Search Results (51)

Background: Chronic inflammation drives colorectal cancer (CRC) progression, with PAR-2, a G-protein coupled receptor, linking extracellular inflammatory signals to tumor-promoting pathways via ERK1/2 phosphorylation, calcium mobilization, TNF-α upregulation, and apoptosis suppression. While curcumin has notable anti-inflammatory and anti-cancer properties, its effects on PAR-2 signaling in inflammation-driven CRC remain underexplored. Objective: This study investigates how curcumin modulates PAR-2 expression and downstream oncogenic signaling in inflammation-driven CRC cells and explores its potential direct interaction with PAR-2 at the structural level. Methods: HT 29 and Caco-2 CRC cell lines were exposed to lipopolysaccharide (LPS) to induce an inflammatory phenotype, followed by treatment with curcumin at 50 µM and 100 µM. PAR-2 and PAR-1 expression, along with downstream markers including ERK1/2, p-ERK, TNF-α, caspase-8, cleaved caspase-8, caspase-3, Bcl 2, and Bax, were analyzed by Western blot and quantitative PCR. Calcium mobilization was assessed using Fluo-4 dye-based fluorescence imaging. Apoptosis was quantified using MTT viability assays, AO/EtBr dual staining, and Annexin V/PI flow cytometry. In parallel, AlphaFold-predicted structural models of PAR-2 were used to perform molecular docking with curcumin using CB-Dock2, to identify potential binding pockets and assess binding energetics. Results: Curcumin selectively downregulated PAR-2—but not PAR-1—at both transcript and protein levels in a dose-dependent manner. This downregulation was accompanied by suppression of ERK phosphorylation and calcium signaling, inhibition of TNF-α secretion, and reversal of the anti-apoptotic signaling axis (Bcl 2 downregulation and Bax and caspase-3/-8 upregulation). Functional assays confirmed enhanced apoptosis in curcumin-treated cells. Computational docking revealed a high-affinity binding interaction between curcumin and the transmembrane domain of PAR-2, supporting the hypothesis of direct G-Protein-Coupled Receptor (GPCR) modulation. Conclusions: Our findings reveal that curcumin targets the PAR-2/ERK/TNF-α axis and reactivates apoptotic pathways in inflammation-driven CRC, establishing it as a potent, mechanistically validated candidate for therapeutic repurposing in CRC. Full article

This study aimed to investigate the molecular binding mechanisms of bromocriptine toward histamine-associated targets, exploring both antagonist-like and other potential interaction modes that may support therapeutic repurposing. Network pharmacology was applied to identify histamine-related pathways and prioritize potential protein targets. CXCR4, GHSR, and OXTR were selected based on combined docking scores and pharmacophore modeling evidence. Molecular dynamics (MD) simulations over 100 ns assessed structural stability, flexibility, compactness, and solvent exposure. Binding site contact analysis and MM/PBSA free binding energy calculations were conducted to characterize binding energetics and interaction persistence. Bromocriptine exhibited stable binding to all three receptors, engaging key residues implicated in receptor modulation (e.g., Asp187 in CXCR4, Asp99 in GHSR, Arg232 in OXTR). The MM/PBSA ΔG_binding values of bromocriptine were −22.67 ± 3.70 kcal/mol (CXCR4 complex), −22.11 ± 3.55 kcal/mol (GHSR complex), and −21.43 ± 2.41 kcal/mol (OXTR complex), stronger than standard agonists and comparable to antagonists. Contact profiles revealed shared and unique binding patterns across targets, reflecting their potential for diverse modulatory effects. Bromocriptine demonstrates high-affinity binding to multiple histamine-associated GPCR targets, potentially exerting both inhibitory and modulatory actions. These findings provide a molecular basis for further experimental validation and therapeutic exploration in histamine-related conditions. Full article

Lycopene exhibits a broad spectrum of biological activities with potential therapeutic applications. Despite its established antioxidant and anti-inflammatory properties, the molecular basis for its pharmacological actions remains incompletely defined. Here we investigated the molecular targets, pharmacodynamic feasibility, and tissue-specific expression of lycopene targets using a computational pharmacology approach combined with affinity and protein–protein interaction (PPI) analyses. Lycopene-associated human protein targets were predicted using a Swiss target screening platform. Molecular docking was used to estimate binding affinities, and concentration-affinity (CA) ratios were calculated based on physiologically relevant plasma concentrations (75–210 nM). PPI networks of lycopene targets were constructed to identify highly connected targets, and tissue expression analysis was assessed for high-affinity targets using protein-level data from the Human Protein Atlas database. Of the 94 predicted targets, 37% were nuclear receptors and 18% were Family A G Protein Coupled Receptors (GPCRs). Among the top 15 high-affinity targets, nuclear receptors and GPCRs comprised 40% and 26.7%, respectively. Twenty targets had affinities < 10 μM, with six key targets (MAP2K2, SCN2A, SLC6A5, SCN3A, TOP2A, and TRIM24) showing submicromolar binding. CA ratio analysis identified MAP2K2, SCN2A, and SLC6A5 as pharmacodynamically feasible targets (CA > 1). PPI analysis revealed 32 targets with high interaction and 9 with significant network connectivity. Seven targets (TRIM24, GRIN1, NTRK1, FGFR1, NTRK3, CHRNB4, and PIK3CD) showed both high affinity and centrality in the interaction network. The expression profiling of submicromolar targets revealed widespread tissue distribution for MAP2K2 and SCN3A, while SCN2A, TOP2A, and TRIM24 showed more restricted expression patterns. This integrative analysis identifies a subset of lycopene targets with both high affinity and pharmacological feasibility, particularly MAP2K2, SCN2A, and TRIM24. Lycopene appears to exert its biological effects through modulation of interconnected signalling networks involving nuclear receptors, GPCRs, and ion channels. These findings support the potential of lycopene as a multi-target therapeutic agent and provide a rationale for future experimental and clinical validation. Full article

G-protein-coupled receptors (GPCRs) are vital transmembrane proteins that regulate a wide range of physiological processes by transmitting extracellular signals into intracellular responses. Among them, the β2-adrenergic receptor (β2-AR) plays a central role in bronchodilation, smooth muscle relaxation, and cardiovascular modulation, making it a key therapeutic target for diseases such as asthma, chronic obstructive pulmonary disease (COPD), and hypertension. This study explores the potential of natural bioactive compounds like ephedrine, quercetin, catechin, and resveratrol as alternative ligands for β2-AR through molecular docking analysis. Using AutoDock 4.6, these compounds were docked with the binding site of the β2-AR (PDB ID: 2RH1), and their binding affinities and interaction map were evaluated. Results showed that all compounds exhibited favorable binding energies and stable interactions with key receptor residues, with quercetin demonstrating the highest affinity. The findings suggest that these natural compounds may serve as promising leads for the development of safer, plant-derived modulators of β2-AR, supporting the role of computational approaches in natural product-based drug discovery. However, as docking cannot determine functional activity, these findings should be interpreted as preliminary and require experimental validation. Full article

G-protein-coupled receptors (GPCRs) are a group of various membrane proteins that mediate essential physiological processes by translating extracellular signals into intracellular responses. The β2-Adrenergic Receptor (β2-AR), a key GPCR, plays a critical role in smooth muscle relaxation, bronchodilation, and cardiovascular function, making it an important therapeutic target for diseases such as asthma and hypertension. Diketopiperazines (DPKs), as cyclic peptides, have shown promise as scaffolds for inhibiting protein interactions and modulating receptor activity, offering a potential alternative to traditional small-molecule inhibitors with reduced side effects. In this study, five DPK derivatives were selected from the PubChem database and evaluated for their binding affinity to the 3D structure of β2-AR (PDB ID = 2RH1) through molecular docking studies using AutoDock 4.6 and MGLTools. The binding energy and hydrogen bond formation of each compound were evaluated to determine their interaction efficiency. Among the compounds, tryptophan-proline diketopiperazine (compound 3) exhibited the highest binding affinity with a binding energy of −5.89 kcal/mol. This enhanced interaction is attributed to the aromatic nature of tryptophan, which promotes strong π-π stacking interactions, and the rigidity of proline, which optimally fits within the receptor’s binding pocket. Hydrophobic interactions further stabilized the complex. These findings highlight compound 3 as a promising β2-AR modulator, providing valuable insights for the design of peptide-based inhibitors targeting β2-AR-related pathologies. Full article

Recent bioassay studies have unexpectedly supported the high (computationally predicted) binding affinities of angiotensin receptor blockers (ARBs) at α-adrenergic receptors (αARs) in isolated smooth muscle. Computational predictions from ligand docking studies are consistent with very low concentrations of ARBs (e.g., sartans or bisartans) that partially reduce (20–50%) the contractile response to phenylephrine, suggesting that some ARBs may function as partial inverse agonists at αARs. Virtual ligand screening (docking) and molecular dynamics (MD) simulations were carried out to explore the binding affinities and stabilities of selected non-peptide ligands (e.g., ARBs and small-molecule opioids) for several G-protein coupled receptor (GPCR) types, including angiotensin II (AngII) type 1 receptor (AT₁R), α1AR, α2AR, and μ-(µOR) and ժ-opioid receptors (ժOR). Results: All ligands docked preferentially to the binding pocket on the cell surface domain of the GPCR types investigated. Drug binding was characterized by weak interactions (hydrophobic, hydrogen bonding, pi-pi) and stronger ionic and salt-bridge interactions (cation-pi and cation-anion interactions). Ligands specific to each GPCR category showed considerable cross-binding with alternative GPCRs, with small-molecule medications appearing less selective than their peptide or ARB functional equivalents. ARBs that exhibit higher affinities for AT₁R also demonstrate higher affinities for µORs and ժORs than opiate ligands, such as fentanyl and naltrexone. Moreover, ARBs had a higher affinity for αARs than either alpha agonists (epinephrine and phenylephrine) or inhibitors (prazosin and doxazosin). MD simulations of membrane-embedded ARB-GPCR complexes proved stable over nanosecond time scales and suggested that some ARBs may behave as agonists or antagonists depending on the GPCR type. Based on the results presented in this and related investigations, we propose that agonists bind to the resting A-site of GPCRs, while inverse agonists occupy the desensitizing D-site, which partial agonists like morphine and fentanyl share, contributing to addiction. ARBs block both AngII and alpha receptors, suggesting that they are more potent antihypertensive drugs than ACE inhibitors. ARBs have the potential to inhibit morphine tolerance and appear to disrupt receptor desensitization processes, potentially by competing at the D-site. Our results suggest the possible therapeutic potential of ARBs in treating methamphetamine and opiate addictions. Full article

Rhodopsin, a G-protein-coupled receptor (GPCR) comprising the protein opsin covalently linked to the chromophore 11-cis retinal, is pivotal in visual phototransduction. Mutations in the gene encoding rhodopsin (RHO) can cause opsin misfolding or reduce its stability, resulting in retinal degenerative disorders such as retinitis pigmentosa (RP). Current therapeutic strategies employing retinoid-based chaperones partially rescue the folding and trafficking of mutant rhodopsin, but are limited by inherent toxicity and instability due to photoinduced isomerization. In the present work, a pharmacophore-based virtual screening protocol combined with molecular docking and molecular dynamics simulations was employed, leading to the identification of a novel non-retinoid opsin ligand that can potentially act as a pharmacological chaperone. Biological validation confirmed that the compound VS1 binds opsin effectively, representing a valuable starting point for structure-based optimization studies aimed at identifying new opsin stabilizers. Full article

Exercise and diet modulate the gut microbiota, which is involved in the regulation of orthopaedic diseases and synthesises a wide range of metabolites that modulate cellular function and play an important role in bone development, remodelling and disease. G protein-coupled receptors (GPCRs), the largest family of transmembrane receptors in the human body, interact with gut microbial metabolites to regulate relevant pathological processes. This paper provides a review of different dietary and exercise effects on the pathogenic gut microbiota and their metabolites associated with GPCRs in orthopaedic diseases. RESULTS: Generally, metabolites produced by gut microbiota contribute to the maintenance of bone health by activating the corresponding GPCRs, which are involved in bone metabolism, regulation of immune response, and maintenance of gut flora homeostasis. Exercise and diet can influence gut microbiota, and an imbalance in gut microbiota homeostasis can trigger a series of adverse immune and metabolic responses by affecting GPCR function, ultimately leading to the onset and progression of various orthopaedic diseases. Understanding these relationships is crucial for elucidating the pathogenesis of orthopaedic diseases and developing personalised probiotic-based therapeutic strategies. In the future, we should further explore how to prevent and treat orthopaedic diseases through GPCR-based modulation of gut microbes and their interactions. The development of substances that precisely modulate gut microbes through different exercises and diets will provide more effective interventions to improve bone health in patients. Full article

Understanding protein structures can facilitate the development of therapeutic drugs. Traditionally, protein structures have been determined through experimental approaches such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy. While these methods are effective and are considered the gold standard, they are very resource-intensive and time-consuming, ultimately limiting their scalability. However, with recent developments in computational biology and artificial intelligence (AI), the field of protein prediction has been revolutionized. Innovations like AlphaFold and RoseTTAFold enable protein structure predictions to be made directly from amino acid sequences with remarkable speed and accuracy. Despite the enormous enthusiasm associated with these newly developed AI-approaches, their true potential in structure-based drug discovery remains uncertain. In fact, although these algorithms generally predict overall protein structures well, essential details for computational ligand docking, such as the exact location of amino acid side chains within the binding pocket, are not predicted with the necessary accuracy. Additionally, docking methodologies are considered more as a hypothesis generator rather than a precise predictor of ligand–target interactions, and thus, usually identify many false-positive hits among only a few correctly predicted interactions. In this paper, we are reviewing the latest development in this cutting-edge field with emphasis on the GPCR target class to assess the potential role of AI approaches in structure-based drug discovery. Full article

Alzheimer’s disease is a neurodegenerative disease that continues to have a rising number of cases. While extensive research has been conducted on Alzheimer’s disease in the last few decades, only a few drugs have been approved by the FDA for its treatment, and even fewer aim to be curative rather than manage symptoms. There remains an urgent need to understand disease pathogenesis, as well as identify new targets for further drug discovery. Alzheimer’s disease (AD) is known to stem from the build-up of amyloid beta (Aβ) plaques, as well as tangles of tau proteins. Furthermore, inflammation in the brain is known to arise from the degeneration of tissue and the build-up of insoluble material. Therefore, there is a potential link between the pathology of AD and inflammation in the brain, especially as the disease progresses to later stages, where neuronal death and degeneration levels are higher. Proteins that are relevant to both brain inflammation and AD, thus, make ideal potential targets for therapeutics; however, the proteins need to be evaluated to determine which targets would be ideal for potential drug therapeutic treatments, or ‘druggable’ targets. Druggability analysis was conducted using two structure-based methods (i.e., drug-like density analysis and SiteMap), as well as a sequence-based approach, SPIDER. The most druggable targets were then evaluated using single-nucleus sequencing data for their clinical relevance to inflammation in AD. For each of the top five targets, small molecule docking was used to evaluate which FDA approved drugs were able to bind with the chosen proteins. The top targets included DRD2 (inhibits adenylyl cyclase activity), C9 (binds with C5B8 to form the membrane attack complex), C4b (binds with C2a to form C3 convertase), C5AR1 (a GPCR that binds C5a), and GABA-A-R (the GPCR involved in inhibiting neurotransmission). Each target had multiple potential inhibitors from the FDA-approved drug list with decent binding infinities. Among these inhibitors, two drugs were found to be top inhibitors for more than one protein target. They were C15H14N2O2 and v316 (paracetamol), originally used to treat pain/inflammation for cataracts and relieve headaches/fever, respectively. These results provide the groundwork for further experimental investigations or clinical trials. Full article

The first member of the arrestin family, visual arrestin-1, was discovered in the late 1970s. Later, the other three mammalian subtypes were identified and cloned. The first described function was regulation of G protein-coupled receptor (GPCR) signaling: arrestins bind active phosphorylated GPCRs, blocking their coupling to G proteins. It was later discovered that receptor-bound and free arrestins interact with numerous proteins, regulating GPCR trafficking and various signaling pathways, including those that determine cell fate. Arrestins have no enzymatic activity; they function by organizing multi-protein complexes and localizing their interaction partners to particular cellular compartments. Today we understand the molecular mechanism of arrestin interactions with GPCRs better than the mechanisms underlying other functions. However, even limited knowledge enabled the construction of signaling-biased arrestin mutants and extraction of biologically active monofunctional peptides from these multifunctional proteins. Manipulation of cellular signaling with arrestin-based tools has research and likely therapeutic potential: re-engineered proteins and their parts can produce effects that conventional small-molecule drugs cannot. Full article

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of “wet-lab” experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets. Full article

G protein-coupled receptors (GPCRs) represent promising therapeutic targets due to their involvement in numerous physiological processes mediated by downstream G protein- and β-arrestin-mediated signal transduction cascades. Although the precise control of GPCR signaling pathways is therapeutically valuable, the molecular details for governing biased GPCR signaling remain elusive. The Angiotensin II type 1 receptor (AT1R), a prototypical class A GPCR with profound implications for cardiovascular functions, has become a focal point for biased ligand-based clinical interventions. Herein, we used single-molecule live-cell imaging techniques to evaluate the changes in stoichiometry and dynamics of AT1R with distinct biased ligand stimulations in real time. It was revealed that AT1R existed predominantly in monomers and dimers and underwent oligomerization upon ligand stimulation. Notably, β-arrestin-biased ligands induced the formation of higher-order aggregates, resulting in a slower diffusion profile for AT1R compared to G protein-biased ligands. Furthermore, we demonstrated that the augmented aggregation of AT1R, triggered by activation from each biased ligand, was completely abrogated in β-arrestin knockout cells. These findings furnish novel insights into the intricate relationship between GPCR aggregation states and biased signaling, underscoring the pivotal role of molecular behaviors in guiding the development of selective therapeutic agents. Full article

The process of discovering small molecule drugs involves screening numerous compounds and optimizing the most promising ones, both in vitro and in vivo. However, approximately 90% of these optimized candidates fail during trials due to unexpected toxicity or insufficient efficacy. Current concepts with respect to drug–protein interactions suggest that each small molecule interacts with an average of 6–11 targets. This implies that approved drugs and even discontinued compounds could be repurposed by leveraging their interactions with unintended targets. Therefore, we developed a computational repurposing framework for small molecules, which combines artificial intelligence/machine learning (AI/ML)-based and chemical similarity-based target prediction methods with cross-species transcriptomics information. This repurposing methodology incorporates eight distinct target prediction methods, including three machine learning methods. By using multiple orthogonal methods for a “dataset” composed of 2766 FDA-approved drugs targeting multiple therapeutic target classes, we identified 27,371 off-target interactions involving 2013 protein targets (i.e., an average of around 10 interactions per drug). Relative to the drugs in the dataset, we identified 150,620 structurally similar compounds. The highest number of predicted interactions were for drugs targeting G protein-coupled receptors (GPCRs), enzymes, and kinases with 10,648, 4081, and 3678 interactions, respectively. Notably, 17,283 (63%) of the off-target interactions have been confirmed in vitro. Approximately 4000 interactions had an IC₅₀ of <100 nM for 1105 FDA-approved drugs and 1661 interactions had an IC₅₀ of <10 nM for 696 FDA-approved drugs. Together, the confirmation of numerous predicted interactions and the exploration of tissue-specific expression patterns in human and animal tissues offer insights into potential drug repurposing for new therapeutic applications. Full article

The cannabinoid receptors CB₁ and CB₂ are class A G protein-coupled receptors (GPCRs) that are activated via endogenous lipids called endocannabinoids. The endocannabinoid system (ECS) plays a critical role in the regulation of several physiological states and a wide range of diseases. In recent years, drug discovery approaches targeting the cannabinoid type 2 receptor (CB₂R) have gained prominence. Particular attention has been given to selective agonists targeting the CB₂ receptors to circumvent the neuropsychotropic side effects associated with CB₁ receptors. The pharmacological modulation of CB₂R holds therapeutic promise for various diseases, such as inflammatory disorders and immunological conditions, as well as pain management and cancer treatment. Recently, the utilization of fluorescent probes has emerged as a valuable technique for investigating the interactions between ligands and proteins at an exceptional level of spatial and temporal precision. In this review, we aim to examine the progress made in the development of fluorescent probes targeting CB₂ receptors and highlight their significance in facilitating the successful clinical translation of CB₂R-based therapies. Full article