Molecules targeting a novel homotrimer cavity of Spike protein attenuate replication of SARS-CoV-2.

The SARS-CoV-2 Spike glycoprotein (S) utilizes a unique trimeric conformation to interact with the ACE2 receptor on host cells, making it a prime target for inhibitors that block viral entry. We have previously identified a novel proteinaceous cavity within the Spike protein homotrimer that could serve as a binding site for small molecules. However, it is not known whether these molecules would inhibit, stimulate, or have no effect on viral replication. To address this, we employed structural-based screening to identify small molecules that dock into the trimer cavity and assessed their impact on viral replication. Our findings show that a cohort of identified small molecules binding to the Spike trimer cavity effectively reduces the replication of various SARS-CoV-2 variants. These molecules exhibited inhibitory effects on B.1 (European original, D614G, EDB2) and B.1.617.2 (δ) variants, while showing moderate activity against the B.1.1.7 (α) variant. We further categorized these molecules into distinct groups based on their structural similarities. Our experiments demonstrated a dose-dependent viral replication inhibitory activity of these compounds, with some, like BCC0040453 exhibiting no adverse effects on cell viability even at high concentrations. Further investigation revealed that pre-incubating virions with compounds like BCC0031216 at different temperatures significantly inhibited viral replication, suggesting their specificity towards the S protein. Overall, our study highlights the inhibitory impact of a diverse set of chemical molecules on the biological activity of the Spike protein. These findings provide valuable insights into the role of the trimer cavity in the viral replication cycle and aid drug discovery programs aimed at targeting the coronavirus family.

Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking.

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

Identification of a broad-spectrum high-affinity peptide ligand for the purification of spike proteins.

Since the outbreak of coronavirus disease 2019, the global demand for vaccines has increased rapidly to prevent infection and protect high-risk populations. However, identifying viral mutations poses an additional challenge for chromatographic purification of vaccines and subunit vaccines. In this study, a new affinity peptide model, X1VX2GLNX3WX4RYSK, was established, and a library of 612 peptides was generated for ligand screening. Based on a multistep strategy of ligand screening, 18 candidate peptides were obtained. The top ranking peptide, LP14 (YVYGLNIWLRYSK), and two other representative peptides, LP02 and LP06, with lower rankings were compared via molecular dynamics simulation. The results revealed that peptide binding to the receptor binding domain (RBD) was driven by hydrophobic interactions and the key residues involved in the binding were identified. Surface plasmon resonance analysis further confirmed that LP14 had the highest affinity for the wild RBD (Kd=0.520 µmol/L), and viral mutation had little influence on the affinity of LP14, demonstrating its great potential as a broad-spectrum ligand for RBD purification. Finally, chromatographic performance of LP14-coupled gel-packed column verified that both wild and omicron RBDs could be purified and were eluted by 0.1 mol/L Gly-HCl buffer (pH 3.0). This research identified a broad-spectrum peptide for RBD purification based on rational design and demonstrated its potential application in the purification of RBDs from complex feedstock.

NMR characterization and ligand binding site of the stem-loop 2 motif from the Delta variant of SARS-CoV-2.

The stem-loop 2 motif (s2m) in SARS-CoV-2 (SCoV-2) is located in the 3'-UTR. Although s2m has been reported to display characteristics of a mobile genomic element that might lead to an evolutionary advantage, its function has remained unknown. The secondary structure of the original SCoV-2 RNA sequence (Wuhan-Hu-1) was determined by NMR in late 2020, delineating the base-pairing pattern and revealing substantial differences in secondary structure compared to SARS-CoV-1 (SCoV-1). The existence of a single G29742-A29756 mismatch in the upper stem of s2m leads to its destabilization and impedes a complete NMR analysis. With Delta, a variant of concern has evolved with one mutation compared to the original sequence that replaces G29742 by U29742. We show here that this mutation results in a more defined structure at ambient temperature accompanied by a rise in melting temperature. Consequently, we were able to identify >90% of the relevant NMR resonances using a combination of selective RNA labeling and filtered 2D NOESY as well as 4D NMR experiments. We present a comprehensive NMR analysis of the secondary structure, (sub)nanosecond dynamics, and ribose conformation of s2m Delta based on heteronuclear 13C NOE and T 1 measurements and ribose carbon chemical shift-derived canonical coordinates. We further show that the G29742U mutation in Delta has no influence on the druggability of s2m compared to the Wuhan-Hu-1 sequence. With the assignment at hand, we identify the flexible regions of s2m as the primary site for small molecule binding.

FRAGSITE2: A structure and fragment-based approach for virtual ligand screening.

Protein function annotation and drug discovery often involve finding small molecule binders. In the early stages of drug discovery, virtual ligand screening (VLS) is frequently applied to identify possible hits before experimental testing. While our recent ligand homology modeling (LHM)-machine learning VLS method FRAGSITE outperformed approaches that combined traditional docking to generate protein-ligand poses and deep learning scoring functions to rank ligands, a more robust approach that could identify a more diverse set of binding ligands is needed. Here, we describe FRAGSITE2 that shows significant improvement on protein targets lacking known small molecule binders and no confident LHM identified template ligands when benchmarked on two commonly used VLS datasets: For both the DUD-E set and DEKOIS2.0 set and ligands having a Tanimoto coefficient (TC) < 0.7 to the template ligands, the 1% enrichment factor (EF1% ) of FRAGSITE2 is significantly better than those for FINDSITEcomb2.0 , an earlier LHM algorithm. For the DUD-E set, FRAGSITE2 also shows better ROC enrichment factor and AUPR (area under the precision-recall curve) than the deep learning DenseFS scoring function. Comparison with the RF-score-VS on the 76 target subset of DEKOIS2.0 and a TC < 0.99 to training DUD-E ligands, FRAGSITE2 has double the EF1% . Its boosted tree regression method provides for more robust performance than a deep learning multiple layer perceptron method. When compared with the pretrained language model for protein target features, FRAGSITE2 also shows much better performance. Thus, FRAGSITE2 is a promising approach that can discover novel hits for protein targets. FRAGSITE2's web service is freely available to academic users at http://sites.gatech.edu/cssb/FRAGSITE2.

High-Efficiency Transformation and Expression of Genomic Libraries in Yeast.

Saccharomyces cerevisiae is a powerful system for the expression of genome-wide or combinatorial libraries for diverse types of screening. However, expressing large libraries in yeast requires high-efficiency transformation and controlled expression. Transformation of yeast using electroporation methods is more efficient than chemical methods; however, protocols described for electroporation require large amounts of linearized plasmid DNA and often yield approximately 106 cfu/µg of plasmid DNA. We optimized the electroporation of yeast cells for the expression of whole-genome libraries to yield up to 108 cfu/µg plasmid DNA. The protocol generates sufficient transformants for 10-100× coverage of diverse genome libraries with small amounts of genomic libraries (0.1 µg of DNA per reaction) and provides guidance on calculations to estimate library size coverage and transformation efficiency. It describes the preparation of electrocompetent yeast cells with lithium acetate and dithiothreitol conditioning step and the transformation of cells by electroporation with carrier DNA. We validated the protocol using three yeast surface display libraries and demonstrated using nanopore sequencing that libraries' size and diversity are preserved. Moreover, expression analysis confirmed library functionality and the method's efficacy. Hence, this protocol yields a sufficient representation of the genome of interest for downstream screening purposes while limiting the amount of the genomic library required.

Multivalent calix[4]arene-based mannosylated dendrons as new FimH ligands and inhibitors.

We report the synthesis and biological characterization of a novel class of multivalent glycoconjugates as hit compounds for the design of new antiadhesive therapies against urogenital tract infections (UTIs) caused by uropathogenic E. coli strains (UPEC). The first step of UTIs is the molecular recognition of high mannose N-glycan expressed on the surface of urothelial cells by the bacterial lectin FimH, allowing the pathogen adhesion required for mammalian cell invasion. The inhibition of FimH-mediated interactions is thus a validated strategy for the treatment of UTIs. To this purpose, we designed and synthesized d-mannose multivalent dendrons supported on a calixarene core introducing a significant structural change from a previously described family of dendrimers bearing the same dendrons units on a flexible pentaerythritol scaffold core. The new molecular architecture increased the inhibitory potency against FimH-mediated adhesion processes by about 16 times, as assessed by yeast agglutination assay. Moreover, the direct molecular interaction of the new compounds with FimH protein was assessed by on-cell NMR experiments acquired in the presence of UPEC cells.

Inhibition of Neutral Sphingomyelinase 2 by Novel Small Molecule Inhibitors Results in Decreased Release of Extracellular Vesicles by Vascular Smooth Muscle Cells and Attenuated Calcification.

Vascular calcification (VC) is an important contributor and prognostic factor in the pathogenesis of cardiovascular diseases. VC is an active process mediated by the release of extracellular vesicles by vascular smooth muscle cells (VSMCs), and the enzyme neutral sphingomyelinase 2 (nSMase2 or SMPD3) plays a key role. Upon activation, the enzyme catalyzes the hydrolysis of sphingomyelin, thereby generating ceramide and phosphocholine. This conversion mediates the release of exosomes, a type of extracellular vesicles (EVs), which ultimately forms the nidus for VC. nSMase2 therefore represents a drug target, the inhibition of which is thought to prevent or halt VC progression. In search of novel druglike small molecule inhibitors of nSMase2, we have used virtual ligand screening to identify potential ligands. From an in-silico collection of 48,6844 small druglike molecules, we selected 996 compounds after application of an in-house multi-step procedure combining different filtering and docking procedures. Selected compounds were functionally tested in vitro; from this, we identified 52 individual hit molecules that inhibited nSMase2 activity by more than 20% at a concentration of 150 µM. Further analysis showed that five compounds presented with IC50s lower than 2 µM. Of these, compounds ID 5728450 and ID 4011505 decreased human primary VSMC EV release and calcification in vitro. The hit molecules identified here represent new classes of nSMase2 inhibitors that may be developed into lead molecules for the therapeutic or prophylactic treatment of VC.

Structure-based discovery of a novel small-molecule inhibitor of TEAD palmitoylation with anticancer activity.

The paralogous oncogenic transcriptional coactivators YAP and TAZ are the distal effectors of the Hippo signaling pathway, which plays a critical role in cell proliferation, survival and cell fate specification. They are frequently deregulated in most human cancers, where they contribute to multiple aspects of tumorigenesis including growth, metabolism, metastasis and chemo/immunotherapy resistance. Thus, they provide a critical point for therapeutic intervention. However, due to their intrinsically disordered structure, they are challenging to target directly. Since YAP/TAZ exerts oncogenic activity by associating with the TEAD1-4 transcription factors, to regulate target gene expression, YAP activity can be controlled indirectly by regulating TEAD1-4. Interestingly, TEADs undergo autopalmitoylation, which is essential for their stability and function, and small-molecule inhibitors that prevent this posttranslational modification can render them unstable. In this article we report discovery of a novel small molecule inhibitor of YAP activity. We combined structure-based virtual ligand screening with biochemical and cell biological studies and identified JM7, which inhibits YAP transcriptional reporter activity with an IC50 of 972 nMoles/Ltr. Further, it inhibits YAP target gene expression, without affecting YAP/TEAD localization. Mechanistically, JM7 inhibits TEAD palmitoylation and renders them unstable. Cellular thermal shift assay revealed that JM7 directly binds to TEAD1-4 in cells. Consistent with the inhibitory effect of JM7 on YAP activity, it significantly impairs proliferation, colony-formation and migration of mesothelioma (NCI-H226), breast (MDA-MB-231) and ovarian (OVCAR-8) cancer cells that exhibit increased YAP activity. Collectively, these results establish JM7 as a novel lead compound for development of more potent inhibitors of TEAD palmitoylation for treating cancer.

Phytochemical Profile, In Vitro Bioactivity Evaluation, In Silico Molecular Docking and ADMET Study of Essential Oils of Three Vitex Species Grown in Tarai Region of Uttarakhand.

A comparative study of volatiles, antioxidant activity, phytotoxic activity, as well as in silico molecular docking and ADMET study, was conducted for essential oils from three Vitex species, viz., V. agnus-castus, V. negundo, and V. trifolia. Essential oils (OEs) extracted by hydrodistillation were subjected to compositional analysis using GC-MS. A total number of 37, 45, and 43 components were identified in V. agnus-castus, V. negundo, and V. trifolia, respectively. The antioxidant activity of EOs, assessed using different radical-scavenging (DPPH, H2O2 and NO), reducing power, and metal chelating assays, were found to be significant as compared with those of the standards. The phytotoxic potential of the EOs was performed in the receptor species Raphanusraphanistrum (wild radish) and the EOs showed different levels of intensity of seed germination inhibition and root and shoot length inhibition. The molecular docking study was conducted to screen the antioxidant and phytotoxic activity of the major and potent compounds against human protein target, peroxiredoxin 5, and 4-hydroxyphenylpyruvate dioxygenase protein (HPPD). Results showed good binding affinities and attributed the strongest inhibitory activity to 13-epi-manoyl oxide for both the target proteins.

Identification of antiparasitic drug targets using a multi-omics workflow in the acanthocephalan model.

BACKGROUND: With the expansion of animal production, parasitic helminths are gaining increasing economic importance. However, application of several established deworming agents can harm treated hosts and environment due to their low specificity. Furthermore, the number of parasite strains showing resistance is growing, while hardly any new anthelminthics are being developed. Here, we present a bioinformatics workflow designed to reduce the time and cost in the development of new strategies against parasites. The workflow includes quantitative transcriptomics and proteomics, 3D structure modeling, binding site prediction, and virtual ligand screening. Its use is demonstrated for Acanthocephala (thorny-headed worms) which are an emerging pest in fish aquaculture. We included three acanthocephalans (Pomphorhynchus laevis, Neoechinorhynchus agilis, Neoechinorhynchus buttnerae) from four fish species (common barbel, European eel, thinlip mullet, tambaqui). RESULTS: The workflow led to eleven highly specific candidate targets in acanthocephalans. The candidate targets showed constant and elevated transcript abundances across definitive and accidental hosts, suggestive of constitutive expression and functional importance. Hence, the impairment of the corresponding proteins should enable specific and effective killing of acanthocephalans. Candidate targets were also highly abundant in the acanthocephalan body wall, through which these gutless parasites take up nutrients. Thus, the candidate targets are likely to be accessible to compounds that are orally administered to fish. Virtual ligand screening led to ten compounds, of which five appeared to be especially promising according to ADMET, GHS, and RO5 criteria: tadalafil, pranazepide, piketoprofen, heliomycin, and the nematicide derquantel. CONCLUSIONS: The combination of genomics, transcriptomics, and proteomics led to a broadly applicable procedure for the cost- and time-saving identification of candidate target proteins in parasites. The ligands predicted to bind can now be further evaluated for their suitability in the control of acanthocephalans. The workflow has been deposited at the Galaxy workflow server under the URL tinyurl.com/yx72rda7 .

In situ crystal data-collection and ligand-screening system at SPring-8.

In situ diffraction data collection using crystallization plates has been utilized for macromolecules to evaluate crystal quality without requiring additional sample treatment such as cryocooling. Although it is difficult to collect complete data sets using this technique due to the mechanical limitation of crystal rotation, recent advances in methods for data collection from multiple crystals have overcome this issue. At SPring-8, an in situ diffraction measurement system was constructed consisting of a goniometer for a plate, an articulated robot and plate storage. Using this system, complete data sets were obtained utilizing the small-wedge measurement method. Combining this system with an acoustic liquid handler to prepare protein-ligand complex crystals by applying fragment compounds to trypsin crystals for in situ soaking, binding was confirmed for seven out of eight compounds. These results show that the system functioned properly to collect complete data for structural analysis and to expand the capability for ligand screening in combination with a liquid dispenser.

The ß-lactam ticarcillin is a Staphylococcus aureus UDP-N-acetylglucosamine 2-epimerase binder.

Infectious diseases account for 25% of the causes of death worldwide and this rate is expected to increase due to antibiotic resistance. Among the bacteria associated with healthcare infections, Staphylococcus aureus is a prevalent pathogen and about 50% of the isolates are found to be methicillin-resistant. Here we describe the identification of ticarcillin as a weak binder of the S. aureus UDP-N-acetylglucosamine 2-epimerase. After a docking screening, ticarcillin was identified as a ligand in using the recently proposed isothermal analysis of differential scanning fluorimetry data. Finally, an equilibrium MD simulation confirmed the docking binding mode as a stable pose, with large contributions to the binding energy coming from interactions between Arg206 and Arg207 and the carboxylate groups in ticarcillin.

Structural Characterization of KOR Inactive and Active States for 3D Pharmacology and Drug Discovery.

The structure of the human kappa opioid receptor (KOR) in complex with the long-acting antagonist JDTic was solved crystallographically in 2012 and, along with structures of other opioid receptors, revolutionized our understanding of opioid system function and pharmacology. More recently, active state KOR structure was also determined, giving important insights into activation mechanisms of the receptor. In this review, we will discuss how the understanding of atomistic structures of KOR established a key platform for deciphering details of subtype and functional selectivity of KOR-targeting ligands and for discovery of new chemical probes with potentially beneficial pharmacological profiles.

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.

An automated platform for structural analysis of membrane proteins through serial crystallography.

Membrane proteins are central to many pathophysiological processes, yet remain very difficult to analyze structurally. Moreover, high-throughput structure-based drug discovery has not yet been exploited for membrane proteins because of lack of automation. Here, we present a facile and versatile platform for in meso membrane protein crystallization, enabling rapid atomic structure determination at both cryogenic and room temperatures. We apply this approach to human integral membrane proteins, which allowed us to identify different conformational states of intramembrane enzyme-product complexes and analyze by molecular dynamics simulations the structural dynamics of the ADIPOR2 integral membrane protein. Finally, we demonstrate an automated pipeline combining high-throughput microcrystal soaking, automated laser-based harvesting, and serial crystallography, enabling screening of small-molecule libraries with membrane protein crystals grown in meso. This approach brings needed automation to this important class of drug targets and enables high-throughput structure-based ligand discovery with membrane proteins.

eSPC: an online data-analysis platform for molecular biophysics.

All biological processes rely on the formation of protein-ligand, protein-peptide and protein-protein complexes. Studying the affinity, kinetics and thermodynamics of binding between these pairs is critical for understanding basic cellular mechanisms. Many different technologies have been designed for probing interactions between biomolecules, each based on measuring different signals (fluorescence, heat, thermophoresis, scattering and interference, among others). Evaluation of the data from binding experiments and their fitting is an essential step towards the quantification of binding affinities. Here, user-friendly online tools to analyze biophysical data from steady-state fluorescence spectroscopy, microscale thermophoresis and differential scanning fluorimetry experiments are presented. The modules of the data-analysis platform (https://spc.embl-hamburg.de/) contain classical thermodynamic models and clear user guidelines for the determination of equilibrium dissociation constants (Kd) and thermal unfolding parameters such as melting temperatures (Tm).

A simple and sensitive detection of the binding ligands by using the receptor aggregation and NMR spectroscopy: a test case of the maltose binding protein.

Protein-ligand interaction is one of the highlights of molecular recognition. The most popular application of this type of interaction is drug development which requires a high throughput screening of a ligand that binds to the target protein. Our goal was to find a binding ligand with a simple detection, and once this type of ligand was found, other methods could then be used to measure the detailed kinetic or thermodynamic parameters. We started with the idea that the ligand NMR signal would disappear if it was bound to the non-tumbling mass. In order to create the non-tumbling mass, we tried the aggregates of a target protein, which was fused to the elastin-like polypeptide. We chose the maltose binding proteinas a test case, and we tried it with several sugars, which included maltose, glucose, sucrose, lactose, galactose, maltotriose, and ß-cyclodextrin. The maltose signal in the H-1 NMR spectrum disappeared completely as hoped around the protein to ligand ratio of 1:3 at 298 K where the proteins aggregated. The protein signals also disappeared upon aggregation except for the fast-moving part, which resulted in a cleaner background than the monomeric form. Since we only needed to look for a disappearing signal amongst those from the mixture, it should be useful in high throughput screening. Other types of sugars except for the maltotriose and ß-cyclodextrin, which are siblings of the maltose, did not seem to bind at all. We believe that our system would be especially more effective when dealing with a smaller target protein, so both the protein and the bound ligand would lose their signals only when the aggregates formed. We hope that our proposed method would contribute to accelerating the development of the potent drug candidates by simultaneously identifying several binders directly from a mixture.

Insights into Dynamic Mechanism of Ligand Binding to Peroxisome Proliferator-Activated Receptor γ toward Potential Pharmacological Applications.

Peroxisome proliferator-activated receptor γ (PPARγ) is a member of the nuclear receptor superfamily, which regulates the transcription of a variety of genes involved in lipid and glucose metabolism, inflammation, and cell proliferation. These functions correlate with the onset of type-2 diabetes, obesity, and immune disorders, which makes PPARγ a promising target for drug development. The majority of PPARγ functions are regulated by binding of small molecule ligands, which cause conformational changes of PPARγ followed by coregulator recruitment. The ligand-binding domain (LBD) of PPARγ contains a large Y-shaped cavity that can be occupied by various classes of compounds such as full agonists, partial agonists, natural lipids, and in some cases, a combination of multiple molecules. Several crystal structure studies have revealed the binding modes of these compounds in the LBD and insight into the resulting conformational changes. Notably, the apo form of the PPARγ LBD contains a highly mobile region that can be stabilized by ligand binding. Furthermore, recent biophysical investigations have shed light on the dynamic mechanism of how ligands induce conformational changes in PPARγ and result in functional output. This information may be useful for the design of new and repurposed structures of ligands that serve a different function from original compounds and more potent pharmacological effects with less undesirable clinical outcomes. This review provides an overview of the peculiar characteristics of the PPARγ LBD by examining a series of structural studies focused on the dynamic mechanism of binding and the potential applications of strategies for ligand screening and chemical labeling.

Screening Methods for Cell-Free Synthesized GPCR/Nanoparticle Samples.

Cell-free protein expression systems and lipid nanoparticle technologies are core platforms for membrane protein synthesis. The implementation of preassembled nanodiscs allows the co-translational insertion of membrane proteins into tailored lipid bilayers in the absence of any artificial hydrophobic compounds. This strategy is particularly interesting for detergent sensitive or otherwise critical membrane proteins such as G-protein-coupled receptors (GPCRs). Cell-free expression reactions are completed within a day and the formed GPCR/nanodisc particles can be purified directly out of the reaction mixture by affinity tags and without any further manipulation. The streamlined procedure reduces risk of GPCR denaturation and the sample quality can further be supported by supplying chaperones or other beneficial compounds directly into the expression reactions.GPCRs inserted into nanoparticle membranes are excellent tools for a variety of applications such as ligand screening, engineering or even structural characterization. In this chapter, we provide protocols for the reaction set-up and efficient cell-free production of functionally folded GPCRs reaching µM concentrations in the final expression reactions. We further exemplify the tuning of GPCR sample quality and discuss their application for throughput ligand screening and for the analysis of ligand-binding characteristics.