Mind the Gap - Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand–receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs

Molecular Modeling and Experimental Studies on Ligand Recognition in the LPA5 G Protein-Coupled Receptor

Lysophosphatidic acid (LPA) is a phospholipid growth factor mediating numerous biological effects such as platelet aggregation, mast cell activation, cell differentiation, cell migration, and cell survival by acting on specific LPA G protein-coupled receptors. Currently there are nine LPA receptors identified in the literature, LPA1-9. LPA1-3 are members of the endothelial differentiation gene (EDG) family and share approximately 50% sequence identity at the primary sequence level. LPA4-9 are structurally distinct from the EDG receptors with LPA5 sharing approximately 30% sequence identity with LPA4 at the primary sequence level. Due to the emerging role of LPA5 in human platelet activation, cancer, and neuropathic pain, a thorough characterization of LPA5is needed for the development of compounds to serve as starting points for anti-thrombotic and anti-cancer therapies as well as to inhibit neuropathic pain. In this dissertation we describe LPA5 pharmacophore model development and performance, LPA5 homology model evaluation and optimization through docking and site-directed mutagenesis studies, and structure-activity relationships (SAR) analysis at LPA5. Docking simulations were performed with the LPA5 homology model to computationally identify residues involved in ligand recognition. Pharmacophore modeling was performed to identify compounds with functional groups necessary for receptor inhibition to serve as starting points for therapeutic lead discovery. Our pharmacophore models identified weak partial antagonists and we validated headgroup recognition in alkyl-LPA (AGP 18:1), octadecenylthiophosphate (OTP 18:1), and oleyl-LPA (LPA 18:1). Specifically we proved three cationic residues to be involved in headgroup recongition: R78 (R2.60), R261 (R6.62), and R276 (R7.32). Furthermore we confirmed F71 (F2.53), F101 (F3.32), and M105 (M3.36) as three important residues involved in hydrophobic interactions with AGP, OTP, and LPA ligands. Also, we confirmed an alkyl-LPA preference in LPA5 relative to acyl-LPA. The SAR results suggests that the LPA5 binding pocket exhibits a bend that better accomadates cis relative to tran aslkenes located nine carbons from the headgroup, and that surrounding regions of the binding pocket are less bent, disfavoring recognition of ligands with cis double bonds located closer to or farther from the headgroup

Fragment-based lead discovery on G-protein-coupled receptors

Introduction: G-protein-coupled receptors (GPCRs) form one of the largest groups of potential targets for novel medications. Low druggability of many GPCR targets and inefficient sampling of chemical space in high-throughput screening expertise however often hinder discovery of drug discovery leads for GPCRs. Fragment-based drug discovery is an alternative approach to the conventional strategy and has proven its efficiency on several enzyme targets. Based on developments in biophysical screening techniques, receptor stabilization and in vitro assays, virtual and experimental fragment screening and fragment-based lead discovery recently became applicable for GPCR targets. Areas covered: This article provides a review of the biophysical as well as biological detection techniques suitable to study GPCRs together with their applications to screen fragment libraries and identify fragment-size ligands of cell surface receptors. The article presents several recent examples including both virtual and experimental protocols for fragment hit discovery and early hit to lead progress. Expert opinion: With the recent progress in biophysical detection techniques, the advantages of fragment-based drug discovery could be exploited for GPCR targets. Structural information on GPCRs will be more abundantly available for early stages of drug discovery projects, providing information on the binding process and efficiently supporting the progression of fragment hit to lead. In silico approaches in combination with biological assays can be used to address structurally challenging GPCRs and confirm biological relevance of interaction early in the drug discovery project

Part I, Unified Pharmacophore Protein Models of the Benzodiazepine Receptor Subtypes ; Part II, Subtype

Part I. New models of unified pharmacophore/receptors have been constructed guided by the synthesis of subtype selective compounds in light of recent developments both in ligand synthesis and structural studies of the binding site itself. The evaluation of experimental data in combination with comparative models of the α1β2γ2, α2β2γ2, α3β2γ2 and α5β2γ2 GABA(A) receptors has led to an orientation of the pharmacophore model within the benzodiazepine binding site (Bz BS). These results not only are important for the rational design of new selective ligands, but also for the identification and evaluation of possible roles which specific residues may have within the benzodiazepine binding pocket. More importantly, the process summarized here may be used as a general template to help scientists develop novel ligands for receptors for which the three dimensional structure has not yet been confirmed by X-ray crystallography or cryo-electron microscopy. Presented here are new models of the α1β2γ2, α2β2γ2, α3β2γ2 and α5β2γ2 GABA(A) receptors which have incorporated homology models built based on the acetylcholine binding protein. These new models will further our ability to understand structural characteristics of ligands which act as agonists, antagonists, or inverse agonists to the Bz BS of the GABA(A) receptor. This approach will also serve as a powerful model for structure based approaches carried out using ligand-protein docking methods. Part II. An effective strategy to alleviate memory deficits would be to enhance memory and cognitive processes by augmenting the impact of acetylcholine released from cholinergic neurons of the hippocampus. Using the included volume pharmacophore presented in Part I, a number of a5 selective compounds were synthesized, notably PWZ-029. PWZ-029 was examined in rats in the passive and active avoidance, spontaneous locomotor activity, elevated plus maze and grip strength tests which are indicative of the effects on memory acquisition, locomotor activity, anxiety, and muscle tone. Improvement of task learning was shown at a dose of 5mg/kg in passive avoidance test without effect on anxiety or muscle tone. Moderate negative modulation at GABA(A) receptors containing the α5 subunit using a moderate inverse agonist such as PWZ-029, is a sufficient condition for eliciting enhanced encoding/consolidation of declarative memory. Using low temperature NMR and X-ray analysis, it was shown that enhanced selectivity and potent in vitro affinity of α5 selective benzodiazepine dimers was possible with aliphatic linkers of 3 to 5 carbons in length. Although originally proposed to enhance solubility, oxygen-containing linkers caused the dimer to fold back on itself leading to the inability of dimers to enter the binding pocket. In addition, studies of a series of PWZ-029 analogs found that the electrostatic potential near the ligands\u27 terminal substituent correlated with its binding selectivity toward the α5β2γ2 versus α1β2γ2 Bzr/GABA(A) ergic isoform. Investigations further found that compound PWZ-029, which exhibits reasonable binding selectivity toward GABA(A) receptors containing the a5 subunit and possesses a favorable electrophysiological profile, was able to attenuate scopolamine induced contextual memory impairment in mice. This compound appears to be useful (Harris, Delorey et al.) for the treatment of cognitive deficits in rodents as well as primates (Rowlett et al.) and may well be a compound for the treatment of patients with Alzheimers disease

Discovery of new selective antagonists of G-protein coupled receptors of therapeutic interest

GPCR are integral membrane receptor proteins that are characterized by heptahelical transmembrane domains connected by intracellular and extracellular loops. GPCRs are an attractive class of proteins for drug discovery, with more than 50% of all drugs regulating GPCR function, and some 30% of these drugs directly target GPCRs. Despite the number of GPCR crystal structures determined recently, they only represent a small fraction of total number of GPCRs known. Homology modelling has been the methodology used to fill the gap. However, the low sequence similarity between targets and templates hampers these studies. Aimed at overcoming these drawbacks template selection and the refinement process were studied in this work. Thus, several atomistic models of rat M3 muscarinic receptor were constructed from human M2 muscarinic receptor, human histamine 1 receptor and bovine rhodopsin receptor as templates. Moreover, in order to determine the effect of ligand in the simulation system, an extra model of M2 receptor was refined with NMS bound inside and an extra model refined without ligand. Results show the sampling time 500ns is adequate simulation time and molecular dynamics simulation of the protein embedded in a lipid bilayer as a refinement process improves on the homology models. Specifically, the refinement process can correct the length of the TM segment of the target receptor; the accuracy of the model greatly depends on the proximity of the template and the target in the phylogenetic tree and finally, the presence of a ligand produces a faster equilibration of the system. This methodology was used to study the pharmacological profile of bradykinin receptors B1 and B2. The B1 receptor was constructed using the chemokine CXC4 and bovine rhodopsin receptors as templates. Antagonists selected for the docking studies include Compound 11, Compound 12, Chroman28, SSR240612, NPV-SAA164 and PS020990. Analysis of the ligand-receptor complexes permitted the definition of a pharmacophore that describes the stereochemical requirements of antagonist binding. For the B2 receptor, a similar procedure was followed using the same template. In this case, the set of compounds used were Fasitibant, FR173657, Anatibant, WIN64338, Bradyzide, CHEMBL442294, and JSM10292. The outcome of this study is summarized in a 3D pharmacophore that explains the observed structure-activity results and provides insight into the design of novel molecules with antagonistic profile. To prove the validity of the pharmacophoric hypotheses, a virtual screening process was carried out. The results of the binding studies show about a 33% success rate with a correlation between the number of pharmacophore points fulfilled and their antagonistic potency. Some of these structures are disclosed in this thesis. Moreover, the B1R and B2R pharmacophores developed were compared and the observed differences permitted to explain the stereochemical requirements for receptor-selective ligands. The final study of this study was to establish a rational explanation for the role of zinc in preventing the dimerization of the serotonin 5-Hydroxytryptamine 1A receptor (5-HT1A) and Galanin receptor 1 (GALR1) involved in depression. Homology modeling was used to build atomistic models of these receptors using the crystallographic structures of 5-HT1B and κ– opioid receptor, respectively. First, prospective zinc binding sites were identified for the 5-HT1A using a molecular probe. Second, heterodimers of the two receptors were constructed with different interfaces: TM4 and TM5; TM6 and TM7; TM1 and TM2. Analysis of the 12 zinc-binding sites and the heterodimer interfaces suggests that there is a coincidence between zinc binding sites and heterodimerization interfaces providing a rational explanation for the role of zinc in the molecular processes associated with heterodimer preventionLos receptores acoplados a proteínas G (GPCRs) son proteínas de membrana que se caracterizan por dominios transmembrana heptahelicoidales conectados por lazos intracelulares y extracelulares. GPCRs son un atractivo grupo de proteínas para el descubrimiento de nuevos fármacos puesto que más del 50% de los medicamentos en el mercado que regulan su función y alrededor del 30% que tienen un GPCR como diana. A pesar del gran número de estructuras cristalográficas de GPCRs que se han determinado recientemente, estas solamente representan una pequeña fracción del número total de GPCRs. La homología de secuencia se utiliza de forma rutinaria para llenar el vacío, sin embargo, la baja identidad de secuencia entre miembros de esta familia obstaculiza estos estudios. Con el objetivo de superar estos inconvenientes, tanto el proceso de selección de la plantilla, como el proceso de refinamiento del modelo han sido estudiados en este trabajo. Se construyeron modelos atómicos del receptor muscarínico M3 de rata a partir del receptor humano M2 muscarínico, del de histamina humano 1 y de la rodopsina bovina como plantilla. Por otra parte, con el fin de determinar el efecto del ligando en el proceso de refinamiento, el receptor M2 fue refinado con el ligando NMS y además se construyó un modelo sin ligando. Los resultados muestran que un tiempo de muestreo 500ns es adecuado y que la dinámica molecular representa un proceso de refinamiento adecuado. Esta metodología se utilizó para estudiar el perfil farmacológico de los receptores de bradiquinina B1 y B2. El receptor B1 se construyó usando los receptores CXC4 de quimoquina y rodopsina bovina como plantillas. Los antagonistas seleccionados para los estudios de anclaje incluyen el Compuesto 11, el Compuesto 12, Chroman28, SSR240612, NVP-SAA164 y PS020990. El análisis de los complejos ligando-receptor permite la definición de un farmacóforo que describe los requisitos estereoquímicos de unión de antagonistas. Para el receptor B2, se siguió un procedimiento similar utilizando las mismas plantillas. En este caso, el conjunto de los compuestos utilizados fueron Fasitibant, FR173657, Anatibant, WIN64338, Bradyzide, CHEMBL442294 y JSM10292. El resultado de este estudio se resume en un farmacóforo 3D que explica los resultados estructura-actividad observados y ofrece información sobre el diseño de nuevas moléculas con el perfil antagonista. Para probar la validez de las hipótesis farmacofóricas, se llevó a cabo un proceso de cribado virtual. Los resultados de los estudios de unión muestran sobre una tasa de éxito del 33% con una correlación entre el número de puntos farmacóforicos cumplido y su potencia antagonista. Algunas de estas estructuras se describen en esta tesis. Por otra parte, los farmacóforos de B1R y B2R desarrollados se compararon y a través de las diferencias observadas explicar los requisitos estereoquımicos para que los ligandos sean selectivos. El estudio final de este trabajo fue el establecer una explicación racional para el papel del zinc en la prevención de la dimerización del receptor de serotonina 5-hidroxitriptamina 1A (5-HT1A) y el receptor galanina 1 (GALR1) que participan en la depresión. Homología de secuencia se utilizó para construir modelos atómicos de estos receptores utilizando las estructuras cristalográficas de los receptores 5-HT 1B y κ de opiáceos, respectivamente. En primer lugar, se identificaron los posibles sitios de unión de zinc para el 5-HT1A usando una sonda molecular. En segundo lugar, los heterodímeros de los dos receptores fueron construidos con diferentes interfaces: TM4 y TM5; TM6 y TM7; TM1 y TM2. El análisis de los 12 sitios de unión de zinc y las interfaces heterodímero sugiere que existe una coincidencia entre los sitios de unión de zinc y las interfaces de heterodimerización que proporcionan una explicación racional para el papel del zinc en los procesos moleculares asociados con la prevención heterodímero.Postprint (published version

A New Pharmacophore Model for the Design of Sigma-1 Ligands Validated on a Large Experimental Dataset

The recent publication of the σ1R crystal structure is an important cornerstone for the derivation of more accurate activity prediction models. We report here a comparative study involving a set of more than 25,000 structures from our internal database that had been screened for σ1R affinity. Using the recently published crystal structure, 5HK1, two new pharmacophore models were generated. The first one, 5HK1–Ph.A, was obtained by an algorithm that identifies the most important receptor-ligand interactions including volume restrictions enforced by the atomic structure of the recognition site. The second, 5HK1–Ph.B, resulted from a manual edition of the first one by the fusion of two hydrophobic (HYD) features. Finally, we also docked the database using a high throughput docking technique and scored the resulting poses with seven different scoring functions. Statistical performance measures were obtained for the two models, comparing them with previously published σ1R pharmacophores (Hit Rate, sensitivity, specificity, and Receiver Operator Characteristic) and 5HK1–Ph.B emerged as the best one in discriminating between active and inactive compounds, with a ROC-AUC value above 0.8 and enrichment values above 3 at different fractions of screened samples. 5HK1–Ph.B also showed better results than the direct docking, which may be due to the rigidity of the crystal structure in the docking process (i.e., feature tolerances in the pharmacophore model). Additionally, the impact of the HYD interactions and the penalty for desolvating ligands with polar atoms may be not adequately captured by scoring functions, whereas HYD groups filling up such regions of the binding site are entailed in the pharmacophore model. Altogether, using annotated data from a large and diverse compound collection together with crystal structure information provides a sound basis for the generation and validation of predictive models to design new molecules

Untersuchung der Struktur und Interaktion mit allosterischen Modulatoren der Familie C GPCRs mit Hilfe von Sequenz-, Struktur- und Ligand-basierten Verfahren

This study focuses on structural features of a particular GPCR type, the family C GPCRs. Structure- and ligand-based approaches were adopted for prediction of novel mGluR5 binding ligand and their binding modes. The objectives of this study were: 1. An analysis of function and structural implication of amino acids in the TM region of family C GPCRs. 2. The prediction of the TM domain structure of mGluR5. 3. The discovery of novel selective allosteric modulators of mGluR5 by virtual screening. 4. The prediction of a ligand binding mode for the allosteric binding site in mGluR5. GPCRs are a super-family of structurally related proteins although their primary amino acid sequence can be diverse. Using sequence information a conservation analysis of family C GPCRs should be applied to reveal characteristic differences and similarities with respect function, folding and ligand binding. Using experimental data and conservation analysis the allosteric binding site of mGluR5 should be characterized regarding NAM and PAM and selective ligand binding. For further evaluation experimental knowledge about family A GPCRs as well as conservation between vertebrate rhodopsins was planned to be compared to results obtained for family C GPCRs (Section 4.1 Conservation analysis of family C GPCRs). Since no receptor structure is available for any family C GPCR, discussion of conserved sequence positions between family A and C GPCRs requires the prediction of a receptor structure for mGluR5 using a family A receptor as template. In order to predict the mGluR5 structure a sequence alignment to a GPCR template protein will have to be proposed and GPCR specific features considered in structure calculation (Section 4.1.4 Structure prediction of mGluR5). The obtained structure was intended to be involved in ligand binding mode prediction of newly discovered active molecules. For discovery of novel selective mGluR modulators several ligand-based virtual screening protocols were adapted and evaluated. Prediction models were derived for selection of possibly active molecules using a diverse collection of known mGluR binding ligands. For that purpose a data collection of known mGluR binding ligands should be established and this reference collection analyzed with respect to different ligand activity classes, NAM or PAM and selective modulators. The prediction of novel NAMs and PAMs using several combinations of 2D-, 3D-, pharmacophore or molecule shape encoding methods with machine learning techniques and similarity determining methods should be tested in a prospective manner (Section 4.2 Virtual screening for novel mGluR modulators). In collaboration with Merz Pharmaceuticals (Merz GmbH & Co. KGaA, Frankfurt am Main, Germany) the modulating effect of a few hundred molecules should be approved in a functional cell-based assay. With the objective to predict a binding mode of the discovered active molecules, molecule docking should be applied using the allosteric binding site of the modeled mGluR5 structure (Section 4.2.4 Modeling of binding modes). Predicted ligand binding modes are to be correlated to conservation profiles that had resulted from the sequence-based entropy analysis and information from mutation experiments, and shall be compared to known ligand binding poses from crystal structures of family A GPCRs.Im Rahmen dieser Arbeit wurden Konzepte zur Aufklärung struktureller und funktioneller Eigenschaften von G-Protein gekoppelten Rezeptoren (GPCR) der Familie C entwickelt und angewendet. Mit unterschiedlichen Methodiken der Bio- und Chemieinformatik orientiert an experimentellen Ergebnissen wurden Fragestellungen bezüglich des Funktionsmechanismus von GPCRs untersucht. In Verlauf wurde anhand verfügbarer experimenteller Daten aus Mutations- und Ligandenbindungsstudien ein Vergleich konservierter Bereiche der Rezeptor-Familien A und C angefertigt. Die Konserviertheitsanalyse stützte sich auf die Berechnung der Shannon-Entropie und wurde für ein multiples Sequenzalignment von Transmembrandomänen unterschiedlicher 96 Familie C GPCRs ermittelt. Konservierte Bereiche wurden mit Hilfe experimenteller Daten interpretiert und insbesondere zur Definition von Regionen in der allosterischen Bindetasche hinsichtlich Selektivität verwendet. Mit dem Ziel, neue selektive allosterische Modulatoren für den metabotropen Glutamatrezeptor des Typs fünf (mGluR5) zu finden, wurden mehrere Liganden-basierte Ansätze zur virtuellen Vorhersage der Aktivität von Molekülen entwickelt und getestet. Die dabei angewendete Strategie basierte auf der Kenntnis bereits bekannter Liganden, deren Strukturen und Aktivitätswerte für das Erstellen von Vorhersagemodelle genutzt werden konnten. Die prospektive Vorhersage stützte sich auf unterschiedliche Methoden zur Ähnlichkeitsberechnung und Arten der Molekülkodierung. Die Testung der Moleküle erfolgte hinsichtlich ihrer modulatorischen Wirkung am mGluR5. Die Art der Messung erfasste die Änderungen des Ca2+-Levels in der Zelle. mGluR5-bindende Modulatoren wurden zur Selektivitätsbestimmung einer Testung am mGluR1 unterzogen. Insgesamt konnten 8 von 228 getesteten Molekülen im Aktivitätsbereich unter 10μM ermittelt werden, darunter befand sich ein positiver allosterischer Modulator. Von den restlichen sieben negativen Modulatoren (NAM) waren fünf selektiv für mGluR5. Alle identifizierten NAMs wurden mittels molekularem Dockings auf mögliche Interaktion mit der Transmembrandomäne von mGluR5 untersucht. Die Bindungshypothese entsprach einer Überlagerung der gefundenen Moleküle und ihrer möglicher Interaktionspunkte. Exemplarisch am mGluR5 konnte somit die Eignung einer modellierten GPCR-Struktur für eine Hypothesengenerierung bezüglich Ligandenbindung und struktureller Zusammenhänge untersucht werden

Los receptores para el reconocimiento de patrones moleculares: aportaciones de la química computacional para el diseño de fármacos y la modulación de la inmunidad innata

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, Departamento de Química Orgánica y Farmacéutica, leída el 18/11/2019In this Thesis we have aimed the study of the molecular recognition processes of receptors involved in the innate immunity. More concretely, we have focused in two different types of lectins, Galectins and DC-SIGN, and in Toll-like receptor 4. We have made use of computational techniques, including docking and virtual screening, molecular dynamics simulations, conformational analysis and quantum mechanics calculations. The work has been organized into several chapters that are summarized as follows: Chapter 1 corresponds to the current knowledge and perspectives about receptors related to immunity, in particular: galectins, DC-SIGN, and Toll-like receptor 4, corresponding to the molecular recognition events and modulation by small molecules. Chapter 2 describes the state-of-the-art methods in molecular modeling and computational chemistry applied to the study of molecular recognition processes and drug design...En esta tesis hemos estudiado los procesos reconocimiento molecular de receptores involucrados en la inmunidad innata. Más concretamente, nos hemos centrado en dos tipos diferentes de lectinas, Galectinas y DC-SIGN, y en el receptor Toll-like 4 (TLR4). Hemos utilizado técnicas computacionales, incluyendo docking y cribado virtual, simulaciones de dinámica molecular, análisis conformacional y cálculos de mecánica cuántica. El trabajo se ha organizado en diferentes capítulos que se resumen como sigue: El capítulo 1 corresponde al estado del arte y las perspectivas relacionadas con los estudios de reconocimiento molecular proteína-carbohidrato y diseño de nuevos moduladores con actividad biológica en receptores de la inmunidad, en particular galectinas, DC-SIGN y el receptor Toll-like 4. El capítulo 2 describe el estado actual de los métodos en modelado molecular y química computacional aplicados al estudio de los procesos de reconocimiento molecular y diseño de fármacos...Fac. de FarmaciaTRUEunpu