Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding

The G protein inhibitor YM-254890 is an allosteric glue

Given the prominence of G protein coupled receptors (GPCRs) as drug targets, targeting their immediate downstream effectors, G proteins, could be of immense therapeutic value. The discovery that the natural product YM-254890 (YM) can arrest uveal melanoma by specifically inhibiting constitutively active Gq/11without impacting other G protein families demonstrates the potential of this approach. However, efforts to find other G protein family-specific inhibitors have had limited success. Better understanding the mechanism of YM could facilitate efforts to develop other highly specific G protein inhibitors. We hypothesized that differences between the conformational distributions of various G proteins play an important role in determining he specificity of inhibitors like YM. To explore this hypothesis, we built Markov state models (MSMs) from molecular dynamics simulations of the Gα subunits of three different G proteins, as YM predominantly contacts Gα. We also modeled the heterotrimeric versions of these proteins where Gα is bound to the Gβγ heterodimer. We find that YM-sensitive Gα proteins have a higher probability of adopting YM-bound-like conformations than insensitive variants. There is also strong allosteric coupling between the YM- and Gβγ-binding interfaces of Gα. This allostery gives rise to positive cooperativity, wherein the presence of Gβγ enhances preorganization for YM binding. We predict that YM acts as an "allosteric" glue that allosterically stabilizes the complex between Gα and Gβγ despite the minimal contacts between YM and Gβγ.

Mechanistic insights into G-protein coupling with an agonist-bound G-protein-coupled receptor

G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by promoting guanine nucleotide exchange. Here, we investigate the coupling of G proteins with GPCRs and describe the events that ultimately lead to the ejection of GDP from its binding pocket in the Gα subunit, the rate-limiting step during G-protein activation. Using molecular dynamics simulations, we investigate the temporal progression of structural rearrangements of GDP-bound Gs protein (Gs·GDP; hereafter GsGDP) upon coupling to the β2-adrenergic receptor (β2AR) in atomic detail. The binding of GsGDP to the β2AR is followed by long-range allosteric effects that significantly reduce the energy needed for GDP release: the opening of α1-αF helices, the displacement of the αG helix and the opening of the α-helical domain. Signal propagation to the Gs occurs through an extended receptor interface, including a lysine-rich motif at the intracellular end of a kinked transmembrane helix 6, which was confirmed by site-directed mutagenesis and functional assays. From this β2AR-GsGDP intermediate, Gs undergoes an in-plane rotation along the receptor axis to approach the β2AR-Gsempty state. The simulations shed light on how the structural elements at the receptor-G-protein interface may interact to transmit the signal over 30 Å to the nucleotide-binding site. Our analysis extends the current limited view of nucleotide-free snapshots to include additional states and structural features responsible for signaling and G-protein coupling specificity.

Ligand-induced conformational changes in the β1-adrenergic receptor revealed by hydrogen-deuterium exchange mass spectrometry

G Protein Coupled Receptors (GPCRs) constitute the largest family of signalling proteins responsible for translating extracellular stimuli into intracellular functions. They play crucial roles in numerous physiological processes and are major targets for drug discovery. Dysregulation of GPCRs is implicated in various diseases, making understanding their structural dynamics critical for therapeutic development. Here, we use Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS) to explore the structural dynamics of the turkey β1-adrenergic receptor (tβ1AR) bound with nine different ligands, including agonists, partial agonists, and antagonists. We find that these ligands induce distinct dynamic patterns across the receptor, which can be grouped by compound modality. Notably, full agonist binding destabilises the intracellular loop 1 (ICL1), while antagonist binding stabilises it, highlighting ICL1's role in G protein recruitment. Our findings indicate that the conserved L72 residue in ICL1 is crucial for maintaining receptor structural integrity and stabilising the GDP-bound state. Overall, our results provide a platform for determining drug modality and highlight how HDX-MS can be used to dissect receptor ligand interaction properties and GPCR mechanism.

Mechanistic insights into G-protein activation via phosphorylation mediated non-canonical pathway

Activation of heterotrimeric G-proteins (Gαβγ) downstream to receptor tyrosine kinases (RTKs) is a well-established crosstalk between the signaling pathways mediated by G-protein coupled receptors (GPCRs) and RTKs. While GPCR serves as a guanine exchange factor (GEF) in the canonical activation of Gα that facilitates the exchange of GDP for GTP, the mechanism through which RTK phosphorylations induce Gα activation remains unclear. Recent experimental studies revealed that the epidermal growth factor receptor (EGFR), a well-known RTK, phosphorylates the helical domain tyrosine residues Y154 and Y155 and accelerates the GDP release from the Gαi3, a subtype of Gα-protein. Using well-tempered metadynamics and extensive unbiased molecular dynamics simulations, we captured the GDP release event and identified the intermediates between bound and unbound states through Markov state models. In addition to weakened salt bridges at the domain interface, phosphorylations induced the unfolding of helix αF, which contributed to increased flexibility near the hinge region, facilitating a greater distance between domains in the phosphorylated Gαi3. Although the larger domain separation in the phosphorylated system provided an unobstructed path for the nucleotide, the accelerated release of GDP was attributed to increased fluctuations in several conserved regions like P-loop, switch 1, and switch 2. Overall, this study provides atomistic insights into the activation of G-proteins induced by RTK phosphorylations and identifies the specific structural motifs involved in the process. The knowledge gained from the study could establish a foundation for targeting non-canonical signaling pathways and developing therapeutic strategies against the ailments associated with dysregulated G-protein signaling.

G Protein Activation Occurs via a Largely Universal Mechanism

Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over pathway-II, which we experimentally corroborate by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.

A quantitative pharmacology model for cannabinoid CB1 receptor mediated by Gi/Gs protein competition

BACKGROUND AND PURPOSE

Orthosteric agonism of the CB1 receptor normally associates with Gi signalling resulting in a net inhibition of cAMP production. Empirical evidence shows CB1 causes a net cAMP stimulation through Gs coupling under two conditions: co-stimulation with the D2 receptor and high-level CB1 expression. Two hypotheses have been proposed to account for these paradoxical effects, (1) Gi is consumed by coupling to D2 or extra CB1 and excess CB1 binds to Gs and (2), the formation of dimers CB1 -CB1 or CB1 -D2 switches Gi/Gs preference. This study explored the mechanisms of Gi/Gs preference based on a mathematical model of the CB1 receptor.

EXPERIMENTAL APPROACH

The model was based on Hypothesis 1 and known mechanisms. The model was calibrated to align with multiple types of data (cAMP, Gi dissociation and internalisation). The key step of Hypothesis 1 was examined by simulation from the model. An experiment was proposed to distinguish Hypothesis 1 and 2.

KEY RESULTS

The model successfully descripted multiple types of data under Hypothesis 1. Simulations from the model indicated that precoupling of G protein with receptors is necessary for this hypothesis. The model designed experiments to distinguish Hypothesis 1 and 2 by increasing Gi & Gs in parallel with CB1 overexpression. The two hypotheses result in distinct cAMP responses.

CONCLUSION AND IMPLICATIONS

A mathematical model of CB1 -regulated Gi/Gs pathways was developed. It indicated Hypothesis 1 is feasible and G protein precoupling is a key step causing cAMP signalling switch. The model-designed experiments provided guides for future experimentation.

Folding@home: Achievements from over 20 years of citizen science herald the exascale era

Simulations of biomolecules have enormous potential to inform our understanding of biology but require extremely demanding calculations. For over 20 years, the Folding@home distributed computing project has pioneered a massively parallel approach to biomolecular simulation, harnessing the resources of citizen scientists across the globe. Here, we summarize the scientific and technical advances this perspective has enabled. As the project's name implies, the early years of Folding@home focused on driving advances in our understanding of protein folding by developing statistical methods for capturing long-timescale processes and facilitating insight into complex dynamical processes. Success laid a foundation for broadening the scope of Folding@home to address other functionally relevant conformational changes, such as receptor signaling, enzyme dynamics, and ligand binding. Continued algorithmic advances, hardware developments such as graphics processing unit (GPU)-based computing, and the growing scale of Folding@home have enabled the project to focus on new areas where massively parallel sampling can be impactful. While previous work sought to expand toward larger proteins with slower conformational changes, new work focuses on large-scale comparative studies of different protein sequences and chemical compounds to better understand biology and inform the development of small-molecule drugs. Progress on these fronts enabled the community to pivot quickly in response to the COVID-19 pandemic, expanding to become the world's first exascale computer and deploying this massive resource to provide insight into the inner workings of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and aid the development of new antivirals. This success provides a glimpse of what is to come as exascale supercomputers come online and as Folding@home continues its work.

Gαs slow conformational transition upon GTP binding and a novel Gαs regulator

G proteins are major signaling partners for G protein-coupled receptors (GPCRs). Although stepwise structural changes during GPCR-G protein complex formation and guanosine diphosphate (GDP) release have been reported, no information is available with regard to guanosine triphosphate (GTP) binding. Here, we used a novel Bayesian integrative modeling framework that combines data from hydrogen-deuterium exchange mass spectrometry, tryptophan-induced fluorescence quenching, and metadynamics simulations to derive a kinetic model and atomic-level characterization of stepwise conformational changes incurred by the β2-adrenergic receptor (β2AR)-Gs complex after GDP release and GTP binding. Our data suggest rapid GTP binding and GTP-induced dissociation of Gαs from β2AR and Gβγ, as opposed to a slow closing of the Gαs α-helical domain (AHD). Yeast-two-hybrid screening using Gαs AHD as bait identified melanoma-associated antigen D2 (MAGE D2) as a novel AHD-binding protein, which was also shown to accelerate the GTP-induced closing of the Gαs AHD.

MEN1 mutations mediate clinical resistance to menin inhibition

Chromatin-binding proteins are critical regulators of cell state in haematopoiesis1,2. Acute leukaemias driven by rearrangement of the mixed lineage leukaemia 1 gene (KMT2Ar) or mutation of the nucleophosmin gene (NPM1) require the chromatin adapter protein menin, encoded by the MEN1 gene, to sustain aberrant leukaemogenic gene expression programs3-5. In a phase 1 first-in-human clinical trial, the menin inhibitor revumenib, which is designed to disrupt the menin-MLL1 interaction, induced clinical responses in patients with leukaemia with KMT2Ar or mutated NPM1 (ref. 6). Here we identified somatic mutations in MEN1 at the revumenib-menin interface in patients with acquired resistance to menin inhibition. Consistent with the genetic data in patients, inhibitor-menin interface mutations represent a conserved mechanism of therapeutic resistance in xenograft models and in an unbiased base-editor screen. These mutants attenuate drug-target binding by generating structural perturbations that impact small-molecule binding but not the interaction with the natural ligand MLL1, and prevent inhibitor-induced eviction of menin and MLL1 from chromatin. To our knowledge, this study is the first to demonstrate that a chromatin-targeting therapeutic drug exerts sufficient selection pressure in patients to drive the evolution of escape mutants that lead to sustained chromatin occupancy, suggesting a common mechanism of therapeutic resistance.

Agonist concentration-dependent changes in FPR1 conformation lead to biased signaling for selective activation of phagocyte functions

The bacteria-derived formyl peptide fMet-Leu-Phe (fMLF) is a potent chemoattractant of phagocytes that induces chemotaxis at subnanomolar concentrations. At higher concentrations, fMLF inhibits chemotaxis while stimulating degranulation and superoxide production, allowing phagocytes to kill invading bacteria. How an agonist activates distinct cellular functions at different concentrations remains unclear. Using a bioluminescence resonance energy transfer-based FPR1 biosensor, we found that fMLF at subnanomolar and micromolar concentrations induced distinct conformational changes in FPR1, a Gi-coupled chemoattractant receptor that activates various phagocyte functions. Neutrophil-like HL-60 cells exposed to subnanomolar concentrations of fMLF polarized rapidly and migrated along a chemoattractant concentration gradient. These cells also developed an intracellular Ca²⁺ concentration gradient. In comparison, high nanomolar and micromolar concentrations of fMLF triggered the PLC-β/diacyl glycerol/inositol trisphosphate pathway downstream of the heterotrimeric Gi proteins, leading to Ca²⁺ mobilization from intracellular stores and Ca²⁺ influx from extracellular milieu. A robust and uniform rise in cytoplasmic Ca²⁺ level was required for degranulation and superoxide production but disrupted cytoplasmic Ca²⁺ concentration gradient and inhibited chemotaxis. In addition, elevated ERK1/2 phosphorylation and β-arrestin2 membrane translocation were associated with diminished chemotaxis in the presence of fMLF above 1 nM. These findings suggest a mechanism for FPR1 agonist concentration-dependent signaling that leads to a switch from migration to bactericidal activities in phagocytes.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

The Conformational Dynamics of Heterotrimeric G Proteins During GPCR-Mediated Activation

Heterotrimeric G proteins (G proteins) are essential cellular signaling proteins that mediate extracellular signals to achieve various cellular functions. G-protein-coupled receptors (GPCRs) are the major guanine nucleotide exchange factors (GEFs) that induce G proteins to release guanosine diphosphate and rapidly bind to guanosine triphosphate, resulting in G protein activation. G proteins undergo dynamic conformational changes during the activation/inactivation process, and the precise structural mechanism of GPCR-mediated G protein activation is of great interest. Over the last decade, a number of GPCR-G protein complex structures have been identified, yet an understanding of the mechanisms underlying allosteric conformational changes during receptor-mediated G protein activation and GPCR-G protein coupling selectivity is only now emerging. This review discusses recent studies on the dynamic conformational changes of G proteins and provides insight into the structural mechanism of GPCR-mediated G protein activation.

Opening of a cryptic pocket in β-lactamase increases penicillinase activity

A protein is a shape-shifter, but it is currently unclear which of the many structures a protein can adopt are relevant for its function. Here, we examine conformations that contain a “cryptic” pocket (i.e., a pocket absent in ligand-free structures). Cryptic pockets have potential utility in drug discovery efforts because they provide a means to target “undruggable” proteins (i.e., proteins lacking known pockets) or enhance rather than inhibit protein function. In this study, we use a combination of thiol-labeling and kinetic assays, NMR, and molecular dynamic simulations to identify the function of the Ω-loop cryptic pocket in β-lactamase enzymes. We find that an open pocket population is beneficial for hydrolysis of the substrate benzylpenicillin.

Understanding the functional role of protein-excited states has important implications in protein design and drug discovery. However, because these states are difficult to find and study, it is still unclear if excited states simply result from thermal fluctuations and generally detract from function or if these states can actually enhance protein function. To investigate this question, we consider excited states in β-lactamases and particularly a subset of states containing a cryptic pocket which forms under the Ω-loop. Given the known importance of the Ω-loop and the presence of this pocket in at least two homologs, we hypothesized that these excited states enhance enzyme activity. Using thiol-labeling assays to probe Ω-loop pocket dynamics and kinetic assays to probe activity, we find that while this pocket is not completely conserved across β-lactamase homologs, those with the Ω-loop pocket have a higher activity against the substrate benzylpenicillin. We also find that this is true for TEM β-lactamase variants with greater open Ω-loop pocket populations. We further investigate the open population using a combination of NMR chemical exchange saturation transfer experiments and molecular dynamics simulations. To test our understanding of the Ω-loop pocket’s functional role, we designed mutations to enhance/suppress pocket opening and observed that benzylpenicillin activity is proportional to the probability of pocket opening in our designed variants. The work described here suggests that excited states containing cryptic pockets can be advantageous for function and may be favored by natural selection, increasing the potential utility of such cryptic pockets as drug targets.

Enhanced sampling protocol to elucidate fusion peptide opening of SARS-CoV-2 spike protein

Large-scale conformational transitions in the spike protein S2 domain are required during host-cell infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although conventional molecular dynamics simulations have been extensively used to study therapeutic targets of SARS-CoV-2, it is still challenging to gain molecular insight into the key conformational changes because of the size of the spike protein and the long timescale required to capture these transitions. In this work, we have developed an efficient simulation protocol that leverages many short simulations, a dynamic selection algorithm, and Markov state models to interrogate the structural changes of the S2 domain. We discovered that the conformational flexibility of the dynamic region upstream of the fusion peptide in S2 is coupled to the proteolytic cleavage state of the spike protein. These results suggest that opening of the fusion peptide likely occurs on a submicrosecond timescale after cleavage at the S2' site. Building on the structural and dynamical information gained to date about S2 domain dynamics, we provide proof of principle that a small molecule bound to a seam neighboring the fusion peptide can slow the opening of the fusion peptide, leading to a new inhibition strategy for experiments to confirm. In aggregate, these results will aid the development of drug cocktails to inhibit infections caused by SARS-CoV-2 and other coronaviruses.

SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression and replication that depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate 0.1 seconds of the viral proteome. Our adaptive sampling simulations predict dramatic opening of the apo spike complex, far beyond that seen experimentally, explaining and predicting the existence of 'cryptic' epitopes. Different spike variants modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also discover dramatic conformational changes across the proteome, which reveal over 50 'cryptic' pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

G protein-coupled receptor GPR151 is involved in trigeminal neuropathic pain through the induction of Gβγ/extracellular signal-regulated kinase-mediated neuroinflammation in the trigeminal ganglion

ABSTRACT

Trigeminal nerve injury-induced neuropathic pain is a debilitating chronic orofacial pain syndrome but lacks effective treatment. G protein-coupled receptors (GPCRs), especially orphan GPCRs (oGPCRs) are important therapeutic targets in pain medicine. Here, we screened upregulated oGPCRs in the trigeminal ganglion (TG) after partial infraorbital nerve transection (pIONT) and found that Gpr151 was the most significantly upregulated oGPCRs. Gpr151 mRNA was increased from pIONT day 3 and maintained for more than 21 days. Furthermore, GPR151 was expressed in the neurons of the TG after pIONT. Global mutation or knockdown of Gpr151 in the TG attenuated pIONT-induced mechanical allodynia. In addition, the excitability of TG neurons was increased after pIONT in wild-type (WT) mice, but not in Gpr151-/- mice. Notably, GPR151 bound to Gαi protein, but not Gαq, Gα12, or Gα13, and activated the extracellular signal-regulated kinase (ERK) through Gβγ. Extracellular signal-regulated kinase was also activated by pIONT in the TG of WT mice, but not in Gpr151-/- mice. Gene microarray showed that Gpr151 mutation reduced the expression of a large number of neuroinflammation-related genes that were upregulated in WT mice after pIONT, including chemokines CCL5, CCL7, CXCL9, and CXCL10. The mitogen-activated protein kinase inhibitor (PD98059) attenuated mechanical allodynia and reduced the upregulation of these chemokines after pIONT. Collectively, this study not only revealed the involvement of GPR151 in the maintenance of trigeminal neuropathic pain but also identified GPR151 as a Gαi-coupled receptor to induce ERK-dependent neuroinflammation. Thus, GPR151 may be a potential drug target for the treatment of trigeminal neuropathic pain.

The conformational transition during G protein-coupled receptor (GPCR) and G protein interaction

The precise structural mechanism of G protein-coupled receptor (GPCR)-G protein coupling has been of significant research interest because it provides fundamental knowledge on cellular signaling and valuable information for GPCR-targeted drug development. Over the last decade, several GPCR-G protein complex structures have been identified. However, these structures are mere snapshots of guanosine diphosphate (GDP)-released stable GPCR-G protein complexes, which have limited the understanding of the allosteric conformational transition during receptor binding to GDP release and the GPCR-G protein coupling selectivity. Recently, deeper insights into the mechanism underlying stepwise conformational changes during GPCR-G protein coupling were obtained using hydrogen/deuterium exchange mass spectrometry, hydroxyl radical footprinting-mass spectrometry, X-ray crystallography, cryoelectron microscopy, and molecular dynamics simulation techniques. This review summarizes these recent developments.

Computational study on the allosteric mechanism of Leishmania major IF4E-1 by 4E-interacting protein-1: Unravelling the determinants of m7GTP cap recognition

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Atomistic details on perturbations induced by Lm4E-IP1 binding are described.

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The modulation of LmIF4E-1 affinity for the cap is confirmed by energetic analyses.

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Signaling paths between the allosteric and othosteric sites of LmIF4E-1 are predicted.

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Lm4E-IP1 binding increases the side-chain entropy of W83 and R172 of LmIF4E-1.

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A mechanism of dynamic allostery is proposed for the regulation mediated by Lm4E-IP1.

During their life cycle, Leishmania parasites display a fine-tuned regulation of the mRNA translation through the differential expression of isoforms of eukaryotic translation initiation factor 4E (LeishIF4Es). The interaction between allosteric modulators such as 4E-interacting proteins (4E-IPs) and LeishIF4E affects the affinity of this initiation factor for the mRNA cap. Here, several computational approaches were employed to elucidate the molecular bases of the previously-reported allosteric modulation in L. major exerted by 4E-IP1 (Lm4E-IP1) on eukaryotic translation initiation factor 4E 1 (LmIF4E-1). Molecular dynamics (MD) simulations and accurate binding free energy calculations (ΔG_bind) were combined with network-based modeling of residue-residue correlations. We also describe the differences in internal motions of LmIF4E-1 apo form, cap-bound, and Lm4E-IP1-bound systems. Through community network calculations, the differences in the allosteric pathways of allosterically-inhibited and active forms of LmIF4E-1 were revealed. The ΔG_bind values show significant differences between the active and inhibited systems, which are in agreement with the available experimental data. Our study thoroughly describes the dynamical perturbations of LmIF4E-1 cap-binding site triggered by Lm4E-IP1. These findings are not only essential for the understanding of a critical process of trypanosomatids’ gene expression but also for gaining insight into the allostery of eukaryotic IF4Es, which could be useful for structure-based design of drugs against this protein family.

Cryo-EM structure of an activated GPCR-G protein complex in lipid nanodiscs

G-protein-coupled receptors (GPCRs) are the largest superfamily of transmembrane proteins and the targets of over 30% of currently marketed pharmaceuticals. Although several structures have been solved for GPCR-G protein complexes, few are in a lipid membrane environment. Here, we report cryo-EM structures of complexes of neurotensin, neurotensin receptor 1 and Gαi1β1γ1 in two conformational states, resolved to resolutions of 4.1 and 4.2 Å. The structures, determined in a lipid bilayer without any stabilizing antibodies or nanobodies, reveal an extended network of protein-protein interactions at the GPCR-G protein interface as compared to structures obtained in detergent micelles. The findings show that the lipid membrane modulates the structure and dynamics of complex formation and provide a molecular explanation for the stronger interaction between GPCRs and G proteins in lipid bilayers. We propose an allosteric mechanism for GDP release, providing new insights into the activation of G proteins for downstream signaling.

A set of common movements within GPCR-G-protein complexes from variability analysis of cryo-EM datasets

G-protein coupled receptors (GPCRs) are among the most versatile signal transducers in the cell. Once activated, GPCRs sample a large conformational space and couple to G-proteins to initiate distinct signaling pathways. The dynamical behavior of GPCR-G-protein complexes is difficult characterize structurally, and it might hinder obtaining routine high-resolution density maps in single-particle reconstructions. Here, we used variability analysis on the rhodopsin-G_i-Fab16 complex cryo-EM dataset, and the results provide insights into the dynamic nature of the receptor-complex interaction. We compare the outcome of this analysis with recent results obtained on the cannabinoid-G_i- and secretin-G_s-receptor complexes. Despite differences related to the biochemical compositions of the three samples, a set of consensus movements emerges. We anticipate that systematic variability analysis on GPCR-G-protein complexes may provide useful information not only at the biological level, but also for improving the preparation of more stable samples for cryo-EM single-particle analysis.

Tethered agonist exposure in intact adhesion/class B2 GPCRs through intrinsic structural flexibility of the GAIN domain

Adhesion G protein-coupled receptors (aGPCRs)/family B2 GPCRs execute critical tasks during development and the operation of organs, and their genetic lesions are associated with human disorders, including cancers. Exceptional structural aGPCR features are the presence of a tethered agonist (TA) concealed within a GPCR autoproteolysis-inducing (GAIN) domain and their non-covalent heteromeric two-subunit layout. How the TA is poised for activation while maintaining this delicate receptor architecture is central to conflicting signaling paradigms that either involve or exclude aGPCR heterodimer separation. We investigated this matter in five mammalian aGPCR homologs (ADGRB3, ADGRE2, ADGRE5, ADGRG1, and ADGRL1) and demonstrate that intact aGPCR heterodimers exist at the cell surface, that the core TA region becomes unmasked in the cleaved GAIN domain, and that intra-GAIN domain movements regulate the level of tethered agonist exposure, thereby likely controlling aGPCR activity. Collectively, these findings delineate a unifying mechanism for TA-dependent signaling of intact aGPCRs.

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called "lag time"). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5-10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

pH-Induced Local Unfolding of the Phl p 6 Pollen Allergen From cpH-MD

Susceptibility to endosomal degradation is a decisive contribution to a protein's immunogenicity. It is assumed that the processing kinetics of structured proteins are inherently linked to their probability of local unfolding. In this study, we quantify the impact of endosomal acidification on the conformational stability of the major timothy grass pollen allergen Phl p 6. We use state of the art sampling approaches in combination with constant pH MD techniques to profile pH-dependent local unfolding events in atomistic detail. Integrating our findings into the current view on type 1 allergic sensitization, we characterize local protein dynamics in the context of proteolytic degradation at neutral and acidic pH for the wild type protein and point mutants with varying proteolytic stability. We analyze extensive simulation data using Markov state models and retrieve highly reliable thermodynamic and kinetic information at varying pH levels. Thereby we capture the impact of endolysosomal acidification on the structure and dynamics of the Phl p 6 mutants. We find that upon protonation at lower pH values, the conformational flexibilities in key areas of the wild type protein, i.e., T-cell epitopes and early proteolytic cleavage sites, increase significantly. A decrease of the pH even leads to local unfolding in otherwise stable secondary structure elements, which is a prerequisite for proteolytic cleavage. This effect is even more pronounced in the destabilized mutant, while no unfolding was observed for the stabilized mutant. In summary, we report detailed structural models which rationalize the experimentally observed cleavage pattern during endosomal acidification.

GDP Release from the Open Conformation of Gα Requires Allosteric Signaling from the Agonist-Bound Human β2 Adrenergic Receptor

G-protein-coupled receptors (GPCRs) transmit signals into the cell in response to ligand binding at its extracellular domain, which is characterized by the coupling of agonist-induced receptor conformational change to guanine nucleotide (GDP) exchange with guanosine triphosphate on a heterotrimeric (αβγ) guanine nucleotide-binding protein (G-protein), leading to the activation of the G-protein. The signal transduction mechanisms have been widely researched in vivo and in silico. However, coordinated communication from stimulating ligands to the bound GDP still remains elusive. In the present study, we used microsecond (μS) molecular dynamic (MD) simulations to directly probe the communication from the β₂ adrenergic receptor (β₂AR) with an agonist or an antagonist or no ligand to GDP bound to the open conformation of the Gα protein. Molecular mechanism-general Born surface area calculation results indicated either the agonist or the antagonist destabilized the binding between the receptor and the G-protein but the agonist caused a higher level of destabilization than the antagonist. This is consistent with the role of agonist in the activation of the G-protein. Interestingly, while GDP remained bound with the Gα-protein for the two inactive systems (antagonist-bound and apo form), GDP dissociated from the open conformation of the Gα protein for the agonist activated system. Data obtained from MD simulations indicated that the receptor and the Gα subunit play a big role in coordinated communication and nucleotide exchange. Based on residue interaction network analysis, we observed that engagement of agonist-bound β₂AR with an α5 helix of G_α is essential for the GDP release and the residues in the phosphate-binding loop, α1 helix, and α5 helix play very important roles in the GDP release. The insights on GPCR-G-protein communication will facilitate the rational design of agonists and antagonists that target both active and inactive GPCR binding pockets, leading to more precise drugs.

Protein-Protein Binding as a Two-Step Mechanism: Preselection of Encounter Poses during the Binding of BPTI and Trypsin

Biomolecular recognition between proteins follows complex mechanisms, the understanding of which can substantially advance drug discovery efforts. Here, we track each step of the binding process in atomistic detail with molecular dynamics simulations using trypsin and its inhibitor bovine pancreatic trypsin inhibitor (BPTI) as a model system. We use umbrella sampling to cover a range of unbinding pathways. Starting from these simulations, we subsequently seed classical simulations at different stages of the process and combine them to a Markov state model. We clearly identify three kinetically separated states (an unbound state, an encounter state, and the final complex) and describe the mechanisms that dominate the binding process. From our model, we propose the following sequence of events. The initial formation of the encounter complex is driven by long-range interactions because opposite charges in trypsin and BPTI draw them together. The encounter complex features the prealigned binding partners with binding sites still partially surrounded by solvation shells. Further approaching leads to desolvation and increases the importance of van der Waals interactions. The native binding pose is adopted by maximizing short-range interactions. Thereby side-chain rearrangements ensure optimal shape complementarity. In particular, BPTI’s P1 residue adapts to the S1 pocket and prime site residues reorient to optimize interactions. After the paradigm of conformation selection, binding-competent conformations of BPTI and trypsin are already present in the apo ensembles and their probabilities increase during this proposed two-step association process. This detailed characterization of the molecular forces driving the binding process includes numerous aspects that have been discussed as central to the binding of trypsin and BPTI and protein complex formation in general. In this study, we combine all these aspects into one comprehensive model of protein recognition. We thereby contribute to enhance our general understanding of this fundamental mechanism, which is particularly critical as the development of biopharmaceuticals continuously gains significance.

Conformational distributions of isolated myosin motor domains encode their mechanochemical properties

Myosin motor domains perform an extraordinary diversity of biological functions despite sharing a common mechanochemical cycle. Motors are adapted to their function, in part, by tuning the thermodynamics and kinetics of steps in this cycle. However, it remains unclear how sequence encodes these differences, since biochemically distinct motors often have nearly indistinguishable crystal structures. We hypothesized that sequences produce distinct biochemical phenotypes by modulating the relative probabilities of an ensemble of conformations primed for different functional roles. To test this hypothesis, we modeled the distribution of conformations for 12 myosin motor domains by building Markov state models (MSMs) from an unprecedented two milliseconds of all-atom, explicit-solvent molecular dynamics simulations. Comparing motors reveals shifts in the balance between nucleotide-favorable and nucleotide-unfavorable P-loop conformations that predict experimentally measured duty ratios and ADP release rates better than sequence or individual structures. This result demonstrates the power of an ensemble perspective for interrogating sequence-function relationships.

Dynamics Rationalize Proteolytic Susceptibility of the Major Birch Pollen Allergen Bet v 1

Proteolytic susceptibility during endolysosomal degradation is decisive for allergic sensitization. In the major birch pollen allergen Bet v 1 most protease cleavage sites are located within its secondary structure elements, which are inherently inaccessible to proteases. The allergen thus must unfold locally, exposing the cleavage sites to become susceptible to proteolysis. Hence, allergen cleavage rates are presumed to be linked to their fold stability, i.e., unfolding probability. Yet, these locally unfolded structures have neither been captured in experiment nor simulation due to limitations in resolution and sampling time, respectively. Here, we perform classic and enhanced molecular dynamics (MD) simulations to quantify fold dynamics on extended timescales of Bet v 1a and two variants with higher and lower cleavage rates. Already at the nanosecond-timescale we observe a significantly higher flexibility for the destabilized variant compared to Bet v 1a and the proteolytically stabilized mutant. Estimating the thermodynamics and kinetics of local unfolding around an initial cleavage site, we find that the Bet v 1 variant with the highest cleavage rate also shows the highest probability for local unfolding. For the stabilized mutant on the other hand we only find minimal unfolding probability. These results strengthen the link between the conformational dynamics of allergen proteins and their stability during endolysosomal degradation. The presented approach further allows atomistic insights in the conformational ensemble of allergen proteins and provides probability estimates below experimental detection limits.

Sodium-induced population shift drives activation of thrombin

The equilibrium between active E and inactive E* forms of thrombin is assumed to be governed by the allosteric binding of a Na+ ion. Here we use molecular dynamics simulations and Markov state models to sample transitions between active and inactive states. With these calculations we are able to compare thermodynamic and kinetic properties depending on the presence of Na+. For the first time, we directly observe sodium-induced conformational changes in long-timescale computer simulations. Thereby, we are able to explain the resulting change in activity. We observe a stabilization of the active form in presence of Na+ and a shift towards the inactive form in Na+-free simulations. We identify key structural features to quantify and monitor this conformational shift. These include the accessibility of the S1 pocket and the reorientation of W215, of R221a and of the Na+ loop. The structural characteristics exhibit dynamics at various timescales: Conformational changes in the Na+ binding loop constitute the slowest observed movement. Depending on its orientation, it induces conformational shifts in the nearby substrate binding site. Only after this shift, residue W215 is able to move freely, allowing thrombin to adopt a binding-competent conformation.

Spatial and temporal alterations in protein structure by EGF regulate cryptic cysteine oxidation

Stimulation of plasma membrane receptor tyrosine kinases (RTKs), such as the epidermal growth factor receptor (EGFR), locally increases the abundance of reactive oxygen species (ROS). These ROS then oxidize cysteine residues in proteins to potentiate downstream signaling. Spatial confinement of ROS is an important regulatory mechanism of redox signaling that enables the stimulation of different RTKs to oxidize distinct sets of downstream proteins. To uncover additional mechanisms that specify cysteines that are redox regulated by EGF stimulation, we performed time-resolved quantification of the EGF-dependent oxidation of 4200 cysteine sites in A431 cells. Fifty-one percent of cysteines were statistically significantly oxidized by EGF stimulation. Furthermore, EGF induced three distinct spatiotemporal patterns of cysteine oxidation in functionally organized protein networks, consistent with the spatial confinement model. Unexpectedly, protein crystal structure analysis and molecular dynamics simulations indicated widespread redox regulation of cryptic cysteine residues that are solvent exposed only upon changes in protein conformation. Phosphorylation and increased flux of nucleotide substrates served as two distinct modes by which EGF specified the cryptic cysteine residues that became solvent exposed and redox regulated. Because proteins that are structurally regulated by different RTKs or cellular perturbations are largely unique, these findings suggest that solvent exposure and redox regulation of cryptic cysteine residues contextually delineate redox signaling networks.

Conformational Transitions and the Activation of Heterotrimeric G Proteins by G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are particularly attractive targets for therapeutic pharmaceuticals. This is because they are involved in almost all facets of physiology, in many pathophysiological processes, they are tractable due to their cell surface location, and can exhibit highly textured pharmacology. While the development of new drugs does not require the molecular details of the mechanism of activity for a particular target, there has been increasing interest in the GPCR field in these details. In part, this has come with the recognition that differential activity at a particular target might be a way in which to leverage drug activity, either through manipulation of efficacy or through differential coupling (signaling bias). To this end, the past few years have seen a number of publications that have specifically attempted to address one or more aspects of the molecular reaction pathway, leading to activation of heterotrimeric G proteins by GPCRs.

Structural basis for GPCR-independent activation of heterotrimeric Gi proteins

Heterotrimeric G proteins are key molecular switches that control cell behavior. The canonical activation of G proteins by agonist-occupied G protein-coupled receptors (GPCRs) has recently been elucidated from the structural perspective. In contrast, the structural basis for GPCR-independent G protein activation by a novel family of guanine-nucleotide exchange modulators (GEMs) remains unknown. Here, we present a 2.0-Å crystal structure of Gαi in complex with the GEM motif of GIV/Girdin. Nucleotide exchange assays, molecular dynamics simulations, and hydrogen-deuterium exchange experiments demonstrate that GEM binding to the conformational switch II causes structural changes that allosterically propagate to the hydrophobic core of the Gαi GTPase domain. Rearrangement of the hydrophobic core appears to be a common mechanism by which GPCRs and GEMs activate G proteins, although with different efficiency. Atomic-level insights presented here will aid structure-based efforts to selectively target the noncanonical G protein activation.

Enspara: Modeling molecular ensembles with scalable data structures and parallel computing

Markov state models (MSMs) are quantitative models of protein dynamics that are useful for uncovering the structural fluctuations that proteins undergo, as well as the mechanisms of these conformational changes. Given the enormity of conformational space, there has been ongoing interest in identifying a small number of states that capture the essential features of a protein. Generally, this is achieved by making assumptions about the properties of relevant features-for example, that the most important features are those that change slowly. An alternative strategy is to keep as many degrees of freedom as possible and subsequently learn from the model which of the features are most important. In these larger models, however, traditional approaches quickly become computationally intractable. In this paper, we present enspara, a library for working with MSMs that provides several novel algorithms and specialized data structures that dramatically improve the scalability of traditional MSM methods. This includes ragged arrays for minimizing memory requirements, message passing interface-parallelized implementations of compute-intensive operations, and a flexible framework for model construction and analysis.

Advanced Methods for Accessing Protein Shape-Shifting Present New Therapeutic Opportunities

A protein is a dynamic shape-shifter whose function is determined by the set of structures it adopts. Unfortunately, atomically detailed structures are only available for a few conformations of any given protein, and these structures have limited explanatory and predictive power. Here, we provide a brief historical perspective on protein dynamics and introduce recent advances in computational and experimental methods that are providing unprecedented access to protein shape-shifting. Next, we focus on how these tools are revealing the mechanism of allosteric communication and features like cryptic pockets; both of which present new therapeutic opportunities. A major theme is the importance of considering the relative probabilities of different structures and the control one can exert over protein function by modulating this balance.