. If their genome information is preserved, the task is accomplished. Viruses have evolved to infect organisms and propagate with high degree of adaptation, as it is the case of the SARS-CoV-2, agent of the 2020 world pandemic. The technological progress observed in the field of structural biology, especially in cryo-EM, has offered scientists the possibility of a better understanding of virus origins, behavior, and structural organization. In this minireview we summarize few perspectives about the origins and organization of viruses and the advances of cryo-EM to aid structural virologists to sample the virosphere.

Establishing the allosteric mechanism in CRISPR-Cas9

Allostery is a fundamental property of proteins, which regulates biochemical information transfer between spatially distant sites. Here, we report on the critical role of molecular dynamics (MD) simulations in discovering the mechanism of allosteric communication within CRISPR-Cas9, a leading genome editing machinery with enormous promises for medicine and biotechnology. MD revealed how allostery intervenes during at least three steps of the CRISPR-Cas9 function: affecting DNA recognition, mediating the cleavage and interfering with the off-target activity. An allosteric communication that activates concerted DNA cleavages was found to led through the L1/L2 loops, which connect the HNH and RuvC catalytic domains. The identification of these "allosteric transducers" inspired the development of novel variants of the Cas9 protein with improved specificity, opening a new avenue for controlling the CRISPR-Cas9 activity. Discussed studies also highlight the critical role of the recognition lobe in the conformational activation of the catalytic HNH domain. Specifically, the REC3 region was found to modulate the dynamics of HNH by sensing the formation of the RNA:DNA hybrid. The role of REC3 was revealed to be particularly relevant in the presence of DNA mismatches. Indeed, interference of REC3 with the RNA:DNA hybrid containing mismatched pairs at specific positions resulted in locking HNH in an inactive "conformational checkpoint" conformation, thereby hampering off-target cleavages. Overall, MD simulations established the fundamental mechanisms underlying the allosterism of CRISPR-Cas9, aiding engineering strategies to develop new CRISPR-Cas9 variants for improved genome editing.

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Protein conformational dynamics play fundamental roles in regulation of enzymatic catalysis, ligand binding, allostery, and signaling, which are important biological processes. Understanding how the balance between structure and dynamics governs biological function is a new frontier in modern structural biology and has ignited several technical and methodological developments. Among these, CPMG relaxation dispersion solution NMR methods provide unique, atomic-resolution information on the structure, kinetics, and thermodynamics of protein conformational equilibria occurring on the µs-ms timescale. Here, the study presents detailed protocols for acquisition and analysis of a ¹⁵N relaxation dispersion experiment. As an example, the pipeline for the analysis of the µs-ms dynamics in the C-terminal domain of bacteria Enzyme I is shown.

1H, 13C, 15 N backbone resonance assignment of the recognition lobe subdomain 3 (Rec3) from Streptococcus pyogenes CRISPR-Cas9

Rec3 is a subdomain of the recognition (Rec) lobe within CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-associated protein Cas9 that is involved in nucleic acid binding and is critical to HNH endonuclease activation. Here, we report the backbone resonance assignments of an engineered construct of the Rec3 subdomain from Streptococcus pyogenes Cas9. We also analyze backbone chemical shift data to predict secondary structure and an overall fold that is consistent with that of Rec3 from the full-length S. pyogenes Cas9 protein.

Allosteric inhibition explained through conformational ensembles sampling distinct "mixed" states

Allosteric modulation provides an effective avenue for selective and potent enzyme inhibition. Here, we summarize and critically discuss recent advances on the mechanisms of allosteric partial agonists for three representative signalling enzymes activated by cyclic nucleotides: the cAMP-dependent protein kinase (PKA), the cGMP-dependent protein kinase (PKG), and the exchange protein activated by cAMP (EPAC). The comparative analysis of partial agonism in PKA, PKG and EPAC reveals a common emerging theme, i.e. the sampling of distinct “mixed” conformational states, either within a single domain or between distinct domains. Here, we show how such “mixed” states play a crucial role in explaining the observed functional response, i.e. partial agonism and allosteric pluripotency, as well as in maximizing inhibition while minimizing potency losses. In addition, by combining Nuclear Magnetic Resonance (NMR), Molecular Dynamics (MD) simulations and Ensemble Allosteric Modeling (EAM), we also show how to map the free-energy landscape of conformational ensembles containing “mixed” states. By discussing selected case studies, we illustrate how MD simulations and EAM complement NMR to quantitatively relate protein dynamics to function. The resulting NMR- and MD-based EAMs are anticipated to inform not only the design of new generations of highly selective allosteric inhibitors, but also the choice of multidrug combinations.

Targeting the cryptic sites: NMR-based strategy to improve protein druggability by controlling the conformational equilibrium

Cryptic ligand binding sites, which are not evident in the unligated structures, are beneficial in tackling with difficult but attractive drug targets, such as protein-protein interactions (PPIs). However, cryptic sites have thus far not been rationally pursued in the early stages of drug development. Here, we demonstrated by nuclear magnetic resonance that the cryptic site in Bcl-xL exists in a conformational equilibrium between the open and closed conformations under the unligated condition. While the fraction of the open conformation in the unligated wild-type Bcl-xL is estimated to be low, F143W mutation that is distal from the ligand binding site can substantially elevate the population. The F143W mutant showed a higher hit rate in a phage-display peptide screening, and the hit peptide bound to the cryptic site of the wild-type Bcl-xL. Therefore, by controlling the conformational equilibrium in the cryptic site, the opportunity to identify a PPI inhibitor could be improved.

RNA sectors and allosteric function within the ribosome

The ribosome translates the genetic code into proteins in all domains of life. Its size and complexity demand long-range interactions that regulate ribosome function. These interactions are largely unknown. Here, we apply a global coevolution method, statistical coupling analysis (SCA), to identify coevolving residue networks (sectors) within the 23S ribosomal RNA (rRNA) of the large ribosomal subunit. As in proteins, SCA reveals a hierarchical organization of evolutionary constraints with near-independent groups of nucleotides forming physically contiguous networks within the three-dimensional structure. Using a quantitative, continuous-culture-with-deep-sequencing assay, we confirm that the top two SCA-predicted sectors contribute to ribosome function. These sectors map to distinct ribosome activities, and their origins trace to phylogenetic divergences across all domains of life. These findings provide a foundation to map ribosome allostery, explore ribosome biogenesis, and engineer ribosomes for new functions. Despite differences in chemical structure, protein and RNA enzymes appear to share a common internal logic of interaction and assembly.

Driving Protein Conformational Cycles in Physiology and Disease: "Frustrated" Amino Acid Interaction Networks Define Dynamic Energy Landscapes: Amino Acid Interaction Networks Change Progressively Along Alpha Tryptophan Synthase's Catalytic Cycle

A general framework by which dynamic interactions within a protein will promote the necessary series of structural changes, or "conformational cycle," required for function is proposed. It is suggested that the free-energy landscape of a protein is biased toward this conformational cycle. Fluctuations into higher energy, although thermally accessible, conformations drive the conformational cycle forward. The amino acid interaction network is defined as those intraprotein interactions that contribute most to the free-energy landscape. Some network connections are consistent in every structural state, while others periodically change their interaction strength according to the conformational cycle. It is reviewed here that structural transitions change these periodic network connections, which then predisposes the protein toward the next set of network changes, and hence the next structural change. These concepts are illustrated by recent work on tryptophan synthase. Disruption of these dynamic connections may lead to aberrant protein function and disease states.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

Analysis of polyphenolic metabolites from in vitro gastrointestinal digested soft fruit extracts identify malvidin-3-glucoside as an inhibitor of PTP1B

Protein-tyrosine phosphatase 1B (PTP1B, EC 3.1.3.48) is an important regulator of insulin signalling. Herein, we employed experimental and computational biology techniques to investigate the inhibitory properties of phenolics, identified from four in vitro gastrointestinal digested (IVGD) soft fruits, on PTP1B. Analysis by LC-MS/MS identified specific phenolics that inhibited PTP1B in vitro. Enzyme kinetics identified the mode of inhibition, while dynamics, stability and binding mechanisms of PTP1B-ligand complex were investigated through molecular modelling, docking, molecular dynamics (MD) simulations, and MM/PBSA binding free energy estimation. IVGD extracts and specific phenolics identified from the four soft fruits inhibited PTP1B (P < 0.0001) activity. Among the phenolics tested, the greatest inhibition was shown by malvidin-3-glucoside (P < 0.0001) and gallic acid (P < 0.0001). Malvidin-3-glucoside (Ki = 3.8 µg/mL) was a competitive inhibitor and gallic acid (Ki = 33.3 µg/mL) a non-competitive inhibitor of PTP1B. Malvidin-3-glucoside exhibited better binding energy than gallic acid and the synthetic inhibitor Dephostatin (-7.38 > -6.37 > -5.62 kcal/mol) respectively. Principal component analysis demonstrated malvidin-3-glucoside PTP1B-complex occupies more conformational space where critical WPD-loop displayed a higher degree of motion. MM/PBSA binding free energy for malvidin-3-glucoside to PTP1B was found to be higher than other complexes mediated by Van der Waals energy rather than electrostatic interaction for the other two inhibitors (-80.32 ± 1.25 > -40.64 ± 1.43 > -21.63 ± 1.73 kcal/mol) respectively. Altogether, we have established novel insights into the specific binding of dietary phenolics and have identified malvidin-3-glucoside as an PTP1B inhibitor, which may be further industrially developed for the treatment of type-2 diabetes.

Automated assignment of methyl NMR spectra from large proteins

As structural biology trends towards larger and more complex biomolecular targets, a detailed understanding of their interactions and underlying structures and dynamics is required. The development of methyl-TROSY has enabled NMR spectroscopy to provide atomic-resolution insight into the mechanisms of large molecular assemblies in solution. However, the applicability of methyl-TROSY has been hindered by the laborious and time-consuming resonance assignment process, typically performed with domain fragmentation, site-directed mutagenesis, and analysis of NOE data in the context of a crystal structure. In response, several structure-based automatic methyl assignment strategies have been developed over the past decade. Here, we present a comprehensive analysis of all available methods and compare their input data requirements, algorithmic strategies, and reported performance. In general, the methods fall into two categories: those that primarily rely on inter-methyl NOEs, and those that utilize methyl PRE- and PCS-based restraints. We discuss their advantages and limitations, and highlight the potential benefits from standardizing and combining different methods.