Differences in allosteric communication pipelines in the inactive and active states of a GPCR

AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks

Allostery, the presence of functional interactions between distant parts of proteins, is a critical concept in the field of biochemistry and molecular biology, particularly in the context of protein function and regulation. Understanding the principles of allosteric regulation is essential for advancing our knowledge of biology and developing new therapeutic strategies. This paper presents AlloViz, an open-source Python package designed to quantitatively determine, analyse, and visually represent allosteric communication networks on the basis of molecular dynamics (MD) simulation data. The software integrates well-known techniques for understanding allosteric properties simplifying the process of accessing, rationalising, and representing protein allostery and communication routes. It overcomes the inefficiency of having multiple methods with heterogeneous implementations and showcases the advantages of using MD simulations and multiple replicas to obtain statistically sound information on protein dynamics; it also enables the calculation of "consensus-like" scores aggregating methods that consider multiple structural aspects of allosteric networks. We demonstrate the features of AlloViz on two proteins: β-arrestin 1, a key player for regulating G protein-coupled receptor (GPCR) signalling, and the protein tyrosine phosphatase 1B, an important pharmaceutical target for allosteric inhibitors. The software includes comprehensive documentation and examples, tutorials, and a user-friendly graphical interface.

SARS-CoV-2 3CLPro Dihedral Angles Reveal Allosteric Signaling

In allosteric proteins, identifying the pathways that signals take from allosteric ligand-binding sites to enzyme active sites or binding pockets and interfaces remains challenging. This avenue of research is motivated by the goals of understanding particular macromolecular systems of interest and creating general methods for their study. An especially important protein that is the subject of many investigations in allostery is the SARS-CoV-2 main protease (Mpro), which is necessary for coronaviral replication. It is both an attractive drug target and, due to intense interest in it for the development of pharmaceutical compounds, a gauge of the state-of-the-art approaches in studying protein inhibition. Here we develop a computational method for characterizing protein allostery and use it to study Mpro. We propose a role of the protein's C-terminal tail in allosteric modulation and warn of unintuitive traps that can plague studies of the role of protein dihedrals angles in transmitting allosteric signals.

Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling

Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces, it is challenging to determine which amino acid pair interactions are cooperative. In this work, we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with Gα subunits. Our results reveal six GPCR:Gα contacts that are common to the different Gα subtypes and show strong cooperativity in the formation of interface. Both the C terminus helix5 and the core of the G protein are codependent entities and play an important role in GPCR coupling. We show that a promiscuous GPCR coupling to different Gα subtypes, makes all the GPCR:Gα contacts that are specific to each Gα subtype (Gαs, Gαi, and Gαq). This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.

State-dependent dynamics of extramembrane domains in the β2 -adrenergic receptor

G protein-coupled receptors (GPCRs) are membrane-bound signaling proteins that play an essential role in cellular signaling processes. Due to their intrinsic function of transmitting internal signals in response to external cues, these receptors are adapted to be highly dynamic in nature. The β2 -adrenergic receptor (β2 AR) is a representative member of the family that has been extensively analyzed in terms of its structure and activation. Although the structure of the transmembrane domain has been characterized in the different functional states of the receptor, the conformational dynamics of the extramembrane domains, especially the intrinsically disordered regions are still emerging. In this study, we analyze the state-dependent dynamics of extramembrane domains of β2 AR using atomistic molecular dynamics simulations. We introduce a parameter, the residue excess dynamics that allows us to better quantify receptor dynamics. Using this measure, we show that the dynamics of the extramembrane domains are sensitive to the receptor state. Interestingly, the ligand-bound intermediateR ' state shows the maximal dynamics compared to either the active R*G or inactive R states. Ligand binding appears to be correlated with high residue excess dynamics that are dampened upon G protein coupling. The intracellular loop-3 (ICL3) domain has a tendency to flip towards the membrane upon ligand binding, which could contribute to receptor "priming." We highlight an important ICL1-helix-8 interplay that is broken in the ligand-bound state but is retained in the active state. Overall, our study highlights the importance of characterizing the functional dynamics of the GPCR loop domains.

Biased Signaling in Mutated Variants of β2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

Bayesian network models identify co-operative GPCR:G protein interactions that contribute to G protein coupling

Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior of interface interactions and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces it is challenging to determine which amino acid pair interactions are cooperative. In this work we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with G proteins. Our results reveal a strong co-dependency in the formation of interface GPCR:G protein contacts. This observation indicates that cooperativity of GPCR:G protein interactions is necessary for the coupling and selectivity of G proteins and is thus critical for receptor function. We have identified subnetworks containing polar and hydrophobic interactions that are common among multiple GPCRs coupling to different G protein subtypes (Gs, Gi and Gq). These common subnetworks along with G protein-specific subnetworks together confer selectivity to the G protein coupling. This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.

Unraveling allostery within the angiotensin II type 1 receptor for Gαq and β-arrestin coupling

G protein-coupled receptors engage both G proteins and β-arrestins, and their coupling can be biased by ligands and mutations. Here, to resolve structural elements and mechanisms underlying effector coupling to the angiotensin II (AngII) type 1 receptor (AT1R), we combined alanine scanning mutagenesis of the entire sequence of the receptor with pharmacological profiling of Gαq and β-arrestin engagement to mutant receptors and molecular dynamics simulations. We showed that Gαq coupling to AT1R involved a large number of residues spread across the receptor, whereas fewer structural regions of the receptor contributed to β-arrestin coupling regulation. Residue stretches in transmembrane domain 4 conferred β-arrestin bias and represented an important structural element in AT1R for functional selectivity. Furthermore, we identified allosteric small-molecule binding sites that were enclosed by communities of residues that produced biased signaling when mutated. Last, we showed that allosteric communication within AT1R emanating from the Gαq coupling site spread beyond the orthosteric AngII-binding site and across different regions of the receptor, including currently unresolved structural regions. Our findings reveal structural elements and mechanisms within AT1R that bias Gαq and β-arrestin coupling and that could be harnessed to design biased receptors for research purposes and to develop allosteric modulators.

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

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

Computational design of dynamic receptor-peptide signaling complexes applied to chemotaxis

Engineering protein biosensors that sensitively respond to specific biomolecules by triggering precise cellular responses is a major goal of diagnostics and synthetic cell biology. Previous biosensor designs have largely relied on binding structurally well-defined molecules. In contrast, approaches that couple the sensing of flexible compounds to intended cellular responses would greatly expand potential biosensor applications. Here, to address these challenges, we develop a computational strategy for designing signaling complexes between conformationally dynamic proteins and peptides. To demonstrate the power of the approach, we create ultrasensitive chemotactic receptor-peptide pairs capable of eliciting potent signaling responses and strong chemotaxis in primary human T cells. Unlike traditional approaches that engineer static binding complexes, our dynamic structure design strategy optimizes contacts with multiple binding and allosteric sites accessible through dynamic conformational ensembles to achieve strongly enhanced signaling efficacy and potency. Our study suggests that a conformationally adaptable binding interface coupled to a robust allosteric transmission region is a key evolutionary determinant of peptidergic GPCR signaling systems. The approach lays a foundation for designing peptide-sensing receptors and signaling peptide ligands for basic and therapeutic applications.

Distinct activation mechanisms regulate subtype selectivity of Cannabinoid receptors

Design of cannabinergic subtype selective ligands is challenging because of high sequence and structural similarities of cannabinoid receptors (CB₁ and CB₂). We hypothesize that the subtype selectivity of designed selective ligands can be explained by the ligand binding to the conformationally distinct states between cannabinoid receptors. Analysis of ~ 700 μs of unbiased simulations using Markov state models and VAMPnets identifies the similarities and distinctions between the activation mechanism of both receptors. Structural and dynamic comparisons of metastable intermediate states allow us to observe the distinction in the binding pocket volume change during CB₁ and CB₂ activation. Docking analysis reveals that only a few of the intermediate metastable states of CB₁ show high affinity towards CB₂ selective agonists. In contrast, all the CB₂ metastable states show a similar affinity for these agonists. These results mechanistically explain the subtype selectivity of these agonists by deciphering the activation mechanism of cannabinoid receptors.

Intermediate-aided allostery mechanism for α-glucosidase by Xanthene-11v as an inhibitor using residue interaction network analysis

Exploring allosteric inhibition and the discovery of new inhibitor binding sites are important studies in protein regulation mechanisms and drug discovery. Structural and network-based analyses of trajectories resulting from molecular dynamics (MD) simulations have been developed to discover protein dynamics, landscape, functions, and allosteric regions. Here, an experimentally suggested non-competitive inhibitor, xanthene-11v, was considered to explore its allosteric inhibition mechanism in α-glucosidase MAL12. Comparative structural and network analyses were applied to eight 250 ns independent MD simulations, four of which were performed in the free state and four of which were performed in ligand-bound forms. Projected two-dimensional free energy landscapes (FEL) were constructed from the probabilistic distribution of conformations along the first two principal components. The post-simulation analyses of the coordinates, side-chain torsion angles, non-covalent interaction networks, network communities, and their centralities were performed on α-glucosidase conformations and the intermediate sub-states. Important communities of residues have been found that connect the allosteric site to the active site. Some of these residues like Thr307, Arg312, TYR344, ILE345, Phe357, Asp406, Val407, Asp408, and Leu436 are the key messengers in the transition pathway between allosteric and active sites. Evaluating the probability distribution of distances between gate residues including Val407 in one community and Phe158, and Pro65 in another community depicted the closure of this gate due to the inhibitor binding. Six macro states of protein were deduced from the topology of FEL and analysis of conformational preference of free and ligand-bound systems to these macro states shows a combination of lock-and-key, conformational selection, and induced fit mechanisms are effective in ligand binding. All these results reveal structural states, allosteric mechanisms, and key players in the inhibition pathway of α-glucosidase by xanthene-11v.

Activation mechanism of the human Smoothened receptor

Smoothened (SMO) is a membrane protein of the class F subfamily of G protein-coupled receptors (GPCRs) and maintains homeostasis of cellular differentiation. SMO undergoes conformational change during activation, transmitting the signal across the membrane, making it amenable to bind to its intracellular signaling partner. Receptor activation has been studied at length for class A receptors, but the mechanism of class F receptor activation remains unknown. Agonists and antagonists bound to SMO at sites in the transmembrane domain (TMD) and the cysteine-rich domain have been characterized, giving a static view of the various conformations SMO adopts. Although the structures of the inactive and active SMO outline the residue-level transitions, a kinetic view of the overall activation process remains unexplored for class F receptors. We describe SMO's activation process in atomistic detail by performing 300 μs of molecular dynamics simulations and combining it with Markov state model theory. A molecular switch, conserved across class F and analogous to the activation-mediating D-R-Y motif in class A receptors, is observed to break during activation. We also show that this transition occurs in a stage-wise movement of the transmembrane helices: TM6 first, followed by TM5. To see how modulators affect SMO activity, we simulated agonist and antagonist-bound SMO. We observed that agonist-bound SMO has an expanded hydrophobic tunnel in SMO's core TMD, whereas antagonist-bound SMO shrinks this tunnel, further supporting the hypothesis that cholesterol travels through a tunnel inside Smoothened to activate it. In summary, this study elucidates the distinct activation mechanism of class F GPCRs and shows that SMO's activation process rearranges the core TMD to open a hydrophobic conduit for cholesterol transport.

Catalytic site mutations confer multiple states of G protein activation

Heterotrimeric guanine nucleotide-binding proteins (G proteins) that function as molecular switches for cellular growth and metabolism are activated by GTP and inactivated by GTP hydrolysis. In uveal melanoma, a conserved glutamine residue critical for GTP hydrolysis in the G protein α subunit is often mutated in Gαq or Gα11 to either leucine or proline. In contrast, other glutamine mutations or mutations in other Gα subtypes are rare. To uncover the mechanism of the genetic selection and the functional role of this glutamine residue, we analyzed all possible substitutions of this residue in multiple Gα isoforms. Through cell-based measurements of activity, we showed that some mutants were further activated and inactivated by G protein-coupled receptors. Through biochemical, molecular dynamics, and nuclear magnetic resonance-based structural studies, we showed that the Gα mutants were functionally distinct and conformationally diverse, despite their shared inability to hydrolyze GTP. Thus, the catalytic glutamine residue contributes to functions beyond GTP hydrolysis, and these functions include subtype-specific, allosteric modulation of receptor-mediated subunit dissociation. We conclude that G proteins do not function as simple on-off switches. Rather, signaling emerges from an ensemble of active states, a subset of which are favored in disease and may be uniquely responsive to receptor-directed ligands.

Biased agonists differentially modulate the receptor conformation ensembles in Angiotensin II type 1 receptor

The structural features that contribute to the efficacy of biased agonists targeting G protein-coupled receptors (GPCRs) towards G proteins or β-arrestin (β-arr) signaling pathways is nebulous, although such knowledge is critical in designing biased ligands. The dynamics of the agonist-GPCR complex is one of the critical factors in determining agonist bias. Angiotensin II type I receptor (AT1R) is an ideal model system to study the molecular basis of bias since it has multiple β-arr2 and Gq protein biased agonists as well as experimentally solved three dimensional structures. Using Molecular Dynamics (MD) simulations for the Angiotensin II type I receptor (AT1R) bound to ten different agonists, we infer that the agonist bound receptor samples conformations with different relative weights, from both the inactive and active state ensembles of the receptor. This concept is perhaps extensible to other class A GPCRs. Such a weighted mixed ensemble recapitulates the inter-residue distance distributions measured for different agonists bound AT1R using DEER experiments. The ratio of the calculated relative strength of the allosteric communication to β-arr2 vs Gq coupling sites scale similarly to the experimentally measured bias factors. Analysis of the inter-residue distance distributions of the activation microswitches involved in class A GPCR activation suggests that β-arr2 biased agonists turn on different combination of microswitches with different relative strengths of activation. We put forth a model that activation microswitches behave like rheostats that tune the relative efficacy of the biased agonists toward the two signaling pathways. Finally, based on our data we propose that the agonist specific residue contacts in the binding site elicit a combinatorial response in the microswitches that in turn differentially modulate the receptor conformation ensembles resulting in differences in coupling to Gq and β-arrestin.

Allosteric Modulators of Dopamine D2 Receptors for Fine-Tuning of Dopaminergic Neurotransmission in CNS Diseases: Overview, Pharmacology, Structural Aspects and Synthesis

Allosteric modulation of G protein-coupled receptors (GPCRs) is nowadays a hot topic in medicinal chemistry. Allosteric modulators, i.e., compounds which bind in a receptor site topologically distinct from orthosteric sites, exhibit a number of advantages. They are more selective, safer and display a ceiling effect which prevents overdosing. Allosteric modulators of dopamine D₂ receptor are potential drugs against a number of psychiatric and neurological diseases, such as schizophrenia and Parkinson's disease. In this review, an insightful summary of current research on D₂ receptor modulators is presented, ranging from their pharmacology and structural aspects of ligand-receptor interactions to their synthesis.

Hotspot Identification and Drug Design of Protein-Protein Interaction Modulators Using the Fragment Molecular Orbital Method

Protein-protein interactions (PPIs) are essential for the function of many proteins. Aberrant PPIs have the potential to lead to disease, making PPIs promising targets for drug discovery. There are over 64,000 PPIs in the human interactome reference database; however, to date, very few PPI modulators have been approved for clinical use. Further development of PPI-specific therapeutics is highly dependent on the availability of structural data and the existence of reliable computational tools to explore the interface between two interacting proteins. The fragment molecular orbital (FMO) quantum mechanics method offers comprehensive and computationally inexpensive means of identifying the strength (in kcal/mol) and the chemical nature (electrostatic or hydrophobic) of the molecular interactions taking place at the protein-protein interface. We have integrated FMO and PPI exploration (FMO-PPI) to identify the residues that are critical for protein-protein binding (hotspots). To validate this approach, we have applied FMO-PPI to a dataset of protein-protein complexes representing several different protein subfamilies and obtained FMO-PPI results that are in agreement with published mutagenesis data. We observed that critical PPIs can be divided into three major categories: interactions between residues of two proteins (intermolecular), interactions between residues within the same protein (intramolecular), and interactions between residues of two proteins that are mediated by water molecules (water bridges). We extended our findings by demonstrating how this information obtained by FMO-PPI can be utilized to support the structure-based drug design of PPI modulators (SBDD-PPI).

In Silico Study of Allosteric Communication Networks in GPCR Signaling Bias

Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias.

Dynamics and Mechanistic Underpinnings to Pharmacology of Class A GPCRs - An NMR Perspective

One-third of current pharmaceuticals target G protein-coupled receptors (GPCRs), the largest receptor superfamily in humans and mediators of diverse physiological processes. This review summarizes the recent progress in GPCR structural dynamics, focusing on class A receptors and insights derived from nuclear magnetic resonance (NMR) and other spectroscopic techniques. We describe the structural aspects of GPCR activation and the various pharmacological models that capture aspects of receptor signaling behaviour. Spectroscopic studies revealed that receptors and their signaling complexes are dynamic allosteric systems that sample multiple functional states under basal conditions. The distribution of states within the conformational ensemble and the kinetics of transitions between states are regulated through the binding of ligands, allosteric modulators, and the membrane environment. This ensemble view of GPCRs provides a mechanistic framework for understanding many of the pharmacological phenomena associated with receptor signaling, such as basal activity, efficacy, and functional bias.

Activation mechanism of the class D fungal GPCR dimer Ste2

The fungal class D1 G-protein-coupled receptor (GPCR) Ste2 has a different arrangement of transmembrane helices compared with mammalian GPCRs and a distinct mode of coupling to the heterotrimeric G protein Gpa1-Ste2-Ste181. In addition, Ste2 lacks conserved sequence motifs such as DRY, PIF and NPXXY, which are associated with the activation of class A GPCRs2. This suggested that the activation mechanism of Ste2 may also differ. Here we determined structures of Saccharomyces cerevisiae Ste2 in the absence of G protein in two different conformations bound to the native agonist α-factor, bound to an antagonist and without ligand. These structures revealed that Ste2 is indeed activated differently from other GPCRs. In the inactive state, the cytoplasmic end of transmembrane helix H7 is unstructured and packs between helices H1-H6, blocking the G protein coupling site. Agonist binding results in the outward movement of the extracellular ends of H6 and H7 by 6 Å. On the intracellular surface, the G protein coupling site is formed by a 20 Å outward movement of the unstructured region in H7 that unblocks the site, and a 12 Å inward movement of H6. This is a distinct mechanism in GPCRs, in which the movement of H6 and H7 upon agonist binding facilitates G protein coupling.

Mechanistic Origin of Partial Agonism of Tetrahydrocannabinol for Cannabinoid Receptors

Cannabinoid receptor 1 (CB₁) is a therapeutically relevant drug target for controlling pain, obesity, and other central nervous system disorders. However, full agonists and antagonists of CB₁ have been reported to cause serious side effects in patients. Therefore, partial agonists have emerged as a viable alternative as they can mitigate overstimulation and side effects. One of the key bottlenecks in the design of partial agonists, however, is the lack of understanding of the molecular mechanism of partial agonism itself. In this study, we examine two mechanistic hypotheses for the origin of partial agonism in cannabinoid receptors and predict the mechanistic basis of partial agonism exhibited by Δ⁹-Tetrahydrocannabinol (THC) against CB₁. In particular, we inspect whether partial agonism emerges from the ability of THC to bind in both agonist and antagonist-binding poses or from its ability to only partially activate the receptor. We used extensive molecular dynamics simulations and Markov state modeling to capture the THC binding in both antagonist and agonist-binding poses in the CB₁ receptor. Furthermore, we predict that binding of THC in the agonist-binding pose leads to rotation of toggle switch residues and causes partial outward movement of intracellular transmembrane helix 6 (TM6). Our simulations also suggest that the alkyl side chain of THC plays a crucial role in determining partial agonism by stabilizing the ligand in the agonist and antagonist-like poses within the pocket. Taken together, this study provides important insights into the mechanistic origin of the partial agonism of THC.

Phenylalanine 193 in Extracellular Loop 2 of the β 2-Adrenergic Receptor Coordinates β-Arrestin Interaction

G protein-coupled receptors (GPCRs) transduce a diverse variety of extracellular stimuli into intracellular signaling. These receptors are the most clinically productive drug targets at present. Despite decades of research on the signaling consequences of molecule-receptor interactions, conformational components of receptor-effector interactions remain incompletely described. The β ₂-adrenergic receptor (β ₂AR) is a prototypical and extensively studied GPCR that can provide insight into this aspect of GPCR signaling thanks to robust structural data and rich pharmacopeia. Using bioluminescence resonance energy transfer -based biosensors, second messenger assays, and biochemical techniques, we characterize the properties of β ₂AR-F193A. This single point mutation in extracellular loop 2 of the β ₂AR is sufficient to intrinsically bias the β ₂AR away from β-arrestin interaction and demonstrates altered regulatory outcomes downstream of this functional selectivity. This study highlights the importance of extracellular control of intracellular response to stimuli and suggests a previously undescribed role for the extracellular loops of the receptor and the extracellular pocket formed by transmembrane domains 2, 3, and 7 in GPCR regulation that may contribute to biased signaling at GPCRs. SIGNIFICANCE STATEMENT: The role of extracellular G protein-coupled receptor (GPCR) domains in mediating intracellular interactions is poorly understood. We characterized the effects of extracellular loop mutations on agonist-promoted interactions of GPCRs with G protein and β-arrestin. Our studies reveal that F193 in extracellular loop 2 in the β₂-adrenergic receptor mediates interactions with G protein and β-arrestin with a biased loss of β-arrestin binding. These results provide new insights on the role of the extracellular domain in differentially modulating intracellular interactions with GPCRs.

Allosteric Effect of Nanobody Binding on Ligand-Specific Active States of the β2 Adrenergic Receptor

Nanobody binding stabilizes G-protein-coupled receptors (GPCR) in a fully active state and modulates their affinity for bound ligands. However, the atomic-level basis for this allosteric regulation remains elusive. Here, we investigate the conformational changes induced by the binding of a nanobody (Nb80) on the active-like β2 adrenergic receptor (β2AR) via enhanced sampling molecular dynamics simulations. Dimensionality reduction analysis shows that Nb80 stabilizes structural features of the β2AR with an ∼14 Å outward movement of transmembrane helix 6 and a close proximity of transmembrane (TM) helices 5 and 7, and favors the fully active-like conformation of the receptor, independent of ligand binding, in contrast to the conditions under which no intracellular binding partner is bound, in which case the receptor is only stabilized in an intermediate-active state. This activation is supported by the residues located at hotspots located on TMs 5, 6, and 7, as shown by supervised machine learning methods. Besides, ligand-specific subtle differences in the conformations assumed by intracellular loop 2 and extracellular loop 2 are captured from the trajectories of various ligand-bound receptors in the presence of Nb80. Dynamic network analysis further reveals that Nb80 binding triggers tighter and stronger local communication networks between the Nb80 and the ligand-binding sites, primarily involving residues around ICL2 and the intracellular end of TM3, TM5, TM6, as well as ECL2, ECL3, and the extracellular ends of TM6 and TM7. In particular, we identify unique allosteric signal transmission mechanisms between the Nb80-binding site and the extracellular domains in conformations modulated by a full agonist, BI167107, and a G-protein-biased partial agonist, salmeterol, involving mainly TM1 and TM2, and TM5, respectively. Altogether, our results provide insights into the effect of intracellular binding partners on the GPCR activation mechanism, which should be taken into account in structure-based drug discovery.

Allosteric communication regulates ligand-specific GPCR activity

G protein-coupled receptors (GPCRs) are membrane-bound proteins that are ubiquitously expressed in many cell types and take part in mediating multiple signaling pathways. GPCRs are dynamic proteins and exist in an equilibrium between an ensemble of conformational states such as inactive and fully active states. This dynamic nature of GPCRs is one of the factors that confers their basal activity even in the absence of any ligand-mediated activation. Ligands selectively bind and stabilize a subset of the conformations from the ensemble leading to a shift in the equilibrium toward the inactive or the active state depending on the nature of the ligand. This ligand-selective effect is achieved through allosteric communication between the ligand binding site and G protein or β-arrestin coupling site. Similarly, the G protein coupling to the receptor exerts the allosteric effect on the ligand binding region leading to increased binding affinity for agonists and decreased affinity for antagonists or inverse agonists. In this review, we enumerate the current state of our understanding of the mechanism of allosteric communication in GPCRs with a specific focus on the critical role of computational methods in delineating the residues involved in allosteric communication. Analyzing allosteric communication mechanism using molecular dynamics simulations has revealed (a) a structurally conserved mechanism of allosteric communication that regulates the G protein coupling, (b) a rational structure-based approach to designing selective ligands, and (c) an approach to designing allosteric GPCR mutants that are either ligand and G protein or β-arrestin selective.

β2-adrenoceptor ligand efficacy is tuned by a two-stage interaction with the Gαs C terminus

Classical pharmacological models have incorporated an "intrinsic efficacy" parameter to capture system-independent effects of G protein-coupled receptor (GPCR) ligands. However, the nonlinear serial amplification of downstream signaling limits quantitation of ligand intrinsic efficacy. A recent biophysical study has characterized a ligand "molecular efficacy" that quantifies the influence of ligand-dependent receptor conformation on G protein activation. Nonetheless, the structural translation of ligand molecular efficacy into G protein activation remains unclear and forms the focus of this study. We first establish a robust, accessible, and sensitive assay to probe GPCR interaction with G protein and the Gα C terminus (G-peptide), an established structural determinant of G protein selectivity. We circumvent the need for extensive purification protocols by the single-step incorporation of receptor and G protein elements into giant plasma membrane vesicles (GPMVs). We use previously established SPASM FRET sensors to control the stoichiometry and effective concentration of receptor-G protein interactions. We demonstrate that GPMV-incorporated sensors (v-SPASM sensors) provide enhanced dynamic range, expression-insensitive readout, and a reagent level assay that yields single point measurements of ligand molecular efficacy. Leveraging this technology, we establish the receptor-G-peptide interaction as a sufficient structural determinant of this receptor-level parameter. Combining v-SPASM measurements with molecular dynamics (MD) simulations, we elucidate a two-stage receptor activation mechanism, wherein receptor-G-peptide interactions in an intermediate orientation alter the receptor conformational landscape to facilitate engagement of a fully coupled orientation that tunes G protein activation.

Loss of a water-mediated network results in reduced agonist affinity in a β2-adrenergic receptor clinical variant

The β₂-adrenergic receptor (β₂AR) is a member of the G protein-coupled receptor (GPCR) family that is an important drug target for asthma and COPD. Clinical studies coupled with biochemical data have identified a critical receptor variant, Thr164Ile, to have a reduced response to agonist-based therapy, although the molecular mechanism underlying this seemingly "non-deleterious" substitution is not clear. Here, we couple molecular dynamics simulations with network analysis and free-energy calculations to identify the molecular determinants underlying the differential drug response. We are able to identify hydration sites in the transmembrane domain that are essential to maintain the integrity of the binding site but are absent in the variant. The loss of these hydration sites in the variant correlates with perturbations in the intra-protein interaction network and rearrangements in the orthosteric ligand binding site. In conjunction, we observe an altered binding and reduced free energy of a series of agonists, in line with experimental trends. Our work identifies a functional allosteric pathway connected by specific hydration sites in β₂AR that has not been reported before and provides insight into water-mediated networks in GPCRs in general. Overall, the work is one of the first step towards developing variant-specific potent and selective agonists.

Dynamical nonequilibrium molecular dynamics reveals the structural basis for allostery and signal propagation in biomolecular systems

ABSTRACT

A dynamical approach to nonequilibrium molecular dynamics (D-NEMD), proposed in the 1970s by Ciccotti et al., is undergoing a renaissance and is having increasing impact in the study of biological macromolecules. This D-NEMD approach, combining MD simulations in stationary (in particular, equilibrium) and nonequilibrium conditions, allows for the determination of the time-dependent structural response of a system using the Kubo-Onsager relation. Besides providing a detailed picture of the system's dynamic structural response to an external perturbation, this approach also has the advantage that the statistical significance of the response can be assessed. The D-NEMD approach has been used recently to identify a general mechanism of inter-domain signal propagation in nicotinic acetylcholine receptors, and allosteric effects in β -lactamase enzymes, for example. It complements equilibrium MD and is a very promising approach to identifying and analysing allosteric effects. Here, we review the D-NEMD approach and its application to biomolecular systems, including transporters, receptors, and enzymes.

Network Re-Wiring During Allostery and Protein-Protein Interactions: A Graph Spectral Approach

The process of allostery is often guided by subtle changes in the non-covalent interactions between residues of a protein. These changes may be brought about by minor perturbations by natural processes like binding of a ligand or protein-protein interaction. The challenge lies in capturing minute changes at the residue interaction level and following their propagation at local as well as global distances. While macromolecular effects of the phenomenon of allostery are inferred from experiments, a computational microscope can elucidate atomistic-level details leading to such macromolecular effects. Network formalism has served as an attractive means to follow this path and has been pursued further for the past couple of decades. In this chapter some concepts and methods are summarized, and recent advances are discussed. Specifically, the changes in strength of interactions (edge weight) and their repercussion on the overall protein organization (residue clustering) are highlighted. In this review, we adopt a graph spectral method to probe these subtle changes in a quantitative manner. Further, the power of this method is demonstrated for capturing re-ordering of side-chain interactions in response to ligand binding, which culminates into formation of a protein-protein complex in β₂-adrenergic receptors.

Predicted Mode of Binding to and Allosteric Modulation of the μ-Opioid Receptor by Kratom's Alkaloids with Reported Antinociception In Vivo

Pain management devoid of serious opioid adverse effects is still far from reach despite vigorous research and development efforts. Alternatives to classical opioids have been sought for years, and mounting reports of individuals finding pain relief with kratom have recently intensified research on this natural product. Although the composition of kratom is complex, the pharmacological characterization of its most abundant alkaloids has drawn attention to three molecules in particular, owing to their demonstrated antinociceptive activity and limited side effects in vivo. These three molecules are mitragynine (MG), its oxidized active metabolite, 7-hydroxymitragynine (7OH), and the indole-to-spiropseudoindoxy rearrangement product of MG known as mitragynine pseudoindoxyl (MP). Although these three alkaloids have been shown to preferentially activate the G protein signaling pathway by binding and allosterically modulating the μ-opioid receptor (MOP), a molecular level understanding of this process is lacking and yet important for the design of improved therapeutics. The molecular dynamics study and experimental validation reported here provide an atomic level description of how MG, 7OH, and MP bind and allosterically modulate the MOP, which can eventually guide structure-based drug design of improved therapeutics.

β-Arrestin as a Therapeutic Target in Heart Failure

Heart failure is a major source of morbidity and mortality, driven, in part, by maladaptive sympathetic hyperactivity in response to poor cardiac output. Current therapies target β-adrenergic and angiotensin II G protein-coupled receptors to reduce adverse cardiac remodeling and improve clinical outcomes; however, there is a pressing need for new therapeutic approaches to preserve cardiac function. β-arrestin is a multifunctional protein which has come under analysis in recent years as a key player in G protein-coupled receptor signal transduction and a potential therapeutic target in heart failure. β-arrestin attenuates β-adrenergic and angiotensin II receptor signaling to limit the deleterious response to excessive sympathetic stimulation while simultaneously transactivating cardioprotective signaling cascades that preserve cardiac structure and function in response to injury. β-arrestin signaling may provide unique advantages compared to classic heart failure treatment approaches, but a number of challenges currently limit clinical applications. In this review, we discuss the role and functions of β-arrestin and the current attempts to develop G protein-coupled receptor agonists biased towards β-arrestin activation. Furthermore, we examine the functional diversity of cardiac β-arrestin isotypes to explore key considerations in the promise of β-arrestin as a pharmacotherapeutic target in heart failure.

Structure and Dynamics of GPCRs in Lipid Membranes: Physical Principles and Experimental Approaches

Over the past decade, the vast amount of information generated through structural and biophysical studies of GPCRs has provided unprecedented mechanistic insight into the complex signalling behaviour of these receptors. With this recent information surge, it has also become increasingly apparent that in order to reproduce the various effects that lipids and membranes exert on the biological function for these allosteric receptors, in vitro studies of GPCRs need to be conducted under conditions that adequately approximate the native lipid bilayer environment. In the first part of this review, we assess some of the more general effects that a membrane environment exerts on lipid bilayer-embedded proteins such as GPCRs. This is then followed by the consideration of more specific effects, including stoichiometric interactions with specific lipid subtypes. In the final section, we survey a range of different membrane mimetics that are currently used for in vitro studies, with a focus on NMR applications.

Atomic-Level Characterization of the Methadone-Stabilized Active Conformation of µ-Opioid Receptor

Methadone is a synthetic opioid agonist with notoriously unique properties, such as lower abuse liability and induced relief of withdrawal symptoms and drug cravings, despite acting on the same opioid receptors triggered by classic opioids-in particular the µ-opioid receptor (MOR). Its distinct pharmacologic properties, which have recently been attributed to the preferential activation of β-arrestin over G proteins, make methadone a standard-of-care maintenance medication for opioid addiction. Although a recent biophysical study suggests that methadone stabilizes different MOR active conformations from those stabilized by classic opioid drugs or G protein-biased agonists, how this drug modulates the conformational equilibrium of MOR and what specific active conformation of the receptor it stabilizes are unknown. Here, we report the results of submillisecond adaptive sampling molecular dynamics simulations of a predicted methadone-bound MOR complex and compare them with analogous data obtained for the classic opioid morphine and the G protein-biased ligand TRV130. The model, which is supported by existing experimental data, is analyzed using Markov state models and transfer entropy analysis to provide testable hypotheses of methadone-specific conformational dynamics and activation kinetics of MOR. SIGNIFICANCE STATEMENT: Opioid addiction has reached epidemic proportions in both industrialized and developing countries. Although methadone maintenance treatment represents an effective therapeutic approach for opioid addiction, it is not as widely used as needed. In this study, we contribute an atomic-level understanding of how methadone exerts its unique function in pursuit of more accessible treatments for opioid addiction. In particular, we present details of a methadone-specific active conformation of the µ-opioid receptor that has thus far eluded experimental structural characterization.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

An investigation into the allosteric mechanism of GPCR A2A adenosine receptor with trajectory-based information theory and complex network model

G protein-coupled receptors (GPCRs), a large superfamily of transmembrane (TM) proteins, allosterically transduce the signal of ligand binding in the extracellular (EC) domain to couple to effector proteins in the intracellular (IC) domain, therefore forming the largest class of drug targets. The A_2A adenosine receptor (A_2AAR), a class-A GPCR, has been extensively studied as it offers numerous possibilities for therapeutic applications. However, the mechanism of allosteric communication between EC and IC domains is not completely clear. In this work, we utilize torsional mutual information to quantify the correlated motions of residue pairs from its molecular dynamics (MD) simulation trajectories, and further use the complex network model to obtain allosteric pipelines and hubs. The identified allosteric communication pipelines mainly transmit the signal from EC domain to the cytoplasmic ends of TM helix 5 (TM5), TM6 and TM7. The allosteric hubs, mostly located at TM5, TM6 and TM7, play an important role in mediating allosteric signal transmission to keep the receptor rigid and prevent G protein from binding to IC domain, which can explain the reason why their mutations distant from ligand-binding site do not affect the ligand binding affinity but affect the ligand efficacy. Additionally, we identify the key residues located in antagonist ZM241385 binding pocket which mediate multiple allosteric pathways and have been experimentally proven to play a critical role in affecting the ligand potency. This study is helpful for understanding the allosteric communication mechanism of A_2AAR, and can provide valuable information for the structure-based drug design of GPCRs.Communicated by Ramaswamy H. Sarma.

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.

Distinctive communication networks in inactive states of β2 -adrenergic receptor: Mutual information and entropy transfer analysis

Mutual information and entropy transfer analysis employed on two inactive states of human beta-2 adrenergic receptor (β₂ -AR) unraveled distinct communication pathways. Previously, a so-called "highly" inactive state of the receptor was observed during 1.5 microsecond long molecular dynamics simulation where the largest intracellular loop (ICL3) was swiftly packed onto the G-protein binding cavity, becoming entirely inaccessible. Mutual information quantifying the degree of correspondence between backbone-C_α fluctuations was mostly shared between intra- and extra-cellular loop regions in the original inactive state, but shifted to entirely different regions in this latest inactive state. Interestingly, the largest amount of mutual information was always shared among the mobile regions. Irrespective of the conformational state, polar residues always contributed more to mutual information than hydrophobic residues, and also the number of polar-polar residue pairs shared the highest degree of mutual information compared to those incorporating hydrophobic residues. Entropy transfer, quantifying the correspondence between backbone-C_α fluctuations at different timesteps, revealed a distinctive pathway directed from the extracellular site toward intracellular portions in this recently exposed inactive state for which the direction of information flow was the reverse of that observed in the original inactive state where the mobile ICL3 and its intracellular surroundings drove the future fluctuations of extracellular regions.

Probing the correlation between ligand efficacy and conformational diversity at the α1A-adrenoreceptor reveals allosteric coupling of its microswitches

G protein-coupled receptors (GPCRs) use a series of conserved microswitches to transmit signals across the cell membrane via an allosteric network encompassing the ligand-binding site and the G protein-binding site. Crystal structures of GPCRs provide snapshots of their inactive and active states, but poorly describe the conformational dynamics of the allosteric network that underlies GPCR activation. Here, we analyzed the correlation between ligand binding and receptor conformation of the α1A-adrenoreceptor, a GPCR that stimulates smooth muscle contraction in response to binding noradrenaline. NMR of [13CϵH3]methionine-labeled α1A-adrenoreceptor variants, each exhibiting differing signaling capacities, revealed how different classes of ligands modulate the conformational equilibria of this receptor. [13CϵH3]Methionine residues near the microswitches exhibited distinct states that correlated with ligand efficacies, supporting a conformational selection mechanism. We propose that allosteric coupling among the microswitches controls the conformation of the α1A-adrenoreceptor and underlies the mechanism of ligand modulation of GPCR signaling in cells.

Electrostatic Switching Controls Channel Dynamics of the Sensor Protein VirB10 in A. tumefaciens Type IV Secretion System

Type IV secretion systems are large nanomachines assembled across the bacterial cell envelope for effector translocation and conjugation. VirB10 traverses the inner and outer membranes, sensing cellular signals for coordinating the conformational switch for pilus biogenesis and/or secretion. Mutations uncoupling secretion from pilus biogenesis were identified in Agrobacterium tumefaciens VirB10 including a gating defect mutation G272R that made VirB10 unresponsive to intracellular ATP, causing unregulated secretion of VirE2 in a contact-independent manner. Comparative long-timescale molecular dynamics of the wild type and G272R mutant of the A. tumefaciens VirB10_CTD tetradecamer reveals how the G272R mutation locks the oligomer in a rigid conformation by swapping the ionic interactions between the loops from the β-barrel close to the inner leaflet of the outer membrane. This electrostatic switching changes the allosteric communication pathway from the extracellular loop to the base of the barrel, suggesting that the local conformational dynamics in the loops can gate information across VirB10.

Novel M2 -selective, Gi -biased agonists of muscarinic acetylcholine receptors

BACKGROUND AND PURPOSE

More than 30% of currently marketed medications act via GPCRs. Thus, GPCRs represent one of the most important pharmacotherapeutic targets. In contrast to traditional agonists activating multiple signalling pathways, agonists activating a single signalling pathway represent a new generation of drugs with increased specificity and fewer adverse effects.

EXPERIMENTAL APPROACH

We have synthesized novel agonists of muscarinic ACh receptors and tested their binding and function (on levels of cAMP and inositol phosphates) in CHO cells expressing individual subtypes of muscarinic receptors, primary cultures of rat aortic smooth muscle cells and suspensions of digested native tissues from rats. Binding of the novel compounds to M₂ receptors was modelled in silico.

KEY RESULTS

Two of the tested new compounds (1-(thiophen-2-ylmethyl)-3,6-dihydro-2H-pyridinium and 1-methyl-1-(thiophen-2-ylmethyl)-3,6-dihydro-2H-pyridinium) only inhibited cAMP synthesis in CHO cells, primary cultures, and native tissues, with selectivity for M₂ muscarinic receptors and displaying bias towards the G_i signalling pathway at all subtypes of muscarinic receptors. Molecular modelling revealed interactions with the orthosteric binding site in a way specific for a given agonist followed by agonist-specific changes in the conformation of the receptor.

CONCLUSIONS AND IMPLICATIONS

The identified compounds may serve as lead structures in the search for novel non-steroidal and non-opioid analgesics acting via M₂ and M₄ muscarinic receptors with reduced side effects associated with activation of the phospholipase C signalling pathway.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

Common activation mechanism of class A GPCRs

Class A G-protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology. Understanding receptor activation mechanism is critical for discovering novel therapeutics since about one-third of all marketed drugs target members of this family. GPCR activation is an allosteric process that couples agonist binding to G-protein recruitment, with the hallmark outward movement of transmembrane helix 6 (TM6). However, what leads to TM6 movement and the key residue level changes of this movement remain less well understood. Here, we report a framework to quantify conformational changes. By analyzing the conformational changes in 234 structures from 45 class A GPCRs, we discovered a common GPCR activation pathway comprising of 34 residue pairs and 35 residues. The pathway unifies previous findings into a common activation mechanism and strings together the scattered key motifs such as CWxP, DRY, Na+ pocket, NPxxY and PIF, thereby directly linking the bottom of ligand-binding pocket with G-protein coupling region. Site-directed mutagenesis experiments support this proposition and reveal that rational mutations of residues in this pathway can be used to obtain receptors that are constitutively active or inactive. The common activation pathway provides the mechanistic interpretation of constitutively activating, inactivating and disease mutations. As a module responsible for activation, the common pathway allows for decoupling of the evolution of the ligand binding site and G-protein-binding region. Such an architecture might have facilitated GPCRs to emerge as a highly successful family of proteins for signal transduction in nature.

Computational design of G Protein-Coupled Receptor allosteric signal transductions

Membrane receptors sense and transduce extracellular stimuli into intracellular signaling responses but the molecular underpinnings remain poorly understood. We report a computational approach for designing protein allosteric signaling functions. By combining molecular dynamics simulations and design calculations, the method engineers amino-acid 'microswitches' at allosteric sites that modulate receptor stability or long-range coupling, to reprogram specific signaling properties. We designed 36 dopamine D2 receptor variants, whose constitutive and ligand-induced signaling agreed well with our predictions, repurposed the D2 receptor into a serotonin biosensor and predicted the signaling effects of more than 100 known G-protein-coupled receptor (GPCR) mutations. Our results reveal the existence of distinct classes of allosteric microswitches and pathways that define an unforeseen molecular mechanism of regulation and evolution of GPCR signaling. Our approach enables the rational design of allosteric receptors with enhanced stability and function to facilitate structural characterization, and reprogram cellular signaling in synthetic biology and cell engineering applications.

Differential Dynamics Underlying the Gln27Glu Population Variant of the β2-Adrenergic Receptor

The β₂-adrenergic receptor (β₂AR) is a membrane-bound G-protein-coupled receptor and an important drug target for asthma. Clinical studies report that the population variant Gln27Glu is associated with a differential response to common asthma drugs, such as albuterol, isoproterenol and terbutaline. Interestingly, the 27th amino acid is positioned on the N-terminal region that is the most flexible and consequently the least studied part of the receptor. In this study, we probe the molecular origin of the differential drug binding by performing structural modeling and simulations of the wild-type (Gln) and variant (Glu) receptors followed by ensemble docking with the ligands, albuterol, isoproterenol and terbutaline. In line with clinical studies, the ligands were observed to interact preferentially with the Glu variant. Our results indicate that the Glu residue at the 27th position perturbs the network of electrostatic interactions that connects the N-terminal region to the binding site in the wild-type receptor. As a result, the Glu variant is observed to bind better to the three ligands tested in this study. Our study provides a structural basis to explain the variable drug response associated with the 27th position polymorphism in the β₂AR and is a starting step to identify genotype-specific therapeutics.

Conformational plasticity of the intracellular cavity of GPCR-G-protein complexes leads to G-protein promiscuity and selectivity

While the dynamics of the intracellular surface in agonist-stimulated GPCRs is well studied, the impact of GPCR dynamics on G-protein selectivity remains unclear. Here, we combine molecular dynamics simulations with live-cell FRET and secondary messenger measurements, for 21 GPCR-G-protein combinations, to advance a dynamic model of the GPCR-G-protein interface. Our data show C terminus peptides of Gαs, Gαi, and Gαq proteins assume a small ensemble of unique orientations when coupled to their cognate GPCRs, similar to the variations observed in 3D structures of GPCR-G-protein complexes. The noncognate G proteins interface with latent intracellular GPCR cavities but dissociate due to weak and unstable interactions. Three predicted mutations in β2-adrenergic receptor stabilize binding of noncognate Gαq protein in its latent cavity, allowing promiscuous signaling through both Gαs and Gαq in a dose-dependent manner. This demonstrates that latent GPCR cavities can be evolved, by design or nature, to tune G-protein selectivity, giving insights to pluridimensional GPCR signaling.

The Molecular Basis of G Protein-Coupled Receptor Activation

G protein-coupled receptors (GPCRs) mediate the majority of cellular responses to external stimuli. Upon activation by a ligand, the receptor binds to a partner heterotrimeric G protein and promotes exchange of GTP for GDP, leading to dissociation of the G protein into α and βγ subunits that mediate downstream signals. GPCRs can also activate distinct signaling pathways through arrestins. Active states of GPCRs form by small rearrangements of the ligand-binding, or orthosteric, site that are amplified into larger conformational changes. Molecular understanding of the allosteric coupling between ligand binding and G protein or arrestin interaction is emerging from structures of several GPCRs crystallized in inactive and active states, spectroscopic data, and computer simulations. The coupling is loose, rather than concerted, and agonist binding does not fully stabilize the receptor in an active conformation. Distinct intermediates whose populations are shifted by ligands of different efficacies underlie the complex pharmacology of GPCRs.

Atomistic Modeling of the ABL Kinase Regulation by Allosteric Modulators Using Structural Perturbation Analysis and Community-Based Network Reconstruction of Allosteric Communications

In this work, we have examined the molecular mechanisms of allosteric regulation of the ABL tyrosine kinase at the atomic level. Atomistic modeling of the ABL complexes with a panel of allosteric modulators has been performed using a combination of molecular dynamics simulations, structural residue perturbation scanning, and a novel community analysis of the residue interaction networks. Our results have indicated that allosteric inhibitors and activators may exert a differential control on allosteric signaling between the kinase binding sites and functional regions. While the inhibitor binding can strengthen the closed ABL state and induce allosteric communications directed from the allosteric pocket to the ATP binding site, the DPH activator may induce a more dynamic open form and activate allosteric couplings between the ATP and substrate binding sites. By leveraging a network-centric theoretical framework, we have introduced a novel community analysis method and global topological parameters that have unveiled the hierarchical modularity and the intercommunity bridging sites in the residue interaction network. We have found that allosteric functional hotspots responsible for the kinase regulation may serve the intermodular bridges in the global interaction network. The central conclusion from this analysis is that the regulatory switch centers play a fundamental role in the modular network organization of ABL as the unique intercommunity bridges that connect the SH2 and SH3 domains with the catalytic core into a functional kinase assembly. The hierarchy of network organization in the ABL regulatory complexes may allow for the synergistic action of dense intercommunity links required for the robust signal transfer in the catalytic core and sparse network bridges acting as the regulatory control points that orchestrate allosteric transitions between the inhibited and active kinase forms.

Recent Advances in Computational Protocols Addressing Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDP) are abundant in the human genome and have recently emerged as major therapeutic targets for various diseases. Unlike traditional proteins that adopt a definitive structure, IDPs in free solution are disordered and exist as an ensemble of conformations. This enables the IDPs to signal through multiple signaling pathways and serve as scaffolds for multi-protein complexes. The challenge in studying IDPs experimentally stems from their disordered nature. Nuclear magnetic resonance (NMR), circular dichroism, small angle X-ray scattering, and single molecule Förster resonance energy transfer (FRET) can give the local structural information and overall dimension of IDPs, but seldom provide a unified picture of the whole protein. To understand the conformational dynamics of IDPs and how their structural ensembles recognize multiple binding partners and small molecule inhibitors, knowledge-based and physics-based sampling techniques are utilized in-silico, guided by experimental structural data. However, efficient sampling of the IDP conformational ensemble requires traversing the numerous degrees of freedom in the IDP energy landscape, as well as force-fields that accurately model the protein and solvent interactions. In this review, we have provided an overview of the current state of computational methods for studying IDP structure and dynamics and discussed the major challenges faced in this field.

Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications

Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.