Recent Advances in Structure-Based Drug Design Targeting Class A G Protein-Coupled Receptors Utilizing Crystal Structures and Computational Simulations

Neddylation steers the fate of cellular receptors

Cellular receptors regulate physiological responses by interacting with ligands, thus playing a crucial role in intercellular communication. Receptors are categorized on the basis of their location and engage in diverse biochemical mechanisms, which include posttranslational modifications (PTMs). Considering the broad impact and diversity of PTMs on cellular functions, we focus narrowly on neddylation, a modification closely resembling ubiquitination. We systematically organize its canonical and noncanonical roles in modulating proteins associated with cellular receptors with the goal of providing a more detailed perspective on the intricacies of both intracellular and cell-surface receptors.

Drug Discovery in the Age of Artificial Intelligence: Transformative Target-Based Approaches

The complexities inherent in drug development are multi-faceted and often hamper accuracy, speed and efficiency, thereby limiting success. This review explores how recent developments in machine learning (ML) are significantly impacting target-based drug discovery, particularly in small-molecule approaches. The Simplified Molecular Input Line Entry System (SMILES), which translates a chemical compound's three-dimensional structure into a string of symbols, is now widely used in drug design, mining, and repurposing. Utilizing ML and natural language processing techniques, SMILES has revolutionized lead identification, high-throughput screening and virtual screening. ML models enhance the accuracy of predicting binding affinity and selectivity, reducing the need for extensive experimental screening. Additionally, deep learning, with its strengths in analyzing spatial and sequential data through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), shows promise for virtual screening, target identification, and de novo drug design. Fragment-based approaches also benefit from ML algorithms and techniques like generative adversarial networks (GANs), which predict fragment properties and binding affinities, aiding in hit selection and design optimization. Structure-based drug design, which relies on high-resolution protein structures, leverages ML models for accurate predictions of binding interactions. While challenges such as interpretability and data quality remain, ML's transformative impact accelerates target-based drug discovery, increasing efficiency and innovation. Its potential to deliver new and improved treatments for various diseases is significant.

Targeting Thyroid-Stimulating Hormone Receptor: A Perspective on Small-Molecule Modulators and Their Therapeutic Potential

TSHR is a member of the glycoprotein hormone receptors, a subfamily of class A G-protein-coupled receptors and plays pivotal roles in various physiological and pathological processes, particularly in thyroid growth and hormone production. The aberrant TSHR function has been implicated in several human diseases including Graves' disease and orbitopathy, nonautoimmune hyperthyroidism, hypothyroidism, cancer, neurological disorders, and osteoporosis. Consequently, TSHR is recognized as an attractive therapeutic target, and targeting TSHR with small-molecule modulators including agonists, antagonists, and inverse agonists offers great potential for drug discovery. In this perspective, we summarize the structures and biological functions of TSHR as well as the recent advances in the development of small-molecule TSHR modulators, highlighting their chemotypes, mode of actions, structure-activity relationships, characterizations, in vitro/in vivo activities, and therapeutic potential. The challenges, new opportunities, and future directions in this area are also discussed.

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

Exploring orphan GPCRs in neurodegenerative diseases

Neurodegenerative disorders represent a significant and growing health burden worldwide. Unfortunately, limited therapeutic options are currently available despite ongoing efforts. Over the past decades, research efforts have increasingly focused on understanding the molecular mechanisms underlying these devastating conditions. Orphan receptors, a class of receptors with no known endogenous ligands, emerge as promising druggable targets for diverse diseases. This review aims to direct attention to a subgroup of orphan GPCRs, in particular class A orphans that have roles in neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and Multiple sclerosis. We highlight the diverse roles orphan receptors play in regulating critical cellular processes such as synaptic transmission, neuronal survival and neuro-inflammation. Moreover, we discuss the therapeutic potential of targeting orphan receptors for the treatment of neurodegenerative disorders, emphasizing recent advances in drug discovery and preclinical studies. Finally, we outline future directions and challenges in orphan receptor research.

In silico identification of a biarylamine acting as agonist at human β3 adrenoceptors and exerting BRL37344-like effects on mouse metabolism

Human β3-adrenoceptor (β3AR) agonists were considered potential agents for the treatment of metabolic disorders. However, compounds tested as β3AR ligands have shown marked differences in pharmacological profile in rodent and human species, although these compounds remain attractive as they were successfully repurposed for the therapy of urinary incontinence. In this work, some biarylamine compounds were designed and tested in silico as potential β3AR agonists on 3-D models of mouse or human β3ARs. Based on the theoretical results, we identified, synthesized and tested a biarylamine compound (polibegron). In CHO-K1 cells expressing the human β3AR, polibegron and the β3AR agonist BRL 37344 were partial agonists for stimulating cAMP accumulation (50 and 57% of the response to isoproterenol, respectively). The potency of polibegron was 1.71- and 4.5-fold higher than that of isoproterenol and BRL37344, respectively. These results indicate that polibegron acts as a potent, but partial, agonist at human β3ARs. In C57BL/6N mice with obesity induced by a high-fat diet, similar effects of the equimolar intraperitoneal administration of polibegron and BRL37344 were observed on weight, visceral fat and plasma levels of glucose, cholesterol and triglycerides. Similarities and differences between species related to ligand-receptor interactions can be useful for drug designing.

Orphan GPR52 as an emerging neurotherapeutic target

GPR52 is a highly conserved, brain-enriched, Gs/olf-coupled orphan G protein-coupled receptor (GPCR) that controls various cyclic AMP (cAMP)-dependent physiological and pathological processes. Stimulation of GPR52 activity might be beneficial for the treatment of schizophrenia, psychiatric disorders and other human neurological diseases, whereas inhibition of its activity might provide a potential therapeutic approach for Huntington's disease. Excitingly, HTL0048149 (HTL'149), an orally available GPR52 agonist, has been advanced into phase I human clinical trials for the treatment of schizophrenia. In this concise review, we summarize the current understanding of GPR52 receptor distribution as well as its structure and functions, highlighting the recent advances in drug discovery efforts towards small-molecule GPR52 ligands. The opportunities and challenges presented by targeting GPR52 for novel therapeutics are also briefly discussed.

The multifaceted functions of β-arrestins and their therapeutic potential in neurodegenerative diseases

Arrestins are multifunctional proteins that regulate G-protein-coupled receptor (GPCR) desensitization, signaling, and internalization. The arrestin family consists of four subtypes: visual arrestin1, β-arrestin1, β-arrestin2, and visual arrestin-4. Recent studies have revealed the multifunctional roles of β-arrestins beyond GPCR signaling, including scaffolding and adapter functions, and physically interacting with non-GPCR receptors. Increasing evidence suggests that β-arrestins are involved in the pathogenesis of a variety of neurodegenerative diseases, including Alzheimer's disease (AD), frontotemporal dementia (FTD), and Parkinson's disease (PD). β-arrestins physically interact with γ-secretase, leading to increased production and accumulation of amyloid-beta in AD. Furthermore, β-arrestin oligomers inhibit the autophagy cargo receptor p62/SQSTM1, resulting in tau accumulation and aggregation in FTD. In PD, β-arrestins are upregulated in postmortem brain tissue and an MPTP model, and the β2AR regulates SNCA gene expression. In this review, we aim to provide an overview of β-arrestin1 and β-arrestin2, and describe their physiological functions and roles in neurodegenerative diseases. The multifaceted roles of β-arrestins and their involvement in neurodegenerative diseases suggest that they may serve as promising therapeutic targets.

GPCR-IPL score: multilevel featurization of GPCR-ligand interaction patterns and prediction of ligand functions from selectivity to biased activation

G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure-activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR-ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR-ligand complexes. As a result, we developed GPCR-ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out 'residue level' (for flexible transmembrane helices of GPCRs), (2) zoomed-in 'pocket level' (for sophisticated mode of action) and (3) 'atom level' (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and β-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.

Characterizing conformational states in GPCR structures using machine learning

G protein-coupled receptors (GPCRs) play a pivotal role in signal transduction and represent attractive targets for drug development. Recent advances in structural biology have provided insights into GPCR conformational states, which are critical for understanding their signaling pathways and facilitating structure-based drug discovery. In this study, we introduce a machine learning approach for conformational state annotation of GPCRs. We represent GPCR conformations as high-dimensional feature vectors, incorporating information about amino acid residue pairs involved in the activation pathway. Using a dataset of GPCR conformations in inactive and active states obtained through molecular dynamics simulations, we trained machine learning models to distinguish between inactive-like and active-like conformations. The developed model provides interpretable predictions and can be used for the large-scale analysis of molecular dynamics trajectories of GPCRs.

Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer

Drug discovery and development (DDD) is a highly complex process that necessitates precise monitoring and extensive data analysis at each stage. Furthermore, the DDD process is both timeconsuming and costly. To tackle these concerns, artificial intelligence (AI) technology can be used, which facilitates rapid and precise analysis of extensive datasets within a limited timeframe. The pathophysiology of cancer disease is complicated and requires extensive research for novel drug discovery and development. The first stage in the process of drug discovery and development involves identifying targets. Cell structure and molecular functioning are complex due to the vast number of molecules that function constantly, performing various roles. Furthermore, scientists are continually discovering novel cellular mechanisms and molecules, expanding the range of potential targets. Accurately identifying the correct target is a crucial step in the preparation of a treatment strategy. Various forms of AI, such as machine learning, neural-based learning, deep learning, and network-based learning, are currently being utilised in applications, online services, and databases. These technologies facilitate the identification and validation of targets, ultimately contributing to the success of projects. This review focuses on the different types and subcategories of AI databases utilised in the field of drug discovery and target identification for cancer.

Palmitoylation of the Glucagon-like Peptide-1 Receptor Modulates Cholesterol Interactions at the Receptor-Lipid Microenvironment

The G protein-coupled receptor (GPCR) superfamily of cell surface receptors has been shown to be functionally modulated by post-translational modifications. The glucagon-like peptide receptor-1 (GLP-1R), which is a drug target in diabetes and obesity, undergoes agonist-dependent palmitoyl tail conjugation. The palmitoylation in the C-terminal domain of GLP-1R has been suggested to modulate the receptor-lipid microenvironment. In this work, we have performed coarse-grain molecular dynamics simulations of palmitoylated and nonpalmitoylated GLP-1R to analyze the differential receptor-lipid interactions. Interestingly, the placement and dynamics of the C-terminal domain of GLP-1R are found to be directly dependent on the palmitoyl tail. We observe that both cholesterol and phospholipids interact with the receptor but display differential interactions in the presence and absence of the palmitoyl tail. We characterize important cholesterol-binding sites and validate sites that have been previously reported in experimentally resolved structures of the receptor. We show that the receptor acts like a conduit for cholesterol flip-flop by stabilizing cholesterol in the membrane core. Taken together, our work represents an important step in understanding the molecular effects of lipid modifications in GPCRs.

Structure, function and drug discovery of GPCR signaling

G protein-coupled receptors (GPCRs) are versatile and vital proteins involved in a wide array of physiological processes and responses, such as sensory perception (e.g., vision, taste, and smell), immune response, hormone regulation, and neurotransmission. Their diverse and essential roles in the body make them a significant focus for pharmaceutical research and drug development. Currently, approximately 35% of marketed drugs directly target GPCRs, underscoring their prominence as therapeutic targets. Recent advances in structural biology have substantially deepened our understanding of GPCR activation mechanisms and interactions with G-protein and arrestin signaling pathways. This review offers an in-depth exploration of both traditional and recent methods in GPCR structure analysis. It presents structure-based insights into ligand recognition and receptor activation mechanisms and delves deeper into the mechanisms of canonical and noncanonical signaling pathways downstream of GPCRs. Furthermore, it highlights recent advancements in GPCR-related drug discovery and development. Particular emphasis is placed on GPCR selective drugs, allosteric and biased signaling, polyphamarcology, and antibody drugs. Our goal is to provide researchers with a thorough and updated understanding of GPCR structure determination, signaling pathway investigation, and drug development. This foundation aims to propel forward-thinking therapeutic approaches that target GPCRs, drawing upon the latest insights into GPCR ligand selectivity, activation, and biased signaling mechanisms.

Solid-state NMR chemical shift analysis for determining the conformation of ATP bound to Na,K-ATPase in its native membrane

Structures of membrane proteins determined by X-ray crystallography and, increasingly, by cryo-electron microscopy often fail to resolve the structural details of unstable or reactive small molecular ligands in their physiological sites. This work demonstrates that 13C chemical shifts measured by magic-angle spinning (MAS) solid-state NMR (SSNMR) provide unique information on the conformation of a labile ligand in the physiological site of a functional protein in its native membrane, by exploiting freeze-trapping to stabilise the complex. We examine the ribose conformation of ATP in a high affinity complex with Na,K-ATPase (NKA), an enzyme that rapidly hydrolyses ATP to ADP and inorganic phosphate under physiological conditions. The 13C SSNMR spectrum of the frozen complex exhibits peaks from all ATP ribose carbon sites and some adenine base carbons. Comparison of experimental chemical shifts with density functional theory (DFT) calculations of ATP in different conformations and protein environments reveals that the ATP ribose ring adopts an C3'-endo (N) conformation when bound with high affinity to NKA in the E1Na state, in contrast to the C2'-endo (S) ribose conformations of ATP bound to the E2P state and AMPPCP in the E1 complex. Additional dipolar coupling-mediated measurements of H-C-C-H torsional angles are used to eliminate possible relative orientations of the ribose and adenine rings. The utilization of chemical shifts to determine membrane protein ligand conformations has been underexploited to date and here we demonstrate this approach to be a powerful tool for resolving the fine details of ligand-protein interactions.

Opportunities and challenges in drug discovery targeting the orphan receptor GPR12

G-protein-coupled receptor 12 (GPR12) is a brain-specific expression orphan G-protein-coupled receptor (oGPCR) that regulates various physiological processes. It is an emerging therapeutic target for central nervous system (CNS) disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), attention deficit hyperactivity disorder (ADHD), and schizophrenia, as well as other human diseases, such as cancer, obesity, and metabolic disorders. GPR12 remains a less extensively investigated oGPCR, particularly in terms of its biological functions, signaling pathways, and ligand discovery. The discovery of drug-like small-molecule modulators to probe the brain functions of GPR12 or to act as a potential drug candidates, as well as the identification of reliable biomarkers, are vital to elucidate the roles of this receptor in various human diseases and develop novel target-based therapeutics.

Dynamics of the Apo µ-Opioid Receptor in Complex with Gi Protein

Opioid receptors, particularly the µ-opioid receptor (μOR), play a pivotal role in mediating the analgesic and addictive effects of opioid drugs. G protein signaling is an important pathway of μOR function, usually associated with painkilling effects. However, the molecular mechanisms underlying the interaction between the μOR and G protein remain poorly understood. In this study, we employed classical all-atom molecular dynamics simulations to investigate the structural changes occurring with the μOR-G protein complex under two different conditions: with the G protein in the apo form (open) and with the GDP bound G protein (closed, holo form). The receptor was in the apo form and active conformation in both cases, and the simulation time comprised 1µs for each system. In order to assess the effect of the G protein coupling on the receptor activation state, three parameters were monitored: the correlation of the distance between TM3 and TM6 and the RMSD of the NPxxYA motif; the universal activation index (A100); and the χ2 dihedral distribution of residue W2936.48. When complexed with the open G protein, receptor conformations with intermediate activation state prevailed throughout the molecular dynamics, whereas in the condition with the closed G protein, mostly inactive conformations of the receptor were observed. The major effect of the G protein in the receptor conformation comes from a steric hindrance involving an intracellular loop of the receptor and a β-sheet region of the G protein. This suggests that G-protein precoupling is essential for receptor activation, but this fact is not sufficient for complete receptor activation.

The crosstalk between 5-HT2AR and mGluR2 in schizophrenia

Schizophrenia is a severe brain disorder that usually produces a lifetime of disability. First generation or typical antipsychotics such as haloperidol and second generation or atypical antipsychotics such as clozapine and risperidone remain the current standard for schizophrenia treatment. In some patients with schizophrenia, antipsychotics produce complete remission of positive symptoms, such as hallucinations and delusions. However, antipsychotic drugs are ineffective against cognitive deficits and indeed treated schizophrenia patients have small improvements or even deterioration in several cognitive domains. This underlines the need for novel and more efficient therapeutic targets for schizophrenia treatment. Serotonin and glutamate have been identified as key parts of two neurotransmitter systems involved in fundamental brain processes. Serotonin (or 5-hydroxytryptamine) 5-HT2A receptor (5-HT2AR) and metabotropic glutamate 2 receptor (mGluR2) are G protein-coupled receptors (GPCRs) that interact at epigenetic and functional levels. These two receptors can form GPCR heteromeric complexes through which their pharmacology, function and trafficking becomes affected. Here we review past and current research on the 5-HT2AR-mGluR2 heterocomplex and its potential implication in schizophrenia and antipsychotic drug action. This article is part of the Special Issue on "The receptor-receptor interaction as a new target for therapy".

Computational approaches for the design of modulators targeting protein-protein interactions

BACKGROUND

Protein-protein interactions (PPIs) are intriguing targets for designing novel small-molecule inhibitors. The role of PPIs in various infectious and neurodegenerative disorders makes them potential therapeutic targets . Despite being portrayed as undruggable targets, due to their flat surfaces, disorderedness, and lack of grooves. Recent progresses in computational biology have led researchers to reconsider PPIs in drug discovery.

AREAS COVERED

In this review, we introduce in-silico methods used to identify PPI interfaces and present an in-depth overview of various computational methodologies that are successfully applied to annotate the PPIs. We also discuss several successful case studies that use computational tools to understand PPIs modulation and their key roles in various physiological processes.

EXPERT OPINION

Computational methods face challenges due to the inherent flexibility of proteins, which makes them expensive, and result in the use of rigid models. This problem becomes more significant in PPIs due to their flexible and flat interfaces. Computational methods like molecular dynamics (MD) simulation and machine learning can integrate the chemical structure data into biochemical and can be used for target identification and modulation. These computational methodologies have been crucial in understanding the structure of PPIs, designing PPI modulators, discovering new drug targets, and predicting treatment outcomes.

The role of G protein-coupled receptor in neutrophil dysfunction during sepsis-induced acute respiratory distress syndrome

Sepsis is defined as a life-threatening dysfunction due to a dysregulated host response to infection. It is a common and complex syndrome and is the leading cause of death in intensive care units. The lungs are most vulnerable to the challenge of sepsis, and the incidence of respiratory dysfunction has been reported to be up to 70%, in which neutrophils play a major role. Neutrophils are the first line of defense against infection, and they are regarded as the most responsive cells in sepsis. Normally, neutrophils recognize chemokines including the bacterial product N-formyl-methionyl-leucyl-phenylalanine (fMLP), complement 5a (C5a), and lipid molecules Leukotriene B4 (LTB4) and C-X-C motif chemokine ligand 8 (CXCL8), and enter the site of infection through mobilization, rolling, adhesion, migration, and chemotaxis. However, numerous studies have confirmed that despite the high levels of chemokines in septic patients and mice at the site of infection, the neutrophils cannot migrate to the proper target location, but instead they accumulate in the lungs, releasing histones, DNA, and proteases that mediate tissue damage and induce acute respiratory distress syndrome (ARDS). This is closely related to impaired neutrophil migration in sepsis, but the mechanism involved is still unclear. Many studies have shown that chemokine receptor dysregulation is an important cause of impaired neutrophil migration, and the vast majority of these chemokine receptors belong to the G protein-coupled receptors (GPCRs). In this review, we summarize the signaling pathways by which neutrophil GPCR regulates chemotaxis and the mechanisms by which abnormal GPCR function in sepsis leads to impaired neutrophil chemotaxis, which can further cause ARDS. Several potential targets for intervention are proposed to improve neutrophil chemotaxis, and we hope that this review may provide insights for clinical practitioners.

Systematic analyses of the sequence conservation and ligand interaction patterns of purinergic P1 and P2Y receptors provide a structural basis for receptor selectivity

Purinergic receptors are membrane proteins that regulate numerous cellular functions by catalyzing reactions involving purine nucleotides or nucleosides. Among the three receptor families, i.e., P1, P2X, and P2Y, the P1 and P2Y receptors share common structural features of class A GPCR. Comprehensive sequence and structural analysis revealed that the P1 and P2Y receptors belong to two distinct groups. They exhibit different ligand-binding site features that can distinguish between specific activators. These specific amino acid residues in the binding cavity may be involved in the selectivity and unique pharmacological behavior of each subtype. In this study, we conducted a structure-based analysis of purinergic P1 and P2Y receptors to identify their evolutionary signature and obtain structural insights into ligand recognition and selectivity. The structural features of the P1 and P2Y receptor classes were compared based on sequence conservation and ligand interaction patterns. Orthologous protein sequences were collected for the P1 and P2Y receptors, and sequence conservation was calculated based on Shannon entropy to identify highly conserved residues. To analyze the ligand interaction patterns, we performed docking studies on the P1 and P2Y receptors using known ligand information extracted from the ChEMBL database. We analyzed how the conserved residues are related to ligand-binding sites and how the key interacting residues differ between P1 and P2Y receptors, or between agonists and antagonists. We extracted new similarities and differences between the receptor subtypes, and the results can be used for designing new ligands by predicting hotspot residues that are important for functional selectivity.

Key Residues in δ Opioid Receptor Allostery Explored by the Elastic Network Model and the Complex Network Model Combined with the Perturbation Method

Opioid receptors, a kind of G protein-coupled receptors (GPCRs), mainly mediate an analgesic response via allosterically transducing the signal of endogenous ligand binding in the extracellular domain to couple to effector proteins in the intracellular domain. The δ opioid receptor (DOP) is associated with emotional control besides pain control, which makes it an attractive therapeutic target. However, its allosteric mechanism and key residues responsible for the structural stability and signal communication are not completely clear. Here we utilize the Gaussian network model (GNM) and amino acid network (AAN) combined with perturbation methods to explore the issues. The constructed fcfGNM_MD, where the force constants are optimized with the inverse covariance estimation based on the correlated fluctuations from the available DOP molecular dynamics (MD) ensemble, shows a better performance than traditional GNM in reproducing residue fluctuations and cross-correlations and in capturing functionally low-frequency modes. Additionally, fcfGNM_MD can consider implicitly the environmental effects to some extent. The lowest mode can well divide DOP segments and identify the two sodium ion (important allosteric regulator) binding coordination shells, and from the fastest modes, the key residues important for structure stabilization are identified. Using fcfGNM_MD combined with a dynamic perturbation-response method, we explore the key residues related to the sodium ion binding. Interestingly, we identify not only the key residues in sodium ion binding shells but also the ones far away from the perturbation sites, which are involved in binding with DOP ligands, suggesting the possible long-range allosteric modulation of sodium binding for the ligand binding to DOP. Furthermore, utilizing the weighted AAN combined with attack perturbations, we identify the key residues for allosteric communication. This work helps strengthen the understanding of the allosteric communication mechanism in δ opioid receptor and can provide valuable information for drug design.

Class A and C GPCR Dimers in Neurodegenerative Diseases

Neurodegenerative diseases affect over 30 million people worldwide with an ascending trend. Most individuals suffering from these irreversible brain damages belong to the elderly population, with onset between 50 and 60 years. Although the pathophysiology of such diseases is partially known, it remains unclear upon which point a disease turns degenerative. Moreover, current therapeutics can treat some of the symptoms but often have severe side effects and become less effective in long-term treatment. For many neurodegenerative diseases, the involvement of G proteincoupled receptors (GPCRs), which are key players of neuronal transmission and plasticity, has become clearer and holds great promise in elucidating their biological mechanism. With this review, we introduce and summarize class A and class C GPCRs, known to form heterodimers or oligomers to increase their signalling repertoire. Additionally, the examples discussed here were shown to display relevant alterations in brain signalling and had already been associated with the pathophysiology of certain neurodegenerative diseases. Lastly, we classified the heterodimers into two categories of crosstalk, positive or negative, for which there is known evidence.

G protein coupled pattern recognition receptors expressed in neutrophils : Recognition, activation/modulation, signaling and receptor regulated functions

Neutrophils, the most abundant white blood cell in human blood, express receptors that recognize damage/microbial associated pattern molecules of importance for cell recruitment to sites of inflammation. Many of these receptors belong to the family of G protein coupled receptors (GPCRs). These receptor-proteins span the plasma membrane in expressing cells seven times and the down-stream signaling rely in most cases on an activation of heterotrimeric G proteins. The GPCRs expressed in neutrophils recognize a number of structurally diverse ligands (activating agonists, allosteric modulators, and inhibiting antagonists) and share significant sequence homologies. Studies of receptor structure and function have during the last 40 years generated important information on GPCR biology in general; this knowledge aids in the overall understanding of general pharmacological principles, governing regulation of neutrophil function and inflammatory processes, including novel leukocyte receptor activities related to ligand recognition, biased/functional selective signaling, allosteric modulation, desensitization, and reactivation mechanisms as well as communication (receptor transactivation/cross-talk) between GPCRs. This review summarizes the recent discoveries and pharmacological hallmarks with focus on some of the neutrophil expressed pattern recognition GPCRs. In addition, unmet challenges, including recognition by the receptors of diverse ligands and how biased signaling mediate different biological effects are described/discussed.

Mind the Gap-Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

GPCR Agonist-to-Antagonist Conversion: Enabling the Design of Nucleoside Functional Switches for the A2A Adenosine Receptor

Modulators of the G protein-coupled A2A adenosine receptor (A2AAR) have been considered promising agents to treat Parkinson's disease, inflammation, cancer, and central nervous system disorders. Herein, we demonstrate that a thiophene modification at the C8 position in the common adenine scaffold converted an A2AAR agonist into an antagonist. We synthesized and characterized a novel A2AAR antagonist, 2 (LJ-4517), with Ki = 18.3 nM. X-ray crystallographic structures of 2 in complex with two thermostabilized A2AAR constructs were solved at 2.05 and 2.80 Å resolutions. In contrast to A2AAR agonists, which simultaneously interact with both Ser2777.42 and His2787.43, 2 only transiently contacts His2787.43, which can be direct or water-mediated. The n-hexynyl group of 2 extends into an A2AAR exosite. Structural analysis revealed that the introduced thiophene modification restricted receptor conformational rearrangements required for subsequent activation. This approach can expand the repertoire of adenosine receptor antagonists that can be designed based on available agonist scaffolds.

L-DOPA and Droxidopa: From Force Field Development to Molecular Docking into Human β2-Adrenergic Receptor

The increasing interest in the molecular mechanism of the binding of different agonists and antagonists to β₂-adrenergic receptor (β₂AR) inactive and active states has led us to investigate protein–ligand interactions using molecular docking calculations. To perform this study, the 3.2 Å X-ray crystal structure of the active conformation of human β₂AR in the complex with the endogenous agonist adrenaline has been used as a template for investigating the binding of two exogenous catecholamines to this adrenergic receptor. Here, we show the derivation of L-DOPA and Droxidopa OPLS all atom (AA) force field (FF) parameters via quantum mechanical (QM) calculations, molecular dynamics (MD) simulations in aqueous solutions of the two catecholamines and the molecular docking of both ligands into rigid and flexible β₂AR models. We observe that both ligands share with adrenaline similar experimentally observed binding anchor sites, which are constituted by Asp113/Asn312 and Ser203/Ser204/Ser207 side chains. Moreover, both L-DOPA and Droxidopa molecules exhibit binding affinities comparable to that predicted for adrenaline, which is in good agreement with previous experimental and computational results. L-DOPA and Droxidopa OPLS AA FFs have also been tested by performing MD simulations of these ligands docked into β₂AR proteins embedded in lipid membranes. Both hydrogen bonds and hydrophobic interaction networks observed over the 1 μs MD simulation are comparable with those derived from molecular docking calculations and MD simulations performed with the CHARMM FF.

Protein Fusion Strategies for Membrane Protein Stabilization and Crystal Structure Determination

Crystal structures of membrane proteins are highly desired for their use in the mechanistic understanding of their functions and the designing of new drugs. However, obtaining the membrane protein structures is difficult. One way to overcome this challenge is with protein fusion methods, which have been successfully used to determine the structures of many membrane proteins, including receptors, enzymes and adhesion molecules. Existing fusion strategies can be categorized into the N or C terminal fusion, the insertion fusion and the termini restraining. The fusions facilitate protein expression, purification, crystallization and phase determination. Successful applications often require further optimization of protein fusion linkers and interactions, whose design can be facilitated by a shared helix strategy and by AlphaFold prediction in the future.

Optimization of Peptide Linker-Based Fluorescent Ligands for the Histamine H1 Receptor

The histamine H₁ receptor (H₁R) has recently been implicated in mediating cell proliferation and cancer progression; therefore, high-affinity H₁R-selective fluorescent ligands are desirable tools for further investigation of this behavior in vitro and in vivo. We previously reported a H₁R fluorescent ligand, bearing a peptide-linker, based on antagonist VUF13816 and sought to further explore structure-activity relationships (SARs) around the linker, orthostere, and fluorescent moieties. Here, we report a series of high-affinity H₁R fluorescent ligands varying in peptide linker composition, orthosteric targeting moiety, and fluorophore. Incorporation of a boron-dipyrromethene (BODIPY) 630/650-based fluorophore conferred high binding affinity to our H₁R fluorescent ligands, remarkably overriding the linker SAR observed in corresponding unlabeled congeners. Compound 31a, both potent and subtype-selective, enabled H₁R visualization using confocal microscopy at a concentration of 10 nM. Molecular docking of 31a with the human H₁R predicts that the optimized peptide linker makes interactions with key residues in the receptor.

The Multifaceted Role of GPCRs in Amyotrophic Lateral Sclerosis: A New Therapeutic Perspective?

Amyotrophic lateral sclerosis (ALS) is a degenerating disease involving the motor neurons, which causes a progressive loss of movement ability, usually leading to death within 2 to 5 years from the diagnosis. Much effort has been put into research for an effective therapy for its eradication, but still, no cure is available. The only two drugs approved for this pathology, Riluzole and Edaravone, are onlyable to slow down the inevitable disease progression. As assessed in the literature, drug targets such as protein kinases have already been extensively examined as potential drug targets for ALS, with some molecules already in clinical trials. Here, we focus on the involvement of another very important and studied class of biological entities, G protein-coupled receptors (GPCRs), in the onset and progression of ALS. This workaimsto give an overview of what has been already discovered on the topic, providing useful information and insights that can be used by scientists all around the world who are putting efforts into the fight against this very important neurodegenerating disease.

Sodium or Not Sodium: Should Its Presence Affect the Accuracy of Pose Prediction in Docking GPCR Antagonists?

The function of the allosteric sodium ion in stabilizing the inactive form of GPCRs has been extensively described in the past decades. Its presence has been reported to be essential for the binding of antagonist molecules in the orthosteric site of these very important therapeutical targets. Among the GPCR–antagonist crystal structures available, in most cases, the sodium ion could not be experimentally resolved, obliging computational scientists using GPCRs as targets for virtual screening to ask: “Should the sodium ion affect the accuracy of pose prediction in docking GPCR antagonists?” In the present study, we examined the performance of three orthogonal docking programs in the self-docking of GPCR antagonists to try to answer this question. The results of the present work highlight that if the sodium ion is resolved in the crystal structure used as the target, it should also be taken into account during the docking calculations. If the crystallographic studies were not able to resolve the sodium ion then no advantage would be obtained if this is manually inserted in the virtual target. The outcomes of the present analysis are useful for researchers exploiting molecular docking-based virtual screening to efficiently identify novel GPCR antagonists.

GPCR Inhibition in Treating Lymphoma

G protein-coupled receptors (GPCRs) are important classes of cell surface receptors involved in multiple physiological functions. Aberrant expression, upregulation, and mutation of GPCR signaling pathways are frequent in many types of cancers, promoting hyperproliferation, angiogenesis, and metastasis. Recent studies showed that alterations of GPCRs are involved in different lymphoma types. Herein, we review the synthetic strategies to obtain GPCR inhibitors, focusing on CXCR4 inhibitors which represent most of the GPCR inhibitors available in the market or under preclinical investigations for these diseases.

Advances in computer-aided drug design for type 2 diabetes

INTRODUCTION

The number of diabetic patients is increasing, posing a heavy social and economic burden worldwide. Traditional drug development technology is time-consuming and costly, and the emergence of computer-aided drug design (CADD) has changed this situation. This study reviews the applications of CADD in diabetic drug designing.

AREAS COVERED

In this article, the authors focus on the advance in CADD in diabetic drug design by elaborating the discovery, including peroxisome proliferator-activated receptor (PPAR), G protein-coupled receptor 40 (GPR40), dipeptidyl peptidase-IV (DDP-IV), protein tyrosine phosphatase 1B (PTP1B), sodium-dependent glucose transporter 2 (SGLT-2), and glucokinase (GK). Some drug discovery of these targets is related to CADD strategies.

EXPERT OPINION

There is no doubt that CADD has contributed to the discovery of novel anti-diabetic agents. However, there are still many limitations and challenges, such as lack of co-crystal complex, dynamic simulations, water, and metal ion treatment. In the near future, artificial intelligence (AI) may be a promising strategy to accelerate drug discovery and reduce costs by identifying candidates. Moreover, AlphaFold, a deep learning model that predicts the 3D structure of proteins, represents a considerable advancement in the structural prediction of proteins, especially in the absence of homologous templates for protein structures.

Fentanyl Structure as a Scaffold for Opioid/Non-Opioid Multitarget Analgesics

One of the strategies in the search for safe and effective analgesic drugs is the design of multitarget analgesics. Such compounds are intended to have high affinity and activity at more than one molecular target involved in pain modulation. In the present contribution we summarize the attempts in which fentanyl or its substructures were used as a μ-opioid receptor pharmacophoric fragment and a scaffold to which fragments related to non-opioid receptors were attached. The non-opioid ‘second’ targets included proteins as diverse as imidazoline I₂ binding sites, CB₁ cannabinoid receptor, NK₁ tachykinin receptor, D₂ dopamine receptor, cyclooxygenases, fatty acid amide hydrolase and monoacylglycerol lipase and σ₁ receptor. Reviewing the individual attempts, we outline the chemistry, the obtained pharmacological properties and structure-activity relationships. Finally, we discuss the possible directions for future work.

P2X3-selective mechanism of Gefapixant, a drug candidate for the treatment of refractory chronic cough

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The mechanism by which Gefapixant/AF-219 selectively acts on the P2X3 receptor is unclear.

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The negative allosteric site of AF-219 at P2X3 is also a potent allosteric site for other P2X subtypes.

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The selectivity of AF-219 for P2X3 is determined by the accessibility of binding site and the internal shape of this pocket.

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The finding will provide new perspectives for drug design against P2X3-mediated diseases such as RCC.

Gefapixant/AF-219, a selective inhibitor of the P2X3 receptor, is the first new drug other than dextromethorphan to be approved for the treatment of refractory chronic cough (RCC) in nearly 60 years. To date, seven P2X subtypes (P2X1-7) activated by extracellular ATP have been cloned, and subtype selectivity of P2X inhibitors is a prerequisite for reducing side effects. We previously identified the site and mechanism of action of Gefapixant/AF-219 on the P2X3 receptor, which occupies a pocket consisting of the left flipper (LF) and lower body (LB) domains. However, the mechanism by which AF-219 selectively acts on the P2X3 receptor is unknown. Here, we combined mutagenesis, chimera construction, molecular simulations, covalent occupation and chemical synthesis, and find that the negative allosteric site of AF-219 at P2X3 is also present in other P2X subtypes, at least for P2X1, P2X2 and P2X4. By constructing each chimera of AF-219 sensitive P2X3 and insensitive P2X2 subtypes, the insensitive P2X2 subtype was made to acquire the inhibitory properties of AF-219 and AF-353, an analog of AF-219 with higher affinity. Our results suggest that the selectivity of AF-219/AF-353 for P2X3 over the other P2X subtypes is determined by a combination of the accessibility of P2X3 binding site and the internal shape of this pocket, a finding that could provide new perspectives for drug design against P2X3-mediated diseases such as RCC, idiopathic pulmonary fibrosis, hypertension and overactive bladder disorder.

Targeting GPCRs and Their Signaling as a Therapeutic Option in Melanoma

Simple Summary

Sixteen G-protein-coupled receptors (GPCRs) have been involved in melanogenesis or melanomagenesis. Here, we review these GPCRs, their associated signaling, and therapies.

Abstract

G-protein-coupled receptors (GPCRs) serve prominent roles in melanocyte lineage physiology, with an impact at all stages of development, as well as on mature melanocyte functions. GPCR ligands are present in the skin and regulate melanocyte homeostasis, including pigmentation. The role of GPCRs in the regulation of pigmentation and, consequently, protection against external aggression, such as ultraviolet radiation, has long been established. However, evidence of new functions of GPCRs directly in melanomagenesis has been highlighted in recent years. GPCRs are coupled, through their intracellular domains, to heterotrimeric G-proteins, which induce cellular signaling through various pathways. Such signaling modulates numerous essential cellular processes that occur during melanomagenesis, including proliferation and migration. GPCR-associated signaling in melanoma can be activated by the binding of paracrine factors to their receptors or directly by activating mutations. In this review, we present melanoma-associated alterations of GPCRs and their downstream signaling and discuss the various preclinical models used to evaluate new therapeutic approaches against GPCR activity in melanoma. Recent striking advances in our understanding of the structure, function, and regulation of GPCRs will undoubtedly broaden melanoma treatment options in the future.

Probing GPCR Dimerization Using Peptides

G protein-coupled receptors (GPCRs) are the largest class of membrane proteins and the most common and extensively studied pharmacological target. Numerous studies over the last decade have confirmed that GPCRs do not only exist and function in their monomeric form but in fact, have the ability to form dimers or higher order oligomers with other GPCRs, as well as other classes of receptors. GPCR oligomers have become increasingly attractive to investigate as they have the ability to modulate the pharmacological responses of the receptors which in turn, could have important functional roles in diseases, such as cancer and several neurological & neuropsychiatric disorders. Despite the growing evidence in the field of GPCR oligomerisation, the lack of structural information, as well as targeting the 'undruggable' protein-protein interactions (PPIs) involved in these complexes, has presented difficulties. Outside the field of GPCRs, targeting PPIs has been widely studied, with a variety of techniques being investigated; from small-molecule inhibitors to disrupting peptides. In this review, we will demonstrate several physiologically relevant GPCR dimers and discuss an array of strategies and techniques that can be employed when targeting these complexes, as well as provide ideas for future development.

Analysis of L-DOPA and droxidopa binding to human β2-adrenergic receptor

Over the last two decades, an increasing number of studies has been devoted to a deeper understanding of the molecular process involved in the binding of various agonists and antagonists to active and inactive conformations of β2-adrenergic receptor (β2AR). The 3.2 Å x-ray crystal structure of human β2AR active state in combination with the endogenous low affinity agonist adrenaline offers an ideal starting structure for studying the binding of various catecholamines to adrenergic receptors. We show that molecular docking of levodopa (L-DOPA) and droxidopa into rigid and flexible β2AR models leads for both ligands to binding anchor sites comparable to those experimentally reported for adrenaline, namely D113/N312 and S203/S204/S207 side chains. Both ligands have a hydrogen bond network that is extremely similar to those of noradrenaline and dopamine. Interestingly, redocking neutral and protonated versions of adrenaline to rigid and flexible β2AR models results in binding poses that are more energetically stable and distinct from the x-ray crystal structure. Similarly, lowest energy conformations of noradrenaline and dopamine generated by docking into flexible β2AR models had binding free energies lower than those of best poses in rigid receptor models. Furthermore, our findings show that L-DOPA and droxidopa molecules have binding affinities comparable to those predicted for adrenaline, noradrenaline, and dopamine, which are consistent with previous experimental and computational findings and supported by the molecular dynamics simulations of β2AR-ligand complexes performed here.

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations

Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A_2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A_2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.

The design of new ligands as chemical modulators of G protein-coupled receptors (GPCRs) has benefited considerably during the last years of advances in both the structural and computational biology disciplines. Within the last area, the use of free energy calculation methods has arisen as a computational tool to predict ligand affinities to explain structure-affinity relationships and guide lead optimization campaigns. However, our comprehension of the structural determinants of ligands with different pharmacological profile is scarce, and knowledge of the chemical modifications associated with an agonistic or antagonistic profile would be extremely valuable. We herein report an original implementation of the thermodynamic cycles associated with free energy perturbation (FEP) simulations, to mimic the conformational equilibrium between active and inactive GPCRs, and establish a framework to describe pharmacological profiles as a function of the ligands selectivity for a given receptor conformation. The advantage of this method resides into its simplicity of use, and the only consideration of active and inactive conformations of the receptor, with no simulation of the transitions between them. This model can accurately predict the pharmacological profile of series of full and partial agonists as opposed to antagonists of the A_2A adenosine receptor, and moreover, how certain mutations associated with modulation of basal activity can influence this pharmacological profiles, which enables our understanding of such clinically relevant mutations.

Discovery of Next-Generation Tropomyosin Receptor Kinase Inhibitors for Combating Multiple Resistance Associated with Protein Mutation

Tropomyosin receptor kinase (TRK) inhibition is an effective therapeutic approach for treatment of a variety of cancers. Despite the use of first-generation TRK inhibitor (TRKI) larotrectinib (1) resulting in significant therapeutic response in patients, acquired resistance develops invariably. The emergence of secondary mutations occurring at the solvent-front, xDFG, and gatekeeper regions of TRK represents a common mechanism for acquired resistance. However, xDFG mutations remain insensitive to second-generation macrocyclic TRKIs selitrectinib (3) and repotrectinib (4) designed to overcome the resistance mediated by solvent-front and gatekeeper mutations. Here, we report the structure-based drug design and discovery of a next-generation TRKI. The structure-activity relationship studies culminated in the identification of a promising drug candidate 8 that showed excellent in vitro potency on a panel of TRK mutants, especially TRKA^G667C in the xDFG motif, and improved in vivo efficacy than 1 and 3 in TRK wild-type and mutant fusion-driven tumor xenograft models, respectively.

Fluorescence intensity fluctuation analysis of receptor oligomerization in membrane domains

Fluorescence micrographs of the plasma membrane of cells expressing fluorescently labeled G protein-coupled receptors (GPCRs) often exhibit small clusters of pixels (or puncta) with intensities that are higher than those of the surrounding pixels. Although studies of GPCR interactions in uniform membrane areas abound, understanding the details of the GPCR interactions within such puncta as well as the nature of the membrane formations underlying the puncta is hampered by the lack of adequate experimental techniques. Here, we introduce an enhancement of a recently developed method termed fluorescence intensity fluctuation spectrometry, which permits analysis of protein-protein interactions within the puncta in live cell membranes. We applied the novel fluorescence intensity fluctuation data analysis protocol to previously published data from cells expressing human secretin receptors and determined that the oligomer size increases with receptor concentration and duration of treatment with cognate ligand, not only within uniform regions of the membrane (in agreement with previous publications) but also within the puncta. In addition, we found that the number density and fractional area of the puncta increased after treatment with ligand. This method could be applied for probing the evolution in the time of the chain of events that begins with ligand binding and continues with coated pits formation and receptor internalization for other GPCRs and, indeed, other membrane receptors in living cells.

DESP: Deep Enhanced Sampling of Proteins' Conformation Spaces Using AI-Inspired Biasing Forces

The molecular structures (i.e., conformation spaces, CS) of bio-macromolecules and the dynamics that molecules exhibit are crucial to the understanding of the basis of many diseases and in the continuous attempts to retarget known drugs/medications, improve the efficacy of existing drugs, or develop novel drugs. These make a better understanding and the exploration of the CS of molecules a research hotspot. While it is generally easy to computationally explore the CS of small molecules (such as peptides and ligands), the exploration of the CS of a larger biomolecule beyond the local energy well and beyond the initial equilibrium structure of the molecule is generally nontrivial and can often be computationally prohibitive for molecules of considerable size. Therefore, research efforts in this area focus on the development of ways that systematically favor the sampling of new conformations while penalizing the resampling of previously sampled conformations. In this work, we present Deep Enhanced Sampling of Proteins’ Conformation Spaces Using AI-Inspired Biasing Forces (DESP), a technique for enhanced sampling that combines molecular dynamics (MD) simulations and deep neural networks (DNNs), in which biasing potentials for guiding the MD simulations are derived from the KL divergence between the DNN-learned latent space vectors of [a] the most recently sampled conformation and those of [b] the previously sampled conformations. Overall, DESP efficiently samples wide CS and outperforms conventional MD simulations as well as accelerated MD simulations. We acknowledge that this is an actively evolving research area, and we continue to further develop the techniques presented here and their derivatives tailored at achieving DNN-enhanced steered MD simulations and DNN-enhanced targeted MD simulations.

Flow-mediated vasodilation through mechanosensitive G protein-coupled receptors in endothelial cells

Currently, endothelium-dependent vasodilatation involves three main mechanisms: production of nitric oxide (NO) by endothelial nitric oxide synthase (eNOS), synthesis of prostanoids by cyclooxygenase, and/or opening of calcium-sensitive potassium channels. Researchers have proposed multiple mechanosensors that may be involved in flow-mediated vasodilation (FMD), including G protein-coupled receptors (GPCRs), ion channels, and intercellular junction proteins, among others. However, GPCRs are considered the major mechanosensors that play a pivotal role in shear stress signal transduction. Among mechanosensitive GPCRs, G protein-coupled receptor 68, histamine H1 receptors, sphingosine-1-phosphate receptor 1, and bradykinin B2 receptors have been identified as endothelial sensors of flow shear stress regulating flow-mediated vasodilation. Thus, this review aims to expound on the mechanism whereby flow shear stress promotes vasodilation through the proposed mechanosensitive GPCRs in ECs.

Direct ligand screening against membrane proteins on live cells enabled by DNA-programmed affinity labelling

DNA-programmed affinity labelling (DPAL) enables the screening of chemical compounds against membrane proteins directly on live cells.

Regioselective Formation of Substituted Indoles: Formal Synthesis of Lysergic Acid

A Diels-Alder reaction-based strategy for the synthesis of indoles and related heterocycles is reported. An intramolecular cycloaddition of alkyne-tethered 3-aminopyrones gives 4-substituted indolines in good yield and with complete regioselectivity. Additional substitution is readily tolerated in the transformation, allowing synthesis of complex and non-canonical substitution patterns. Oxidative conditions give the corresponding indoles. The strategy also allows the synthesis of carbazoles. The method was showcased in a formal synthesis of lysergic acid.

In Silico Design, Synthesis and Evaluation of Novel Series of Benzothiazole- Based Pyrazolidinediones as Potent Hypoglycemic Agents

Background:

The discovery of novel ligand binding domain (LBD) of peroxisome proliferator- activated receptor γ (PPARγ) has recently attracted attention to few research groups in order to develop more potent and safer antidiabetic agents.

Objective:

This study is focused on docking-based design and synthesis of novel compounds combining benzothiazole and pyrazolidinedione scaffold as potential antidiabetic agents.

Methods:

Several benzothiazole-pyrazolidinedione hybrids were synthesized and tested for their in vivo anti-hyperglycemic activity. Interactions profile of title compounds against PPARγ was examined through molecular modelling approach.

Results:

All tested compounds exhibited anti-hyperglycemic activity similar or superior to the reference drug Rosiglitazone. Introducing chlorine atom and alkyl group at position-6 and -5 respectively on benzothiazole core resulted in enhancing the anti-hyperglycemic effect. Docking study revealed that such groups demonstrated favorable hydrophobic interactions with novel LBD Ω- pocket of PPARγ protein.

Conclusion:

Among the tested compounds, N-(6-chloro-5-methylbenzo[d]thiazol-2-yl-4-(4((3,5- dioxopyrazolidin-4-ylidene)methyl)phenoxy)butanamide 5b was found to be the most potent compound and provided valuable insights to further develop novel hybrids as anti-hyperglycemic agents.

Structural investigations of cell-free expressed G protein-coupled receptors

G protein-coupled receptors (GPCRs) are of great pharmaceutical interest and about 35% of the commercial drugs target these proteins. Still there is huge potential left in finding molecules that target new GPCRs or that modulate GPCRs differentially. For a rational drug design, it is important to understand the structure, binding and activation of the protein of interest. Structural investigations of GPCRs remain challenging, although huge progress has been made in the last 20 years, especially in the generation of crystal structures of GPCRs. This is mostly caused by issues with the expression yield, purity or labeling. Cell-free protein synthesis (CFPS) is an efficient alternative for recombinant expression systems that can potentially address many of these problems. In this article the use of CFPS for structural investigations of GPCRs is reviewed. We compare different CFPS systems, including the cellular basis and reaction configurations, and strategies for an efficient solubilization. Next, we highlight recent advances in the structural investigation of cell-free expressed GPCRs, with special emphasis on the role of photo-crosslinking approaches to investigate ligand binding sites on GPCRs.

The discovery of a new antibody for BRIL-fused GPCR structure determination

G-protein-coupled receptors (GPCRs)—the largest family of cell-surface membrane proteins—mediate the intracellular signal transduction of many external ligands. Thus, GPCRs have become important drug targets. X-ray crystal structures of GPCRs are very useful for structure-based drug design (SBDD). Herein, we produced a new antibody (SRP2070) targeting the thermostabilised apocytochrome b562 from Escherichia coli M7W/H102I/R106L (BRIL). We found that a fragment of this antibody (SRP2070Fab) facilitated the crystallisation of the BRIL-tagged, ligand bound GPCRs, 5HT_1B and AT₂R. Furthermore, the electron densities of the ligands were resolved, suggesting that SPR2070Fab is versatile and adaptable for GPCR SBDD. We anticipate that this new tool will significantly accelerate structure determination of other GPCRs and the design of small molecular drugs targeting them.