Internal water channel formation in CXCR4 is crucial for Gi-protein coupling upon activation by CXCL12

Oxysterols Modulate Protein-Sterol Interactions to Impair CXCR4 Signaling in Aging Cells

Organismal aging is accompanied by the accumulation of senescent cells in the body, which drives tissue dysfunction. Senescent cells have a distinctive profile, including proliferation arrest, resistance to apoptosis, altered gene expression, and high inflammation. Despite global signaling and metabolic dysregulation during senescence, the underlying reasons for changes in signaling remain unclear. GPCRs are pivotal in cellular signaling, dynamically mediating the complex interplay between cells and their surrounding environment to maintain cellular homeostasis. The chemokine receptor CXCR4 plays a crucial role in modulating immune responses and inflammation. It has been shown that the expression of CXCR4 increases in cells undergoing senescence, which enhances inflammation postactivation. Here, we examine CXCR4 signaling in deeply senescent cells (aged cells), where cholesterol and its oxidized derivatives, oxysterols, affect receptor function. We report elevated oxysterol levels in senescent cells, which altered classical CXCL12-mediated CXCR4 signaling. Tail-oxidized sterols disrupted signaling more than ring-oxidized counterparts. Molecular dynamics simulations revealed that 27-hydroxycholesterol displaces cholesterol and binds strongly to alter the conformation of critical signaling residues, modifying the sterol-CXCR4 interaction landscape. Our study provides a molecular view of the observed mitigated GPCR signaling in the presence of oxysterols, which switched G-protein signaling from Gαi/o to Gαs class. Overall, we present an altered paradigm of GPCR signaling, where cholesterol oxidation alters the signaling outcome in aged cells.

Investigating the Effect of GLU283 Protonation State on the Conformational Heterogeneity of CCR5 by Molecular Dynamics Simulations

CCR5 is a class A GPCR and serves as one of the coreceptors facilitating HIV-1 entry into host cells. This receptor has vital roles in the immune system and is involved in the pathogenesis of different diseases. Various studies were conducted to understand its activation mechanism, including structural studies in which inactive and active states of the receptor were determined in complex with various binding partners. These determined structures provided opportunities to perform molecular dynamics (MD) simulations and to analyze conformational changes observed in the protein structures. The atomic-level dynamic studies allow us to explore the effects of ionizable residues on the receptor. Here, our aim was to investigate the conformational changes in CCR5 when it forms a complex with either the inhibitor maraviroc (MRV), an approved anti-HIV drug, or HIV-1 envelope protein GP120, and compare these changes to the receptor's apo form. In our simulations, we considered both ionized and protonated states of ionizable binding site residue GLU2837.39 in CCR5 as the protonation state of this residue was considered ambiguously in previous studies. Our molecular simulations results suggested that in fact, the change in the protonation state of GLU2837.39 caused interaction profiles to be different between CCR5 and its binding partners, GP120 or MRV. We observed that when the protonated state of GLU2837.39 was considered in complex with the envelope protein GP120, there were substantial structural changes in CCR5, indicating that it adopts a more active-like conformation. On the other hand, CCR5 in complex with MRV always adopted an inactive conformation regardless of the protonation state. Hence, the CCR5 coreceptor displays conformational heterogeneity not only depending on its binding partner but also influenced by the protonation state of the binding site binding site residue GLU2837.39. This outcome is also in accordance with some studies showing that GP120 binding could activate signaling pathways. This outcome could also have significant implications for discovering novel CCR5 inhibitors as anti-HIV drugs using in silico methods such as molecular docking, as it may be necessary to consider the protonated state of GLU2837.39.

State transitions of coupled Gi-protein: Insights into internal water channel dynamics within dopamine receptor D3 from in silico submolecular analyses

Dopamine is a crucial neurotransmitter in the central nervous system (CNS) that facilitates communication among neurons. Activation of dopamine receptors in the CNS regulates key functions such as movement, cognition, and emotion. Disruption of these receptors can result in severe neurological diseases. Although recent research has elucidated the structure of D3R in complex with Gi-protein, revealing the binding and activation mechanisms, the precise conformational changes induced by G-protein activation and GDP/GTP exchange remain unclear. In this study, atomic-level long-term molecular dynamics (MD) simulations were employed to investigate the dynamics of D3R in complex with different states of Gi-protein and β-arrestin. Our simulations revealed distinct molecular switches within D3R and fluctuations in the distance between Ras and helical domains of G-protein across different G-protein-D3R states. Notably, the D3R-GTP-Gi state exhibited increased activity compared with the D3R-empty-Gi state. Additionally, analyses of potential of mean force (PMF) and free energy landscapes for various systems revealed the formation of a continuous water channel exclusively in the D3R-Gi-GTP state. Furthermore, allosteric communication pathways were proposed for active D3R bound to Gi-protein. This study offers insights into the activation mechanism when Gi-protein interacts with active D3R, potentially aiding in developing selective drugs targeting the dopaminergic system.

Interaction and dynamics of chemokine receptor CXCR4 binding with CXCL12 and hBD-3

Chemokine receptor CXCR4 is involved in diverse diseases. A comparative study was conducted on CXCR4 embedded in a POPC lipid bilayer binding with CXCL12 in full and truncated forms, hBD-3 in wildtype, analog, and mutant forms based on in total 63 µs all-atom MD simulations. The initial binding structures of CXCR4 with ligands were predicted using HADDOCK docking or random-seed method, then μs-long simulations were performed to refine the structures. CXCR4&ligand binding structures predicted agree with available literature data. Both kinds of ligands bind stably to the N-terminus, extracellular loop 2 (ECL2), and ECL3 regions of CXCR4; the C2-C3 (K32-R38) region and occasionally the head of hBD-3 bind stably with CXCR4. hBD-3 analogs with Cys11-Cys40 disulfide bond can activate CXCR4 based on the Helix3-Helix6 distance calculation, but not other analogs or mutant. The results provide insight into understanding the dynamics and activation mechanism of CXCR4 receptor binding with different ligands.

Unveiling G-protein coupled receptors as potential targets for ovarian cancer nanomedicines: from RNA sequencing data analysis to in vitro validation

Genetic heterogeneity in ovarian cancer indicates the need for personalised treatment approaches. Currently, very few G-protein coupled receptors (GPCRs) have been investigated for active targeting with nanomedicines such as antibody-conjugated drugs and drug-loaded nanoparticles, highlighting a neglected potential to develop personalised treatment. To address the genetic heterogeneity of ovarian cancer, a future personalised approach could include the identification of unique GPCRs expressed in cancer biopsies, matched with personalised GPCR-targeted nanomedicines, for the delivery of lethal drugs to tumour tissue before, during and after surgery. Here we report on the systematic analysis of public ribonucleic acid-sequencing (RNA-seq) gene expression data, which led to prioritisation of 13 GPCRs as candidates with frequent overexpression in ovarian cancer tissues. Subsequently, primary ovarian cancer cells derived from ascites and ovarian cancer cell lines were used to confirm frequent gene expression for the selected GPCRs. However, the expression levels showed high variability within our selection of samples, therefore, supporting and emphasising the need for the future development of case-to-case personalised targeting approaches.

C-X-C motif chemokine ligand 12-C-X-C chemokine receptor type 4 signaling axis in cancer and the development of chemotherapeutic molecules

Chemokines are small, secreted cytokines crucial in the regulation of a variety of cell functions. The binding of chemokine C-X-C motif chemokine ligand 12 (CXCL12) (stromal cell-derived factor 1) to a G-protein-coupled receptor C-X-C chemokine receptor type 4 (CXCR4) triggers downstream signaling pathways with effects on cell survival, proliferation, chemotaxis, migration, and gene expression. Intensive and extensive investigations have provided evidence suggesting that the CXCL12-CXCR4 axis plays a pivotal role in tumor development, survival, angiogenesis, metastasis, as well as in creating tumor microenvironment, thus implying that this axis is a potential target for the development of cancer therapies. The structures of CXCL12 and CXCR4 have been resolved with experimental methods such as X-ray crystallography, NMR, or cryo-EM. Therefore, it is possible to apply structure-based computational approaches to discover, design, and modify therapeutic molecules for cancer treatments. Here, we summarize the current understanding of the roles played by the CXCL12-CXCR4 signaling axis in cellular functions linking to cancer progression and metastasis. This review also provides an introduction to protein structures of CXCL12 and CXCR4 and the application of computer simulation and analysis in understanding CXCR4 activation and antagonist binding. Furthermore, examples of strategies and current progress in CXCL12-CXCR4 axis-targeted development of therapeutic anticancer inhibitors are discussed.

Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation

The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.

Pathological progression of osteoarthritis: a perspective on subchondral bone

Osteoarthritis (OA) is a degenerative bone disease associated with aging. The rising global aging population has led to a surge in OA cases, thereby imposing a significant socioeconomic burden. Researchers have been keenly investigating the mechanisms underlying OA. Previous studies have suggested that the disease starts with synovial inflammation and hyperplasia, advancing toward cartilage degradation. Ultimately, subchondral-bone collapse, sclerosis, and osteophyte formation occur. This progression is deemed as "top to bottom." However, recent research is challenging this perspective by indicating that initial changes occur in subchondral bone, precipitating cartilage breakdown. In this review, we elucidate the epidemiology of OA and present an in-depth overview of the subchondral bone's physiological state, functions, and the varied pathological shifts during OA progression. We also introduce the role of multifunctional signal pathways (including osteoprotegerin (OPG)/receptor activator of nuclear factor-kappa B ligand (RANKL)/receptor activator of nuclear factor-kappa B (RANK), and chemokine (CXC motif) ligand 12 (CXCL12)/CXC motif chemokine receptor 4 (CXCR4)) in the pathology of subchondral bone and their role in the "bottom-up" progression of OA. Using vivid pattern maps and clinical images, this review highlights the crucial role of subchondral bone in driving OA progression, illuminating its interplay with the condition.

Comparison, Analysis, and Molecular Dynamics Simulations of Structures of a Viral Protein Modeled Using Various Computational Tools

The structural analysis of proteins is a major domain of biomedical research. Such analysis requires resolved three-dimensional structures of proteins. Advancements in computer technology have led to progress in biomedical research. In silico prediction and modeling approaches have facilitated the construction of protein structures, with or without structural templates. In this study, we used three neural network-based de novo modeling approaches-AlphaFold2 (AF2), Robetta-RoseTTAFold (Robetta), and transform-restrained Rosetta (trRosetta)-and two template-based tools-the Molecular Operating Environment (MOE) and iterative threading assembly refinement (I-TASSER)-to construct the structure of a viral capsid protein, hepatitis C virus core protein (HCVcp), whose structure have not been fully resolved by laboratory techniques. Templates with sufficient sequence identity for the homology modeling of complete HCVcp are currently unavailable. Therefore, we performed domain-based homology modeling for MOE simulations. The templates for each domain were obtained through sequence-based searches on NCBI and the Protein Data Bank. Then, the modeled domains were assembled to construct the complete structure of HCVcp. The full-length structure and two truncated forms modeled using various computational tools were compared. Molecular dynamics (MD) simulations were performed to refine the structures. The root mean square deviation of backbone atoms, root mean square fluctuation of Cα atoms, and radius of gyration were calculated to monitor structural changes and convergence in the simulations. The model quality was evaluated through ERRAT and phi-psi plot analysis. In terms of the initial prediction for protein modeling, Robetta and trRosetta outperformed AF2. Regarding template-based tools, MOE outperformed I-TASSER. MD simulations resulted in compactly folded protein structures, which were of good quality and theoretically accurate. Thus, the predicted structures of certain proteins must be refined to obtain reliable structural models. MD simulation is a promising tool for this purpose.

The pathological role of C-X-C chemokine receptor type 4 (CXCR4) in colorectal cancer (CRC) progression; special focus on molecular mechanisms and possible therapeutics

Colorectal cancer (CRC) is comprised of transformed cells and non-malignant cells including cancer-associated fibroblasts (CAF), endothelial vasculature cells, and tumor-infiltrating cells. These nonmalignant cells, as well as soluble factors (e.g., cytokines), and the extracellular matrix (ECM), form the tumor microenvironment (TME). In general, the cancer cells and their surrounding TME can crosstalk by direct cell-to-cell contact and via soluble factors, such as cytokines (e.g., chemokines). TME not only promotes cancer progression through growth-promoting cytokines but also provides resistance to chemotherapy. Understanding the mechanisms of tumor growth and progression and the roles of chemokines in CRC will likely suggest new therapeutic targets. In this line, a plethora of reports has evidenced the critical role of chemokine receptor type 4 (CXCR4)/C-X-C motif chemokine ligand 12 (CXCL12 or SDF-1) axis in CRC pathogenesis. In the current review, we take a glimpse into the role of the CXCR4/CXCL12 axis in CRC growth, metastasis, angiogenesis, drug resistance, and immune escape. Also, a summary of recent reports concerning targeting CXCR4/CXCL12 axis for CRC management and therapy has been delivered.

Structural Basis of the Binding Mode of the Antineoplastic Compound Motixafortide (BL-8040) in the CXCR4 Chemokine Receptor

Modulation of the CXCL12-CXCR4 signaling axis is of the utmost importance due to its central involvement in several pathological disorders, including inflammatory diseases and cancer. Among the different currently available drugs that inhibit CXCR4 activation, motixafortide-a best-in-class antagonist of this GPCR receptor-has exhibited promising results in preclinical studies of pancreatic, breast, and lung cancers. However, detailed information on the interaction mechanism of motixafortide is still lacking. Here, we characterize the motixafortide/CXCR4 and CXCL12/CXCR4 protein complexes by using computational techniques including unbiased all-atom molecular dynamics simulations. Our microsecond-long simulations of the protein systems indicate that the agonist triggers changes associated with active-like GPCR conformations, while the antagonist favors inactive conformations of CXCR4. Detailed ligand-protein analysis indicates the importance of motixafortide's six cationic residues, all of which established charge-charge interactions with acidic CXCR4 residues. Furthermore, two synthetic bulky chemical moieties of motixafortide work in tandem to restrict the conformations of important residues associated with CXCR4 activation. Our results not only elucidate the molecular mechanism by which motixafortide interacts with the CXCR4 receptor and stabilizes its inactive states, but also provide essential information to rationally design CXCR4 inhibitors that preserve the outstanding pharmacological features of motixafortide.

Computational investigation of functional water molecules in GPCRs bound to G protein or arrestin

G protein-coupled receptors (GPCRs) are membrane proteins constituting the largest family of drug targets. The activated GPCR binds either the heterotrimeric G proteins or arrestin through its activation cycle. Water molecules have been reported to play a role in GPCR activation. Nevertheless, reported studies are focused on the hydrophobic helical bundle region. How water molecules function in GPCR bound either G protein or arrestin is rarely studied. To address this issue, we carried out computational studies on water molecules in both GPCR/G protein complexes and GPCR/arrestin complexes. Using inhomogeneous fluid theory (IFT), we locate all possible hydration sites in GPCRs binding either to G protein or arrestin. We observe that the number of water molecules on the interaction surface between GPCRs and signal proteins are correlated with the insertion depths of the α5-helix from G-protein or "finger loop" from arrestin in GPCRs. In three out of the four simulation pairs, the interfaces of Rhodopsin, M₂R and NTSR1 in the G protein-associated systems show more water-mediated hydrogen-bond networks when compared to these in arrestin-associated systems. This reflects that more functionally relevant water molecules may probably be attracted in G protein-associated structures than that in arrestin-associated structures. Moreover, we find the water-mediated interaction networks throughout the NPxxY region and the orthosteric pocket, which may be a key for GPCR activation. Reported studies show that non-biased agonist, which can trigger both GPCR-G protein and GPCR-arrestin activation signal, can result in pharmacologically toxicities. Our comprehensive studies of the hydration sites in GPCR/G protein complexes and GPCR/arrestin complexes may provide important insights in the design of G-protein biased agonists.

Biased Activation Mechanism Induced by GPCR Heterodimerization: Observations from μOR/δOR Dimers

GPCRs regulate multiple intracellular signaling cascades. Biasedly activating one signaling pathway over the others provides additional clinical utility to optimize GPCR-based therapies. GPCR heterodimers possess different functions from their monomeric states, including their selectivity to different transducers. However, the biased signaling mechanism induced by the heterodimerization remains unclear. Motivated by the issue, we select an important GPCR heterodimer (μOR/δOR heterodimer) as a case and use microsecond Gaussian accelerated molecular dynamics simulation coupled with potential of mean force and protein structure network (PSN) to probe mechanisms regarding the heterodimerization-induced constitutive β-arrestin activity and efficacy change of the agonist DAMGO. The results show that only the lowest energy state of the μOR/δOR heterodimer, which adopts a slightly outward shift of TM6 and an ICL2 conformation close to the receptor core, can selectively accommodate β-arrestins. PSN further reveals important roles of H8, ICL1, and ICL2 in regulating the constitutive β-arrestin-biased activity for the apo μOR/δOR heterodimer. In addition, the heterodimerization can allosterically alter the binding mode of DAMGO mainly by means of W7.35. Consequently, DAMGO transmits the structural signal mainly through TM6 and TM7 in the dimer, rather than TM3 similar to the μOR monomer, thus changing the efficacy of DAMGO from a balanced agonist to the β-arrestin-biased one. On the other side, the binding of DAMGO to the heterodimer can stabilize μOR/δOR heterodimers through a stronger interaction of TM1/TM1 and H8/H8, accordingly enhancing the interaction of μOR with δOR and the binding affinity of the dimer to the β-arrestin. The agonist DAMGO does not change main compositions of the regulation network from the dimer interface to the transducer binding pocket of the μOR protomer, but induces an increase in the structural communication of the network, which should contribute to the enhanced β-arrestin coupling. Our observations, for the first time, reveal the molecular mechanism of the biased signaling induced by the heterodimerization for GPCRs, which should be beneficial to more comprehensively understand the GPCR bias signaling.

Computer-aided discovery, design, and investigation of COVID-19 therapeutics

Coronavirus disease 2019 (COVID-19) pandemic is currently the most serious public health threat faced by mankind. Thus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, is being intensively investigated. Several vaccines are now available for clinical use. However, owing to the highly mutated nature of RNA viruses, the SARS-CoV-2 is changing at a rapid speed. Breakthrough infections by SARS-CoV-2 variants have been seen in vaccinated individuals. As a result, effective therapeutics for treating COVID-19 patients is urgently required. With the advance of computer technology, computational methods have become increasingly powerful in the biomedical research and pharmaceutical drug discovery. The applications of these techniques have largely reduced the costs and simplified processes of pharmaceutical drug developments. Intensive and extensive studies on SARS-CoV-2 proteins have been carried out and three-dimensional structures of the major SARS-CoV-2 proteins have been resolved and deposited in the Protein Data Bank. These structures provide the foundations for drug discovery and design using the structure-based computations, such as molecular docking and molecular dynamics simulations. In this review, introduction to the applications of computational methods in the discovery and design of novel drugs and repurposing of existing drugs for the treatments of COVID-19 is given. The examples of computer-aided investigations and screening of COVID-19 effective therapeutic compounds, functional peptides, as well as effective molecules from the herb medicines are discussed.

Combinatorial Virtual Screening Revealed a Novel Scaffold for TNKS Inhibition to Combat Colorectal Cancer

The abnormal Wnt signaling pathway leads to a high expression of β-catenin, which causes several types of cancer, particularly colorectal cancer (CRC). The inhibition of tankyrase (TNKS) activity can reduce cancer cell growth, invasion, and resistance to treatment by blocking the Wnt signaling pathway. A pharmacophore search and pharmacophore docking were performed to identify potential TNKS inhibitors in the training databases. The weighted MM/PBSA binding free energy of the docking model was calculated to rank the databases. The reranked results indicated that 26.98% of TNKS inhibitors that were present in the top 5% of compounds in the database and near an ideal value ranked 28.57%. The National Cancer Institute database was selected for formal virtual screening, and 11 potential TNKS inhibitors were identified. An enzyme-based experiment was performed to demonstrate that of the 11 potential TNKS inhibitors, NSC295092 and NSC319963 had the most potential. Finally, Wnt pathway analysis was performed through a cell-based assay, which indicated that NSC319963 is the most likely TNKS inhibitor (pIC50 = 5.59). The antiproliferation assay demonstrated that NSC319963 can decrease colorectal cancer cell growth; therefore, the proposed method successfully identified a novel TNKS inhibitor that can alleviate CRC.

Valine-279 Deletion-Mutation on Arginine Vasopressin Receptor 2 Causes Obstruction in G-Protein Binding Site: A Clinical Nephrogenic Diabetes Insipidus Case and Its Sub-Molecular Pathogenic Analysis

Congenital nephrogenic diabetes insipidus (CNDI) is a genetic disorder caused by mutations in arginine vasopressin receptor 2 (AVPR2) or aquaporin 2 genes, rendering collecting duct cells insensitive to the peptide hormone arginine vasopressin stimulation for water reabsorption. This study reports a first identified AVPR2 mutation in Taiwan and demonstrates our effort to understand the pathogenesis caused by applying computational structural analysis tools. The CNDI condition of an 8-month-old male patient was confirmed according to symptoms, family history, and DNA sequence analysis. The patient was identified to have a valine 279 deletion-mutation in the AVPR2 gene. Cellular experiments using mutant protein transfected cells revealed that mutated AVPR2 is expressed successfully in cells and localized on cell surfaces. We further analyzed the pathogenesis of the mutation at sub-molecular levels via long-term molecular dynamics (MD) simulations and structural analysis. The MD simulations showed while the structure of the extracellular ligand-binding domain remains unchanged, the mutation alters the direction of dynamic motion of AVPR2 transmembrane helix 6 toward the center of the G-protein binding site, obstructing the binding of G-protein, thus likely disabling downstream signaling. This study demonstrated that the computational approaches can be powerful tools for obtaining valuable information on the pathogenesis induced by mutations in G-protein-coupled receptors. These methods can also be helpful in providing clues on potential therapeutic strategies for CNDI.