Docking and Virtual Screening Strategies for GPCR Drug Discovery

Based on Virtual Screening and Simulation Exploring the Mechanism of Plant-Derived Compounds with PINK1 to Postherpetic Neuralgia

Accumulating evidence strongly supports that PINK1 mutation can mediate mitochondrial autophagy dysfunction in dopaminergic neurons. This study was conducted to determine the role of PINK1 in the pathogenesis of postherpetic neuralgia (PHN) and find new targets for its treatment. A rigorous literature review was conducted to identify 2801 compounds from more than 200 plants in Asia. Virtual screening was used to shortlist the compounds into 20 groups based on their binding energies. MM/PBSA was used to further screen the compound dataset, and vitexin, luteoloside, and 2'-deoxyadenosine-5'-monophosphate were found to have a score of - 59.439, - 52.421, and - 47.544 kcal/mol, respectively. Pain behavioral quantification, enzyme-linked immunosorbent assay, quantitative polymerase chain reaction, western blotting, and transmission electron microscopy were used to confirm the effective mechanism. Vitexin had the most significant therapeutic effect on rats with PHN followed by luteoloside; 2'-deoxyadenosine-5'-monophosphate had no significant effect. Our findings suggested that vitexin could alleviate PHN by regulating mitochondrial autophagy through PINK1.

Unequal crossing over between CYP11B2 and CYP11B1 causes 11 β -hydroxylase deficiency in a consanguineous family

Cytochrome P450 (CYP) family CYP11B2/CYP11B1 chimeric genes have been shown to arise from unequal crossing over of the genes encoding aldosterone synthase (CYP11B2) and 11β-hydroxylase (CYP11B1) during meiosis. The activity deficiency or impaired activity of aldosterone synthase and 11β-hydroxylase resulting from these chimeric genes are important reasons for 11β-hydroxylase deficiency (11β-OHD). Here，two patients with pseudoprecocious puberty and hypokalemia hypertension and three carriers in a consanguineous marriage family were studied. A single CYP11B2/CYP11B1 chimera consisting of the promoter and exons 1 through 5 of CYP11B2, exons 8 and 9 of CYP11B1, and a breakpoint consisting of part of exon 6 of CYP11B2 and part of exon 6, intron 6, and exon 7 of CYP11B1 were detected in the patients and carriers. At the breakpoint of the chimera, a c 0.1086 G > C ( p.Leu.362 =) synonymous mutation in exon 6 of CYP11B2, a c 0.1157 C＞G(p. A386V) missense mutation in exon 7 of CYP11B1, and an intronic mutation in intron 6 were detected. The allele model of the CYP11B2/CYP11B1 chimera demonstrated homozygosity and heterozygosity in the patients and the carriers, respectively. Molecular docking and enzymatic activity analyses indicated that the CYP11B2/CYP11B1 chimeric protein interacted with the catalytic substrate of aldosterone synthase and had similar enzymatic activity to aldosterone synthase. Our study indicated that deletion of CYP11B1 and CYP11B2 abolished the enzymatic activity of 11 β-hydroxylase and aldosterone synthase; however, the compensation of the enzymatic activity of aldosterone synthase by the CYP11B2/CYP11B1 chimeric protein maintained normal aldosterone levels in vitro. All of the above findings explained the 11β-OHD phenotypes of the proband and patients in the family.

A Novel 5-HT1B Receptor Agonist of Herbal Compounds and One of the Therapeutic Uses for Alzheimer's Disease

The serotonin receptor 5-HT_1B is widely expressed in the central nervous system and has been considered a drug target in a variety of cognitive and psychiatric disorders. The anti-inflammatory effects of 5-HT_1B agonists may present a promising approach for Alzheimer's disease (AD) treatment. Herbal antidepressants used in the treatment of AD have shown functional overlap between the active compounds and 5-HT_1B receptor stimulation. Therefore, compounds in these medicinal plants that target and stimulate 5-HT_1B deserve careful study. Molecular docking, drug affinity responsive target stability, cellular thermal shift assay, fluorescence resonance energy transfer (FRET), and extracellular regulated protein kinases (ERK) 1/2 phosphorylation tests were used to identify emodin-8-O-β-d-glucopyranoside (EG), a compound from Chinese medicinal plants with cognitive deficit attenuating and antidepressant effects, as an agonist of 5-HT_1B. EG selectively targeted 5-HT_1B and activated the 5-HT_1B-induced signaling pathway. The activated 5-HT_1B pathway suppressed tumor necrosis factor (TNF)-α levels, thereby protecting neural cells against beta-amyloid (Aβ)-induced death. Moreover, the agonist activity of EG towards 5-HT_1B receptor, in FRET and ERK1/2 phosphorylation, was antagonized by SB 224289, a 5-HT_1B antagonist. In addition, EG relieved AD symptoms in transgenic worm models. These results suggested that 5-HT_1B receptor activation by EG positively affected Aβ-related inflammatory process regulation and neural death resistance, which were reversed by antagonist SB 224289. The active compounds such as EG might act as potential therapeutic agents through targeting and stimulating 5-HT_1B receptor for AD and other serotonin-related disorders. This study describes methods for identification of 5-HT_1B agonists from herbal compounds and for evaluating agonists with biological functions, providing preliminary information on medicinal herbal pharmacology.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2

The new coronavirus (SARS-CoV-2) halts the world economy and caused unbearable medical emergency due to high transmission rate and also no effective vaccine and drugs has been developed which brought the world pandemic situations. The main protease (Mpro) of SARS-CoV-2 may act as an effective target for drug development due to the conservation level. Herein, we have employed a rigorous literature review pipeline to enlist 3063 compounds from more than 200 plants from the Asian region. Therefore, the virtual screening procedure helps us to shortlist the total compounds into 19 based on their better binding energy. Moreover, the Prime MM-GBSA procedure screened the compound dataset further where curcumin, gartanin and robinetin had a score of (-59.439, -52.421 and - 47.544) kcal/mol, respectively. The top three ligands based on binding energy and MM-GBSA scores have most of the binding in the catalytic groove Cys145, His41, Met165, required for the target protein inhibition. The molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, solvent accessible surface area, radius of gyration and hydrogen bond analysis from simulation trajectories. The post-molecular dynamics analysis also confirms the interactions of the curcumin, gartanin and robinetin in the similar binding pockets. Our computational drug designing approach may contribute to the development of drugs against SARS-CoV-2.

Targeting the PAC1 Receptor for Neurological and Metabolic Disorders

The pituitary adenylate cyclase-activating polypeptide (PACAP)-selective PAC1 receptor (PAC1R, ADCYAP1R1) is a member of the vasoactive intestinal peptide (VIP)/secretin/glucagon family of G protein-coupled receptors (GPCRs). PAC1R has been shown to play crucial roles in the central and peripheral nervous systems. The activation of PAC1R initiates diverse downstream signal transduction pathways, including adenylyl cyclase, phospholipase C, MEK/ERK, and Akt pathways that regulate a number of physiological systems to maintain functional homeostasis. Accordingly, at times of tissue injury or insult, PACAP/PAC1R activation of these pathways can be trophic to blunt or delay apoptotic events and enhance cell survival. Enhancing PAC1R signaling under these conditions has the potential to mitigate cellular damages associated with cerebrovascular trauma (including stroke), neurodegeneration (such as Parkinson's and Alzheimer's disease), or peripheral organ insults. Conversely, maladaptive PACAP/PAC1R signaling has been implicated in a number of disorders, including stressrelated psychopathologies (i.e., depression, posttraumatic stress disorder, and related abnormalities), chronic pain and migraine, and metabolic diseases; abrogating PAC1R signaling under these pathological conditions represent opportunities for therapeutic intervention. Given the diverse PAC1R-mediated biological activities, the receptor has emerged as a relevant pharmaceutical target. In this review, we first describe the current knowledge regarding the molecular structure, dynamics, and function of PAC1R. Then, we discuss the roles of PACAP and PAC1R in the activation of a variety of signaling cascades related to the physiology and diseases of the nervous system. Lastly, we examine current drug design and development of peptides and small molecules targeting PAC1R based on a number of structure- activity relationship studies and key pharmacophore elements. At present, the rational design of PAC1R-selective peptide or small-molecule therapeutics is largely hindered by the lack of structural information regarding PAC1R activation mechanisms, the PACAP-PAC1R interface, and the core segments involved in receptor activation. Understanding the molecular basis governing the PACAP interactions with its different cognate receptors will undoubtedly provide a basis for the development and/or refinement of receptor-selective therapeutics.

A Metadynamics-Based Protocol for the Determination of GPCR-Ligand Binding Modes

G protein-coupled receptors (GPCRs) are a main drug target and therefore a hot topic in pharmaceutical research. One important prerequisite to understand how a certain ligand affects a GPCR is precise knowledge about its binding mode and the specific underlying interactions. If no crystal structure of the respective complex is available, computational methods can be used to deduce the binding site. One of them are metadynamics simulations which have the advantage of an enhanced sampling compared to conventional molecular dynamics simulations. However, the enhanced sampling of higher-energy states hampers identification of the preferred binding mode. Here, we present a novel protocol based on clustering of multiple walker metadynamics simulations which allows identifying the preferential binding mode from such conformational ensembles. We tested this strategy for three different model systems namely the histamine H₁ receptor in combination with its physiological ligand histamine, as well as the β2 adrenoceptor with its agonist adrenaline and its antagonist alprenolol. For all three systems, the proposed protocol was able to reproduce the correct binding mode known from the literature suggesting that the approach can more generally be applied to the prediction of GPCR ligand binding in future.

ImmtorLig_DB: repertoire of virtually screened small molecules against immune receptors to bolster host immunity

Host directed therapies to boost immunity against infection are gaining considerable impetus following the observation that use of antibiotics has become a continuous source for the emergence of drug resistant strains of pathogens. Receptors expressed by the cells of immune system play a cardinal role in initiating sequence of events necessary to ameliorate many morbid conditions. Although, ligands for the immune receptors are available; but their use is limited due to complex structure, synthesis and cost-effectiveness. Virtual screening (VS) is an integral part of chemoinformatics and computer-aided drug design (CADD) and aims to streamline the process of drug discovery. ImmtorLig_DB is a repertoire of 5000 novel small molecules, screened from ZINC database and ranked using structure based virtual screening (SBVS) against 25 immune receptors which play a pivotal role in defending and initiating the activation of immune system. Consequently, in the current study, small molecules were screened by docking on the essential domains present on the receptors expressed by cells of immune system. The screened molecules exhibited efficacious binding to immune receptors, and indicated a possibility of discovering novel small molecules. Other features of ImmtorLig_DB include information about availability, clustering analysis, and estimation of absorption, distribution, metabolism, and excretion (ADME) properties of the screened small molecules. Structural comparisons indicate that predicted small molecules may be considered novel. Further, this repertoire is available via a searchable graphical user interface (GUI) through http://bioinfo.imtech.res.in/bvs/immtor/ .

Methods for Virtual Screening of GPCR Targets: Approaches and Challenges

Virtual screening (VS) has become an integral part of the drug discovery process and is a valuable tool for finding novel chemical starting points for GPCR targets. Ligand-based VS makes use of biochemical data for known, active compounds and has been applied successfully to many diverse GPCRs. Recent progress in GPCR X-ray crystallography has made it possible to incorporate detailed structural information into the VS process. This chapter outlines the latest VS techniques along with examples that highlight successful applications of these methods. Best practices for increasing the likelihood of VS success, as well as ongoing challenges, are also discussed.

Structure-Based Discovery of New Antagonist and Biased Agonist Chemotypes for the Kappa Opioid Receptor

The ongoing epidemics of opioid overdose raises an urgent need for effective antiaddiction therapies and addiction-free painkillers. The κ-opioid receptor (KOR) has emerged as a promising target for both indications, raising demand for new chemotypes of KOR antagonists as well as G-protein-biased agonists. We employed the crystal structure of the KOR-JDTic complex and ligand-optimized structural templates to perform virtual screening of available compound libraries for new KOR ligands. The prospective virtual screening campaign yielded a high 32% hit rate, identifying novel fragment-like and lead-like chemotypes of KOR ligands. A round of optimization resulted in 11 new submicromolar KOR binders (best K_i = 90 nM). Functional assessment confirmed at least two compounds as potent KOR antagonists, while compound 81 was identified as a potent G_i biased agonist for KOR with minimal β-arrestin recruitment. These results support virtual screening as an effective tool for discovery of new lead chemotypes with therapeutically relevant functional profiles.

Molecular Modelling Approaches for the Analysis of Histamine Receptors and Their Interaction with Ligands

Several experimental techniques to analyse histamine receptors are available, e.g. pharmacological characterisation of known or new compounds by different types of assays or mutagenesis studies. To obtain insights into the histamine receptors on a molecular and structural level, crystal structures have to be determined and molecular modelling studies have to be performed. It is widely accepted to generate homology models of the receptor of interest based on an appropriate crystal structure as a template and to refine the resulting models by molecular dynamic simulations. A lot of modelling techniques, e.g. docking, QSAR or interaction fingerprint methods, are used to predict binding modes of ligands and pharmacological data, e.g. affinity or even efficacy. However, within the last years, molecular dynamic simulations got more and more important: First of all, molecular dynamic simulations are very helpful to refine the binding mode of a ligand to a histamine receptor, obtained by docking studies. Furthermore, with increasing computational performance it got possible to simulate complete binding pathways of ions or ligands from the aqueous extracellular phase into the allosteric or orthosteric binding pocket of histamine receptors.

Interacting with GPCRs: Using Interaction Fingerprints for Virtual Screening

The expanding number of crystal structures of G protein-coupled receptors (GPCRs) has increased the knowledge on receptor function and their ability to recognize ligands. Although structure-based virtual screening has been quite successful on GPCRs, scores obtained by docking are typically not indicative for ligand affinity. Methods capturing interactions between protein and ligand in a more explicit manner, such as interaction fingerprints (IFPs), have been applied as an addition or alternative to docking. Originally IFPs captured the interactions of amino acid residues with ligands with specific definitions for the various interaction types. More complex IFPs now capture atom-atom interactions, such as in SYBYL, or fragment-fragment co-occurrences such as in SPLIF. Overall, most of the IFPs have been studied in comparison with docking in retrospective studies. For GPCRs it remains unclear which IFP should be used, if at all, and in what manner. Thus, the performance between five different IFPs was compared on five different representative GPCRs, including several extensions of the original implementations,. Results show that the more detailed IFPs, SYBYL and SPLIF, perform better than the other IFPs (Deng, Credo, and Elements). SPLIF was further tuned based on the number of poses, fingerprint similarity coefficient, and using an ensemble of structures. Enrichments were obtained that were significantly higher than initial enrichments and those obtained by 2D-similarity. With the increase in available crystal structures for GPCRs, and given that IFPs such as SPLIF enhance enrichment in virtual screens, it is anticipated that IFPs will be used in conjunction with docking, especially for GPCRs with a large binding pocket.

Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation

The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges associated with predicting binding free energies for related compounds. Here, we provide a systematic characterization of the performance of free-energy perturbation (FEP) calculations to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first we validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A_2AAR, β₁ adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with experimental binding affinity measurements revealed a highly predictive ranking correlation (average spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, we applied FEP+ in a prospective project, where we predicted the affinity of novel, potent adenosine A_2A receptor (A_2AR) antagonists. Four novel compounds were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compounds) was correctly predicted (within 1 kcal/mol), including one compound with approximately a tenfold increase in affinity compared to the starting compound. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent molecules in drug discovery lead optimization projects.

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

Five G protein-coupled receptors (GPCRs) have been identified to be activated by free fatty acids (FFA). Among them, FFA1 (GPR40) and FFA4 (GPR120) bind long-chain fatty acids, FFA2 (GPR43) and FFA3 (GPR41) bind short-chain fatty acids and GPR84 binds medium-chain fatty acids. Free fatty acid receptors have now emerged as potential targets for the treatment of diabetes, obesity and immune diseases. The recent progress in crystallography of GPCRs has now enabled the elucidation of the structure of FFA1 and provided reliable templates for homology modelling of other FFA receptors. Analysis of the crystal structure and improved homology models, along with mutagenesis data and structure activity, highlighted an unusual arginine charge-pairing interaction in FFA1-3 for receptor modulation, distinct structural features for ligand binding to FFA1 and FFA4 and an arginine of the second extracellular loop as a possible anchoring point for FFA at GPR84. Structural data will be helpful for searching novel small-molecule modulators at the FFA receptors.

The Fragment Molecular Orbital Method Reveals New Insight into the Chemical Nature of GPCR–Ligand Interactions

Our interpretation of ligand-protein interactions is often informed by high-resolution structures, which represent the cornerstone of structure-based drug design. However, visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum Mechanics approaches are often too computationally expensive, but one method, Fragment Molecular Orbital (FMO), offers an excellent compromise and has the potential to reveal key interactions that would otherwise be hard to detect. To illustrate this, we have applied the FMO method to 18 Class A GPCR-ligand crystal structures, representing different branches of the GPCR genome. Our work reveals key interactions that are often omitted from structure-based descriptions, including hydrophobic interactions, nonclassical hydrogen bonds, and the involvement of backbone atoms. This approach provides a more comprehensive picture of receptor-ligand interactions than is currently used and should prove useful for evaluation of the chemical nature of ligand binding and to support structure-based drug design.