Exploring the Activation Process of the β2AR-Gs Complex

Exploring the Activation Mechanism of the GPR183 Receptor

The G protein-coupled receptors (GPCRs) play a pivotal role in numerous biological processes as crucial cell membrane receptors. However, the dynamic mechanisms underlying the activation of GPR183, a specific GPCR, remain largely elusive. To address this, we employed computational simulation techniques to elucidate the activation process and key events associated with GPR183, including conformational changes from inactive to active state, binding interactions with the Gi protein complex, and GDP release. Our findings demonstrate that the association between GPR183 and the Gi protein involves the formation of receptor-specific conformations, the gradual proximity of the Gi protein to the binding pocket, and fine adjustments of the protein conformation, ultimately leading to a stable GPR183-Gi complex characterized by a high energy barrier. The presence of Gi protein partially promotes GPR183 activation, which is consistent with the observation of GPCR constitutive activity test experiments, thus illustrating the reliability of our calculations. Moreover, our study suggests the existence of a stable partially activated state preceding complete activation, providing novel avenues for future investigations. In addition, the relevance of GPR183 for various diseases, such as colitis, the response of eosinophils to Mycobacterium tuberculosis infection, antiviral properties, and pulmonary inflammation, has been emphasized, underscoring its therapeutic potential. Consequently, understanding the activation process of GPR183 through molecular dynamic simulations offers valuable kinetic insights that can aid in the development of targeted therapies.

Exploring the activation mechanism of metabotropic glutamate receptor 2

Homomeric dimerization of metabotropic glutamate receptors (mGlus) is essential for the modulation of their functions and represents a promising avenue for the development of novel therapeutic approaches to address central nervous system diseases. Yet, the scarcity of detailed molecular and energetic data on mGlu2 impedes our in-depth comprehension of their activation process. Here, we employ computational simulation methods to elucidate the activation process and key events associated with the mGlu2, including a detailed analysis of its conformational transitions, the binding of agonists, Gi protein coupling, and the guanosine diphosphate (GDP) release. Our results demonstrate that the activation of mGlu2 is a stepwise process and several energy barriers need to be overcome. Moreover, we also identify the rate-determining step of the mGlu2's transition from the agonist-bound state to its active state. From the perspective of free-energy analysis, we find that the conformational dynamics of mGlu2's subunit follow coupled rather than discrete, independent actions. Asymmetric dimerization is critical for receptor activation. Our calculation results are consistent with the observation of cross-linking and fluorescent-labeled blot experiments, thus illustrating the reliability of our calculations. Besides, we also identify potential key residues in the Gi protein binding position on mGlu2, mGlu2 dimer's TM6-TM6 interface, and Gi α5 helix by the change of energy barriers after mutation. The implications of our findings could lead to a more comprehensive grasp of class C G protein-coupled receptor activation.

Structure and function of an intermediate GPCR-Gαβγ complex

Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-Gαβγ structures, these snapshots primarily capture the fully activated end-state complex. Consequently, a comprehensive understanding of the conformational transitions during GPCR activation and the roles of intermediate GPCR-G protein complexes in signaling remain elusive. Guided by a conformational landscape profiled by 19 F quantitative NMR ( 19 F-qNMR) and Molecular Dynamics (MD) simulations, we resolved the structure of an unliganded GPCR-G protein intermediate complex by blocking its transition to the fully activated end-state complex. More importantly, we presented direct evidence that the intermediate GPCR-Gαsβγ complex initiates a rate-limited nucleotide exchange without progressing to the fully activated end-state complex, thereby bridging a significant gap in our understanding the complexity of GPCR signaling. Understanding the roles of individual conformational states and their complexes in signaling efficacy and bias will help us to design drugs that discriminately target a disease-related conformation.

Predicting Mutational Effects on Ca2+-Activated Chloride Conduction of TMEM16A Based on a Simulation Study

The dysfunction and defects of ion channels are associated with many human diseases, especially for loss-of-function mutations in ion channels such as cystic fibrosis transmembrane conductance regulator mutations in cystic fibrosis. Understanding ion channels is of great current importance for both medical and fundamental purposes. Such an understanding should include the ability to predict mutational effects and describe functional and mechanistic effects. In this work, we introduce an approach to predict mutational effects based on kinetic information (including reaction barriers and transition state locations) obtained by studying the working mechanism of target proteins. Specifically, we take the Ca2+-activated chloride channel TMEM16A as an example and utilize the computational biology model to predict the mutational effects of key residues. Encouragingly, we verified our predictions through electrophysiological experiments, demonstrating a 94% prediction accuracy regarding mutational directions. The mutational strength assessed by Pearson's correlation coefficient is -0.80 between our calculations and the experimental results. These findings suggest that the proposed methodology is reliable and can provide valuable guidance for revealing functional mechanisms and identifying key residues of the TMEM16A channel. The proposed approach can be extended to a broad scope of biophysical systems.

Fine-tuning activation specificity of G-protein-coupled receptors via automated path searching

Physics-based simulation methods can grant atomistic insights into the molecular origin of the function of biomolecules. However, the potential of such approaches has been hindered by their low efficiency, including in the design of selective agonists where simulations of myriad protein-ligand combinations are necessary. Here, we describe an automated input-free path searching protocol that offers (within 14 d using Graphics Processing Unit servers) a minimum free energy path (MFEP) defined in high-dimension configurational space for activating sphingosine-1-phosphate receptors (S1PRs) by arbitrary ligands. The free energy distributions along the MFEP for four distinct ligands and three S1PRs reached a remarkable agreement with Bioluminescence Resonance Energy Transfer (BRET) measurements of G-protein dissociation. In particular, the revealed transition state structures pointed out toward two S1PR3 residues F263/I284, that dictate the preference of existing agonists CBP307 and BAF312 on S1PR1/5. Swapping these residues between S1PR1 and S1PR3 reversed their response to the two agonists in BRET assays. These results inspired us to design improved agonists with both strong polar head and bulky hydrophobic tail for higher selectivity on S1PR1. Through merely three in silico iterations, our tool predicted a unique compound scaffold. BRET assays confirmed that both chiral forms activate S1PR1 at nanomolar concentration, 1 to 2 orders of magnitude less than those for S1PR3/5. Collectively, these results signify the promise of our approach in fine agonist design for G-protein-coupled receptors.

Natural product rhynchophylline prevents stress-induced hair graying by preserving melanocyte stem cells via the β2 adrenergic pathway suppression

Norepinephrine (NA), a stress hormone, can accelerate hair graying by binding to β2 adrenergic receptors (β2AR) on melanocyte stem cells (McSCs). From this, NA-β2AR axis could be a potential target for preventing the stress effect. However, identifying selective blockers for β2AR has been a key challenge. Therefore, in this study, advanced computer-aided drug design (CADD) techniques were harnessed to screen natural molecules, leading to the discovery of rhynchophylline as a promising compound. Rhynchophylline exhibited strong and stable binding within the active site of β2AR, as verified by molecular docking and dynamic simulation assays. When administered to cells, rhynchophylline effectively inhibited NA-β2AR signaling. This intervention resulted in a significant reduction of hair graying in a stress-induced mouse model, from 28.5% to 8.2%. To gain a deeper understanding of the underlying mechanisms, transcriptome sequencing was employed, which revealed that NA might disrupt melanogenesis by affecting intracellular calcium balance and promoting cell apoptosis. Importantly, rhynchophylline acted as a potent inhibitor of these downstream pathways. In conclusion, the study demonstrated that rhynchophylline has the potential to mitigate the negative impact of NA on melanogenesis by targeting β2AR, thus offering a promising solution for preventing stress-induced hair graying.

Intermediate-state-trapped mutants pinpoint G protein-coupled receptor conformational allostery

Understanding the roles of intermediate states in signaling is pivotal to unraveling the activation processes of G protein-coupled receptors (GPCRs). However, the field is still struggling to define these conformational states with sufficient resolution to study their individual functions. Here, we demonstrate the feasibility of enriching the populations of discrete states via conformation-biased mutants. These mutants adopt distinct distributions among five states that lie along the activation pathway of adenosine A2A receptor (A2AR), a class A GPCR. Our study reveals a structurally conserved cation-π lock between transmembrane helix VI (TM6) and Helix8 that regulates cytoplasmic cavity opening as a "gatekeeper" for G protein penetration. A GPCR activation process based on the well-discerned conformational states is thus proposed, allosterically micro-modulated by the cation-π lock and a previously well-defined ionic interaction between TM3 and TM6. Intermediate-state-trapped mutants will also provide useful information in relation to receptor-G protein signal transduction.

FSHR activation through small molecule modulators: Mechanistic insights from MD simulations

Follicle-stimulating hormone receptor (FSHR) is a glycoprotein hormone receptor that plays a vital role in reproduction, cancer progression and osteoporosis. Owing to its therapeutic importance, several small molecule modulators have been identified by researchers through high throughput studies that usually include virtual screening of chemical libraries followed by in vitro validation through radio-ligand binding assays, cAMP accumulation and luciferase-based luminescence assays. The binding site of these modulators and structural changes that accompany modulator binding remains elusive. Here, we address these aspects through molecular docking and MD simulations on well-studied FSHR modulators and comparing the domain motions between agonist/FSH bound and antagonist bound FSHR structures. It was observed that agonist and antagonist modulators bind to the same site, but interact with distinct residues in transmembrane domain(TMD). FSHR(TMD) residues Ile522, Ala595, Ile602 and Val604 were found to interact only with agonist. Notably, these residues are conserved in the close homolog luteinizing hormone/choriogonadotropin receptor (LHCGR) and participate in interaction with its agonist Org43553. We observed distinctly prominent domain motions and conformational changes in TM helices 3, 4 and 6 for agonist bound FSHR structure. These structural changes have also been reported for LHCGR, and few GPCR members suggesting an important and well conserved mechanism of GPHR activation that could be exploited for design of novel modulators.

Exploring the Phospholipid Transport Mechanism of ATP8A1-CDC50

P4-ATPase translocates lipids from the exoplasmic to the cytosolic plasma membrane leaflet to maintain lipid asymmetry distribution in eukaryotic cells. P4-ATPase is associated with severe neurodegenerative and metabolic diseases such as neurological and motor disorders. Thus, it is important to understand its transport mechanism. However, even with progress in X-ray diffraction and cryo-electron microscopy techniques, it is difficult to obtain the dynamic information of the phospholipid transport process in detail. There are still some problems required to be resolved: (1) when does the lipid transport happen? (2) How do the key residues on the transmembrane helices contribute to the free energy of important states? In this work, we explore the phospholipid transport mechanism using a coarse-grained model and binding free energy calculations. We obtained the free energy landscape by coupling the protein conformational changes and the phospholipid transport event, taking ATP8A1-CDC50 (the typical subtype of P4-ATPase) as the research object. According to the results, we found that the phospholipid would bind to the ATP8A1-CDC50 at the early stage when ATP8A1-CDC50 changes from E2P to E2Pi-PL state. We also found that the electrostatic effects play crucial roles in the phospholipid transport process. The information obtained from this work could help us in designing novel drugs for P-type flippase disorders.

The Nature of Functional Features of Different Classes of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are a critical family in the human proteome and are involved in various physiological processes. They are also the most important drug target, with approximately 30% of approved drugs acting on such receptors. The members of the family are divided into six classes based on their structural and functional characteristics. Understanding their structural-functional relationships will benefit us in future drug development. In this article, we investigate the features of protein function, structure, and energy that describe the dynamics of the GPCR activation process between different families. GPCRs straddle the cell membrane and transduce signals from outside the membrane into the cell. During the process, the conformational change in GPCRs that is activated by the binding of signal molecules is essential. During the binding process, different types of signal molecules result in different signal transfer efficiencies. Therefore, the GPCR classes show a variety of structures and activation processes. Based on the experimental crystal structures, we modeled the activation process of the β2 adrenergic receptor (β2AR), glucagon receptor (GCGR), and metabotropic glutamate receptor 2 (mGluR2), which represent class A, B, and C GPCRs, respectively. We calculated their activation free-energy landscapes and analyzed the structure-energy-function relationship. The results show a consistent picture of the activation mechanisms between different types of GPCRs. This could also provide us a way to understand other signal transduction proteins.

Targeting protein conformations with small molecules to control protein complexes

Dynamic protein complexes function in all cellular processes, from signaling to transcription, using distinct conformations that regulate their activity. Conformational switching of proteins can turn on or off their activity through protein-protein interactions, catalytic function, cellular localization, or membrane interaction. Recent advances in structural, computational, and chemical methodologies have enabled the discovery of small-molecule activators and inhibitors of conformationally dynamic proteins by using a more rational design than a serendipitous screening approach. Here, we discuss such recent examples, focusing on the mechanism of protein conformational switching and its regulation by small molecules. We emphasize the rational approaches to control protein oligomerization with small molecules that offer exciting opportunities for investigation of novel biological mechanisms and drug discovery.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

Computational and experimental approaches to probe GPCR activation and signaling

G protein-coupled receptors (GPCRs) regulate different physiological functions, e.g., sensation, growth, digestion, reproductivity, nervous and immune systems response, and many others. In eukaryotes, they are also responsible for intercellular communication in response to pathogens. The major primary messengers binding to these cell-surface receptors constitute small-molecule or peptide hormones and neurotransmitters, nucleotides, lipids as well as small proteins. The simplicity of the way how GPCR signaling can be regulated by their endogenous agonists prompted the usage of GPCRs as major drug targets in modern pharmacology. Drugs targeting GPCRs inhibit pathological processes at the very beginning. This enables to significantly reduce the occurrence of morphological changes caused by diseases. Until recently, X-ray crystallography was the method of the first choice to obtain high-resolution structural information about GPCRs. Following X-ray crystallography, cryo-EM gained attention in GPCR studies as a quick and low-cost alternative. FRET microscopy is also widely used for GPCRs in the analysis of protein-protein interactions (PPIs) in intact cells as well as for screening purposes. Regarding computational methods, molecular dynamics (MD) for many years has proven its usefulness in studying the GPCR activation. MODELLER and Rosetta were widely used to generate preliminary homology models of GPCRs for MD simulation systems. Apart from the conventional all-atom approach with explicitly defined solvent, also other techniques have been applied to GPCRs, e.g., MARTINI or hybrid methods involving the coarse-grained representation, less demanding regarding computational resources, and thus offering much larger simulation timescales.

Mechanism Study of Proteins under Membrane Environment

Membrane proteins play crucial roles in various physiological processes, including molecule transport across membranes, cell communication, and signal transduction. Approximately 60% of known drug targets are membrane proteins. There is a significant need to deeply understand the working mechanism of membrane proteins in detail, which is a challenging work due to the lack of available membrane structures and their large spatial scale. Membrane proteins carry out vital physiological functions through conformational changes. In the current study, we utilized a coarse-grained (CG) model to investigate three representative membrane protein systems: the TMEM16A channel, the family C GPCRs mGlu2 receptor, and the P4-ATPase phospholipid transporter. We constructed the reaction pathway of conformational changes between the two-end structures. Energy profiles and energy barriers were calculated. These data could provide reasonable explanations for TMEM16A activation, the mGlu2 receptor activation process, and P4-ATPase phospholipid transport. Although they all belong to the members of membrane proteins, they behave differently in terms of energy. Our work investigated the working mechanism of membrane proteins and could give novel insights into other membrane protein systems of interest.

Application of Coarse-Grained (CG) Models to Explore Conformational Pathway of Large-Scale Protein Machines

Protein machines are clusters of protein assemblies that function in order to control the transfer of matter and energy in cells. For a specific protein machine, its working mechanisms are not only determined by the static crystal structures, but also related to the conformational transition dynamics and the corresponding energy profiles. With the rapid development of crystallographic techniques, the spatial scale of resolved structures is reaching up to thousands of residues, and the concomitant conformational changes become more and more complicated, posing a great challenge for computational biology research. Previously, a coarse-grained (CG) model aiming at conformational free energy evaluation was developed and showed excellent ability to reproduce the energy profiles by accurate electrostatic interaction calculations. In this study, we extended the application of the CG model to a series of large-scale protein machine systems. The spike protein trimer of SARS-CoV-2, ATP citrate lyase (ACLY) tetramer, and P4-ATPases systems were carefully studied and discussed as examples. It is indicated that the CG model is effective to depict the energy profiles of the conformational pathway between two endpoint structures, especially for large-scale systems. Both the energy change and energy barrier between endpoint structures provide reasonable mechanism explanations for the associated biological processes, including the opening of receptor binding domain (RBD) of spike protein, the phospholipid transportation of P4-ATPase, and the loop translocation of ACLY. Taken together, the CG model provides a suitable alternative in mechanistic studies related to conformational change in large-scale protein machines.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.