Allosteric Signal Research Articles

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

Improving tyrosol production efficiency through shortening the allosteric signal transmission distance of pyruvate decarboxylase.

Tyrosol is an important chemical in medicine and chemical industries, which can be synthesized by a four-enzyme cascade pathway constructed in our previous study. However, the low catalytic efficiency of pyruvate decarboxylase from Candida tropicalis (CtPDC) in this cascade is a rate-limiting step. In this study, we resolved the crystal structure of CtPDC and investigated the mechanism of allosteric substrate activation and decarboxylation of this enzyme toward 4-hydroxyphenylpyruvate (4-HPP). In addition, based on the molecular mechanism and structural dynamic changes, we conducted protein engineering of CtPDC to improve decarboxylation efficiency. The conversion of the best mutant, CtPDCQ112G/Q162H/G415S/I417V (CtPDCMu5), had over two-fold improvement compared to the wild-type. Molecular dynamic (MD) simulation revealed that the key catalytic distances and allosteric transmission pathways were shorter in CtPDCMu5 than in the wild type. Furthermore, when CtPDC in the tyrosol production cascade was replaced with CtPDCMu5, the tyrosol yield reached 38 g·L-1 with 99.6% conversion and 1.58 g·L-1·h-1 space-time yield in 24 h through further optimization of the conditions. Our study demonstrates that protein engineering of the rate-limiting enzyme in the tyrosol synthesis cascade provides an industrial-scale platform for the biocatalytic production of tyrosol. KEY POINTS: • Protein engineering of CtPDC based on allosteric regulation improved the catalytic efficiency of decarboxylation. • The application of the optimum mutant of CtPDC removed the rate-limiting bottleneck in the cascade. • The final titer of tyrosol reached 38 g·L-1 in 24 h in 3 L bioreactor.

Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

Computational insights into ligand-induced G protein and β-arrestin signaling of the dopamine D1 receptor.

The dopamine D1 receptor (D1R), is a class A G protein coupled-receptor (GPCR) which has been a promising drug target for psychiatric and neurological disorders such as Parkinson's disease (PD). Previous studies have suggested that therapeutic effects can be realized by targeting the β-arrestin signaling pathway of dopamine receptors, while overactivation of the G protein-dependent pathways leads to side effects, such as dyskinesias. Therefore, it is highly desirable to develop a D1R ligand that selectively regulates the β-arrestin pathway. Currently, most D1R agonists are signaling-balanced and stimulate both G protein and β-arrestin pathways, with a few reports of G protein biased ligands. However, identification and characterization of β-arrestin biased D1R agonists has been a challenge thus far. In this study, we implemented Gaussian accelerated molecular dynamics (GaMD) simulations to provide valuable computational insights into the possible underlying molecular mechanism of the different signaling properties of two catechol and two non-catechol D1R agonists that are either G protein biased or signaling-balanced. Dynamic network analysis further identified critical residues in the allosteric signaling network of D1R for each ligand at different conformational or binding states. Some of these residues are crucial for G protein or arrestin signals of GPCRs based on previous studies. Finally, we provided a molecular design strategy which can be utilized by medicinal chemists to develop potential β-arrestin biased D1R ligands. The proposed hypotheses are experimentally testable and can guide the development of safer and more effective medications for a variety of CNS disorders.

Monomeric C-reactive protein evokes TCR Signaling-dependent bystander activation of CD4+ T cells

Bystander activation of T cells is defined as induction of effector responses by innate cytokines in the absence of cognate antigens and independent of T cell receptor (TCR) signaling. Here we show that C-reactive protein (CRP), a soluble pattern-recognition receptor assembled noncovalently by five identical subunits, can instead trigger bystander activation of CD4 + T cells by evoking allosteric activation and spontaneous signaling of TCR in the absence of cognate antigens. The actions of CRP depend on pattern ligand-binding induced conformational changes that result in the generation of monomeric CRP (mCRP). mCRP binds cholesterol in plasma membranes of CD4 + T cells, thereby shifting the conformational equilibrium of TCR to the cholesterol-unbound, primed state. The spontaneous signaling of primed TCR leads to productive effector responses manifested by upregulation of surface activation markers and release of IFN-γ. Our results thus identify a novel mode of bystander T cell activation triggered by allosteric TCR signaling, and reveal an interesting paradigm wherein innate immune recognition of CRP transforms it to a direct activator that evokes immediate adaptive immune responses.

Sequence-dependent model of allosteric communication.

The omnipresence and diversity of allosteric regulation in proteins and protein associations complemented by the potential for the design of allosterically acting biologics and drugs call for the development of a new generation of computational models for the analysis of allostery and rational engineering/design of desired signaling and effector molecules determining it. One of the most important challenges is the consideration of the role of amino acid sequence in forming the protein's allosteric communication, including the mode and strength of the allosteric signal that is communicated to the regulated functional site. Here, we present the network-based model with a sequence dependence added in consideration of allosteric communication by combining the structure-based statistical mechanical model of allostery with the Miyazawa-Jernigan residue-residue potential. Applying the model in the analysis of five classical allosteric proteins, we found that it is necessary to consider the following two major determinants: (i) the free energy exerted by the allosteric site on the regulated one and (ii) the background (average) change in dynamics of the overall structure. We show that working together these two components determine the allosteric modulation, calling one to study their dependence on structures, oligomerization states, and sequence divergence in different proteins.

Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions.

As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.

The quaternary question: Determining allostery in spastin through dynamics classification learning and bioinformatics.

The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling.

Identification of residues involved in allosteric signal transmission from amino acid binding site of pyruvate kinase muscle isoform 2.

PKM2 is a rate-limiting enzyme in the glycolytic process and is involved in regulating tumor proliferation. Several amino acids (AAs) such as Asn, Asp, Val, and Cys have been shown to bind to the AA binding pocket of PKM2 and modulate its oligomeric state, substrate binding affinity, and activity. Although previous studies have attributed that the main chain and side chain of bound AAs are responsible for initiating signal to regulate PKM2, the signal transduction pathway remains elusive. To identify the residues involved in signal transfer process, N70 and N75 located at two ends of a β strand connecting the active site and AA binding pocket were altered. Biochemical studies of these variants with various AA ligands (Asn, Asp, Val, and Cys), illustrate that N70 and N75, along with β1 connecting these residues are part of the signal transduction pathway between the AA binding pocket and the active site. The results demonstrate that mutation of N70 to D prevents the transfer of the inhibitory signal mediated by Val and Cys, whereas N75 to L alteration blocks the activating signal initiated by Asn and Asp. Taken together, this study confirms that N70 is one of the residues responsible for transmitting the inhibitory signal and N75 is involved in the activation signal flow.

Determining the mechanisms of the allosteric architecture of DHFR.

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mechanisms by which mutations tune allostery. To examine this, we investigated the effects of allosteric residues in a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. In prior work using saturation mutagenesis, we showed that less than 5% of mutations had a statistically significant influence on allostery. While allostery disrupting mutations were located near the LOV2 insertion site, we found that allostery enhancing mutations were widely dispersed and enriched on the protein surface. However, these experiments did not reveal the mechanism by which the allosteric signal is propagated or how those mutations tune it. To understand these effects, we are characterizing the light-dependent changes in conformational dynamics for the chimeric enzyme by solution nuclear magnetic resonance spectroscopy and analysis of correlations between residue pairs in long timescale molecular dynamics. We have also measured the entropic and enthalpic contribution of select mutations towards the allosteric effect through kinetics assays. From these data, we aim to understand the mechanisms by which the global map of allosteric contributions inside the enzyme operates and provide insight into how allostery can be evolutionarily optimized.

From elucidating mechanisms of allosteric signaling to designing allosteric drugs and biologics.

Allostery is a pervasive phenomenon underlies a multitude of cellular processes. We have previously developed a Structure-Based Statistical Mechanical Model of Allostery (SBSMMA) to quantitatively describe the causality and energetics of allosteric signaling due to perturbations such as ligand binding, mutations, disorder-order transition and post-translational modifications. The computational model was implemented in the AlloSigMA server and AlloMAPS database, which allow one to explore allosteric effects of perturbations in form of the exhaustive Allosteric Signaling/Probing Map (ASM/APM), to identify potential allosteric sites, and to facilitate effector design. Here, we demonstrate some recent work on applying our broadly applicable framework to different aspects of allostery. First, analysis of communication between different sites/regions of the Spike protein from SARS-CoV-2 revealed mutations harbored by variants of concern, as well as glycosylation, that originate strong signaling to the distant receptor-binding domain despite the separation. Using reverse perturbation of allosteric communication and ASM/APM, we identified potential druggable sites that can induce tunable allosteric responses in different functional regions of Spike. Second, while the strengths of allosteric medicines are widely recognized, rational design of effectors remains a challenging problem. We demonstrated with GPCRs and kinases that effector design should begin with the search/design for latent/non-natural binding sites, followed by fragment-based design of ligands, and consequently mutual adjustments of site-ligand pairs to obtain and tune the desired binding affinity and allosteric signals. Third, rapid progress in harnessing allostery calls for an understanding of how communication is established by different structural elements and how it can be modified. We obtained a picture of conserved allosteric communication characteristic in major folds, alterations of structure-driven signaling via sequence-determined divergence to distinct functions, and its diversification in multi-domain proteins and oligomers, which will facilitate engineering/design of allosteric communication.

Probing GPCR allosteric activation and biased signaling with rigidity propagation and geometric Monte-Carlo simulations.

GPCR diverse signaling pathways are driven by complex pharmacology arising from a functional conformational ensemble and allosteric modifications rarely captured by structural methods. Our allostery algorithms, which are based on mathematical rigidity theory, provide a mechanical interpretation of allosteric signaling and are designed to predict if perturbation of rigidity at one site of the protein can propagate across a network and in turn cause a change in rigidity at a second distant site, resulting in allosteric transmission. We model the GPCR as a constraint network (graph) consisting of nodes (atoms) and edges (i.e., constraints such as covalent bonds, electrostatic interactions, hydrogen bonds, and hydrophobic contacts). Starting with a set of known GPCR structures we can detect how ligands at either orthosteric site or other regions trigger rigidity changes which propagate to functionally important regions (such as G-protein interface or GDP pocket) in turn cause a rearrangement and alteration of the shape of the cytoplasmic binding region. In collaborations with NMR experimentalists, 19FNMR and computational allostery predictions was used to delineate allostery and distinct key functional activation and precoupled intermediate states in A2AR complexed with heterotrimeric G-protein. NMR showed that binding of G-protein stabilizes a precoupled activation intermediate state and two distinct active states which facilitate nucleotide exchange by full or partial agonists. Rigidity theory allostery algorithms showed Gbg is critical in facilitating allostery within the ternary complex. Recent work investigates the selectivity and efficacy in A2AR in the presence of different G protein subtypes using simulations, allostery predictions and NMR.

The Many (Inter)faces of Anti-CRISPRs: Modulation of CRISPR-Cas Structure and Dynamics by Mechanistically Diverse Inhibitors.

The discovery of protein inhibitors of CRISPR-Cas systems, called anti-CRISPRs (Acrs), has enabled the development of highly controllable and precise CRISPR-Cas tools. Anti-CRISPRs share very little structural or sequential resemblance to each other or to other proteins, which raises intriguing questions regarding their modes of action. Many structure-function studies have shed light on the mechanism(s) of Acrs, which can act as orthosteric or allosteric inhibitors of CRISPR-Cas machinery, as well as enzymes that irreversibly modify CRISPR-Cas components. Only recently has the breadth of diversity of Acr structures and functions come to light, and this remains a rapidly evolving field. Here, we draw attention to a plethora of Acr mechanisms, with particular focus on how their action toward Cas proteins modulates conformation, dynamic (allosteric) signaling, nucleic acid binding, and cleavage ability.

Allosteric Signaling in PDZ Energetic Networks: Embedding Error Analysis.

Allosteric signaling in proteins has been known for some half a century, yet how the signal traverses the protein remains an active area of research. Recently, the importance of electrostatics to achieve long-range signaling has become increasingly appreciated. Our laboratory has been working on developing network approaches to capture such interactions. In this study, we turn our attention to the well-studied allosteric model protein, PDZ. We study the allosteric dynamics on a per-residue basis in key constructs involving the PDZ domain, its allosteric effector, and its peptide ligand. We utilize molecular dynamics trajectories to create the networks for the constructs to explore the allosteric effect by plotting the heat kernel results onto axes defined by principal components. We introduce a new metric to quantitate the volume sampled by a residue in the latent space. We relate our findings to PDZ and the greater field of allostery.

Structural basis of broad-spectrum β-lactam resistance in Staphylococcus aureus

Broad-spectrum β-lactam antibiotic resistance in Staphylococcus aureus is a global healthcare burden1,2. In clinical strains, resistance is largely controlled by BlaR13, a receptor that senses β-lactams through the acylation of its sensor domain, inducing transmembrane signalling and activation of the cytoplasmic-facing metalloprotease domain4. The metalloprotease domain has a role in BlaI derepression, inducing blaZ (β-lactamase PC1) and mecA (β-lactam-resistant cell-wall transpeptidase PBP2a) expression3–7. Here, overcoming hurdles in isolation, we show that BlaR1 cleaves BlaI directly, as necessary for inactivation, with no requirement for additional components as suggested previously8. Cryo-electron microscopy structures of BlaR1—the wild type and an autocleavage-deficient F284A mutant, with or without β-lactam—reveal a domain-swapped dimer that we suggest is critical to the stabilization of the signalling loops within. BlaR1 undergoes spontaneous autocleavage in cis between Ser283 and Phe284 and we describe the catalytic mechanism and specificity underlying the self and BlaI cleavage. The structures suggest that allosteric signalling emanates from β-lactam-induced exclusion of the prominent extracellular loop bound competitively in the sensor-domain active site, driving subsequent dynamic motions, including a shift in the sensor towards the membrane and accompanying changes in the zinc metalloprotease domain. We propose that this enhances the expulsion of autocleaved products from the active site, shifting the equilibrium to a state that is permissive of efficient BlaI cleavage. Collectively, this study provides a structure of a two-component signalling receptor that mediates action—in this case, antibiotic resistance—through the direct cleavage of a repressor.

Probing conformational landscapes of binding and allostery in the SARS-CoV-2 omicron variant complexes using microsecond atomistic simulations and perturbation-based profiling approaches: hidden role of omicron mutations as modulators of allosteric signaling and epistatic relationships.

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 spike protein complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which can be contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using the dynamics-based mutational scanning of spike residues, we identified structural stability and binding affinity hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron mutations on allosteric interactions and communications in the complexes. The results of this analysis revealed specific roles of Omicron mutations as conformationally plastic and evolutionary adaptable modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes performed in the background of the original strain, we characterized regions of epistatic couplings that are centered around the binding affinity hotspots N501Y and Q498R. Our results dissected the vital role of these epistatic centers in regulating protein stability, efficient ACE2 binding and allostery which allows for accumulation of multiple Omicron immune escape mutations at other sites. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Study on the allosteric activation mechanism of SHP2 via elastic network models and neural relational inference molecular dynamics simulation.

As a ubiquitous protein tyrosine phosphatase, SHP2 is involved in PD-1/PD-L1 mediated tumor immune escape and undergoes substantial conformational changes. Therefore, it is considered an ideal target for tumor intervention. However, the allosteric mechanisms of SHP2 binding PD-1 intracellular ITIM/ITSM phosphopeptides remain unclear, which greatly hinders the development of novel structure-based anticancer allosteric inhibitors. In this work, the open and closed structural models of SHP2 are first constructed based on this knowledge; next their motion modes are investigated via elastic network models such as the Gaussian network model (GNM), anisotropic network model (ANM) and adaptive anisotropic network model (aANM); and finally, a possible allosteric signaling pathway is proposed using a neural relational inference molecular dynamics (NRI-MD) simulation embedded with an artificial intelligence (AI) strategy. In GNM and ANM, the N-SH2, C-SH2 and PTP domains all exhibit distinct dynamics partitions, and the N-SH2/C-SH2 regions show a rigid rotation relative to PTP. According to a series of intermediate snapshots given by aANM, N-SH2 is first identified with pY223 specifically, inducing a D'E-loop to change from β-sheets to random coils, and then, C-SH2 serves as a fulcrum to drive N-SH2 to rotate 110° completely away from the original active sites of PTP. Finally, a possible allosteric signaling-transfer path for SHP2, namely R220-R138-T108-R32, is proposed based on NRI-MD sampling. This work provides a possible allosteric mechanism of SHP2, which is helpful for the following design of novel allosteric inhibitors and is expected to be used in clinical synergies with PD-1 monoclonal antibody.

Structure-Based Function and Regulation of NCX Variants: Updates and Challenges.

The plasma-membrane homeostasis Na+/Ca2+ exchangers (NCXs) mediate Ca2+ extrusion/entry to dynamically shape Ca2+ signaling/in biological systems ranging from bacteria to humans. The NCX gene orthologs, isoforms, and their splice variants are expressed in a tissue-specific manner and exhibit nearly 104-fold differences in the transport rates and regulatory specificities to match the cell-specific requirements. Selective pharmacological targeting of NCX variants could benefit many clinical applications, although this intervention remains challenging, mainly because a full-size structure of eukaryotic NCX is unavailable. The crystal structure of the archaeal NCX_Mj, in conjunction with biophysical, computational, and functional analyses, provided a breakthrough in resolving the ion transport mechanisms. However, NCX_Mj (whose size is nearly three times smaller than that of mammalian NCXs) cannot serve as a structure-dynamic model for imitating high transport rates and regulatory modules possessed by eukaryotic NCXs. The crystal structures of isolated regulatory domains (obtained from eukaryotic NCXs) and their biophysical analyses by SAXS, NMR, FRET, and HDX-MS approaches revealed structure-based variances of regulatory modules. Despite these achievements, it remains unclear how multi-domain interactions can decode and integrate diverse allosteric signals, thereby yielding distinct regulatory outcomes in a given ortholog/isoform/splice variant. This article summarizes the relevant issues from the perspective of future developments.