Electronic sculpting of ligand-GPCR subtype selectivity:the case of angiotensin II

GPCR subtypes possess distinct functional and pharmacological profiles, and thus development of subtype-selective ligands has immense therapeutic potential. This is especially the case for the angiotensin receptor subtypes AT1R and AT2R, where a functional negative control has been described and AT2R activation highlighted as an important cancer drug target. We describe a strategy to fine-tune ligand selectivity for the AT2R/AT1R subtypes through electronic control of ligand aromatic-prolyl interactions. Through this strategy an AT2R high affinity (<i>K</i>_i = 3 nM) agonist analogue that exerted 18,000-fold higher selectivity for AT2R versus AT1R was obtained. We show that this compound is a negative regulator of AT1R signaling since it is able to inhibit MCF-7 breast carcinoma cellular proliferation in the low nanomolar range

Sharing data from molecular simulations

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 (https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations

Darstellung und Charakterisierung neuartiger, chiraler, basischer Benzilsäureester mit anticholinerger Wirkung

Basische Benzilsäureester stellen mit ihrer ausgeprägten anticholinergen Wirksamkeit potenzielle Arzneistoffe zur Behandlung der Harninkontinenz, der Ulkuserkrankung und des Morbus Parkinson dar. Von besonderem Interesse sind Benzilsäurevertreter, die neben anticholinergen auch dopaminerge Effekte aufweisen. Wegen ihrer dualistischen Wirkung könnten sie eine neue Klasse von Antiparkinsonica begründen. Aufgrund der vielfältigen Funktionen von Muscarinrezeptoren treten bei wenig selektiv wirksamen Arzneistoffen atropinartige Nebenwirkungen auf. Mit der Entwicklung von Verbindungen, die eine erhöhte muscarinerge Subtypenselektivität besitzen, lassen sich Nebenwirkungen reduzieren. Ziel der Arbeit war eine Wirkungsoptimierung chiraler N-Methyl-4-piperidyl benzilate durch Variation von stereochemischen Parametern und Einführen elektronisch verschiedenartiger Substituenten in die aromatischen Ringe. In Radioligand-Bindungsstudien an M1- bis M3-Rezeptoren wurden die Auswirkungen der sterischen und strukturellen Variationen untersucht. Die Ergebnisse der Bindungsstudien zeigen, dass sich Affinität und Subtypenselektivität durch die absolute Konfiguration des stereogenen Zentrums und die Art der Kernsubstitution modifizieren lassen. Mit Hilfe von Molecular Modelling ist es gelungen, auf Basis der experimentellen Bindungsdaten ein aussagekräftiges Rezeptormodell für N-Methyl-4-piperidyl benzilate zu entwickeln. Sowohl die Affinitätsunterschiede enantiomerer Benzilate als auch die Unterschiede der Rezeptorsubtypenselektivität werden durch das Rezeptormodell umfassend erklärt.Basic substituted benzilic esters with distinctive anticholinergic effects are potential drugs for the treatment of urinary incontinence, duodenal and gastric ulcers and Parkinson disease. Derivatives of benzilic esters, exhibiting a combination of anticholinergic and dopaminergic effects, are of special interest because, as a consequence of their dualistic effect, they are in a position to form a new class of Antiparkinson drugs. As muscarinic receptor subtypes possess a large variety of functional properties, drugs which show less selectivity on muscarinic receptors exhibit atropine-like side effects. A reduction of these side effects may be achieved by the development of more selective anticholinergic compounds. The objective was to optimise the effect of N-Methyl-4-piperidyl benzilates through a variation of sterical parameters and the introduction of electronically differentiated substituents within the aromatic rings. The effect of sterical and structural variations was investigated in radioligand binding studies on muscarinic receptors (M1 – M3). The results of these binding studies reveal that a modification of affinity and selectivity can be achieved by varying the absolute configuration of the stereogenic center and the properties of the substitution of the aromatic system. The development of a relevant model of the receptor ligand complex for N-Methyl-4-piperidyl benzilates was achieved by molecular modelling on the basis of experimental binding studies. Both the diverse affinity of enantiomeric benzilic esters and the subtype selectivity on muscarinic receptors are comprehensively explained by this model

UST Seminar. The Regulatory role of membrane Lipids for sinaling processes in the Central Nervous System

Cell membranes have significant influence over signaling proteins that are embedded within them. One important class of such proteins are G protein coupled receptors (GPCRs). GPCRs are abundantly distributed in the central nervous system (CNS) where they sense molecules outside the cell and activate diverse signal transduction pathways inside the cell yielding a distinct cellular response

On the construction of LIECE models for the serotonin receptor 5-HT[Formula: see text]R

Computer-aided approaches to ligand design need to balance accuracy with speed. This is particularly true for one of the key parameters to be optimized during ligand development, the free energy of binding ([Formula: see text]G[Formula: see text]). Here, we developed simple models based on the Linear Interaction Energy approximation to free energy calculation for a G protein-coupled receptor, the serotonin receptor 2A, and critically evaluated their accuracy. Several lessons can be taken from our calculations, providing information on the influence of the docking software used, the conformational state of the receptor, the cocrystallized ligand, and its comparability to the training/test ligands

Membrane protein structure, function, and dynamics: a perspective from experiments and theory

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.JTD, IA, and MR used the computational resources of the Modeling Facility of the Department of Chemistry, University of California Irvine funded by NSF Grant CHE-0840513 for this work. A-NB was supported in part by the Marie Curie International Reintegration Award IRG-26920.TWA was supported by ARC DP120103548, NSF MCB1052477, DE Shaw Anton (PSCA00061P; NRBSC, through NIH RC2GM093307), VLSCI (VR0200), and NCI (dd7). BA and SV acknowledge the support by ERC advanced Grant No. 268888. ZC and PG would like to acknowledge Reference Framework (NSRF) 2011–2013, National Action ‘‘Cooperation,’’ under grant entitled ‘‘Magnetic Nanoparticles for targeted MRI therapy (NANOTHER),’’ with code ‘‘11RYM-1-1799.’’ The program is cofunded by the European Regional Development Fund and national resources. Part of the calculations presented herein were performed using resources of the LinkSCEEM-2 project, funded by the EC under FP7 through Capacities Research Infrastructure, INFRA-2010-1.2.3 Virtual Research Communities, Combination of Collaborative Project and Coordination and Support Actions (CPCSA) under Grant agreement no. RI-261600. GB was supported in part by NSF grant MCB1330728 from the National Science Foundation and Grant PO1GM55876-14A1 from the National Institutes of Health. LD received funding from EU FP7 (PIOF-GA-2012-329534). LD, and MLK used the computational resources of Temple University, supported by the National Science Foundation through major research instrumentation grant number CNS-09-58854. JS acknowledges support from the Instituto de Salud Carlos III FEDER (CP12/03139

C-edge loops of arrestin function as a membrane anchor

G-protein-coupled receptors are membrane proteins that are regulated by a small family of arrestin proteins. During formation of the arrestin–receptor complex, arrestin first interacts with the phosphorylated receptor C terminus in a pre-complex, which activates arrestin for tight receptor binding. Currently, little is known about the structure of the pre-complex and its transition to a high-affinity complex. Here we present molecular dynamics simulations and site-directed fluorescence experiments on arrestin-1 interactions with rhodopsin, showing that loops within the C-edge of arrestin function as a membrane anchor. Activation of arrestin by receptor-attached phosphates is necessary for C-edge engagement of the membrane, and we show that these interactions are distinct in the pre-complex and high-affinity complex in regard to their conformation and orientation. Our results expand current knowledge of C-edge structure and further illuminate the conformational transitions that occur in arrestin along the pathway to tight receptor binding.This work was supported by grants from the Deutsche Forschungsgemeinschaft (SO1037/1-2 to M.E.S.), the Berlin Institute of Health (Delbrück Fellowship BIH_PRO_314 to M.E.S.) and the Instituto de Salud Carlos III, El Fondo Europeo de Desarrollo Regional (FEDER) (CP12/03139 and PI15/00460 to J.S.). M.E.S. and J.S. participate in the European COST Action CM1207 (GLISTEN)

Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity

Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models