Surface Plasmon Resonance as a Tool for Ligand Binding Investigation of Engineered GPR17 Receptor, a G Protein Coupled Receptor Involved in Myelination

Lipid Metabolic Disorders Induced by Organophosphate Esters in Silver Carp from the Middle Reaches of the Yangtze River

The Yangtze River fishery resources have declined strongly over the past few decades. One suspected reason for the decline in fishery productivity, including silver carp (Hypophthalmichthys molitrix), has been linked to organophosphate esters (OPEs) contaminant exposure. In this study, the adverse effect of OPEs on lipid metabolism in silver carp captured from the Yangtze River was examined, and our results indicated that muscle concentrations of the OPEs were positively associated with serum cholesterol and total lipid levels. In vivo laboratory results revealed that exposure to environmental concentrations of OPEs significantly increased the concentrations of triglyceride, cholesterol, and total lipid levels. Lipidome analysis further confirmed the lipid metabolism dysfunction induced by OPEs, and glycerophospholipids and sphingolipids were the most affected lipids. Hepatic transcriptomic analysis found that OPEs caused significant alterations in the transcription of genes involved in lipid metabolism. Pathways associated with lipid homeostasis, including the peroxisome proliferator-activated receptor (PPAR) signal pathway, cholesterol metabolism, fatty acid biosynthesis, and steroid biosynthesis, were significantly changed. Furthermore, the affinities of OPEs were different, but the 11 OPEs tested could bind with PPARγ, suggesting that OPEs could disrupt lipid metabolism by interacting with PPARγ. Overall, this study highlighted the harmful effects of OPEs on wild fish and provided mechanistic insights into OPE-induced metabolic disorders.

Fluorescent Tools for the Imaging of Dopamine D2 -Like Receptors

The family of dopamine D2 -like receptors represents an interesting target for a variety of neurological diseases, e. g. Parkinson's disease (PD), addiction, or schizophrenia. In this study we describe the synthesis of a new set of fluorescent ligands as tools for visualization of dopamine D2 -like receptors. Pharmacological characterization in radioligand binding studies identified UR-MN212 (20) as a high-affinity ligand for D2 -like receptors (pKi (D2long R)=8.24, pKi (D3 R)=8.58, pKi (D4 R)=7.78) with decent selectivity towards D1 -like receptors. Compound 20 is a neutral antagonist in a Go1 activation assay at the D2long R, D3 R, and D4 R, which is an important feature for studies using whole cells. The neutral antagonist 20, equipped with a 5-TAMRA dye, displayed rapid association to the D2long R in binding studies using confocal microscopy demonstrating its suitability for fluorescence microscopy. Furthermore, in molecular brightness studies, the ligand's binding affinity could be determined in a single-digit nanomolar range that was in good agreement with radioligand binding data. Therefore, the fluorescent compound can be used for quantitative characterization of native D2 -like receptors in a broad variety of experimental setups.

Shedding Light on the D1 -Like Receptors: A Fluorescence-Based Toolbox for Visualization of the D1 and D5 Receptors

Dopamine D1 -like receptors are the most abundant type of dopamine receptors in the central nervous system and, even after decades of discovery, still highly interesting for the study of neurological diseases. We herein describe the synthesis of a new set of fluorescent ligands, structurally derived from D1 R antagonist SCH-23390 and labeled with two different fluorescent dyes, as tool compounds for the visualization of D1 -like receptors. Pharmacological characterization in radioligand binding studies identified UR-NR435 (25) as a high-affinity ligand for D1 -like receptors (pKi (D1 R)=8.34, pKi (D5 R)=7.62) with excellent selectivity towards D2 -like receptors. Compound 25 proved to be a neutral antagonist at the D1 R and D5 R in a Gs heterotrimer dissociation assay, an important feature to avoid receptor internalization and degradation when working with whole cells. The neutral antagonist 25 displayed rapid association and complete dissociation to the D1 R in kinetic binding studies using confocal microscopy verifying its applicability for fluorescence microscopy. Moreover, molecular brightness studies determined a single-digit nanomolar binding affinity of the ligand, which was in good agreement with radioligand binding data. For this reason, this fluorescent ligand is a useful tool for a sophisticated characterization of native D1 receptors in a variety of experimental setups.

Alchemical Free Energy Calculations on Membrane-Associated Proteins

Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.

The committed oligodendrocyte precursor cell, a newly-defined intermediate progenitor cell type in oligodendroglial lineage

In the central nervous system, oligodendrocytes (OLs) produce myelin sheaths that provide trophic support to neuronal axons and increase the propagation speed of action potential. OLs are constantly generated from OL precursor cells (OPCs) throughout life span. The production of myelinating OLs consists of three canonical stages: OPCs, newly-formed OLs (NFOs), and mature myelinating OLs. Recently, single-cell RNA transcriptomic analyses identified a new population of oligodendroglial cells, namely differentiation committed OPCs (COPs). COPs represent a critical intermediate population between OPCs and NFOs, as revealed by specific expression of G-protein coupled receptor 17 (GPR17). The dysregulation of COPs leads to the remyelination failure in demyelinating diseases and impairs the replacement of lost myelin sheaths due to aging. Hence, understanding the development of COPs and their underlying regulatory network will be helpful in establishing new strategies for promoting myelin repair in demyelinating diseases. This review summarizes the current knowledge on the development and functions of COPs under both physiological and pathological conditions. Overall, COPs function as "checkpoints" to prevent inappropriate precocious OL differentiation and myelination through expressing distinct regulatory factors. Deepening our understanding of COPs may not only advance our knowledge of how OL lineage progresses during development, but also open the door to new treatments for demyelinating diseases.

TitrationAnalysis: a tool for high throughput binding kinetics data analysis for multiple label-free platforms

Label-free techniques including Surface Plasmon Resonance (SPR) and Biolayer Interferometry (BLI) are biophysical tools widely used to collect binding kinetics data of bimolecular interactions. To efficiently analyze SPR and BLI binding kinetics data, we have built a new high throughput analysis tool named the TitrationAnalysis. It can be used as a package in the Mathematica scripting environment and ultilize the non-linear curve-fitting module of Mathematica for its core function. This tool can fit the binding time course data and estimate association and dissociation rate constants ( k a and k d respectively) for determining apparent dissociation constant ( K D) values. The high throughput fitting process is automatic, requires minimal knowledge on Mathematica scripting and can be applied to data from multiple label-free platforms. We demonstrate that the TitrationAnalysis is optimal to analyze antibody-antigen binding data acquired on Biacore T200 (SPR), Carterra LSA (SPR imaging) and ForteBio Octet Red384 (BLI) platforms. The k a, k d and K D values derived using TitrationAnalysis very closely matched the results from the commercial analysis software provided specifically for these instruments. Additionally, the TitrationAnalysis tool generates user-directed customizable results output that can be readily used in downstream Data Quality Control associated with Good Clinical Laboratory Practice operations. With the versatility in source of data input source and options of analysis result output, the TitrationAnalysis high throughput analysis tool offers investigators a powerful alternative in biomolecular interaction characterization.

Identification and characterization of select oxysterols as ligands for GPR17

BACKGROUND AND PURPOSE

G-protein coupled receptor 17 (GPR17) is an orphan receptor involved in the process of myelination, due to its ability to inhibit the maturation of oligodendrocyte progenitor cells (OPCs) into myelinating oligodendrocytes. Despite multiple claims that the biological ligand has been identified, it remains an orphan receptor.

EXPERIMENTAL APPROACH

Seventy-seven oxysterols were screened in a cell-free [³⁵ S]GTPγS binding assay using membranes from cells expressing GPR17. The positive hits were characterized using adenosine 3',5' cyclic monophosphate (cAMP), inositol monophosphate (IP1) and calcium mobilization assays, with results confirmed in rat primary oligodendrocytes. Rat and pig brain extracts were separated by high-performance liquid chromatography (HPLC) and endogenous activator(s) were identified in receptor activation assays. Gene expression studies of GPR17, and CYP46A1 (cytochrome P450 family 46 subfamily A member 1) enzymes responsible for the conversion of cholesterol into specific oxysterols, were performed using quantitative real-time PCR.

KEY RESULTS

Five oxysterols were able to stimulate GPR17 activity, including the brain cholesterol, 24(S)-hydroxycholesterol (24S-HC). A specific brain fraction from rat and pig extracts containing 24S-HC activates GPR17 in vitro. Expression of Gpr17 during mouse brain development correlates with the expression of Cyp46a1 and the levels of 24S-HC itself. Other active oxysterols have low brain concentrations below effective ranges.

CONCLUSIONS AND IMPLICATIONS

Oxysterols, including but not limited to 24S-HC, could be physiological activators for GPR17 and thus potentially regulate OPC differentiation and myelination through activation of the receptor.

Biophysical Approaches for the Characterization of Protein-Metabolite Interactions

With an estimate of hundred thousands of protein molecules per cell and the number of metabolites several orders of magnitude higher, protein-metabolite interactions are omnipresent. In vitro analyses are one of the main pillars on the way to establish a solid understanding of how these interactions contribute to maintaining cellular homeostasis. A repertoire of biophysical techniques is available by which protein-metabolite interactions can be quantitatively characterized in terms of affinity, specificity, and kinetics in a broad variety of solution environments. Several of those provide information on local or global conformational changes of the protein partner in response to ligand binding. This review chapter gives an overview of the state-of-the-art biophysical toolbox for the study of protein-metabolite interactions. It briefly introduces basic principles, highlights recent examples from the literature, and pinpoints promising future directions.

Functional Heterodimerization between the G Protein-Coupled Receptor GPR17 and the Chemokine Receptors 2 and 4: New Evidence

GPR17, a G protein-coupled receptor, is a pivotal regulator of myelination. Its endogenous ligands trigger receptor desensitization and downregulation allowing oligodendrocyte terminal maturation. In addition to its endogenous agonists, GPR17 could be promiscuously activated by pro-inflammatory oxysterols and chemokines released at demyelinating lesions. Herein, the chemokine receptors CXCR2 and CXCR4 were selected to perform both in silico modelling and in vitro experiments to establish their structural and functional interactions with GPR17. The relative propensity of GPR17 and CXCR2 or CXCR4 to form homo- and hetero-dimers was assessed by homology modelling and molecular dynamics (MD) simulations, and co-immunoprecipitation and immunoenzymatic assay. The interaction between chemokine receptors and GPR17 was investigated by determining receptor-mediated modulation of intracellular cyclic adenosine monophosphate (cAMP). Our data show the GPR17 association with CXCR2 or CXCR4 and the negative regulation of these interactions by CXCR agonists or antagonists. Moreover, GPR17 and CXCR2 heterodimers can functionally influence each other. In contrast, CXCR4 can influence GPR17 functionality, but not vice versa. According to MD simulations, all the dimers reached conformational stability and negative formation energy, confirming the experimental observations. The cross-talk between these receptors could play a role in the development of the neuroinflammatory milieu associated with demyelinating events.

Natural product-based PROteolysis TArgeting Chimeras (PROTACs)

Covering: upto 2022Natural products have an embedded recognition of protein surfaces. They possess this property as they are produced by biosynthetic enzymes and are substrates for one or more enzymes in the biosynthetic pathway. The inherent advantages, compared to synthetic compound libraries, is this ligand-protein binding which is, in many cases, a function of the 3-dimensional properties. Protein degradation is a recent novel therapeutic approach with several compounds now in the clinic. This review highlights the potential of PROteolysis TArgeting Chimeras (PROTACs) in the area of natural products. The approach will complement existing approaches such as the direct use of a bioactive natural product or its analogues, pharmacophore development and drug-antibody conjugates. The chemical synthesis and challenges of using natural product-based PROTACs are summarised. The review also highlights methods to detect the ternary complexes necessary for PROTAC mechanism of action.

Using Structure-guided Fragment-Based Drug Discovery to Target Pseudomonas aeruginosa Infections in Cystic Fibrosis

Cystic fibrosis (CF) is progressive genetic disease that predisposes lungs and other organs to multiple long-lasting microbial infections. Pseudomonas aeruginosa is the most prevalent and deadly pathogen among these microbes. Lung function of CF patients worsens following chronic infections with P. aeruginosa and is associated with increased mortality and morbidity. Emergence of multidrug-resistant, extensively drug-resistant and pandrug-resistant strains of P. aeruginosa due to intrinsic and adaptive antibiotic resistance mechanisms has failed the current anti-pseudomonal antibiotics. Hence new antibacterials are urgently needed to treat P. aeruginosa infections. Structure-guided fragment-based drug discovery (FBDD) is a powerful approach in the field of drug development that has succeeded in delivering six FDA approved drugs over the past 20 years targeting a variety of biological molecules. However, FBDD has not been widely used in the development of anti-pseudomonal molecules. In this review, we first give a brief overview of our structure-guided FBDD pipeline and then give a detailed account of FBDD campaigns to combat P. aeruginosa infections by developing small molecules having either bactericidal or anti-virulence properties. We conclude with a brief overview of the FBDD efforts in our lab at the University of Cambridge towards targeting P. aeruginosa infections.

GPCR Systems Pharmacology: A Different Perspective on the Development of Biased Therapeutics

G protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors and are the target of approximately one-third of all Food and Drug Administration (FDA)-approved pharmaceutical drugs. GPCRs interact with many transducers, such as heterotrimeric G proteins, GPCR kinases (GRKs), and β-arrestins. Recent experiments have demonstrated that some ligands can activate distinct effector proteins over others, a phenomenon termed biased agonism. These discoveries have raised the potential of developing drugs which preferentially activate therapeutic signaling pathways over those that lead to deleterious side effects. However, to date, only one biased GPCR therapeutic has received FDA approval and many others have either failed to meet their specified primary endpoints and or demonstrate superiority over currently available treatments. Additionally, there is a lack of understanding regarding how biased agonism measured at a GPCR leads to specific downstream physiologic responses. Here, we briefly summarize the history and current status of biased agonism at GPCRs and suggest adoption of a systems pharmacology approach upon which to develop GPCR-targeted drugs that demonstrate heightened therapeutic efficacy with improved side effect profiles.

Microsecond Active-Site Dynamics Primarily control Proteolytic Activity of Bromelain: A Single Molecular Level Study with a Denaturant, a Stabilizer and a Macromolecular Crowder

Proteins are dynamic entity with various molecular motions at different timescale and length scale. Molecular motions are crucial for the optimal function of an enzyme. It seems intuitive that these motions are crucial for optimal enzyme activity. However, it is not easy to directly correlate an enzyme's dynamics and activity due to biosystems' enormous complexity. amongst many factors, structure and dynamics are two prime aspects that combinedly control the activity. Therefore, having a direct correlation between protein dynamics and activity is not straightforward. Herein, we observed and correlated the structural, functional, and dynamical responses of an industrially crucial proteolytic enzyme, bromelain with three versatile classes of chemicals: GnHCl (protein denaturant), sucrose (protein stabilizer), and Ficoll-70 (macromolecular crowder). The only free cysteine (Cys-25 at the active-site) of bromelain has been tagged with a cysteine-specific dye to unveil the structural and dynamical changes through various spectroscopic studies both at bulk and at the single molecular level. Proteolytic activity is carried out using casein as the substrate. GnHCl and sucrose shows remarkable structure-dynamics-activity relationships. Interestingly, with Ficoll-70, structure and activity are not correlated. However, microsecond dynamics and activity are beautifully correlated in this case also. Overall, our result demonstrates that bromelain dynamics in the microsecond timescale around the active-site is probably a key factor in controlling its proteolytic activity.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Oligodendrocyte Dysfunction in Amyotrophic Lateral Sclerosis: Mechanisms and Therapeutic Perspectives

Myelin is the lipid-rich structure formed by oligodendrocytes (OLs) that wraps the axons in multilayered sheaths, assuring protection, efficient saltatory signal conduction and metabolic support to neurons. In the last few years, the impact of OL dysfunction and myelin damage has progressively received more attention and is now considered to be a major contributing factor to neurodegeneration in several neurological diseases, including amyotrophic lateral sclerosis (ALS). Upon OL injury, oligodendrocyte precursor cells (OPCs) of adult nervous tissue sustain the generation of new OLs for myelin reconstitution, but this spontaneous regeneration process fails to successfully counteract myelin damage. Of note, the functions of OPCs exceed the formation and repair of myelin, and also involve the trophic support to axons and the capability to exert an immunomodulatory role, which are particularly relevant in the context of neurodegeneration. In this review, we deeply analyze the impact of dysfunctional OLs in ALS pathogenesis. The possible mechanisms underlying OL degeneration, defective OPC maturation, and impairment in energy supply to motor neurons (MNs) have also been examined to provide insights on future therapeutic interventions. On this basis, we discuss the potential therapeutic utility in ALS of several molecules, based on their remyelinating potential or capability to enhance energy metabolism.

Quantifying the Affinity of Trypanosoma cruzi RPA-1 to the Single-Stranded DNA Overhang of the Telomere Using Surface Plasmon Resonance

Surface plasmon resonance (SPR) biosensors provide real-time binding affinity measurements between a pair of biomolecules, characterizing its interaction dynamics. An example of Trypanosoma cruzi's RPA-1 and a single-stranded DNA telomere sequence is presented with detailed guidelines and fundamentals for SPR technology.

Development of the first in vivo GPR17 ligand through an iterative drug discovery pipeline: A novel disease-modifying strategy for multiple sclerosis

The GPR17 receptor, expressed on oligodendroglial precursors (OPCs, the myelin producing cells), has emerged as an attractive target for a pro-myelinating strategy in multiple sclerosis (MS). However, the proof-of-concept that selective GPR17 ligands actually exert protective activity in vivo is still missing. Here, we exploited an iterative drug discovery pipeline to prioritize novel and selective GPR17 pro-myelinating agents out of more than 1,000,000 compounds. We first performed an in silico high-throughput screening on GPR17 structural model to identify three chemically-diverse ligand families that were then combinatorially exploded and refined. Top-scoring compounds were sequentially tested on reference pharmacological in vitro assays with increasing complexity, ending with myelinating OPC-neuron co-cultures. Successful ligands were filtered through in silico simulations of metabolism and pharmacokinetics, to select the most promising hits, whose dose and ability to target the central nervous system were then determined in vivo. Finally, we show that, when administered according to a preventive protocol, one of them (named by us as galinex) is able to significantly delay the onset of experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. This outcome validates the predictivity of our pipeline to identify novel MS-modifying agents.

Regulation and signaling of the GPR17 receptor in oligodendroglial cells

Remyelination, namely, the formation of new myelin sheaths around denuded axons, counteracts axonal degeneration and restores neuronal function. Considerable advances have been made in understanding this regenerative process that often fails in diseases like multiple sclerosis, leaving axons demyelinated and vulnerable to damage, thus contributing to disease progression. The identification of the membrane receptor GPR17 on a subset of oligodendrocyte precursor cells (OPCs), which mediate remyelination in the adult central nervous system (CNS), has led to a huge amount of evidence that validated this receptor as a new attractive target for remyelinating therapies. Here, we summarize the role of GPR17 in OPC function, myelination and remyelination, describing its atypical pharmacology, its downstream signaling, and the genetic and epigenetic factors modulating its activity. We also highlight crucial insights into GPR17 pathophysiology coming from the demonstration that oligodendrocyte injury, associated with inflammation in chronic neurodegenerative conditions, is invariably characterized by abnormal and persistent GPR17 upregulation, which, in turn, is accompanied by a block of OPCs at immature premyelinating stages. Finally, we discuss the current literature in light of the potential exploitment of GPR17 as a therapeutic target to promote remyelination.