The underappreciated role of allostery in the cellular network

Bait and Cleave: Exosite-Binding Peptides on Quantum Dots Selectively Accelerate Protease Activity for Sensing with Enhanced Sensitivity

The advantageous optical properties of quantum dots (QDs) motivate their use in a wide variety of applications related to imaging and bioanalysis, including the detection of proteases and their activity. Recent studies have shown that surface chemistry on QDs is able to modulate protease activity, but only nonspecifically. Here, we present a strategy to selectively accelerate the activity of a particular target protease by as much as two orders of magnitude. Exosite-binding "bait" peptides were derived from proteins that span a range of biological roles─substrate, receptor, and inhibitor─and were used to increase the affinity of the QD-peptide conjugates for either thrombin or factor Xa, resulting in increased rates of proteolysis for coconjugated substrates. Unlike effects from QD surface chemistry, the acceleration was specific to the target protease with negligible acceleration of other proteases. Benefits of this "bait and cleave" sensing approach included detection limits that improved by more than an order of magnitude, reenabled detection of target protease against an overwhelming background of nontarget proteolysis, and mitigation of the action of inhibitors. The cumulative results point to a generalizable strategy, where the mechanism of acceleration, considerations for the design of bait peptides and conjugates, and routes to expanding the scope of this approach are discussed. Overall, this research represents a major step forward in the rational design of nanoparticle-based enzyme sensors that enhance sensitivity and selectivity.

Transition transferases prime bacterial capsule polymerization

Capsules are long-chain carbohydrate polymers that envelop the surfaces of many bacteria, protecting them from host immune responses. Capsule biosynthesis enzymes are potential drug targets and valuable biotechnological tools for generating vaccine antigens. Despite their importance, it remains unknown how structurally variable capsule polymers of Gram-negative pathogens are linked to the conserved glycolipid anchoring these virulence factors to the bacterial membrane. Using Actinobacillus pleuropneumoniae as an example, we demonstrate that CpsA and CpsC generate a poly(glycerol-3-phosphate) linker to connect the glycolipid with capsules containing poly(galactosylglycerol-phosphate) backbones. We reconstruct the entire capsule biosynthesis pathway in A. pleuropneumoniae serotypes 3 and 7, solve the X-ray crystal structure of the capsule polymerase CpsD, identify its tetratricopeptide repeat domain as essential for elongating poly(glycerol-3-phosphate) and show that CpsA and CpsC stimulate CpsD to produce longer polymers. We identify the CpsA and CpsC product as a wall teichoic acid homolog, demonstrating similarity between the biosynthesis of Gram-positive wall teichoic acid and Gram-negative capsules.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

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.

Pharmacologically targeting intracellular allosteric sites of GPCRs for drug discovery

G-protein-coupled receptors (GPCRs) are a family of cell surface proteins that can sense a variety of extracellular stimuli and mediate multiple signaling transduction pathways involved in human physiology. Recent advances in GPCR structural biology have revealed a relatively conserved intracellular allosteric site in multiple GPCRs, which can be utilized to modulate receptors from the inside. This novel intracellular site partially overlaps with the G-protein and β-arrestin coupling sites, providing a novel avenue for biological intervention. Here, we review evidence available for GPCR structures complexed with intracellular small-molecule allosteric modulators, elucidating drug-target interactions and allosteric mechanisms. Moreover, we highlight the potential of intracellular allosteric modulators in achieving biased signaling, which provides insights into biased allosteric mechanisms.

A multi-enzyme machine polymerizes the Haemophilus influenzae type b capsule

Bacterial capsules have critical roles in host-pathogen interactions. They provide a protective envelope against host recognition, leading to immune evasion and bacterial survival. Here we define the capsule biosynthesis pathway of Haemophilus influenzae serotype b (Hib), a Gram-negative bacterium that causes severe infections in infants and children. Reconstitution of this pathway enabled the fermentation-free production of Hib vaccine antigens starting from widely available precursors and detailed characterization of the enzymatic machinery. The X-ray crystal structure of the capsule polymerase Bcs3 reveals a multi-enzyme machine adopting a basket-like shape that creates a protected environment for the synthesis of the complex Hib polymer. This architecture is commonly exploited for surface glycan synthesis by both Gram-negative and Gram-positive pathogens. Supported by biochemical studies and comprehensive 2D nuclear magnetic resonance, our data explain how the ribofuranosyltransferase CriT, the phosphatase CrpP, the ribitol-phosphate transferase CroT and a polymer-binding domain function as a unique multi-enzyme assembly.

Combining structural and coevolution information to unveil allosteric sites

Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.

Machine learning and protein allostery

The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric mechanisms will have an increasingly important role in bridging a wide spectrum of data-intensive experimental and theoretical technologies.

Correlated Evolution of Low-Frequency Vibrations and Function in Enzymes

Previous studies of the flexibility of ancestral proteins suggest that proteins evolve their function by altering their native state ensemble. Here, we propose a more direct method to analyze such changes during protein evolution by comparing thermally activated vibrations at frequencies below 6 THz, which report on the dynamics of collective protein modes. We analyzed the backbone vibrational density of states of ancestral and extant β-lactamases and thioredoxins and observed marked changes in the vibrational spectrum in response to evolution. Coupled with previously observed changes in protein flexibility, the observed shifts of vibrational mode densities suggest that protein dynamics and dynamical allostery are critical factors for the evolution of enzymes with specialized catalytic and biophysical properties.

Locating dynamic contributions to allostery via determining rates of vibrational energy transfer

Determining rates of energy transfer across non-covalent contacts for different states of a protein can provide information about dynamic and associated entropy changes during transitions between states. We investigate the relationship between rates of energy transfer across polar and nonpolar contacts and contact dynamics for the β₂-adrenergic receptor, a rhodopsin-like G-protein coupled receptor, in an antagonist-bound inactive state and agonist-bound active state. From structures sampled during molecular dynamics (MD) simulations, we find the active state to have, on average, a lower packing density, corresponding to generally more flexibility and greater entropy than the inactive state. Energy exchange networks (EENs) are computed for the inactive and active states from the results of the MD simulations. From the EENs, changes in the rates of energy transfer across polar and nonpolar contacts are found for contacts that remain largely intact during activation. Change in dynamics of the contact, and entropy associated with the dynamics, can be estimated from the change in rates of energy transfer across the contacts. Measurement of change in the rates of energy transfer before and after the transition between states thereby provides information about dynamic contributions to activation and allostery.

Self-Effected Allosteric Coupling and Cooperativity in Hypoxic Response Regulation with Disordered Proteins

Hypersensitive regulation of cellular hypoxic response relies on cooperative displacement of one disordered protein (HIF-1α) by another disordered protein (CITED2) from the target in a negative feedback loop. Considering the weak intramolecule coupling in disordered proteins, the molecular mechanism of high cooperativity in the molecular displacement event remains elusive. Herein, we show that disordered proteins utilize a "self-effected allostery" mechanism to achieve high binding cooperativity. Different from the conventional allostery mechanisms shown by many structured or disordered proteins, this mechanism utilizes one part of the disordered protein as the effector to trigger the allosteric coupling and enhance the binding of the remaining part of the same disordered protein, contributing to high cooperativity of the displacement event. The conserved charge motif of CITED2 is the key determinant of the molecular displacement event by serving as the effector of allosteric coupling. Such self-effected allostery provides an efficient strategy to achieve high cooperativity in the molecular events involving disordered proteins.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

Allostery, and how to define and measure signal transduction

Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.

Known allosteric proteins have central roles in genetic disease

Allostery is a form of protein regulation, where ligands that bind sites located apart from the active site can modify the activity of the protein. The molecular mechanisms of allostery have been extensively studied, because allosteric sites are less conserved than active sites, and drugs targeting them are more specific than drugs binding the active sites. Here we quantify the importance of allostery in genetic disease. We show that 1) known allosteric proteins are central in disease networks, contribute to genetic disease and comorbidities much more than non-allosteric proteins, and there is an association between being allosteric and involvement in disease; 2) they are enriched in many major disease types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes, or diseases of the central nervous system; 3) variants from cancer genome-wide association studies are enriched near allosteric proteins, indicating their importance to polygenic traits; and 4) the importance of allosteric proteins in disease is due, at least partly, to their central positions in protein-protein interaction networks, and less due to their dynamical properties.

Allosterism in the PDZ Family

Dynamic allosterism allows the propagation of signal throughout a protein. The PDZ (PSD-95/Dlg1/ZO-1) family has been named as a classic example of dynamic allostery in small modular domains. While the PDZ family consists of more than 200 domains, previous efforts have primarily focused on a few well-studied PDZ domains, including PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ. Taken together, experimental and computational studies have identified regions of these domains that are dynamically coupled to ligand binding. These regions include the αA helix, the αB lower-loop, and the αC helix. In this review, we summarize the specific residues on the αA helix, the αB lower-loop, and the αC helix of PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ that have been identified as participants in dynamic allostery by either experimental or computational approaches. This review can serve as an index for researchers to look back on the previously identified allostery in the PDZ family. Interestingly, our summary of previous work reveals clear consistencies between the domains. While the PDZ family has a low sequence identity, we show that some of the most consistently identified allosteric residues within PTP-BL PDZ2 and PSD-95 PDZ3 domains are evolutionarily conserved. These residues include A46/A347, V61/V362, and L66/L367 on PTP-BL PDZ2 and PSD-95 PDZ3, respectively. Finally, we expose a need for future work to explore dynamic allostery within (1) PDZ domains with multiple binding partners and (2) multidomain constructs containing a PDZ domain.

In Silico Identification and Experimental Validation of Distal Activity-Enhancing Mutations in Tryptophan Synthase

Allostery is a central mechanism for the regulation of multi-enzyme complexes. The mechanistic basis that drives allosteric regulation is poorly understood but harbors key information for enzyme engineering. In the present study, we focus on the tryptophan synthase complex that is composed of TrpA and TrpB subunits, which allosterically activate each other. Specifically, we develop a rational approach for identifying key amino acid residues of TrpB distal from the active site. Those residues are predicted to be crucial for shifting the inefficient conformational ensemble of the isolated TrpB to a productive ensemble through intra-subunit allosteric effects. The experimental validation of the conformationally driven TrpB design demonstrates its superior stand-alone activity in the absence of TrpA, comparable to those enhancements obtained after multiple rounds of experimental laboratory evolution. Our work evidences that the current challenge of distal active site prediction for enhanced function in computational enzyme design has become within reach.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

Allosteric conformational ensembles have unlimited capacity for integrating information

Integration of binding information by macromolecular entities is fundamental to cellular functionality. Recent work has shown that such integration cannot be explained by pairwise cooperativities, in which binding is modulated by binding at another site. Higher-order cooperativities (HOCs), in which binding is collectively modulated by multiple other binding events, appear to be necessary but an appropriate mechanism has been lacking. We show here that HOCs arise through allostery, in which effective cooperativity emerges indirectly from an ensemble of dynamically interchanging conformations. Conformational ensembles play important roles in many cellular processes but their integrative capabilities remain poorly understood. We show that sufficiently complex ensembles can implement any form of information integration achievable without energy expenditure, including all patterns of HOCs. Our results provide a rigorous biophysical foundation for analysing the integration of binding information through allostery. We discuss the implications for eukaryotic gene regulation, where complex conformational dynamics accompanies widespread information integration.

ADAM10 Site-Dependent Biology: Keeping Control of a Pervasive Protease

Enzymes, once considered static molecular machines acting in defined spatial patterns and sites of action, move to different intra- and extracellular locations, changing their function. This topological regulation revealed a close cross-talk between proteases and signaling events involving post-translational modifications, membrane tyrosine kinase receptors and G-protein coupled receptors, motor proteins shuttling cargos in intracellular vesicles, and small-molecule messengers. Here, we highlight recent advances in our knowledge of regulation and function of A Disintegrin And Metalloproteinase (ADAM) endopeptidases at specific subcellular sites, or in multimolecular complexes, with a special focus on ADAM10, and tumor necrosis factor-α convertase (TACE/ADAM17), since these two enzymes belong to the same family, share selected substrates and bioactivity. We will discuss some examples of ADAM10 activity modulated by changing partners and subcellular compartmentalization, with the underlying hypothesis that restraining protease activity by spatial segregation is a complex and powerful regulatory tool.

Label-free, mass-sensitive single-molecule imaging using interferometric scattering microscopy

Single-molecule imaging has mostly been restricted to the use of fluorescence labelling as a contrast mechanism due to its superior ability to visualise molecules of interest on top of an overwhelming background of other molecules. Recently, interferometric scattering (iSCAT) microscopy has demonstrated the detection and imaging of single biomolecules based on light scattering without the need for fluorescent labels. Significant improvements in measurement sensitivity combined with a dependence of scattering signal on object size have led to the development of mass photometry, a technique that measures the mass of individual molecules and thereby determines mass distributions of biomolecule samples in solution. The experimental simplicity of mass photometry makes it a powerful tool to analyse biomolecular equilibria quantitatively with low sample consumption within minutes. When used for label-free imaging of reconstituted or cellular systems, the strict size-dependence of the iSCAT signal enables quantitative measurements of processes at size scales reaching from single-molecule observations during complex assembly up to mesoscopic dynamics of cellular components and extracellular protrusions. In this review, I would like to introduce the principles of this emerging imaging technology and discuss examples that show how mass-sensitive iSCAT can be used as a strong complement to other routine techniques in biochemistry.

Decoding allosteric regulation by the acyl carrier protein

Enzymes in multistep metabolic pathways utilize an array of regulatory mechanisms to maintain a delicate homeostasis [K. Magnuson, S. Jackowski, C. O. Rock, J. E. Cronan, Jr, Microbiol. Rev. 57, 522-542 (1993)]. Carrier proteins in particular play an essential role in shuttling substrates between appropriate enzymes in metabolic pathways. Although hypothesized [E. Płoskoń et al., Chem. Biol. 17, 776-785 (2010)], allosteric regulation of substrate delivery has never before been demonstrated for any acyl carrier protein (ACP)-dependent pathway. Studying these mechanisms has remained challenging due to the transient and dynamic nature of protein-protein interactions, the vast diversity of substrates, and substrate instability [K. Finzel, D. J. Lee, M. D. Burkart, ChemBioChem 16, 528-547 (2015)]. Here we demonstrate a unique communication mechanism between the ACP and partner enzymes using solution NMR spectroscopy and molecular dynamics to elucidate allostery that is dependent on fatty acid chain length. We demonstrate that partner enzymes can allosterically distinguish between chain lengths via protein-protein interactions as structural features of substrate sequestration are translated from within the ACP four-helical bundle to the protein surface, without the need for stochastic chain flipping. These results illuminate details of cargo communication by the ACP that can serve as a foundation for engineering carrier protein-dependent pathways for specific, desired products.

Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks

Background

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease.

Methods

In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.

Results

We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes.

Conclusions

These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02791-9.

Engineering an Allosteric Control of Protein Function

Allosteric regulation in proteins is fundamental to many important biological processes. Allostery has been employed to control protein functions by regulating protein activity. Engineered allosteric regulation allows controlling protein activity in subsecond time scale and has a broad range of applications, from dissecting spatiotemporal dynamics in biochemical cascades to applications in biotechnology and medicine. Here, we review the concept of allostery in proteins and various approaches to identify allosteric sites and pathways. We then provide an overview of strategies and tools used in allosteric protein regulation and their utility in biological applications. We highlight various classes of proteins, where regulation is achieved through allostery. Finally, we analyze the current problems, critical challenges, and future prospective in achieving allosteric regulation in proteins.

Dynamic 3D proteomes reveal protein functional alterations at high resolution in situ

Biological processes are regulated by intermolecular interactions and chemical modifications that do not affect protein levels, thus escaping detection in classical proteomic screens. We demonstrate here that a global protein structural readout based on limited proteolysis-mass spectrometry (LiP-MS) detects many such functional alterations, simultaneously and in situ, in bacteria undergoing nutrient adaptation and in yeast responding to acute stress. The structural readout, visualized as structural barcodes, captured enzyme activity changes, phosphorylation, protein aggregation, and complex formation, with the resolution of individual regulated functional sites such as binding and active sites. Comparison with prior knowledge, including other ‘omics data, showed that LiP-MS detects many known functional alterations within well-studied pathways. It suggested distinct metabolite-protein interactions and enabled identification of a fructose-1,6-bisphosphate-based regulatory mechanism of glucose uptake in E. coli. The structural readout dramatically increases classical proteomics coverage, generates mechanistic hypotheses, and paves the way for in situ structural systems biology.

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Dynamic structural proteomic screens detect functional changes at high resolution

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Detect enzyme activity, phosphorylation, and molecular interactions in situ

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Generate new molecular hypotheses and increase functional proteomics coverage

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Enabled discovery of a regulatory mechanism of glucose uptake in E. coli

Synergistic Allostery in Multiligand-Protein Interactions

Amide hydrogen-deuterium exchange mass spectrometry is powerful for describing combinatorial coupling effects of a cooperative ligand pair binding at noncontiguous sites: adenosine at the ATP-pocket and a docking peptide (PIFtide) at the PIF-pocket, on a model protein kinase PDK1. Binding of two ligands to PDK1 reveal multiple hotspots of synergistic allostery with cumulative effects greater than the sum of individual effects mediated by each ligand. We quantified this synergism and ranked these hotspots using a difference in deuteration-based approach, which showed that the strongest synergistic effects were observed at three of the critical catalytic loci of kinases: the αB-αC helices, and HRD-motif loop, and DFG-motif. Additionally, we observed weaker synergistic effects at a distal GHI-subdomain locus. Synergistic changes in deuterium exchange observed at a distal site but not at the intermediate sites of the large lobe of the kinase reveals allosteric propagation in proteins to operate through two modes. Direct electrostatic interactions between polar and charged amino acids that mediate targeted relay of allosteric signals, and diffused relay of allosteric signals through soft matter-like hydrophobic core amino acids. Furthermore, we provide evidence that the conserved β-3 strand lysine of protein kinases (Lys111 of PDK1) functions as an integrator node to coordinate allosteric coupling of the two ligand-binding sites. It maintains indirect interactions with the ATP-pocket and mediates a critical salt bridge with a glutamate (Glu130) of αC helix, which is conserved across all kinases. In summary, allosteric propagation in cooperative, dual-liganded enzyme targets is bidirectional and synergistic and offers a strategy for combinatorial drug development.

ACE2, the Receptor that Enables Infection by SARS-CoV-2: Biochemistry, Structure, Allostery and Evaluation of the Potential Development of ACE2 Modulators

Angiotensin converting enzyme 2 (ACE2) is the human receptor that interacts with the spike protein of coronaviruses, including the one that produced the 2020 coronavirus pandemic (COVID-19). Thus, ACE2 is a potential target for drugs that disrupt the interaction of human cells with SARS-CoV-2 to abolish infection. There is also interest in drugs that inhibit or activate ACE2, that is, for cardiovascular disorders or colitis. Compounds binding at alternative sites could allosterically affect the interaction with the spike protein. Herein, we review biochemical, chemical biology, and structural information on ACE2, including the recent cryoEM structures of full-length ACE2. We conclude that ACE2 is very dynamic and that allosteric drugs could be developed to target ACE2. At the time of the 2020 pandemic, we suggest that available ACE2 inhibitors or activators in advanced development should be tested for their ability to allosterically displace the interaction between ACE2 and the spike protein.

Selective Monofunctionalization Enabled by Reaction-History-Dependent Communication in Catalytic Rotaxanes

Selective monofunctionalization of substrates with distant, yet equally reactive functional groups is difficult to achieve, as it requires the second functional group to selectively modulate its reactivity once the first functional group has reacted. We now show that mechanically interlocked catalytic rings can effectively regulate the reactivity of stoppering groups in rotaxanes over a distance of about 2 nm. Our mechanism of communication is enabled by a unique interlocked design, which effectively removes the catalytic rings from the substrates by fast dethreading as soon as the first reaction has taken place. Our method not only led to a rare example of selective monofunctionalization, but also to a "molecular if function". Overall, the study presents a way to get distant functional groups to communicate with each other in a reaction-history-dependent manner by creating linkers that can ultimately perform logical operations at the molecular level.

Interactions by Disorder - A Matter of Context

Living organisms depend on timely and organized interactions between proteins linked in interactomes of high complexity. The recent increased precision by which protein interactions can be studied, and the enclosure of intrinsic structural disorder, suggest that it is time to zoom out and embrace protein interactions beyond the most central points of physical encounter. The present paper discusses protein-protein interactions in the view of structural disorder with an emphasis on flanking regions and contexts of disorder-based interactions. Context constitutes an overarching concept being of physicochemical, biomolecular, and physiological nature, but it also includes the immediate molecular context of the interaction. For intrinsically disordered proteins, which often function by exploiting short linear motifs, context contributes in highly regulatory and decisive manners and constitute a yet largely unrecognized source of interaction potential in a multitude of biological processes. Through selected examples, this review emphasizes how multivalency, charges and charge clusters, hydrophobic patches, dynamics, energetic frustration, and ensemble redistribution of flanking regions or disordered contexts are emerging as important contributors to allosteric regulation, positive and negative cooperativity, feedback regulation and negative selection in binding. The review emphasizes that understanding context, and in particular the role the molecular disordered context and flanking regions take on in protein interactions, constitute an untapped well of energetic modulation potential, also of relevance to drug discovery and development.

The structural basis of T-cell receptor (TCR) activation: An enduring enigma

T cells are critical for protective immune responses to pathogens and tumors. The T-cell receptor (TCR)-CD3 complex is composed of a diverse αβ TCR heterodimer noncovalently associated with the invariant CD3 dimers CD3ϵγ, CD3ϵδ, and CD3ζζ. The TCR mediates recognition of antigenic peptides bound to MHC molecules (pMHC), whereas the CD3 molecules transduce activation signals to the T cell. Whereas much is known about downstream T-cell signaling pathways, the mechanism whereby TCR engagement by pMHC is first communicated to the CD3 signaling apparatus, a process termed early T-cell activation, remains largely a mystery. In this review, we examine the molecular basis for TCR activation in light of the recently determined cryoEM structure of a complete TCR-CD3 complex. This structure provides an unprecedented opportunity to assess various signaling models that have been proposed for the TCR. We review evidence from single-molecule and structural studies for force-induced conformational changes in the TCR-CD3 complex, for dynamically-driven TCR allostery, and for pMHC-induced structural changes in the transmembrane and cytoplasmic regions of CD3 subunits. We identify major knowledge gaps that must be filled in order to arrive at a comprehensive model of TCR activation that explains, at the molecular level, how pMHC-specific information is transmitted across the T-cell membrane to initiate intracellular signaling. An in-depth understanding of this process will accelerate the rational design of immunotherapeutic agents targeting the TCR-CD3 complex.

Does Ras Activate Raf and PI3K Allosterically?

The mechanism through which oncogenic Ras activates its effectors is vastly important to resolve. If allostery is at play, then targeting allosteric pathways could help in quelling activation of MAPK (Raf/MEK/ERK) and PI3K (PI3K/Akt/mTOR) cell proliferation pathways. On the face of it, allosteric activation is reasonable: Ras binding perturbs the conformational ensembles of its effectors. Here, however, we suggest that at least for Raf, PI3K, and NORE1A (RASSF5), that is unlikely. Raf's long disordered linker dampens effective allosteric activation. Instead, we suggest that the high-affinity Ras–Raf binding relieves Raf's autoinhibition, shifting Raf's ensemble from the inactive to the nanocluster-mediated dimerized active state, as Ras also does for NORE1A. PI3K is recruited and allosterically activated by RTK (e.g., EGFR) at the membrane. Ras restrains PI3K's distribution and active site orientation. It stabilizes and facilitates PIP₂ binding at the active site and increases the PI3K residence time at the membrane. Thus, RTKs allosterically activate PI3Kα; however, merging their action with Ras accomplishes full activation. Here we review their activation mechanisms in this light and draw attention to implications for their pharmacology.

SNAPS: Sensor Analytics Point Solutions for Detection and Decision Support Systems

In this review, we discuss the role of sensor analytics point solutions (SNAPS), a reduced complexity machine-assisted decision support tool. We summarize the approaches used for mobile phone-based chemical/biological sensors, including general hardware and software requirements for signal transduction and acquisition. We introduce SNAPS, part of a platform approach to converge sensor data and analytics. The platform is designed to consist of a portfolio of modular tools which may lend itself to dynamic composability by enabling context-specific selection of relevant units, resulting in case-based working modules. SNAPS is an element of this platform where data analytics, statistical characterization and algorithms may be delivered to the data either via embedded systems in devices, or sourced, in near real-time, from mist, fog or cloud computing resources. Convergence of the physical systems with the cyber components paves the path for SNAPS to progress to higher levels of artificial reasoning tools (ART) and emerge as data-informed decision support, as a service for general societal needs. Proof of concept examples of SNAPS are demonstrated both for quantitative data and qualitative data, each operated using a mobile device (smartphone or tablet) for data acquisition and analytics. We discuss the challenges and opportunities for SNAPS, centered around the value to users/stakeholders and the key performance indicators users may find helpful, for these types of machine-assisted tools.

Renaissance of Allostery to Disrupt Protein Kinase Interactions

Protein-protein interactions often regulate the activity of protein kinases by allosterically modulating the conformation of the ATP-binding site. Bidirectional allostery implies that reverse modulation (i.e., from the ATP-binding site to the interaction and regulatory sites) must also be possible. Here, we review both the allosteric regulation of protein kinases and recent work describing how compounds binding at the ATP-binding site can promote or inhibit protein kinase interactions at regulatory sites via the reverse mechanism. Notably, the pharmaceutical industry has been developing compounds that bind to the ATP-binding site of protein kinases and potently disrupt protein-protein interactions between target protein kinases and their regulatory interacting partners. Learning to modulate allosteric processes will facilitate the development of protein-protein interaction modulators.

Dissecting the sharp response of a canonical developmental enhancer reveals multiple sources of cooperativity

Developmental enhancers integrate graded concentrations of transcription factors (TFs) to create sharp gene expression boundaries. Here we examine the hunchback P2 (HbP2) enhancer which drives a sharp expression pattern in the Drosophila blastoderm embryo in response to the transcriptional activator Bicoid (Bcd). We systematically interrogate cis and trans factors that influence the shape and position of expression driven by HbP2, and find that the prevailing model, based on pairwise cooperative binding of Bcd to HbP2 is not adequate. We demonstrate that other proteins, such as pioneer factors, Mediator and histone modifiers influence the shape and position of the HbP2 expression pattern. Comparing our results to theory reveals how higher-order cooperativity and energy expenditure impact boundary location and sharpness. Our results emphasize that the bacterial view of transcription regulation, where pairwise interactions between regulatory proteins dominate, must be reexamined in animals, where multiple molecular mechanisms collaborate to shape the gene regulatory function.

Protein ensembles link genotype to phenotype

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.

Conformational Dynamics and Allosteric Regulation Landscapes of Germline PTEN Mutations Associated with Autism Compared to Those Associated with Cancer

Individuals with germline PTEN tumor-suppressor variants have PTEN hamartoma tumor syndrome (PHTS). Clinically, PHTS has variable presentations; there are distinct subsets of PHTS-affected individuals, such as those diagnosed with autism spectrum disorder (ASD) or cancer. It remains unclear why mutations in one gene can lead to such seemingly disparate phenotypes. Therefore, we sought to determine whether it is possible to predict a given PHTS-affected individual's a priori risk of ASD, cancer, or the co-occurrence of both phenotypes. By integrating network proximity analysis performed on the human interactome, molecular simulations, and residue-interaction networks, we demonstrate the role of conformational dynamics in the structural communication and long-range allosteric regulation of germline PTEN variants associated with ASD or cancer. We show that the PTEN interactome shares significant overlap with the ASD and cancer interactomes, providing network-based evidence that PTEN is a crucial player in the biology of both disorders. Importantly, this finding suggests that a germline PTEN variant might perturb the ASD or cancer networks differently, thus favoring one disease outcome at any one time. Furthermore, protein-dynamic structural-network analysis reveals small-world structural communication mediated by highly conserved functional residues and potential allosteric regulation of PTEN. We identified a salient structural-communication pathway that extends across the inter-domain interface for cancer-only mutations. In contrast, the structural-communication pathway is predominantly restricted to the phosphatase domain for ASD-only mutations. Our integrative approach supports the prediction and potential modulation of the relevant conformational states that influence structural communication and long-range perturbations associated with mutational effects that lead to PTEN-ASD or PTEN-cancer phenotypes.

Allostery in Its Many Disguises: From Theory to Applications

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.

Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

Fuel-Responsive Allosteric DNA-Based Aptamers for the Transient Release of ATP and Cocaine

We show herein that allostery offers a key strategy for the design of out-of-equilibrium systems by engineering allosteric DNA-based nanodevices for the transient loading and release of small organic molecules. To demonstrate the generality of our approach, we used two model DNA-based aptamers that bind ATP and cocaine through a target-induced conformational change. We re-engineered these aptamers so that their affinity towards their specific target is controlled by a DNA sequence acting as an allosteric inhibitor. The use of an enzyme that specifically cleaves the inhibitor only when it is bound to the aptamer generates a transient allosteric control that leads to the release of ATP or cocaine from the aptamers. Our approach confirms that the programmability and predictability of nucleic acids make synthetic DNA/RNA the perfect candidate material to re-engineer synthetic receptors that can undergo chemical fuel-triggered release of small-molecule cargoes and to rationally design non-equilibrium systems.

Allosteric Modulation of Intrinsically Disordered Proteins

The allosteric property of globular proteins is applauded as their intrinsic ability to regulate distant sites, and this property further plays a critical role in a wide variety of cellular regulatory mechanisms. Recent advancements and studies have revealed the manifestation of allostery in intrinsically disordered proteins or regions as allosteric sites present within or mediated by IDP/IDRs facilitates the signaling interactions for various biological mechanisms which would otherwise be impossible for globular proteins to regulate. This thematic review has highlighted the biological outcomes that can be achieved by the mechanism of allosteric regulation of intrinsically disordered proteins or regions. The similar mechanism has been implemented on Adenovirus 5 early region 1A and tumor apoptosis protein p53 in correspondence with other partners in binary and ternary complexes, which are the subject of the current review. Both these proteins regulate once they bind to their partners, consequently, forming either a binary or a ternary complex. Allosteric regulation by IDPs is currently a subject undergoing intense study, and the ongoing research work will ensure a better understanding of precision and efficiency of cellular regulation by them. Allosteric regulation mechanism can also be researched by intrinsically disordered protein-specific force field.