Advances in Computational Techniques to Study GPCR–Ligand Recognition

Effects of pH on opioid receptor activation and implications for drug design

G-protein-coupled receptors are integral membrane proteins that transduce chemical signals from the extracellular matrix into the cell. Traditional drug design has considered ligand-receptor interactions only under normal conditions. However, studies on opioids indicate that such interactions are very different in diseased tissues. In such microenvironments, protons play an important role in structural and functional alterations of both ligands and receptors. The pertinent literature strongly suggests that future drug design should take these aspects into account in order to reduce adverse side effects while preserving desired effects of novel compounds.

AI-driven GPCR analysis, engineering, and targeting

This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.

GPCR-IPL score: multilevel featurization of GPCR-ligand interaction patterns and prediction of ligand functions from selectivity to biased activation

G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure-activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR-ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR-ligand complexes. As a result, we developed GPCR-ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out 'residue level' (for flexible transmembrane helices of GPCRs), (2) zoomed-in 'pocket level' (for sophisticated mode of action) and (3) 'atom level' (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and β-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.

What Makes GPCRs from Different Families Bind to the Same Ligand?

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.

Engineered Allosteric Regulation of Protein Function

Allosteric regulation of proteins has been utilized to study various aspects of cell signaling, from unicellular events to organism-wide phenotypes. However, traditional methods of allosteric regulation, such as constitutively active mutants and inhibitors, lack tight spatiotemporal control. This often leads to unintended signaling consequences that interfere with data interpretation. To overcome these obstacles, researchers employed protein engineering approaches that enable tight control of protein function through allosteric mechanisms. These methods provide high specificity as well as spatial and temporal precision in regulation of protein activity in vitro and in vivo. In this review, we focus on the recent advancements in engineered allosteric regulation and discuss the various bioengineered allosteric techniques available now, from chimeric GPCRs to chemogenetic and optogenetic switches. We highlight the benefits and pitfalls of each of these techniques as well as areas in which future improvements can be made. Additionally, we provide a brief discussion on implementation of engineered allosteric regulation approaches, demonstrating that these tools can shed light on elusive biological events and have the potential to be utilized in precision medicine.

In Silico Study Approach on a Series of 50 Polyphenolic Compounds in Plants; A Comparison on the Bioavailability and Bioactivity Data

Fifty (50) phytocompounds from several subclasses of polyphenols, chosen based on their abundance in the plant world, were analyzed through density functional methods, using computational tools to evaluate their oral availability and particular bioactivity on several cell modulators; key descriptors and molecular features related to the electron density and electrostatic potential for the lowest energy conformers of the investigated molecules were computed. An analysis of the bioactivity scores towards six cell modulators (GPCR ligand, ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor and enzyme inhibitor) was also achieved, in the context of investigating their potential side effects on the human digestive processes. Summarizing, computational results confirmed in vivo and in vitro data regarding the high bioavailability of soy isoflavones and better bioavailability of free aglycones in comparison with their esterified and glycosylated forms. However, by a computational approach analyzing Lipinski’s rule, apigenin and apigenin-7-O-rhamnoside, naringenin, hesperetin, genistein, daidzin, biochanin A and formonetin in the flavonoid series and all hydroxycinnamic acids and all hydroxybenzoic acids excepting ellagic acid were proved to have the best bioavailability data; rhamnoside derivatives, the predominant glycosides in green plants, which were reported to have the lowest bioavailability values by in vivo studies, were revealed to have the best bioavailability data among the studied flavonoids in the computational approach. Results of in silico screening on the phenolic derivatives series also revealed their real inhibitory potency on the six parameters studied, showing a remarkable similitude between the flavonoid series, while flavonoids were more powerful natural cell modulators than the phenyl carboxylic acids tested. Thus, it can be concluded that there is a need for supplementation with digestive enzymes, mainly in the case of individuals with low digestive efficiency, to obtain the best health benefits of polyphenols in humans.

Effect of Ions and Sequence Variants on the Antagonist Binding Properties of the Histamine H1 Receptor

The histamine H₁ receptor (H₁R) is a G protein-coupled receptor (GPCR) and represents a main target in the treatment of allergic reactions as well as inflammatory reactions and depressions. Although the overall effect of antagonists on H₁ function has been extensively investigated, rather little is known about the potential modulatory effect of ions or sequence variants on antagonist binding. We investigated the dynamics of a phosphate ion present in the crystal structure and of a sodium ion, for which we determined the position in the allosteric pocket by metadynamics simulations. Both types of ions exhibit significant dynamics within their binding site; however, some key contacts remain stable over the simulation time, which might be exploited to develop more potent drugs targeting these sites. The dynamics of the ions is almost unaffected by the presence or absence of doxepin, as also reflected in their small effect (less than 1 kcal·mol^-1) on doxepin binding affinity. We also examined the effect of four H₁R sequence variants observed in the human population on doxepin binding. These variants cause a reduction in doxepin affinity of up to 2.5 kcal·mol^-1, indicating that personalized medical treatments that take into account individual mutation patterns could increase precision in the dosage of GPCR-targeting drugs.

P17 induces chemotaxis and differentiation of monocytes via MRGPRX2-mediated mast cell-line activation

BACKGROUND

P17, a peptide isolated from Tetramorium bicarinatum ant venom, is known to induce an alternative phenotype of human monocyte-derived macrophages via activation of an unknown G protein-coupled receptor (GPCR).

OBJECTIVE

We sought to investigate the mechanism of action and the immunomodulatory effects of P17 mediated through MRGPRX2 (Mas-related G protein-coupled receptor X2).

METHODS

To identify the GPCR for P17, we screened 314 GPCRs. Upon identification of MRGPRX2, a battery of in silico, in vitro, ex vivo, and in vivo assays along with the receptor mutation studies were performed. In particular, to investigate the immunomodulatory actions, we used β-hexosaminidase release assay, cytokine releases, quantification of mRNA expression, cell migration and differentiation assays, immunohistochemical labeling, hematoxylin and eosin, and immunofluorescence staining.

RESULTS

P17 activated MRGPRX2 in a dose-dependent manner in β-arrestin recruitment assay. In LAD2 cells, P17 induced calcium and β-hexosaminidase release. Quercetin- and short hairpin RNA-mediated knockdown of MRGPRX2 reduced P17-evoked β-hexosaminidase release. In silico and in vitro mutagenesis studies showed that residue Lys8 of P17 formed a cation-π interaction with the Phe172 of MRGPRX2 and [Ala8]P17 lost its activity partially. P17 activated LAD2 cells to recruit THP-1 and human monocytes in Transwell migration assay, whereas MRGPRX2-impaired LAD2 cells cannot. In addition, P17-treated LAD2 cells stimulated differentiation of THP-1 and human monocytes, as indicated by the enhanced expression of macrophage markers cluster of differentiation 11b and TNF-α by quantitative RT-PCR. Immunohistochemical and immunofluorescent staining suggested monocyte recruitment in mice ears injected with P17.

CONCLUSIONS

Our data provide novel structural information regarding the interaction of P17 with MRGPRX2 and intracellular pathways for its immunomodulatory action.

Trends in application of advancing computational approaches in GPCR ligand discovery

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

Common activation mechanism of class A GPCRs

Class A G-protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology. Understanding receptor activation mechanism is critical for discovering novel therapeutics since about one-third of all marketed drugs target members of this family. GPCR activation is an allosteric process that couples agonist binding to G-protein recruitment, with the hallmark outward movement of transmembrane helix 6 (TM6). However, what leads to TM6 movement and the key residue level changes of this movement remain less well understood. Here, we report a framework to quantify conformational changes. By analyzing the conformational changes in 234 structures from 45 class A GPCRs, we discovered a common GPCR activation pathway comprising of 34 residue pairs and 35 residues. The pathway unifies previous findings into a common activation mechanism and strings together the scattered key motifs such as CWxP, DRY, Na+ pocket, NPxxY and PIF, thereby directly linking the bottom of ligand-binding pocket with G-protein coupling region. Site-directed mutagenesis experiments support this proposition and reveal that rational mutations of residues in this pathway can be used to obtain receptors that are constitutively active or inactive. The common activation pathway provides the mechanistic interpretation of constitutively activating, inactivating and disease mutations. As a module responsible for activation, the common pathway allows for decoupling of the evolution of the ligand binding site and G-protein-binding region. Such an architecture might have facilitated GPCRs to emerge as a highly successful family of proteins for signal transduction in nature.

Pyrazolo[4,3-e][1,2,4]triazolo[1,5-c]pyrimidines to develop functionalized ligands to target adenosine receptors: fluorescent ligands as an example

A series of adenosine receptor antagonists bearing a reactive linker was developed. Functionalization of these derivatives is useful to easily obtain multi-target ligands, receptor probes, drug delivery systems, and diagnostic or theranostic systems. The pyrazolo[4,3-e][1,2,4]triazolo[1,5-c]pyrimidine scaffold was chosen as a pharmacophore for the adenosine receptors. It was substituted at the 5 position with reactive linkers of different lengths. Then, these compounds were used to synthesise probes for the adenosine receptors by functionalization with a fluorescent moiety. Both series of compounds were evaluated for their binding at the four adenosine receptor subtypes. Different affinity and selectivity profiles were observed towards hA1, hA2A and hA3 adenosine receptors. In particular, fluorescent compounds behave as dual hA2A/hA3 ligands. Computational studies suggested different binding modes for developed compounds at the three receptors. Both molecular docking and supervised molecular dynamics (SuMD) simulations confirmed that the preferred binding mode at the single receptor was driven by the substitution present at the 5 position. Obtained results rationalized the compounds' binding profile at the adenosine receptors and pave the way for the development of more potent conjugable and conjugated ligands targeting these membrane receptors.

Molecular Dynamics Simulations of Adenosine Receptors: Advances, Applications and Trends

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Adenosine receptors (ARs) are transmembrane proteins that belong to the G protein-coupled receptors (GPCRs) superfamily and mediate the biological functions of adenosine. To date, four AR subtypes are known, namely A1, A2A, A2B and A3 that exhibit different signaling pathways, tissue localization, and mechanisms of activation. Moreover, the widespread ARs and their implication in numerous physiological and pathophysiological conditions had made them pivotal therapeutic targets for developing clinically effective agents.

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The crystallographic success in identifying the 3D crystal structures of A2A and A1 ARs has dramatically enriched our understanding of their structural and functional properties such as ligand binding and signal transduction. This, in turn, has provided a structural basis for a larger contribution of computational methods, particularly molecular dynamics (MD) simulations, toward further investigation of their molecular properties and designing bioactive ligands with therapeutic potential. MD simulation has been proved to be an invaluable tool in investigating ARs and providing answers to some critical questions. For example, MD has been applied in studying ARs in terms of ligand-receptor interactions, molecular recognition, allosteric modulations, dimerization, and mechanisms of activation, collectively aiding in the design of subtype selective ligands.

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In this review, we focused on the advances and different applications of MD simulations utilized to study the structural and functional aspects of ARs that can foster the structure-based design of drug candidates. In addition, relevant literature was briefly discussed which establishes a starting point for future advances in the field of drug discovery to this pivotal group of drug targets.

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.

Coupling Supervised Molecular Dynamics (SuMD) with Entropy Estimations To Shine Light on the Stability of Multiple Binding Sites

Exploring at the molecular level, all possible ligand-protein approaching pathways and, consequently, identifying the energetically favorable binding sites is considered crucial to depict a clear picture of the whole scenario of ligand-protein binding. In fact, a ligand can recognize a protein in multiple binding sites, adopting multiple conformations in every single binding site and inducing protein modifications upon binding. In the present work, we would like to present how it is possible to couple a supervised molecular dynamics (SuMD) approach to explore, from an unbound state, the most energetically favorable recognition pathways of the ligand to its protein, with an enthalpic and entropic characterization of the most stable ligand-protein bound states, using the protein kinase CK2α as a prototype study. We identified two accessory binding pockets surrounding the ATP-binding site having a strong enthalpic contribution but a different configurational entropy contribution, suggesting that they play a different role.

Tinkering with targeting nucleotide signaling for control of intracellular Leishmania parasites

Nucleotides are one of the most primitive extracellular signalling molecules across all phyla and regulate a multitude of responses. The biological effects of extracellular nucleotides/sides are mediated via the specific purinergic receptors present on the cell surface. In mammalian system, adenine nucleotides are the predominant nucleotides found in the extracellular milieu and mediate a constellation of physiological functions. In the context of host-pathogen interaction, extracellular ATP is recognized as a danger signal and potentiates the release of pro-inflammatory mediators from activated immune cells, on the other hand, its breakdown product adenosine exerts potential anti-inflammatory and immunosuppressive actions. Therefore, it is increasingly apparent that the interplay between extracellular ATP/adenosine ratios has a significant role in coordinating the regulation of the immune system in health and diseases. Several pathogens express ectonucleotidases on their surface and exploit the purinergic signalling as one of the mechanisms to modulate the host immune response. Leishmania pathogens are one of the most successful intracellular pathogens which survive within host macrophages and manipulate protective Th1 response into disease promoting Th2 response. In this review, we discuss the regulation of extracellular ATP and adenosine levels, the role of ATP/adenosine counter signalling in regulating the inflammation and immune responses during infection and how Leishmania parasites exploit the purinergic signalling to manipulate host response. We also discuss the challenges and opportunities in targeting purinergic signalling and the future prospects.

Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A2A adenosine receptor orthosteric binding site using a molecular docking approach? Insights from Dockbench

The allosteric modulation of G protein-coupled receptors (GPCRs) by sodium ions has received considerable attention as crystal structures of several receptors, in their inactive conformation, show a Na⁺ ion bound to specific residues which, in the human A_2A adenosine receptor (hA_2A AR), are Ser91^3.39, Trp246^6.48, Asn280^7.45, and Asn284^7.49. A cluster of water molecules completes the coordination of the sodium ion in the putative allosteric site. It is absolutely consolidated that the progress made in the field of GPCRs structural determination has increased the adoption of docking-driven approaches for the identification or the optimization of novel potent and selective ligands. Despite the extensive use of docking protocols in virtual screening approaches, to date, almost any of these studies have been carried out without taking into account the presence of the sodium cation and its first solvation shell in the putative allosteric binding site. In this study, we have focused our attention on determining how the presence of sodium ion binding and additionally its first hydration sphere, in hA_2AAR could influence the ligand positioning accuracy during molecular docking simulations for most of the available resting and activated hA_2A AR crystal structures, using DockBench as a comparative benchmarking tool and implementing a new correlation coefficient (EM). This work provides indications on the evidence that the posing performance (accuracy and/or precision) of the docking protocols in reproducing the crystallographic poses of different hA_2A AR antagonists is generally increased in the presence of the sodium cation and its first solvation shell, in agreement with experimental observations. Consequently, the inclusion of sodium ion and its first solvation shell should be considered in order to facilitate the selection of new potential ligands in all molecular docking-based virtual screening protocols that aim to find novel GPCRs antagonists and inverse agonists.

Discovery of 2-aminoimidazole and 2-amino imidazolyl-thiazoles as non-xanthine human adenosine A3 receptor antagonists: SAR and molecular modeling studies

A small-molecule combinatorial library of 24 compounds with 2-aminoimidazole and 2-aminoimidazolyl-thiazole derivatives was synthesized using a 2-chloro trityl resin. The generated compound library was tested against all the human adenosine receptors subtypes. The 2-aminoimidazole derivatives (6a-6l) showed weak to moderate affinity towards the human adenosine receptors. Further modification to 2-aminoimidazolyl-thiazole derivatives (12a-12l) resulted in an improvement of affinity at adenosine A₁, A_2A and A₃ receptor subtypes. Compound 12b was the most potent and selective non-xanthine human adenosine A₃ receptor antagonist of this series. A receptor-based modeling study was performed to explore the possible binding mode of these novel 2-aminoimidazole and 2-aminoimidazolyl-thiazole derivatives into human adenosine A₁, A_2A and A₃ receptor subtypes.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

GPCRs: What Can We Learn from Molecular Dynamics Simulations?

Advances in the structural biology of G-protein Coupled Receptors have resulted in a significant step forward in our understanding of how this important class of drug targets function at the molecular level. However, it has also become apparent that they are very dynamic molecules, and moreover, that the underlying dynamics is crucial in shaping the response to different ligands. Molecular dynamics simulations can provide unique insight into the dynamic properties of GPCRs in a way that is complementary to many experimental approaches. In this chapter, we describe progress in three distinct areas that are particularly difficult to study with other techniques: atomic level investigation of the conformational changes that occur when moving between the various states that GPCRs can exist in, the pathways that ligands adopt during binding/unbinding events and finally, the influence of lipids on the conformational dynamics of GPCRs.

Recent Advances in Structure-Based Drug Design Targeting Class A G Protein-Coupled Receptors Utilizing Crystal Structures and Computational Simulations

G protein-coupled receptors (GPCRs) represent the largest and most physiologically important integral membrane protein family, and these receptors respond to a wide variety of physiological and environmental stimuli. GPCRs are among the most critical therapeutic targets for numerous human diseases, and approximately one-third of the currently marketed drugs target this receptor family. The recent breakthroughs in GPCR structural biology have significantly contributed to our understanding of GPCR function, ligand binding, and pharmacological action as well as to the design of new drugs. This perspective highlights the latest advances in GPCR structures with a focus on the receptor-ligand interactions of each receptor family in class A nonrhodopsin GPCRs as well as the structural features for their activation, biased signaling, and allosteric mechanisms. The current state-of-the-art methodologies of structure-based drug design (SBDD) approaches in the GPCR research field are also discussed.

Supporting the Identification of Novel Fragment-Based Positive Allosteric Modulators Using a Supervised Molecular Dynamics Approach: A Retrospective Analysis Considering the Human A2A Adenosine Receptor as a Key Example

Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the identification of novel drug candidates. This strategy has been largely applied in discovering several pharmacological ligand classes, including enzyme inhibitors, receptor antagonists and, more recently, also allosteric (positive and negative) modulators. Recently, Siegal and collaborators reported an interesting study, performed on a detergent-solubilized StaR adenosine A_2A receptor, describing the existence of both fragment-like negative allosteric modulators (NAMs), and fragment-like positive allosteric modulators (PAMs). From this retrospective study, our results suggest that Supervised Molecular Dynamics (SuMD) simulations can support, on a reasonable time scale, the identification of fragment-like PAMs following their receptor recognition pathways and characterizing the possible allosteric binding sites.

The role of 5-arylalkylamino- and 5-piperazino- moieties on the 7-aminopyrazolo[4,3-d]pyrimidine core in affecting adenosine A1 and A2A receptor affinity and selectivity profiles

New 7-amino-2-phenylpyrazolo[4,3-d]pyrimidine derivatives, substituted at the 5-position with aryl(alkyl)amino- and 4-substituted-piperazin-1-yl- moieties, were synthesized with the aim of targeting human (h) adenosine A₁ and/or A_2A receptor subtypes. On the whole, the novel derivatives 1–24 shared scarce or no affinities for the off-target hA_2B and hA₃ ARs. The 5-(4-hydroxyphenethylamino)- derivative 12 showed both good affinity (K_i = 150 nM) and the best selectivity for the hA_2A AR while the 5-benzylamino-substituted 5 displayed the best combined hA_2A (K_i = 123 nM) and A₁ AR affinity (K_i = 25 nM). The 5-phenethylamino moiety (compound 6) achieved nanomolar affinity (K_i = 11 nM) and good selectivity for the hA₁ AR. The 5-(N⁴-substituted-piperazin-1-yl) derivatives 15–24 bind the hA₁ AR subtype with affinities falling in the high nanomolar range. A structure-based molecular modeling study was conducted to rationalize the experimental binding data from a molecular point of view using both molecular docking studies and Interaction Energy Fingerprints (IEFs) analysis.

Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors

The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry. A deeper insight into the underlying mechanisms of interesting phenomena observed in GPCRs, such as biased signaling or allosteric modulation, can be gained with experimental and computational studies. The latter play an important role in this process, since they allow for observations on scales inaccessible for most other methods. One of the key steps in such studies is proper computational reconstruction of actual ligand-receptor or protein-protein interactions, a process called molecular docking. A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs.

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.

Current status and future prospects for enabling chemistry technology in the drug discovery process

This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.