Enhancing the Signaling of GPCRs via Orthosteric Ions

Hydrated cation-π interactions of π-electrons with hydrated Mg2+ and Ca2+ cations

Hydrated cation-π interactions at liquid-solid interfaces between hydrated cations and aromatic ring structures of carbon-based materials are pivotal in many material, biological, and chemical processes, and water serves as a crucial mediator in these interactions. However, a full understanding of the hydrated cation-π interactions between hydrated alkaline earth cations and aromatic ring structures, such as graphene remains elusive. Here, we present a molecular picture of hydrated cation-π interactions for Mg2+ and Ca2+ by using the density functional theory methods. Theoretical results show that the graphene sheet can distort the hydration shell of the hydrated Ca2+ to interact with Ca2+ directly, which is water-cation-π interactions. In contrast, the hydration shell of the hydrated Mg2+ is quite stable and the graphene sheet interacts with Mg2+ indirectly, mediated by water molecules, which is the cation-water-π interactions. These results lead to the anomalous order of adsorption energies for these alkaline earth cations, with hydrated Mg2+-π < hydrated Ca2+-π when the number of water molecules is large (n ≥ 6), contrary to the order observed for cation-π interactions in the absence of water molecules (n = 0). The behavior of hydrated alkaline earth cations adsorbed on a graphene surface is mainly attributed to the competition between the cation-π interactions and hydration effects. These findings provide valuable details of the structures and the adsorption energy of hydrated alkaline earth cations adsorbed onto the graphene surface.

The structure and function of olfactory receptors

Olfactory receptors (ORs) form the most important chemosensory receptor family responsible for our sense of smell in the nasal olfactory epithelium. This receptor family belongs to the class A G protein-coupled receptors (GPCRs). Recent research has indicated that ORs are involved in many nonolfactory physiological processes in extranasal tissue, such as the brain, pancreas, and testes, and implies the possible role of their dysregulation in various diseases. The recently released structures of OR51E2 and consensus OR52 have also unveiled the uniqueness of ORs from other class A GPCR members. In this review, we discuss these recent developments and computational modeling efforts toward understanding the structural properties of unresolved ORs, which could guide potential future OR-targeted drug discovery.

Mechanistic insights into sodium ion-mediated ligand binding affinity and modulation of 5-HT2B GPCR activity: implications for drug discovery and development

PURPOSE

The G-protein coupled receptor (GPCR) family, implicated in neurological disorders and drug targets, includes the sensitive serotonin receptor subtype, 5-HT2B. The influence of sodium ions on ligand binding at the receptor's allosteric region is being increasingly studied for its impact on receptor structure.

METHODS

High-throughput virtual screening of three libraries, specifically the Asinex-GPCR library, which contains 8,532 compounds and FDA-approved (2466 compounds) and investigational compounds (2731)) against the modeled receptor [4IB4-5HT2BRM] using the standard agonist/antagonist (Ergotamine/Methysergide), as previously selected from our studies based on ADMET profiling, and further on basis of binding free energy a single compound - dihydroergotamine is chosen.

RESULTS

This compound displayed strong interactions with the conserved active site. Ions influence ligand binding, with stronger interactions (3-H-bonds and 1-π-bond around 3.35 Å) observed when an agonist and ions are present. Ions entry is guided by conserved motifs in helices III, IV, and VII, which regulate the receptor. Dihydroergotamine, the selected drug, showed binding variance based on ions presence/absence, affecting amino acid residues in these motifs. DCCM and PCA confirmed the stabilization of ligands, with a greater correlation (∼46.6%-PC1) observed with ions. Dihydroergotamine-modified interaction sites within the receptor necessary for activation, serving as a potential 5HT2BRM agonist. RDF analysis showed the sodium ions density around the active site during dihydroergotamine binding.

CONCLUSION

Our study provides insights into sodium ion mobility's role in controlling ligand binding affinity in 5HT2BR, offering therapeutic development insights.

Reanalysis of a μ opioid receptor crystal structure reveals a covalent adduct with BU72

BACKGROUND

The first crystal structure of the active μ opioid receptor (μOR) exhibited several unexplained features. The ligand BU72 exhibited many extreme deviations from ideal geometry, along with unexplained electron density. I previously showed that inverting the benzylic configuration resolved these problems, establishing revised stereochemistry of BU72 and its analog BU74. However, another problem remains unresolved: additional unexplained electron density contacts both BU72 and a histidine residue in the N-terminus, revealing the presence of an as-yet unidentified atom.

RESULTS

These short contacts and uninterrupted density are inconsistent with non-covalent interactions. Therefore, BU72 and μOR form a covalent adduct, rather than representing two separate entities as in the original model. A subsequently proposed magnesium complex is inconsistent with multiple lines of evidence. However, oxygen fits the unexplained density well. While the structure I propose is tentative, similar adducts have been reported previously in the presence of reactive oxygen species. Moreover, known sources of reactive oxygen species were present: HEPES buffer, nickel ions, and a sequence motif that forms redox-active nickel complexes. This motif contacts the unexplained density. The adduct exhibits severe strain, and the tethered N-terminus forms contacts with adjacent residues. These forces, along with the nanobody used as a G protein substitute, would be expected to influence the receptor conformation. Consistent with this, the intracellular end of the structure differs markedly from subsequent structures of active μOR bound to Gi protein.

CONCLUSIONS

Later Gi-bound structures are likely to be more accurate templates for ligand docking and modelling of active G protein-bound μOR. The possibility of reactions like this should be considered in the choice of protein truncation sites and purification conditions, and in the interpretation of excess or unexplained density.

An Atomic Level Investigation of Sodium Ions Regulating Agonist and Antagonist Binding in the Active Site of a Novel Target 5HT2BR Against Drug-Resistant Epilepsy

The study investigates the movement of sodium ions inside the ligand-binding pocket of the class-A GPCR serotonin receptor (5HT_2BR), a primary target for modern drugs. The available PDBs are mutant chimeras, so a 3D structure is modeled and validated by structural similarity (84.05%), Ramachandran favorable residues (93.01%), and clash score. Using MD simulations (500 ns), the ion active site is tracked in the presence and absence of ions and ligands. The ions enter the active site along helices III, VI, and VII, and the primary residue (ASP^3.32) interacts with ions via H-bond (stronger- ~2.4 Å). The radial distribution function around ASP^3.32 rises promptly at intermediate distances (2 Å < r < 4 Å), suggesting a higher probability of finding sodium ions at these distances. The ions stabilize the receptor at a better RMSD and promote stronger interactions (3-H-bonds, 1-π-bond~3.35 Å) with the agonist, and not the antagonist (no H-bond). Simulating unrestrained ligands further confirms this pattern, suggesting that ions might promote agonist binding but not be a prerequisite for antagonist action. The study highlights the mechanistic evaluation of sodium ions mobility in 5HT_2BR modulation and ligand binding, showing potential in drug development.

Synthesis of Bioactive Aminomethylated 8-Hydroxyquinolines via the Modified Mannich Reaction

8-hydroxyquinoline (oxine) is a widely known and frequently used chelating agent, and the pharmacological effects of the core molecule and its derivatives have been studied since the 19th century. There are several synthetic methods to modify this core. The Mannich reaction is one of the most easily implementable examples, which requires mild reaction conditions and simple chemical reagents. The three components of the Mannich reaction are a primary or secondary amine, an aldehyde and a compound having a hydrogen with pronounced activity. In the modified Mannich reaction, naphthol or a nitrogen-containing naphthol analogue (e.g., 8-hydroxyquinoline) is utilised as the active hydrogen provider compound, thus affording the formation of aminoalkylated products. The amine component can be ammonia and primary or secondary amines. The aldehyde component is highly variable, including aliphatic and aromatic aldehydes. Based on the pharmacological relevance of aminomethylated 8-hydroxyquinolines, this review summarises their syntheses via the modified Mannich reaction starting from 8-hydroxyquinoline, formaldehyde and various amines.

Aminosalicylates target GPR35, partly contributing to the prevention of DSS-induced colitis

GPR35, a class A G-protein-coupled receptor, is considered an orphan receptor; the endogenous ligand and precise physiological function of GPR35 remain obscure. GPR35 is expressed relatively highly in the gastrointestinal tract and immune cells. It plays a role in colorectal diseases like inflammatory bowel diseases (IBDs) and colon cancer. More recently, the development of GPR35 targeting anti-IBD drugs is in solid request. Nevertheless, the development process is in stagnation due to the lack of a highly potent GPR35 agonist that is also active comparably in both human and mouse orthologs. Therefore, we proposed to find compounds for GPR35 agonist development, especially for the human ortholog of GPR35. As an efficient way to pick up a safe and effective GPR35 targeting anti-IBD drug, we screened Food and Drug Administration (FDA)-approved 1850 drugs using a two-step DMR assay. Interestingly, we found aminosalicylates, first-line medicine for IBDs whose precise target remains unknown, exhibited activity on both human and mouse GPR35. Among these, pro-drug olsalazine showed the most potency on GPR35 agonism, inducing ERK phosphorylation and β-arrestin2 translocation. In dextran sodium sulfate (DSS)-induced colitis, the protective effect on disease progression and inhibitory effect on TNFα mRNA expression, NF-κB and JAK-STAT3 pathway of olsalazine are compromised in GPR35 knock-out mice. The present study identified a target for first-line medicine aminosalicylates, highlighted that uncleaved pro-drug olsalazine is effective, and provided a new concept for the design of aminosalicylic GPR35 targeting anti-IBD drug.

Insights into divalent cation regulation and G13-coupling of orphan receptor GPR35

Endogenous ions play important roles in the function and pharmacology of G protein-coupled receptors (GPCRs) with limited atomic evidence. In addition, compared with G protein subtypes G_s, G_i/o, and G_q/11, insufficient structural evidence is accessible to understand the coupling mechanism of G_12/13 protein by GPCRs. Orphan receptor GPR35, which is predominantly expressed in the gastrointestinal tract and is closely related to inflammatory bowel diseases (IBDs), stands out as a prototypical receptor for investigating ionic modulation and G₁₃ coupling. Here we report a cryo-electron microscopy structure of G₁₃-coupled GPR35 bound to an anti-allergic drug, lodoxamide. This structure reveals a novel divalent cation coordination site and a unique ionic regulatory mode of GPR35 and also presents a highly positively charged binding pocket and the complementary electrostatic ligand recognition mode, which explain the promiscuity of acidic ligand binding by GPR35. Structural comparison of the GPR35-G₁₃ complex with other G protein subtypes-coupled GPCRs reveals a notable movement of the C-terminus of α5 helix of the Gα₁₃ subunit towards the receptor core and the least outward displacement of the cytoplasmic end of GPR35 TM6. A featured 'methionine pocket' contributes to the G₁₃ coupling by GPR35. Together, our findings provide a structural basis for divalent cation modulation, ligand recognition, and subsequent G₁₃ protein coupling of GPR35 and offer a new opportunity for designing GPR35-targeted drugs for the treatment of IBDs.

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

Translocation Mechanism of Allosteric Sodium Ions in β2-Adrenoceptor

The allosteric modulation of G-protein-coupled receptors (GPCRs) by sodium ions has received significant attention as the crystal structures of several receptors show the binding of sodium ions (Na⁺) at the conserved D^2.50. Theoretical studies have shown that extracellular Na⁺ would enter the allosteric D^2.50 via the orthosteric site. However, it remains unclear how the bound allosteric Na⁺ would leave the GPCRs. In this study, we performed molecular dynamics (MD) simulations to illustrate the energy barriers of Na⁺ transfer through the transmembrane helix bundle of β₂AR. In contrast to the postulations from other GPCRs, the translocation of this allosteric Na⁺ into the intracellular side is found to be significantly difficult. Hence, the translocation direction could be receptor-specific.

Functional expression of opioid receptors and other human GPCRs in yeast engineered to produce human sterols

The yeast Saccharomyces cerevisiae is powerful for studying human G protein-coupled receptors as they can be coupled to its mating pathway. However, some receptors, including the mu opioid receptor, are non-functional, which may be due to the presence of the fungal sterol ergosterol instead of cholesterol. Here we engineer yeast to produce cholesterol and introduce diverse mu, delta, and kappa opioid receptors to create sensitive opioid biosensors that recapitulate agonist binding profiles and antagonist inhibition. Additionally, human mu opioid receptor variants, including those with clinical relevance, largely display expected phenotypes. By testing mu opioid receptor-based biosensors with systematically adjusted cholesterol biosynthetic intermediates, we relate sterol profiles to biosensor sensitivity. Finally, we apply sterol-modified backgrounds to other human receptors revealing sterol influence in SSTR5, 5-HTR4, FPR1, and NPY1R signaling. This work provides a platform for generating human G protein-coupled receptor-based biosensors, facilitating receptor deorphanization and high-throughput screening of receptors and effectors.

In Search of Synergistic Insect Repellents: Modeling of Muscarinic GPCR Interactions with Classical and Bitopic Photoactive Ligands

Insect vector-borne diseases pose serious health problems, so there is a high demand for efficient molecules that could reduce transmission. Using molecular docking and molecular dynamics (MD) simulation, we studied a series of compounds acting on human and insect muscarinic acetylcholine receptors (mAChRs), a novel target of synergistic agents in pest control. We characterized early conformational changes of human M1 and fruit fly type-A mAChR G protein-coupled receptors (GPCRs) in response to DEET, IR3535, and muscarine binding based on the MD analysis of the activation microswitches known to form the signal transduction pathway in class A GPCRs. We indicated groups of microswitches that are the most affected by the presence of a ligand. Moreover, to increase selectivity towards insects, we proposed a new, bitopic, photoswitchable mAChR ligand—BQCA-azo-IR353 and studied its interactions with both receptors. Modeling data showed that using a bitopic ligand may be a promising strategy in the search for better insect control.

Trends in application of advancing computational approaches in GPCR ligand discovery

G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.

Biased Allosteric Modulators: New Frontiers in GPCR Drug Discovery

G protein-coupled receptors (GPCRs) are the largest class of cell surface receptors in the genome and the most successful family of targets of FDA-approved drugs. New frontiers in GPCR drug discovery remain, however, as achieving receptor subtype selectivity and controlling off- and on-target side effects are not always possible with classic agonist and antagonist ligands. These challenges may be overcome by focusing development efforts on allosteric ligands that confer signaling bias. Biased allosteric modulators (BAMs) are an emerging class of GPCR ligands that engage less well-conserved regulatory motifs outside the orthosteric pocket and exert pathway-specific effects on receptor signaling. The unique ways that BAMs texturize receptor signaling present opportunities to fine-tune physiology and develop safer, more selective therapeutics. Here, we provide a conceptual framework for understanding the pharmacology of BAMs, explore their therapeutic potential, and discuss strategies for their discovery.

The Effects of Sodium Ions on Ligand Binding and Conformational States of G Protein-Coupled Receptors-Insights from Mass Spectrometry

The use of mass spectrometry to investigate proteins is now well established and provides invaluable information for both soluble and membrane protein assemblies. Maintaining transient noncovalent interactions under physiological conditions, however, remains challenging. Here, using nanoscale electrospray ionization emitters, we establish conditions that enable mass spectrometry of two G protein-coupled receptors (GPCR) from buffers containing high concentrations of sodium ions. For the Class A GPCR, the adenosine 2A receptor, we observe ligand-induced changes to sodium binding of the receptor at the level of individual sodium ions. We find that antagonists promote sodium binding while agonists attenuate sodium binding. These findings are in line with high-resolution X-ray crystallography wherein only inactive conformations retain sodium ions in allosteric binding pockets. For the glucagon receptor (a Class B GPCR) we observed enhanced ligand binding in electrospray buffers containing high concentrations of sodium, as opposed to ammonium acetate buffers. A combination of native and -omics mass spectrometry revealed the presence of a lipophilic negative allosteric modulator. These experiments highlight the advantages of implementing native mass spectrometry, from electrospray buffers containing high concentrations of physiologically relevant salts, to inform on allosteric ions or ligands with the potential to define their roles on GPCR function.

Dissecting Role of Charged Residue from Transmembrane Domain 5 of Latent Membrane Protein 1 via In Silico Simulations and Wet-Lab Experiments

Charged residues are frequently found in the transmembrane segments of membrane proteins, which reside in the hydrophobic bilayer environment. Charged residues are critical for the function of membrane protein. However, studies of their role in protein oligomerization are limited. By taking the fifth transmembrane domain (TMD5) of latent membrane protein 1 from the Epstein-Barr virus as a prototype model, in silico simulations and wet-lab experiments were performed to investigate how the charged states affect transmembrane domain oligomerization. Molecular dynamics (MD) simulations showed that the D150-protonated TMD5 trimer was stable, whereas unprotonated D150 created bends in the helices which distort the trimeric structure. D150 was mutated to asparagine to mimic the protonated D150 in TMD5, and the MD simulations of different D150N TMD5 trimers supported that the protonation state of D150 was critical for the trimerization of TMD5. In silico mutations found that D150N TMD5 preferred to interact with TMD5 to form the heterotrimer (1 D150N TMD5:2 protonated TMD5s) rather than the heterotrimer (2 D150N TMD5s:1 protonated TMD5). D150R TMD5 interacted with TMD5 to form the heterotrimer (1 D150R TMD5:2 protonated TMD5). These in silico results imply that D150N TMD5 and D150R TMD5 peptides may be probes for disrupting TMD5 trimerization, which was supported by the dominant-negative ToxR assay in bacterial membranes. In all, this study elucidates the role of charged residues at the membrane milieu in membrane protein oligomerization and provides insight into the development of oligomerization-regulating peptides for modulating transmembrane domain lateral interactions.

Clinical HDAC Inhibitors Are Effective Drugs to Prevent the Entry of SARS-CoV2

The outbreak of COVID-19 by the end of 2019 has posed serious health threats to humanity and jeopardized the global economy. However, no effective drugs are available to treat COVID-19 currently and there is a great demand to fight against it. Here, we combined computational screening and an efficient cellular pseudotyped virus system, confirming that clinical HDAC inhibitors can efficiently prevent SARS-CoV-2 and potentially be used to fight against COVID-19.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

Discovering Anti-Cancer Drugs via Computational Methods

New drug discovery has been acknowledged as a complicated, expensive, time-consuming, and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on average, are demanded for a new drug discovery via traditional drug development pipeline. How to reduce the research cost and speed up the development process of new drug discovery has become a challenging, urgent question for the pharmaceutical industry. Computer-aided drug discovery (CADD) has emerged as a powerful, and promising technology for faster, cheaper, and more effective drug design. Recently, the rapid growth of computational tools for drug discovery, including anticancer therapies, has exhibited a significant and outstanding impact on anticancer drug design, and has also provided fruitful insights into the area of cancer therapy. In this work, we discussed the different subareas of the computer-aided drug discovery process with a focus on anticancer drugs.