Structure-inspired design of β-arrestin-biased ligands for aminergic GPCRs

Peptide-derived ligands for the discovery of safer opioid analgesics

Drugs targeting the μ-opioid receptor (MOR) remain the most efficacious analgesics for the treatment of pain, but activation of MOR with current opioid analgesics also produces harmful side effects, notably physical dependence, addiction, and respiratory depression. Opioid peptides have been accepted as promising candidates for the development of safer and more efficacious analgesics. To develop peptide-based opioid analgesics, strategies such as modification of endogenous opioid peptides, development of multifunctional opioid peptides, G protein-biased opioid peptides, and peripherally restricted opioid peptides have been reported. This review seeks to provide an overview of the opioid peptides that produce potent antinociception with much reduced side effects in animal models and highlight the potential advantages of peptides as safer opioid analgesics.

Flexible scaffold-based cheminformatics approach for polypharmacological drug design

Effective treatments for complex central nervous system (CNS) disorders require drugs with polypharmacology and multifunctionality, yet designing such drugs remains a challenge. Here, we present a flexible scaffold-based cheminformatics approach (FSCA) for the rational design of polypharmacological drugs. FSCA involves fitting a flexible scaffold to different receptors using different binding poses, as exemplified by IHCH-7179, which adopted a "bending-down" binding pose at 5-HT2AR to act as an antagonist and a "stretching-up" binding pose at 5-HT1AR to function as an agonist. IHCH-7179 demonstrated promising results in alleviating cognitive deficits and psychoactive symptoms in mice by blocking 5-HT2AR for psychoactive symptoms and activating 5-HT1AR to alleviate cognitive deficits. By analyzing aminergic receptor structures, we identified two featured motifs, the "agonist filter" and "conformation shaper," which determine ligand binding pose and predict activity at aminergic receptors. With these motifs, FSCA can be applied to the design of polypharmacological ligands at other receptors.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

Exploring biased activation characteristics by molecular dynamics simulation and machine learning for the μ-opioid receptor

Biased ligands selectively activating specific downstream signaling pathways (termed as biased activation) exhibit significant therapeutic potential. However, the conformational characteristics revealed are very limited for the biased activation, which is not conducive to biased drug development. Motivated by the issue, we combine extensive accelerated molecular dynamics simulations and an interpretable deep learning model to probe the biased activation features for two complex systems constructed by the inactive μOR and two different biased agonists (G-protein-biased agonist TRV130 and β-arrestin-biased agonist endomorphin2). The results indicate that TRV130 binds deeper into the receptor core compared to endomorphin2, located between W2936.48 and D1142.50, and forms hydrogen bonding with D1142.50, while endomorphin2 binds above W2936.48. The G protein-biased agonist induces greater outward movements of the TM6 intracellular end, forming a typical active conformation, while the β-arrestin-biased agonist leads to a smaller extent of outward movements of TM6. Compared with TRV130, endomorphin2 causes more pronounced inward movements of the TM7 intracellular end and more complex conformational changes of H8 and ICL1. In addition, important residues determining the two different biased activation states were further identified by using an interpretable deep learning classification model, including some common biased activation residues across Class A GPCRs like some key residues on the TM2 extracellular end, ECL2, TM5 intracellular end, TM6 intracellular end, and TM7 intracellular end, and some specific important residues of ICL3 for μOR. The observations will provide valuable information for understanding the biased activation mechanism for GPCRs.

Macrophage β-arrestin-1 deteriorates DSS-induced colitis through interaction with NF-κB signaling

β-arrestin-1 has been demonstrated to participate in the regulation of inflammatory reactions in several diseases. Thus, this study aimed to investigate the role of macrophage β-arrestin-1 in the pathogenesis and progression of ulcerative colitis (UC). A myeloid β-arrestin-1 conditional knockout mouse model was generated to explore the role of macrophage β-arrestin-1. DSS was employed for the establishment of an ulcerative colitis mouse model, using TNF-α as an inflammatory stressor in vitro. The expression level of β-arrestin-1 was detected via western blot and immunofluorescence assays, whilst disease severity was evaluated by clinical score and H&E staining in the DSS-induced colitis model. In the in vitro experiments, the levels of inflammatory cytokines were examined using real-time PCR. NF-κB activation was detected through the double luciferase reporter system, western blot, and electrophoretic mobility shift assay (EMSA). BAY11-7082 was used to inhibit NF-κB activation. Our results exposed that the level of β-arrestin-1 was increased in monocytes/macrophages derived from DSS-induced colitis mice or under the TNF-α challenge. Moreover, conditionally knocking out the expression of myeloid β-arrestin-1 alleviated disease severity, while knocking out the expression of β-arrestin-1 decreased the levels of inflammatory cytokines. Additionally, NF-κB was identified as a central regulatory element of β-arrestin-1 promoter, and using BAY11-7082 to inhibit NF-κB activation lowered the level of β-arrestin-1 under TNF-α challenge. β-arrestin-1 led to the activation of the NF-κB signaling pathway by enhancing binding to IκBα and IKK under the TNF-α challenge. Taken together, our findings demonstrated macrophage β-arrestin-1 contributes to the deterioration of DSS-induced colitis through the interaction with NF-κB signaling, thus highlighting a novel target for the treatment of UC.

Molecular basis of human trace amine-associated receptor 1 activation

The human trace amine-associated receptor 1 (hTAAR1, hTA1) is a key regulator of monoaminergic neurotransmission and the actions of psychostimulants. Despite preclinical research demonstrating its tractability as a drug target, its molecular mechanisms of activation remain unclear. Moreover, poorly understood pharmacological differences between rodent and human TA1 complicate the translation of findings from preclinical disease models into novel pharmacotherapies. To elucidate hTA1's mechanisms on the molecular scale and investigate the underpinnings of its divergent pharmacology from rodent orthologs, we herein report the structure of the human TA1 receptor in complex with a Gαs heterotrimer. Our structure reveals shared structural elements with other TAARs, as well as with its closest monoaminergic orthologue, the serotonin receptor 5-HT4R. We further find that a single mutation dramatically shifts the selectivity of hTA1 towards that of its rodent orthologues, and report on the effects of substituting residues to those found in serotonin and dopamine receptors. Strikingly, we also discover that the atypical antipsychotic medication and pan-monoaminergic antagonist asenapine potently and efficaciously activates hTA1. Together our studies provide detailed insight into hTA1 structure and function, contrast its molecular pharmacology with that of related receptors, and uncover off-target activities of monoaminergic drugs at hTA1.

Key aspects of modern GPCR drug discovery

G-protein-coupled receptors (GPCRs) are the largest and most versatile cell surface receptor family with a broad repertoire of ligands and functions. We've learned an enormous amount about discovering drugs of this receptor class since the first GPCR was cloned and expressed in 1986, such that it's now well-recognized that GPCRs are the most successful target class for approved drugs. Here we take the reader through a GPCR drug discovery journey from target to the clinic, highlighting the key learnings, best practices, challenges, trends and insights on discovering drugs that ultimately modulate GPCR function therapeutically in patients. The future of GPCR drug discovery is inspiring, with more desirable drug mechanisms and new technologies enabling the delivery of better and more successful drugs.

Biased Dopamine D2 Receptors Exhibit Distinct Intracellular Trafficking Properties and ERK Activation in Different Subcellular Domains

Biased signaling or functional selectivity refers to the ability of an agonist or receptor to selectively activate a subset of transducers such as G protein and arrestin in the case of G protein-coupled receptors (GPCRs). Although signaling through arrestin has been reported from various GPCRs, only a few studies have examined side-by-side how it differs from signaling via G protein. In this study, two signaling pathways were compared using dopamine D2 receptor (D2R) mutants engineered via the evolutionary tracer method to selectively transduce signals through G protein or arrestin (D2G and D2Arr, respectively). D2G mediated the inhibition of cAMP production and ERK activation in the cytoplasm. D2Arr, in contrast, mediated receptor endocytosis accompanied by arrestin ubiquitination and ERK activation in the nucleus as well as in the cytoplasm. D2Arr-mediated ERK activation occurred in a manner dependent on arrestin3 but not arrestin2, accompanied by the nuclear translocation of arrestin3 via importin1. D2R-mediated ERK activation, which occurred in both the cytosol and nucleus, was limited to the cytosol when cellular arrestin3 was depleted. This finding supports the results obtained with D2Arr and D2G. Taken together, these observations indicate that biased signal transduction pathways activate distinct downstream mechanisms and that the subcellular regions in which they occur could be different when the same effectors are involved. These findings broaden our understanding on the relation between biased receptors and the corresponding downstream signaling, which is critical for elucidating the functional roles of biased pathways.

Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor

Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-β-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-β-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-β-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.

Ligand selectivity hotspots in serotonin GPCRs

Serotonin is a neurotransmitter regulating numerous physiological processes also modulated by drugs, for example, schizophrenia, depression, migraine, and obesity. However, these drugs typically have adverse effects caused by promiscuous binding across 12 serotonin and more than 20 homologous receptors. Recently, structures of the entire serotonin receptor family uncovered molecular ligand recognition. Here, we present a map of 19 'selectivity hotspots', that is, nonconserved binding site residues governing selectivity via favorable target interactions or repulsive 'off-target' contacts. Furthermore, we review functional rationale from observed ligand-binding affinities and mutagenesis effects. Unifying knowledge underlying specific probes and drugs is critical toward the functional characterization of different receptors and alleviation of adverse effects.

Interplay of thermodynamics and evolution within the ternary ligand-GPCR-G protein complex

Recent studies on G protein-coupled receptors (GPCRs) dynamics report that GPCRs adopt a wide range of conformations that coexist in equilibrium, with the apo state of a GPCR having a high entropy. The formation of a ligand-GPCR-transducer complex comes with a reduction of conformational space and therefore with an entropic cost. We hypothesize that the availability of binding partners, their binding affinity and the rigidity of the respective binding sites are reflected in a distinct degree of sequence conservation to balance the energetic cost of intra- and extracellular binding events. Here, we outline the current findings in delineating the conformational space and include sequential conservation of many-to-many ligand-receptor systems to discuss the entropic cost that comes with GPCR signal transduction.

Structure and Molecular Mechanism of Signaling for the Glucagon-like Peptide-1 Receptor Bound to Gs Protein and Exendin-P5 Biased Agonist

The glucagon-like peptide-1 receptor (GLP-1R) is a key regulator of blood glucose and a prime target for the treatment of type II diabetes and obesity with multiple public drugs. Here we present a comprehensive computational analysis of the interactions of the activated GLP-1R-Gs signaling complex with a G protein biased agonist, Exendin P5 (ExP5), which possesses a unique N-terminal sequence responsible for the signal bias. Using a refined all-atom model of the ExP5-GLP-1R-Gs complex in molecular dynamics (MD) simulations, we propose a novel mechanism of conformation transduction in which the unique interaction network of ExP5 N-terminus propagates the binding signal across an array of conserved residues at the transmembrane domain to enhance Gs protein coupling at the cytoplasmic end of the receptor. Our simulations reveal previously unobserved interactions important for activation by ExP5 toward GDP-GTP signaling, providing new insights into the mechanism of class B G protein-coupled receptor (GPCR) signaling. These findings offer a framework for the structure-based design of more effective therapeutics.

Molecular Basis of Human Trace Amine-Associated Receptor 1 Activation

The human trace amine-associated receptor 1 (hTAAR1, hTA1) is a key regulator of monoaminergic neurotransmission and the actions of psychostimulants. Despite preclinical research demonstrating its tractability as a drug target, its molecular mechanisms of activation remain unclear. Moreover, poorly understood pharmacological differences between rodent and human TA1 complicate the translation of findings from preclinical disease models into novel pharmacotherapies. To elucidate hTA1's mechanisms on the molecular scale and investigate the underpinnings of its divergent pharmacology from rodent orthologs, we herein report the structure of the human TA1 receptor in complex with a Gαs heterotrimer. Our structure reveals shared structural elements with other TAARs, as well as with its closest monoaminergic ortholog, the serotonin receptor 5-HT4R. We further find that a single mutation dramatically shifts the selectivity of hTA1 towards that of its rodent orthologs, and report on the effects of substituting residues to those found in serotonin and dopamine receptors. Strikingly, we also discover that the atypical antipsychotic medication and pan-monoaminergic antagonist asenapine potently and efficaciously activates hTA1. Together our studies provide detailed insight into hTA1 structure and function, contrast its molecular pharmacology with that of related receptors, and uncover off-target activities of monoaminergic drugs at hTA1.

The Lost and Found: Unraveling the Functions of Orphan Genes

Orphan Genes (OGs) are a mysterious class of genes that have recently gained significant attention. Despite lacking a clear evolutionary history, they are found in nearly all living organisms, from bacteria to humans, and they play important roles in diverse biological processes. The discovery of OGs was first made through comparative genomics followed by the identification of unique genes across different species. OGs tend to be more prevalent in species with larger genomes, such as plants and animals, and their evolutionary origins remain unclear but potentially arise from gene duplication, horizontal gene transfer (HGT), or de novo origination. Although their precise function is not well understood, OGs have been implicated in crucial biological processes such as development, metabolism, and stress responses. To better understand their significance, researchers are using a variety of approaches, including transcriptomics, functional genomics, and molecular biology. This review offers a comprehensive overview of the current knowledge of OGs in all domains of life, highlighting the possible role of dark transcriptomics in their evolution. More research is needed to fully comprehend the role of OGs in biology and their impact on various biological processes.

Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells

G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to understand specific aspects of receptor signaling and therapeutic leads with more specific, desired activity. Challenges exist, however, in the development of new biased activators due, in part, to the low throughput of traditional screening approaches. DNA-encoded chemical libraries (DELs) dramatically improve the throughput of drug discovery by allowing a collective selection, rather than discrete screening, of large compound libraries. The use of DELs has been largely limited to affinity-based selections against purified protein targets, which identify binders only. Herein, we report a split protein complementation approach that allows direct identification of DNA-linked molecules that induce the dimerization of two proteins. We used this selection with a DEL against opioid receptor GPCRs on living cells for the identification of small molecules that possess the specific function of activation of either β-arrestin or G protein signaling pathways. This approach was applied to δ-, μ-, and κ-opioid receptors and enabled the discovery of compound [66,66], a selective, G-protein-biased agonist of the κ-opioid receptor (EC₅₀ = 100 nM, E _max = 82%, G_i bias factor = 6.6). This approach should be generally applicable for the direct selection of chemical inducers of dimerization from DELs and expand the utility of DELs to enrich molecules with a specific and desired biochemical function.

Constrained catecholamines gain β2AR selectivity through allosteric effects on pocket dynamics

G protein-coupled receptors (GPCRs) within the same subfamily often share high homology in their orthosteric pocket and therefore pose challenges to drug development. The amino acids that form the orthosteric binding pocket for epinephrine and norepinephrine in the β1 and β2 adrenergic receptors (β1AR and β2AR) are identical. Here, to examine the effect of conformational restriction on ligand binding kinetics, we synthesized a constrained form of epinephrine. Surprisingly, the constrained epinephrine exhibits over 100-fold selectivity for the β2AR over the β1AR. We provide evidence that the selectivity may be due to reduced ligand flexibility that enhances the association rate for the β2AR, as well as a less stable binding pocket for constrained epinephrine in the β1AR. The differences in the amino acid sequence of the extracellular vestibule of the β1AR allosterically alter the shape and stability of the binding pocket, resulting in a marked difference in affinity compared to the β2AR. These studies suggest that for receptors containing identical binding pocket residues, the binding selectivity may be influenced in an allosteric manner by surrounding residues, like those of the extracellular loops (ECLs) that form the vestibule. Exploiting these allosteric influences may facilitate the development of more subtype-selective ligands for GPCRs.

Unveiling the Differences in Signaling and Regulatory Mechanisms between Dopamine D2 and D3 Receptors and Their Impact on Behavioral Sensitization

Dopamine receptors are classified into five subtypes, with D2R and D3R playing a crucial role in regulating mood, motivation, reward, and movement. Whereas D2R are distributed widely across the brain, including regions responsible for motor functions, D3R are primarily found in specific areas related to cognitive and emotional functions, such as the nucleus accumbens, limbic system, and prefrontal cortex. Despite their high sequence homology and similar signaling pathways, D2R and D3R have distinct regulatory properties involving desensitization, endocytosis, posttranslational modification, and interactions with other cellular components. In vivo, D3R is closely associated with behavioral sensitization, which leads to increased dopaminergic responses. Behavioral sensitization is believed to result from D3R desensitization, which removes the inhibitory effect of D3R on related behaviors. Whereas D2R maintains continuous signal transduction through agonist-induced receptor phosphorylation, arrestin recruitment, and endocytosis, which recycle and resensitize desensitized receptors, D3R rarely undergoes agonist-induced endocytosis and instead is desensitized after repeated agonist exposure. In addition, D3R undergoes more extensive posttranslational modifications, such as glycosylation and palmitoylation, which are needed for its desensitization. Overall, a series of biochemical settings more closely related to D3R could be linked to D3R-mediated behavioral sensitization.

Mechanism of activation and biased signaling in complement receptor C5aR1

The complement system plays an important role in the innate immune response to invading pathogens. The complement fragment C5a is one of its important effector components and exerts diverse physiological functions through activation of the C5a receptor 1 (C5aR1) and associated downstream G protein and β-arrestin signaling pathways. Dysfunction of the C5a-C5aR1 axis is linked to numerous inflammatory and immune-mediated diseases, but the structural basis for activation and biased signaling of C5aR1 remains elusive. Here, we present cryo-electron microscopy structures of the activated wild-type C5aR1-G_i protein complex bound to each of the following: C5a, the hexapeptidic agonist C5a^pep, and the G protein-biased agonist BM213. The structures reveal the landscape of the C5a-C5aR1 interaction as well as a common motif for the recognition of diverse orthosteric ligands. Moreover, combined with mutagenesis studies and cell-based pharmacological assays, we deciphered a framework for biased signaling using different peptide analogs and provided insight into the activation mechanism of C5aR1 by solving the structure of C5aR1^I116A mutant-G_i signaling activation complex induced by C089, which exerts antagonism on wild-type C5aR1. In addition, unusual conformational changes in the intracellular end of transmembrane domain 7 and helix 8 upon agonist binding suggest a differential signal transduction process. Collectively, our study provides mechanistic understanding into the ligand recognition, biased signaling modulation, activation, and G_i protein coupling of C5aR1, which may facilitate the future design of therapeutic agents.

Signaling Modulation via Minimal C-Terminal Modifications of Apelin-13

Apelin is an endogenous peptide that is involved in many diseases such as cardiovascular diseases, obesity, and cancer, which has made it an attractive target for drug discovery. Herein, we explore the penultimate and final sequence positions of [Pyr1]-apelin-13 (Ape13) via C-terminal N α-alkylated amide bonds and the introduction of positive charges, potentially targeting the allosteric sodium pocket, by assessing the binding affinity and signaling profiles at the apelin receptor (APJ). Synthetic analogues modified within this segment of Ape13 showed high affinity (K i 0.12-0.17 nM vs Ape13 K i 0.7 nM), potent Gαi1 activation (EC50 Gαi1 0.4-0.9 nM vs Ape13 EC50 1.1 nM), partial agonist behavior disfavoring β-arrestin 2 recruitment for positively charged ligands (e.g., 49 (SBL-AP-058), EC50 β-arr2 275 nM, E max 54%) and high plasma stability for N-alkyl ligands (t 1/2 > 7 h vs Ape13 t 1/2 0.5 h). Combining the benefits of the N α-alkylated amide bond with the guanidino substitution in a constrained ligand led to 63 (SBL-AP-049), which displayed increased plasma stability (t 1/2 5.3 h) and strong reduction of β-arrestin 2 signaling with partial maximal efficacy (EC50 β-arr 864 nM, E max 48%), significantly reducing the hypotensive effect in vivo.

Recent advances in dopamine D2 receptor ligands in the treatment of neuropsychiatric disorders

Dopamine is a biologically active amine synthesized in the central and peripheral nervous system. This biogenic monoamine acts by activating five types of dopamine receptors (D_1-5 Rs), which belong to the G protein-coupled receptor family. Antagonists and partial agonists of D₂ Rs are used to treat schizophrenia, Parkinson's disease, depression, and anxiety. The typical pharmacophore with high D₂ R affinity comprises four main areas, namely aromatic moiety, cyclic amine, central linker and aromatic/heteroaromatic lipophilic fragment. From the literature reviewed herein, we can conclude that 4-(2,3-dichlorophenyl), 4-(2-methoxyphenyl)-, 4-(benzo[b]thiophen-4-yl)-1-substituted piperazine, and 4-(6-fluorobenzo[d]isoxazol-3-yl)piperidine moieties are critical for high D₂ R affinity. Four to six atoms chains are optimal for D₂ R affinity with 4-butoxyl as the most pronounced one. The bicyclic aromatic/heteroaromatic systems are most frequently occurring as lipophilic appendages to retain high D₂ R affinity. In this review, we provide a thorough overview of the therapeutic potential of D₂ R modulators in the treatment of the aforementioned disorders. In addition, this review summarizes current knowledge about these diseases, with a focus on the dopaminergic pathway underlying these pathologies. Major attention is paid to the structure, function, and pharmacology of novel D₂ R ligands, which have been developed in the last decade (2010-2021), and belong to the 1,4-disubstituted aromatic cyclic amine group. Due to the abundance of data, allosteric D₂ R ligands and D₂ R modulators from patents are not discussed in this review.

Protein-Protein Interaction Studies Using Molecular Dynamics Simulation

Protein-protein interaction (PPI) is a crucial event for many biological functions. Studying the molecular details of PPI requires structure determination using X-ray crystallography, nuclear magnetic resistance (NMR), and single particle Cryo-EM. However, sometimes it is not easy to solve the complex structure for various reasons. For example, complex may be unstable, not enough protein expression for structural studies, etc. Further, PPI are intricate processes, and its molecular details cannot be fully explained by experimental observations. Here, we describe a quick and simple method to study the PPI using the combinatorial approach of molecular dynamics simulation and biophysical methods.

Pharmacological targeting of G protein-coupled receptor heteromers

A main rationale for the role of G protein-coupled receptor (GPCR) heteromers as targets for drug development is the putative ability of selective ligands for specific GPCRs to change their pharmacological properties upon GPCR heteromerization. The present study provides a proof of concept for this rationale by demonstrating that heteromerization of dopamine D1 and D3 receptors (D1R and D3R) influences the pharmacological properties of three structurally similar selective dopamine D3R ligands, the phenylpiperazine derivatives PG01042, PG01037 and VK4-116. By using D1R-D3R heteromer-disrupting peptides, it could be demonstrated that the three D3R ligands display different D1R-D3R heteromer-dependent pharmacological properties: PG01042, acting as G protein-biased agonist, counteracted D1R-mediated signaling in the D1R-D3R heteromer; PG01037, acting as a D3R antagonist cross-antagonized D1R-mediated signaling in the D1R-D3R heteromer; and VK4-116 specifically acted as a ß-arrestin-biased agonist in the D1R-D3R heteromer. Molecular dynamics simulations predicted potential molecular mechanisms mediating these qualitatively different pharmacological properties of the selective D3R ligands that are dependent on D1R-D3R heteromerization. The results of in vitro experiments were paralleled by qualitatively different pharmacological properties of the D3R ligands in vivo. The results supported the involvement of D1R-D3R heteromers in the locomotor activation by D1R agonists in reserpinized mice and L-DOPA-induced dyskinesia in rats, highlighting the D1R-D3R heteromer as a main pharmacological target for L-DOPA-induced dyskinesia in Parkinson's disease. More generally, the present study implies that when suspecting its pathogenetic role, a GPCR heteromer, and not its individual GPCR units, should be considered as main target for drug development.

β-Arrestin2-biased Drd2 agonist UNC9995 alleviates astrocyte inflammatory injury via interaction between β-arrestin2 and STAT3 in mouse model of depression

Background

Major depressive disorder (MDD) is a prevalent and devastating psychiatric illness. Unfortunately, the current therapeutic practice, generally depending on the serotonergic system for drug treatment is unsatisfactory and shows intractable side effects. Multiple evidence suggests that dopamine (DA) and dopaminergic signals associated with neuroinflammation are highly involved in the pathophysiology of depression as well as in the mechanism of antidepressant drugs, which is still in the early stage of study and well worthy of investigation.

Methods

We established two chronic stress models, including chronic unpredictable mild stress (CUMS), and chronic social defeat stress (CSDS), to complementarily recapitulate depression-like behaviors. Then, hippocampal tissues were used to detect inflammation-related molecules and signaling pathways. Pathological changes in depressive mouse hippocampal astrocytes were examined by RNA sequencing. After confirming the dopamine receptor 2 (Drd2)/β-arrestin2 signaling changes in the depressive mice brain, we then established the depressive mouse model using the β-arrestin2 knockout mice or administrating the β-arrestin2-biased Drd2 agonist to investigate the roles. Label-free mass spectrometry was used to identify the β-arrestin2-binding proteins as the underlying mechanisms. We modeled neuroinflammation with interleukin-6 (IL-6) and corticosterone treatment and characterized astrocytes using multiple methods including cell viability assay, flow cytometry, and confocal immunofluorescence.

Results

Drd2-biased β-arrestin2 pathway is significantly changed in the progression of depression, and genetic deletion of β-arrestin2 aggravates neuroinflammation and depressive-like phenotypes. Mechanistically, astrocytic β-arrestin2 retains STAT3 in the cytoplasm by structural combination with STAT3, therefore, inhibiting the JAK–STAT3 pathway-mediated inflammatory activation. Furtherly, pharmacological activation of Drd2/β-arrestin2 pathway by UNC9995 abolishes the inflammation-induced loss of astrocytes and ameliorates depressive-like behaviors in mouse model for depression.

Conclusions

Drd2/β-arrestin2 pathway is a potential therapeutic target for depression and β-arrestin2-biased Drd2 agonist UNC9995 is identified as a potential anti-depressant strategy for preventing astrocytic dysfunctions and relieving neuropathological manifestations in mouse model for depression, which provides insights for the therapy of depression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02597-6.

MO-MEMES: A method for accelerating virtual screening using multi-objective Bayesian optimization

The pursuit of potential inhibitors for novel targets has become a very important problem especially over the last 2 years with the world in the midst of the COVID-19 pandemic. This entails performing high throughput screening exercises on drug libraries to identify potential “hits”. These hits are identified using analysis of their physical properties like binding affinity to the target receptor, octanol-water partition coefficient (LogP) and more. However, drug libraries can be extremely large and it is infeasible to calculate and analyze the physical properties for each of those molecules within acceptable time and moreover, each molecule must possess a multitude of properties apart from just the binding affinity. To address this problem, in this study, we propose an extension to the Machine learning framework for Enhanced MolEcular Screening (MEMES) framework for multi-objective Bayesian optimization. This approach is capable of identifying over 90% of the most desirable molecules with respect to all required properties while explicitly calculating the values of each of those properties on only 6% of the entire drug library. This framework would provide an immense boost in identifying potential hits that possess all properties required for a drug molecules.

Structure-Based Evolution of G Protein-Biased μ-Opioid Receptor Agonists

The μ-opioid receptor (μOR) is the major target for opioid analgesics. Activation of μOR initiates signaling through G protein pathways as well as through β-arrestin recruitment. μOR agonists that are biased towards G protein signaling pathways demonstrate diminished side effects. PZM21, discovered by computational docking, is a G protein biased μOR agonist. Here we report the cryoEM structure of PZM21 bound μOR in complex with G_i protein. Structure-based evolution led to multiple PZM21 analogs with more pronounced G_i protein bias and increased lipophilicity to improve CNS penetration. Among them, FH210 shows extremely low potency and efficacy for arrestin recruitment. We further determined the cryoEM structure of FH210 bound to μOR in complex with G_i protein and confirmed its expected binding pose. The structural and pharmacological studies reveal a potential mechanism to reduce β-arrestin recruitment by the μOR, and hold promise for developing next-generation analgesics with fewer adverse effects.

Structure-guided optimization of light-activated chimeric G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) are the largest human receptor family and involved in virtually every physiological process. One hallmark of their function is specific coupling to selected signaling pathways. The ability to tune this coupling would make development of receptors with new capabilities possible. Complexes of GPCRs and G-proteins have recently been resolved at high resolution, but this information was in only few cases harnessed for rational receptor engineering. Here, we demonstrate structure-guided optimization of light-activated OptoXRs. Our hypothesis was that incorporation of GPCR-Gα contacts would lead to improved coupling. We first evaluated structure-based alignments for chimeric receptor fusion. We then show in a light-activated β₂AR that including Gα contacts increased signaling 7- to 20-fold compared with other designs. In turn, contact elimination diminished function. Finally, this platform allowed optimization of a further OptoXR and spectral tuning. Our work exemplifies structure-based OptoXR development for targeted cell and network manipulation.

The Impact of the Secondary Binding Pocket on the Pharmacology of Class A GPCRs

G-protein coupled receptors (GPCRs) are considered important therapeutic targets due to their pathophysiological significance and pharmacological relevance. Class A receptors represent the largest group of GPCRs that gives the highest number of validated drug targets. Endogenous ligands bind to the orthosteric binding pocket (OBP) embedded in the intrahelical space of the receptor. During the last 10 years, however, it has been turned out that in many receptors there is secondary binding pocket (SBP) located in the extracellular vestibule that is much less conserved. In some cases, it serves as a stable allosteric site harbouring allosteric ligands that modulate the pharmacology of orthosteric binders. In other cases it is used by bitopic compounds occupying both the OBP and SBP. In these terms, SBP binding moieties might influence the pharmacology of the bitopic ligands. Together with others, our research group showed that SBP binders contribute significantly to the affinity, selectivity, functional activity, functional selectivity and binding kinetics of bitopic ligands. Based on these observations we developed a structure-based protocol for designing bitopic compounds with desired pharmacological profile.

An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors

Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated by MD remains challenging; thus an intelligent navigation is highly desired. Despite intelligent advantages of deep learning exhibited in analyzing MD trajectory, its black-box nature limits its application. To address this problem, we explore an interpretable convolutional neural network (CNN)-based deep learning framework to automatically identify diverse active states from the MD trajectory for G-protein-coupled receptors (GPCRs), named the ICNNMD model. To avoid the information loss in representing the conformation structure, the pixel representation is introduced, and then the CNN module is constructed to efficiently extract features followed by a fully connected neural network to realize the classification task. More importantly, we design a local interpretable model-agnostic explanation interpreter for the classification result by local approximation with a linear model, through which important residues underlying distinct active states can be quickly identified. Our model showcases higher than 99% classification accuracy for three important GPCR systems with diverse active states. Notably, some important residues in regulating different biased activities are successfully identified, which are beneficial to elucidating diverse activation mechanisms for GPCRs. Our model can also serve as a general tool to analyze MD trajectory for other biomolecular systems. All source codes are freely available at https://github.com/Jane-Liu97/ICNNMD for aiding MD studies.

Discovery of a functionally selective ghrelin receptor (GHSR1a) ligand for modulating brain dopamine

The modulation of growth hormone secretagogue receptor-1a (GHSR_1a) signaling is a promising strategy for treating brain conditions of metabolism, aging, and addiction. GHSR_1a activation results in pleiotropic physiological outcomes through distinct and pharmacologically separable G protein– and β-arrestin (βarr)–dependent signaling pathways. Thus, pathway-selective modulation can enable improved pharmacotherapeutics that can promote therapeutic efficacy while mitigating side effects. Here, we describe the discovery of a brain-penetrant small molecule, N8279 (NCATS-SM8864), that biases GHSR_1a conformations toward Gα_q activation and reduces aberrant dopaminergic behavior in mice. N8279 represents a promising chemical scaffold to advance the development of better treatments for GHSR_1a-related brain disorders involving the pathological dysregulation of dopamine.

The growth hormone secretagogue receptor-1a (GHSR_1a) is the cognate G protein–coupled receptor (GPCR) for the peptide hormone ghrelin. GHSR_1a is a promising therapeutic target for a wide range of metabolic, age-related, and central nervous system (CNS)–based conditions. In addition, growing evidence supports that GHSR_1a is a modulator of dopamine (DA) homeostasis and is neuroprotective within brain DA circuits. GHSR_1a signaling originates from pharmacologically separable G protein– and β-arrestin (βarr)–dependent pathways, and consequently, GHSR_1a-mediated physiological responses depend upon their distinctive signaling contributions. Thus, when treating disorders of disrupted DA homeostasis, a pharmacological strategy that modulates biased GHSR_1a signaling may uncouple desired therapeutic outcomes from unwanted side effects. Here, we report the discovery of a small molecule GHSR_1a agonist, N8279 (NCATS-SM8864), functionally selective for G protein signaling. Comprehensive pharmacological characterization reveals that N8279 elicits potent Gα_q activity at the apo- and ghrelin-bound GHSR_1a. Further biochemical analysis and molecular modeling demonstrate that N8279 signaling requires the extracellular domain of GHSR_1a, especially extracellular loop 2. Collectively, these findings suggest that N8279 possesses an extended binding mode into the extracellular vestibule of the GHSR_1a that preferentially favors Gα_q signaling over alternative G proteins and βarr2-dependent cellular responses. Critically, N8279 is brain-penetrant in mice, exhibits CNS stability, and attenuates dysfunctional DA-mediated behaviors in both genetic and pharmacological mouse models of hyperdopaminergia. Our findings provide insight into the mechanisms governing GPCR functional selectivity and emphasize how biased ligand drug development can produce novel GHSR_1a pharmacotherapeutics to treat pathological disruptions of brain DA homeostasis.

D-arginine Enhances the Effect of Alpha-Amylase on Disassembling Actinomyces viscosus Biofilm

Peri-implantitis is the leading cause of dental implant failure, initially raised by biofilm accumulation on the implant surface. During the development of biofilm, Actinomyces viscosus (A. viscosus) plays a pivotal role in initial attachment as well as the bacterial coaggregation of multispecies pathogens. Hence, eliminating the A. viscosus-associated biofilm is fundamental for the regeneration of the lost bone around implants. Whereas clinical evidence indicated that antimicrobials and debridement did not show significant effects on the decontamination of biofilm on the implant surface. In this study, alpha-amylase was investigated for its effects on disassembling A. viscosus biofilm. Then, in order to substantially disperse biofilm under biosafety concentration, D-arginine was employed to appraise its enhancing effects on alpha-amylase. In addition, molecular dynamics simulations and molecular docking were conducted to elucidate the mechanism of D-arginine enhancing alpha-amylase. 0.1–0.5% alpha-amylase showed significant effects on disassembling A. viscosus biofilm, with definite cytotoxicity toward MC3T3-E1 cells meanwhile. Intriguingly, 8 mM D-arginine drastically enhanced the eradication of A. viscosus biofilm biomass by 0.01% alpha-amylase with biosafety in 30 min. The exopolysaccharides of biofilm were also thoroughly hydrolyzed by 0.01% alpha-amylase with 8 mM D-arginine. The biofilm thickness and integrity were disrupted, and the exopolysaccharides among the extracellular matrix were elusive. Molecular dynamics simulations showed that with the hydrogen bonding of D-arginine to the catalytic triad and calcium-binding regions of alpha-amylase, the atom fluctuation of the structure was attenuated. The distances between catalytic triad were shortened, and the calcium-binding regions became more stable. Molecular docking scores revealed that D-arginine facilitated the maltotetraose binding process of alpha-amylase. In conclusion, these results demonstrate that D-arginine enhances the disassembly effects of alpha-amylase on A. viscosus biofilm through potentiating the catalytic triad and stabilizing the calcium-binding regions, thus providing a novel strategy for the decontamination of biofilm contaminated implant surface.

In Vitro and In Silico Analysis of the Residence Time of Serotonin 5-HT7 Receptor Ligands with Arylpiperazine Structure: A Structure-Kinetics Relationship Study

During the last decade, the kinetics of drug-target interaction has received increasing attention as an important pharmacological parameter in the drug development process. Several studies have suggested that the lipophilicity of a molecule can play an important role. To date, this aspect has been studied for several G protein-coupled receptors (GPCRs) ligands but not for the 5-HT₇ receptor (5-HT₇R), a GPCR proposed as a valid therapeutic target in neurodevelopmental and neuropsychiatric disorders associated with abnormal neuronal connectivity. In this study, we report on structure-kinetics relationships of a set of arylpiperazine-based 5-HT₇R ligands. We found that it is not the overall lipophilicity of the molecule that influences drug-target interaction kinetics but rather the position of polar groups within the molecule. Next, we performed a combination of molecular docking studies and molecular dynamics simulations to gain insights into structure-kinetics relationships. These studies did not suggest specific contact patterns between the ligands and the receptor-binding site as determinants for compounds kinetics. Finally, we compared the abilities of two 5-HT₇R agonists with similar receptor-binding affinities and different residence times to stimulate the 5-HT₇R-mediated neurite outgrowth in mouse neuronal primary cultures and found that the compounds induced the effect with different timing. This study provides the first insights into the binding kinetics of arylpiperazine-based 5-HT₇R ligands that can be helpful to design new 5-HT₇R ligands with fine-tuning of the kinetic profile.

Design and discovery of a high affinity, selective and β-arrestin biased 5-HT7 Receptor Agonist

Compound 1c, 5-chloro-2-(2-(3,4-dihydroisoquinolin-2(1H)-yl)ethyl)-2,3-dihydro-1H-inden-1-one was previously reported from our laboratory showing high affinity binding to the 5-HT₇ receptor (Ki = 0.5 nM). However, compound 1c racemizes readily upon enantiomeric separation. To prevent racemization, we have redesigned and synthesized methyl and carboxyethyl analogs, compounds 2 and 3 respectively, whose binding affinities were similar to those of compound 1c. Compounds 2 and 3 cannot undergo racemization since tautomerism was no longer possible and thus, compound 2 was selected for enantiomeric separation and further evaluation. Upon enantiomeric separation, the levorotatory enantiomer, (-)2 or 2a demonstrated a higher affinity (Ki = 1.2 nM) than the (+)2 or 2b enantiomer (Ki = 93 nM) and a β-arrestin biased functional selectivity for the 5-HT₇ receptor. Although 2a showed about 8 times less activity than 5-HT in the Gs pathway, it showed over 31 times higher activity than 5-HT in the β-arrestin pathway. This constitutes a significant β-arrestin pathway preference and shows 2a to be more potent and more efficacious than the recently published β-arrestin biased 3-(4-chlorophenyl)-1,4,5,6,7,8-hexahydropyrazolo[3,4-d]azepine, the N-debenzylated analog of JNJ18038683 (Compound 7).

Dopamine D2L receptor density influences the recruitment of β-arrestin2 and Gi1 induced by antiparkinsonian drugs

INTRODUCTION

Brain imaging studies have highlighted that the density of dopamine D₂ receptors markedly fluctuates across the stages of Parkinson's disease and in response to pharmacological treatment. Moreover, receptor density constitutes a molecular determinant for the signaling profile of D₂ receptor ligands. We therefore hypothesized that variations in receptor expression could influence D₂ receptor response to antiparkinsonian drugs, most notably with respect to the recruitment bias between G_i1 and β-arrestin2.

METHODS

The recruitment bias of dopamine, pramipexole, ropinirole, and rotigotine was examined using a nanoluciferase-based biosensor for probing the interactions of the D_2L receptor with either G_i1 or β-arrestin2. The characterization of the functional selectivity of these D₂ receptor agonists was performed at two distinct D_2L receptor densities by taking advantage of a cell model carrying an inducible system that enables the overexpression of the D_2L receptor when exposed to doxycycline.

RESULTS

A high receptor density oriented the balanced signaling profile of dopamine towards a preferential recruitment of G_i1. It also moderated the marked G_i1 and β-arrestin2 biases of pramipexole and rotigotine, respectively. At variance, the G_i1 bias of ropinirole appeared as not being influenced by D_2L receptor density.

CONCLUSIONS

Taken together, these observations highlight receptor density as a key driver of the signaling transducer recruitment triggered by antiparkinsonian agents. Moreover, given the putative beneficial properties of β-arrestin2 in promoting locomotion, this study provides molecular insights that position the arrestin-biased ligand rotigotine as a putatively more beneficial D₂ receptor agonist for the treatment of early and late Parkinson's disease.

Update on GPCR-based targets for the development of novel antidepressants

Traditional antidepressants largely interfere with monoaminergic transport or degradation systems, taking several weeks to have their therapeutic actions. Moreover, a large proportion of depressed patients are resistant to these therapies. Several atypical antidepressants have been developed which interact with G protein coupled receptors (GPCRs) instead, as direct targeting of receptors may achieve more efficacious and faster antidepressant actions. The focus of this review is to provide an update on how distinct GPCRs mediate antidepressant actions and discuss recent insights into how GPCRs regulate the pathophysiology of Major Depressive Disorder (MDD). We also discuss the therapeutic potential of novel GPCR targets, which are appealing due to their ligand selectivity, expression pattern, or pharmacological profiles. Finally, we highlight recent advances in understanding GPCR pharmacology and structure, and how they may provide new avenues for drug development.

Dezocine is a Biased Ligand without Significant Beta-Arrestin Activation of the mu Opioid Receptor

Dezocine is an opioid that was used in clinical practice for acute pain management in the US (1986 to 2011) and is currently in use in China. It is not listed as a controlled substance in the US due to no reported cases of addiction. Dezocine is a partial agonist at the mu opioid receptor (MOR); however, it is unclear whether dezocine can activate both the G protein pathway and the beta-arrestin pathway. In this study we hypothesized that dezocine does not activate the beta-arrestin pathway, which could be the potential molecular mechanism by which dezocine is not addictive or at least less addictive than other classic opioids. Both morphine, a MOR full agonist and buprenorphine, a partial MOR agonist similar to dezocine, were used for comparison purposes. The major side effects of dezocine in clinical usage are its gastrointestinal side effects and first pass effects; therefore, we explored the possibility of administering dezocine intranasally in rodents to demonstrate the feasibility of intranasal administration for new clinical usage purposes. With proper formulation it is possible to administer dezocine intranasally to achieve a high concentration in the brain in the rodent model. The results indicate that dezocine does not activate the beta-arrestin pathway in MOR. Intranasal delivery of dezocine achieves a much higher medication concentration in the blood and brain as compared to intraperitoneal injection. It also persists a longer time before it falls below detection in the blood. This study provides a possible explanation of why dezocine is not addictive or at least less addictive than other commonly used opioids. This study also demonstrates that intranasal administration offers an alternative strategy for its potential clinical applications.

Allosteric Effect of Nanobody Binding on Ligand-Specific Active States of the β2 Adrenergic Receptor

Nanobody binding stabilizes G-protein-coupled receptors (GPCR) in a fully active state and modulates their affinity for bound ligands. However, the atomic-level basis for this allosteric regulation remains elusive. Here, we investigate the conformational changes induced by the binding of a nanobody (Nb80) on the active-like β2 adrenergic receptor (β2AR) via enhanced sampling molecular dynamics simulations. Dimensionality reduction analysis shows that Nb80 stabilizes structural features of the β2AR with an ∼14 Å outward movement of transmembrane helix 6 and a close proximity of transmembrane (TM) helices 5 and 7, and favors the fully active-like conformation of the receptor, independent of ligand binding, in contrast to the conditions under which no intracellular binding partner is bound, in which case the receptor is only stabilized in an intermediate-active state. This activation is supported by the residues located at hotspots located on TMs 5, 6, and 7, as shown by supervised machine learning methods. Besides, ligand-specific subtle differences in the conformations assumed by intracellular loop 2 and extracellular loop 2 are captured from the trajectories of various ligand-bound receptors in the presence of Nb80. Dynamic network analysis further reveals that Nb80 binding triggers tighter and stronger local communication networks between the Nb80 and the ligand-binding sites, primarily involving residues around ICL2 and the intracellular end of TM3, TM5, TM6, as well as ECL2, ECL3, and the extracellular ends of TM6 and TM7. In particular, we identify unique allosteric signal transmission mechanisms between the Nb80-binding site and the extracellular domains in conformations modulated by a full agonist, BI167107, and a G-protein-biased partial agonist, salmeterol, involving mainly TM1 and TM2, and TM5, respectively. Altogether, our results provide insights into the effect of intracellular binding partners on the GPCR activation mechanism, which should be taken into account in structure-based drug discovery.

Leveraging nonstructural data to predict structures and affinities of protein-ligand complexes

Structure-based drug design depends on the ability to predict both the three-dimensional structures of candidate molecules bound to their targets and the associated binding affinities. We demonstrate that one can substantially improve the accuracy of these predictions using easily obtained data about completely different molecules that bind to the same target without requiring any target-bound structures of these molecules. The approach we developed to integrate physical and data-driven modeling may find a variety of applications in the rapidly growing field of artificial intelligence for drug discovery.

Over the past five decades, tremendous effort has been devoted to computational methods for predicting properties of ligands—i.e., molecules that bind macromolecular targets. Such methods, which are critical to rational drug design, fall into two categories: physics-based methods, which directly model ligand interactions with the target given the target’s three-dimensional (3D) structure, and ligand-based methods, which predict ligand properties given experimental measurements for similar ligands. Here, we present a rigorous statistical framework to combine these two sources of information. We develop a method to predict a ligand’s pose—the 3D structure of the ligand bound to its target—that leverages a widely available source of information: a list of other ligands that are known to bind the same target but for which no 3D structure is available. This combination of physics-based and ligand-based modeling improves pose prediction accuracy across all major families of drug targets. Using the same framework, we develop a method for virtual screening of drug candidates, which outperforms standard physics-based and ligand-based virtual screening methods. Our results suggest broad opportunities to improve prediction of various ligand properties by combining diverse sources of information through customized machine-learning approaches.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

Structure-based design of a novel third-generation antipsychotic drug lead with potential antidepressant properties

Partial agonist activity at the dopamine D₂ receptor (DRD2) is a key feature of third-generation antipsychotics (TGAs). However, TGAs also act as antagonists or weak partial agonists to the serotonin (5-hydroxytryptamine; 5-HT) 2A receptor (5-HT_2AR). Here we present the crystal structures of aripiprazole- and cariprazine-bound human 5-HT_2AR. Both TGAs adopt an unexpected 'upside-down' pose in the 5-HT_2AR binding pocket, with secondary pharmacophores inserted in a similar way to a 'bolt'. This insight into the binding modes of TGAs offered a structural mechanism underlying their varied partial efficacies at 5-HT_2AR and DRD2. These structures enabled the design of a partial agonist at DRD2/3 and 5-HT_1AR with negligible 5-HT_2AR binding that displayed potent antipsychotic-like activity without motor side effects in mice. This TGA lead also had antidepressant-like effects and improved cognitive performance in mouse models via 5-HT_1AR. This work indicates that 5-HT_2AR affinity is a dispensable contributor to the therapeutic actions of TGAs.

Probe Confined Dynamic Mapping for G Protein-Coupled Receptor Allosteric Site Prediction

Targeting G protein-coupled receptors (GPCRs) through allosteric sites offers advantages over orthosteric sites in identifying drugs with increased selectivity and potentially reduced side effects. In this study, we developed a probe confined dynamic mapping protocol that allows the prediction of allosteric sites at both the GPCR extracellular and intracellular sides, as well as at the receptor-lipid interface. The applied harmonic wall potential enhanced sampling of probe molecules in a selected area of a GPCR while preventing membrane distortion in molecular dynamics simulations. The specific probes derived from GPCR allosteric ligand structures performed better in allosteric site mapping compared to commonly used cosolvents. The M₂ muscarinic, β₂ adrenergic, and P₂Y₁ purinergic receptors were selected for the protocol's retrospective validation. The protocol was next validated prospectively to locate the binding site of [5-fluoro-4-(hydroxymethyl)-2-methoxyphenyl]-(4-fluoro-1H-indol-1-yl)methanone at the D₂ dopamine receptor, and subsequent mutagenesis confirmed the prediction. The protocol provides fast and efficient prediction of key amino acid residues surrounding allosteric sites in membrane proteins and facilitates the structure-based design of allosteric modulators.

Molecular Mechanisms of Diverse Activation Stimulated by Different Biased Agonists for the β2-Adrenergic Receptor

β2AR is an important drug target protein involving many diseases. Biased drugs induce specific signaling and provide additional clinical utility to optimize β2AR-based therapies. However, the biased signaling mechanism has not been elucidated. Motivated by the issue, we chose four agonists with divergent bias (balanced agonist, G-protein-biased agonist, and β-arrestin-biased agonists) and utilized Gaussian accelerated molecular dynamics simulation coupled with a dynamic network to probe the molecular mechanisms of distinct biased activation induced by the structural differences between the four agonists. Our simulations reveal that the G-protein-biased agonist induces an open conformation with the outward shifts of TM6 and TM7 for the intracellular domain, which will be beneficial to couple G protein. In contrast, the β-arrestin-biased agonists regulate an occluded conformation with a slightly outward movement of TM6 and an inward shift of TM7, which should favor β-arrestin signaling. The balanced agonist does not induce an observable outward shift for TM6 but, along with a slight tilt for TM7, leads to an inactive-like conformation. In addition, our results reveal the first time that ICL3 presents specific conformations with different agonists. The G-protein-biased agonist drives ICL3 to open so that the G protein-binding pocket can be available, while the β-arrestin-biased agonists induce ICL3 to form a closed conformation with a stable local α-helix. MM/PBSA analysis further reveals that the hydroxyl groups in the resorcinol of the G-protein-biased agonist form strong interactions with Y5.38 and S5.42, thus preventing tilting of the TM5 extracellular end. The catechol of the balanced agonist and the β-arrestin-biased ones induces the rearrangement of two hydrophobic residues F6.52 and W6.48. However, different from the balanced agonist, the ethyl substituent of β-arrestin-biased agonists forms additional hydrophobic interactions with W6.48 and F6.51 after the rearrangement, which should contribute to the β-arrestin bias. The shortest pathway analysis further reveals that the three residues Y7.43, N7.45, and N7.49 are crucial for allosterically regulating G-protein-biased signaling, while the two residues W6.48 and F6.44 make an important contribution to regulate β-arrestin-biased signaling. For the balanced agonist NE, the allosteric regulation pathway simultaneously involves the residue associated with G-protein-biased signaling like S5.46 and the residues related to β-arrestin-biased signaling like W6.48 and F6.44, thus producing unbiased signaling. The observations could advance our understanding of the biased activation mechanism on class A GPCRs and provide a useful guideline for the design of biased drugs.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Investigation of 1, 3, 4 Oxadiazole Derivative in PTZ-Induced Neurodegeneration: A Simulation and Molecular Approach

Objective

The study investigated the effect 5-[(naphthalen-2-yloxy) methyl]-1,3,4-oxadiaszole2-thiol (B3) in animal model of acute epileptic shock.

Methods

The pharmacokinetics profile of B3 was checked through SwissADME software. The binding affinities of B3, diazepam, and flumazenil (FLZ) were obtained through Auto Dock and PyRx. Post docking analysis and interpretation of hydrogen bonds were performed through Discovery Studio Visualizer 2016. Molecular dynamics simulations of three complexes were carried out through Desmond software package. B3 was then proceeded in PTZ-induced acute seizures models. Flumazenil was used in animal studies for elucidation of possible mechanism of B3. After behavioral studies, the animals were sacrificed, and the brain samples were isolated and stored in 4% formalin for molecular investigations including H and E staining, IHC staining and Elisa etc.

Results

The results demonstrate that B3 at 20 and 40 mg/kg prolonged the onset time of generalized seizures. B3 considerably increased the expression of protective glutathione S-transferase and glutathione reductase and reduced lipid peroxidation and inducible nitric oxide synthase (P < 0.001) in the cortex. B3 significantly suppressed (P < 0.01) the over expression of the inflammatory mediator tumor necrosis factor–α, whose up-regulation is reported in acute epileptic shocks.

Conclusion

Hence, it is concluded from the aforementioned results that B3 provides neuroprotective effects PTZ-induced acute epileptic model. FLZ pretreatment resulted in inhibition of the anticonvulsant effect of B3. B3 possesses anticonvulsant effect which may be mediated through GABA_A mediated antiepileptic pathway.

Discovery of G Protein-Biased Antagonists against 5-HT7R

5-HT₇R belongs to a family of G protein-coupled receptors and is associated with a variety of physiological processes in the central nervous system via the activation of the neurotransmitter serotonin (5-HT). To develop selective and biased 5-HT₇R ligands, we designed and synthesized a series of pyrazolyl-diazepanes 2 and pyrazolyl-piperazines 3, which were evaluated for binding affinities to 5-HTR subtypes and functional selectivity for G protein and β-arrestin signaling pathways of 5-HT₇R. Among them, 1-(3-(3-chlorophenyl)-1H-pyrazol-4-yl)-1,4-diazepane 2c showed the best binding affinity for 5-HT₇R and selectivity over other 5-HTR subtypes. It was also revealed as a G protein-biased antagonist. The self-grooming behavior test was performed with 2c in vivo with Shank3^-/- transgenic (TG) mice, wherein 2c significantly reduced self-grooming duration time to the level of wild-type mice. The results suggest that 5-HT₇R could be a potential therapeutic target for treating autism spectrum disorder stereotypy.

MEMES: Machine learning framework for Enhanced MolEcular Screening

In drug discovery applications, high throughput virtual screening exercises are routinely performed to determine an initial set of candidate molecules referred to as "hits". In such an experiment, each molecule from a large small-molecule drug library is evaluated in terms of physical properties such as the docking score against a target receptor. In real-life drug discovery experiments, drug libraries are extremely large but still there is only a minor representation of the essentially infinite chemical space, and evaluation of physical properties for each molecule in the library is not computationally feasible. In the current study, a novel Machine learning framework for Enhanced MolEcular Screening (MEMES) based on Bayesian optimization is proposed for efficient sampling of the chemical space. The proposed framework is demonstrated to identify 90% of the top-1000 molecules from a molecular library of size about 100 million, while calculating the docking score only for about 6% of the complete library. We believe that such a framework would tremendously help to reduce the computational effort in not only drug-discovery but also areas that require such high-throughput experiments.

Mechanistic insights into dopaminergic and serotonergic neurotransmission - concerted interactions with helices 5 and 6 drive the functional outcome

Brain functions rely on neurotransmitters that mediate communication between billions of neurons. Disruption of this communication can result in a plethora of psychiatric and neurological disorders. In this work, we combine molecular dynamics simulations, live-cell biosensor and electrophysiological assays to investigate the action of the neurotransmitter dopamine at the dopaminergic D2 receptor (D2R). The study of dopamine and closely related chemical probes reveals how neurotransmitter binding translates into the activation of distinct subsets of D2R effectors (i.e.: Gi2, GoB, Gz and β-arrestin 2). Ligand interactions with key residues in TM5 (S5.42) and TM6 (H6.55) in the D2R binding pocket yield a dopamine-like coupling signature, whereas exclusive TM5 interaction is typically linked to preferential G protein coupling (in particular GoB) over β-arrestin. Further experiments for serotonin receptors indicate that the reported molecular mechanism is shared by other monoaminergic neurotransmitter receptors. Ultimately, our study highlights how sequence variation in position 6.55 is used by nature to fine-tune β-arrestin recruitment and in turn receptor signaling and internalization of neurotransmitter receptors.

Delineating the Ligand-Receptor Interactions That Lead to Biased Signaling at the μ-Opioid Receptor

Biased agonists, which selectively stimulate certain signaling pathways controlled by a G protein-coupled receptor (GPCR), hold great promise as drugs that maximize efficacy while minimizing dangerous side effects. Biased agonists of the μ-opioid receptor (μOR) are of particular interest as a means to achieve analgesia through G protein signaling without dose-limiting side effects such as respiratory depression and constipation. Rational structure-based design of biased agonists remains highly challenging, however, because the ligand-mediated interactions that are key to activation of each signaling pathway remain unclear. We identify several compounds for which the R- and S-enantiomers have distinct bias profiles at the μOR. These compounds serve as excellent comparative tools to study bias because the identical physicochemical properties of enantiomer pairs ensure that differences in bias profiles are due to differences in interactions with the μOR binding pocket. Atomic-level simulations of compounds at μOR indicate that R- and S-enantiomers adopt different poses that form distinct interactions with the binding pocket. A handful of specific interactions with highly conserved binding pocket residues appear to be responsible for substantial differences in arrestin recruitment between enantiomers. Our results offer guidance for rational design of biased agonists at μOR and possibly at related GPCRs.

Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors

BACKGROUND

Molecular docking is in regular practice to assess ligand affinity on a target protein crystal structure. In the absence of protein crystal structure, the homology modeling or comparative modeling is the best alternative to elucidate the relationship details between a ligand and protein at the molecular level. The development of accurate homology modeling (HM) and its integration with molecular docking (MD) is essential for successful, rational drug discovery.

OBJECTIVE

The G-protein coupled receptors (GPCRs) are attractive therapeutic targets due to their immense role in human pharmacology. The GPCRs are membrane-bound proteins with the complex constitution, and the understanding of their activation and inactivation mechanisms is quite challenging. Over the past decade, there has been a rapid expansion in the number of solved G-protein-coupled receptor (GPCR) crystal structures; however, the majority of the GPCR structures remain unsolved. In this context, HM guided MD has been widely used for structure-based drug design (SBDD) of GPCRs.

METHODS

The focus of this review is on the recent (i) developments on HM supported GPCR drug discovery in the absence of GPCR crystal structures and (ii) application of HM in understanding the ligand interactions at the binding site, virtual screening, determining receptor subtype selectivity and receptor behaviour in comparison with GPCR crystal structures.

RESULTS

The HM in GPCRs has been extremely challenging due to the scarcity in template structures. In such a scenario, it is difficult to get accurate HM that can facilitate understanding of the ligand-receptor interactions. This problem has been alleviated to some extent by developing refined HM based on incorporating active /inactive ligand information and inducing protein flexibility. In some cases, HM proteins were found to outscore crystal structures.

CONCLUSION

The developments in HM have been highly operative to gain insights about the ligand interaction at the binding site and receptor functioning at the molecular level. Thus, HM guided molecular docking may be useful for rational drug discovery for the GPCRs mediated diseases.