Communications Chemistry

Developing novel drugs against membrane proteins is a major challenge in drug discovery due to the difficulty of stabilizing these targets for high-throughput screenings. Pannexin 1 (PANX1) is a membrane channel protein involved in various physiological and pathological processes, making it a promising target for drug discovery. However, efforts to develop PANX1-targeting therapeutics have been hindered by the inherent challenges of stabilizing the protein channel and conducting effective pharmacological screening. Here, we report a proof-of-concept workflow that integrates the Salipro lipid nanoparticle platform with DNA-Encoded Library screenings in a detergent-free format. In this case study, the Salipro DirectMX method was used to generate functional PANX1 nanoparticles for drug discovery and characterisation. Using a high-stringency selection strategy and computational approaches, we identified a specific set of candidate compounds with selective PANX1 enrichment. Surface Plasmon Resonance analysis confirmed the identification of hit compounds. Cryo-Electron Microscopy of the Salipro-PANX1-Compound complex provided structural insights into a potential compound binding site. Electrophysiological recordings in PANX1-expressing Xenopus laevis oocytes demonstrated dose-dependent inhibition of PANX1-mediated ion conductance by the compounds. These findings establish a robust workflow for ligand discovery against challenging membrane protein targets and provide novel chemical starting points for the development of PANX1 modulators.

G protein-gated inwardly rectifying potassium (GIRK) channels are key regulators of neuronal excitability, making them promising therapeutic targets for central nervous system disorders. Their activation depends on phosphatidylinositol-4,5-bisphosphate (PIP2), which stabilizes the channels open state. A deeper understanding of GIRK-PIP2 interactions could uncover new physiological roles and pave the way for therapies that modulate channel function. This study aimed to advance the targeting of GIRK channels at the PIP2-binding site. Over one million compounds were screened against GIRK2 (PDB ID: 4KFM) using high-throughput virtual screening. A core constraint with a root-mean-square deviation (RMSD) < 2 [A] was applied to assure the accuracy and binding close to PIP2-binding site. The top-scoring ligands were redocked with Glide (SP, XP) and binding free energy was estimated using Molecular Mechanics Generalized Born Surface Area method. The most promising compounds were analyzed for pharmacokinetic/physicochemical properties, followed by molecular dynamics (MD) simulations over 200 ns in membrane bilayer. MD analysis revealed three known compounds (Rosuvastatin, CID: 54365126 and 7304563) as potential competitive GIRK2 modulators, exhibiting stable interactions with residues critical for binding endogenous activators (PIP2, cholesterol), and GIRK-acting drugs. Docking analyses also revealed strong binding to GIRK2 for various metabolites, including leukotrienes, resolvins, acyl-CoAs, and polyphosphates, including adenosine-triphosphate (ATP) and thiamine-triphosphate. Notably, some of the identified compounds can affect similar ion channels, indicating potential cross-reactivity with GIRK2. Furthermore, the binding modes of acyl-CoAs and polyphosphates closely resemble PIP2s hydrophobic and phosphate group engagement. Together, these findings offer promising candidates for experimental validation and therapeutic development. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/653795v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1325e66org.highwire.dtl.DTLVardef@1d3835corg.highwire.dtl.DTLVardef@1550df3org.highwire.dtl.DTLVardef@107007e_HPS_FORMAT_FIGEXP M_FIG C_FIG Abbreviations: ADMET - Absorption, Distribution, Metabolism, Elimination, Toxicity; CID - PubChem Compound Identification; MM-GBSA - Molecular Mechanics with Generalized Born and Surface Area solvation; RMSD - Root-Mean-Square Deviation; SP - Standard Precision; PIP2 - phosphatidylinositol-4,5-bisphosphate; XP - Extra Precision. HIGHLIGHTSO_LIMulti-target screening identifies selective modulators of the GIRK2 channel C_LIO_LILigands target the PIP2-binding site, a novel interface for GIRK2 modulation C_LIO_LIMM-GBSA confirms binding affinity and ligand stability post-docking C_LIO_LIDynamics and bioinformatics predict selectivity and off-target interactions C_LIO_LIStatins and leukotriene-modifying drugs are strong GIRK2 modulator candidates C_LI

Natural products are important sources for drug development, and the precise prediction of their structures assembled by modular proteins is an area of great interest. In this study, we introduce DeepT2, an end-to-end, cost-effective, and accurate machine learning platform to accelerate the identification of type II polyketides (T2PKs), which represent a significant portion of the natural product world. Our algorithm is based on advanced natural language processing models and utilizes the core biosynthetic enzyme, chain length factor (CLF or KS{beta}), as computing inputs. The process involves sequence embedding, data labeling, classifier development, and novelty detection, which enable precise classification and prediction directly from KS{beta} without sequence alignments. Combined with metagenomics and metabolomics, we evaluated the ability of DeepT2 and found this model could easily detect and classify KS{beta} either as a single sequence or a mixture of bacterial genomes, and subsequently identify the corresponding T2PKs in a labeled categorized class or as novel. Our work highlights deep learning as a promising framework for genome mining and therefore provides a meaningful platform for discovering medically important natural products.

Droplet interface bilayers (DIBs) provide a controlled lipid environment for the single-molecule investigation of a range of biologically relevant membrane-bound processes and have garnered attention for their potential applications in bottom-up artificial cells, biosensing, and biophysics. However, the fabrication of DIBs is currently hindered by time-consuming processes and specialized equipment. These fabrication limitations prevent the scale-up of DIB assays, making it difficult to generate the large data sets required to achieve statistically significant conclusions in single-molecule biological assays where heterogeneous behaviour is often observed. This research describes an open-source solution, dubbed "DIB-BOT," constructed by coupling a nanoinjector with an entry-level 3D printer. We present DIB-BOT as a platform to achieve rapid, reproducible, and reliable fabrication of large numbers of DIBs, addressing the limitations of manual methods. Leveraging commercially available off-the-shelf components, DIB-BOT exhibits high spatial reproducibility, minimal user input, and the ability to scale experiments rapidly. Here we demonstrate the utility of the system by integrating pairwise droplet assembly with a fluorescence plate-reader to execute a biologically relevant assay. When compared with manual DIB fabrication, the DIB-BOT had a tenfold reduction in droplet volume error, a threefold reduction in positional error, and 100% droplet yield. Overall, this method has potential to reduce entry barriers to the use of DIB methods, broadening the applications of DIB research, and generating higher quality data sets.

Understanding the mechanism of action (MoA) of bioactive compounds is a central challenge in drug discovery and chemical biology. In this article, we propose a strategy for integrating morphological data with proteomics to provide deeper insights into the MoA of compounds. We combine the rich phenotypic profiles of Cell Painting (CP) with the unbiased protein target detection of Thermal Proteome Profiling (TPP), and construct protein-protein interaction networks based on potential targets identified using both assays. We evaluate our method on public TPP data sets for the five compounds (+)-JQ1, I-BET151, Vemurafenib, Crizotinib and Panobinostat, together with Cell Painting data for 5270 drugs on U2OS cells. We show that the combined approach could accurately identify known MoAs for four out of five compounds. This work highlights the value of multimodal profiling for chemical biology and opens new avenues for data-driven discovery of therapeutic mechanisms.

Protein phase separation has become a widely studied phenomena in biology with implications in cell metabolism and disease. The study of phase separating proteins often relies on the precise determination of their phase diagrams. These phase diagrams give information on the protein concentration required for condensate formation and the respective concentration inside the condensate at defined external conditions (temperature, salt, pH). However, it has so far often proven difficult to accurately measure phase diagrams. Here, we report a method that is based on mass and volume conservation and defined reaction volumes, which we call inPhase. We can use this method to determine accurate values for both dilute and condensed branch protein concentrations. With this information we can produce accurate phase diagrams. We compare our method to the widely used quantitative fluorescence approach and find that it underestimates the partition factor into condensates at least two-fold for FUS and PGL-3. The accessibility of our method opens the possibility for the thermodynamic assessment of entire protein families, generating sufficient quantitative data for testing theory, and for the screening of drugs in pharmaceutical research.

The Src homology-2 domain containing phosphatase SHP2 is a critical regulator of signal transduction, being implicated in cell growth and differentiation. Activating mutations cause developmental disorders and act as oncogenic drivers in hematologic cancers. SHP2 is activated by phosphopeptide binding to the N-SH2 domain, triggering the release of N-SH2 from the catalytic PTP domain. Based on early crystallographic data, it has been widely accepted that opening of the binding cleft of N-SH2 serves as the key "allosteric switch" driving SHP2 activation. To test the putative coupling between binding cleft opening and SHP2 activation as assumed by the "allosteric switch" model, we critically reviewed structural data of SHP2 and we used extensive molecular dynamics (MD) simulation and free energy calculations of isolated N-SH2 in solution, SHP2 in solution, and SHP2 in a crystal environment. Our results demonstrate that the binding cleft in N-SH2 is constitutively flexible and open in solution, and that a closed cleft found in certain structures is a consequence of crystal contacts. The degree of opening of the binding cleft has only a negligible effect on the free energy of SHP2 activation. Instead, SHP2 activation is greatly favored by the opening of the central {beta}- sheet of N-SH2. We conclude that opening of the N-SH2 binding cleft is not the key allosteric switch triggering SHP2 activation. Significance StatementSHP2 is a multi-domain protein, playing an important role in up-regulating cellular processes such as cell survival, proliferation, and programmed cell death. SHP2 mutations cause developmental disorders and were found in many cancer types, including neuroblastoma, breast cancer, and leukemia. In healthy cells, SHP2 mainly takes an autoinhibited, inactive form, and SHP2 is activated upon binding of phosphopeptides to the N-SH2 domain. For the past two decades, the widening of the binding cleft upon peptide binding has been considered as the key event driving SHP2 activation. Here, by analyzing crystallographic data and molecular simulations, we demonstrate that the binding cleft in N-SH2 is, instead, already open and accessible in solution, and its degree of opening does not influence SHP2 activation.

Yeast expression of human G Protein Coupled Receptors (GPCRs) can be used as a biosensor platform for the detection of pharmaceuticals. The Cannabinoid receptors type 1 and 2 (CB1/2R) are of particular interest, given the cornucopia of natural and synthetic cannabinoids being explored as therapeutics. We show for the first time that engineering the N-terminus of CB1R allows for efficient signal transduction in yeast, and that engineering the sterol composition of the yeast membrane optimizes CB2R performance. Using the dual cannabinoid biosensors, large libraries of synthetic cannabinoids and terpenes could be quickly screened to elucidate known and novel structure-activity relationships, including compounds and trends that more selectively target each of the two receptors. The biosensor strains offer a ready platform for evaluating the activity of new synthetic cannabinoids, monitoring drugs of abuse, and developing molecules that target the therapeutically important CB2R receptor while minimizing psychoactive effects.

Recent advancements in genomics and proteomics have identified numerous clinically significant protein targets, with notably 85% categorized as undruggable. These targets present widespread challenges due to their complex structures and dynamics, rendering conventional drug design strategies not always effective. In this study, we introduce Uni-Clip, a contrastive learning framework that incorporates multi-modal features of proteins (structure and residue) and ligands (conformation and graph). Optimized with a specifically designed CF-InfoNCE loss, Uni-Clip enhances the modeling of protein-ligand interactions for both undruggable and druggable proteins. Uni-Clip demonstrates superior performance in benchmark evaluations on widely acknowledged datasets, LIT-PCBA and DUD-E, achieving a 147% and 218% improvements in enrichment factors at 1% compared to baselines. Furthermore, Uni-Clip proves to be a practical tool for various drug discovery applications. In virtual screening for the challenging protein target GPX4 with flat surface, it identified non-covalent inhibitors with an IC50 of 4.17 M, in contrast to the predominantly covalent inhibitors currently known. Through target fishing for benzbromarone, Uni-Clip identified the intrinsically disordered protein c-Myc as a potential target, highlighting benzbromarones potential for repurposing in cancer therapy. Explainable analyses effectively identified binding sites consistent with molecular dynamics and experimental results, even for challenging undruggable targets.

Biocompatible fluorosurfactants are essential for many droplet microfluidic workflows but are often obtained from commercial sources because published syntheses of perfluoropolyether (PFPE)-based surfactants typically require acid chloride intermediates and chemistry-oriented purification methods. These requirements can limit access for biology and clinical laboratories seeking low-cost or customizable surfactant systems. Here we describe a practical method for preparing functional PFPE-based fluorosurfactant materials by direct carbodiimide coupling of functionalized PFPE carboxylic acids(Krytox 157 FSH) to amine-containing head groups under laboratory-accessible conditions. Using this approach, we prepared a PFPE-polyethylene-glycol (PFPE-PEG) material from Jeffamine ED900 and a PFPE-Tris material from Tris base. Because these products were not fully structurally characterized, we present them as functional reaction products and evaluate them by use in biomicrofluidic workflows rather than by definitive compositional assignment. PFPE-Tris was useful for generating relatively uniform small droplets, whereas the PFPE-PEG preparation supported a broader range of biological applications. These materials were used in genomic library screening for {beta}-glucosidase activity, thermocycling-associated droplet workflows, and protein crystallization experiments. In addition, the PFPE-PEG preparation improved emulsion behavior in many protein crystallization screens that were unstable with a commercial droplet oil used in our laboratory. This method reduces the practical barrier to in-house fluorosurfactant preparation and allows biology-focused laboratories to explore head-group chemistry, oil composition, and operating conditions without complete reliance on commercial reagents. The results support this workflow as a useful entry point for biomicrofluidics laboratories, while also highlighting the need for careful interpretation of thermocycled droplet assays and for future analytical characterization of the resulting materials. Significance statementDroplet microfluidics relies on fluorosurfactants that are often costly and difficult to synthesize outside of chemistry-focused settings. We describe a simple, biology-laboratory-compatible approach for generating functional perfluoropolyether-based fluorosurfactant materials using direct carbodiimide coupling and straightforward cleanup. The resulting materials supported multiple biomicrofluidic workflows in our laboratory, including enzymatic screening and protein crystallization, and provide a practical route for groups seeking lower-cost and more customizable surfactant systems.

Liquid-liquid phase separation (LLPS) has recently emerged as a cornerstone mechanism underlying the biogenesis of membraneless organelles (MLOs). However, a quantitative molecular grammar of protein sequences that controls the LLPS remains poorly understood. The progress in this field is hampered by the insufficiency of comprehensive databases and associated computational infrastructure for targeting biophysical and statistical analysis of phase separating biopolymers. Therefore, we have created a novel open-source web platform named BIAPSS (BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences) which contains interactive data analytic tools in combination with a comprehensive repository of bioinformatic data for on-the-fly exploration of sequence-dependent properties of proteins with known LLPS behavior. BIAPSS includes a residue-resolution biophysical analyzer for interrogating individual protein sequences (SingleSEQ tab). The latter allows users to correlate regions prone to phase separation with a large array of physicochemical attributes and various short linear motifs. BIAPSS also includes global statistics derived over the universe of most of the known LLPS-driver protein sequences (MultiSEQ tab) for revealing the regularities and sequence-specific signals driving phase separation. Finally, BIAPSS incorporates an extensive cross-reference section that links all entries to primary LLPS databases and other external resources thereby serving as a central navigation hub for the phase separation community. All of the data used by BIAPSS is freely available for download as well-formatted pre-processed data with detailed descriptions, facilitating rapid implementation in user-defined computational protocols. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/430806v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1d90ddorg.highwire.dtl.DTLVardef@111d084org.highwire.dtl.DTLVardef@90b3b0org.highwire.dtl.DTLVardef@51d71_HPS_FORMAT_FIGEXP M_FIG TOC - graphical abstract C_FIG Author summaryProteins, especially those with low complexity and intrinsically disordered regions, have recently come into the limelight because of mounting evidence showing that these regions can drive the formation of membraneless organelles (MLOs) in cells. The underlying physical mechanism for forming MLOs is liquid-liquid phase separation (LLPS); a thermodynamically driven process whereby a cellular milieu with a relatively well-mixed distribution of biomolecules gets decomposed into liquid droplets where the concentration of selected biomolecules is higher. Deciphering molecular sequence grammar of phase separation has turned out to be challenging because of the complexity of this process in cells and the vastness of sequence space of LLPS-driver proteins. While the field is still in its infancy the growth of experimental data has already spurred the creation of several major databases which collect and annotate bimolecular systems with confirmed LLPS behavior. What is currently missing is a framework that would leverage the existing databases by integrating them with deep biophysical and bioinformatic analysis for identifying statistically significant features of protein sequences implicated in LLPS. In this work, we have addressed this challenge by creating an open-source web platform named BIAPSS (BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences) which integrates a comprehensive repository of pre-processed bioinformatic data for LLPS-driver protein sequences with interactive analytic applications for on-the-fly analysis of biophysical features relevant for LLPS behavior. BIAPSS empowers users with novel and effective tools for exploring LLPS-related sequence signals for individual proteins (SingleSEQ tab) and globally by integrating common regularities across subgroups or the entire LLPS sequence superset (MultiSEQ). The long-term plan for BIAPSS is to serve as a unifying hub for the experimental and computational community with a comprehensive set of analytic tools, biophysically featured data, and standardized protocols facilitating the identification of sequence hot spots driving the LLPS, which all can support applications for designing new sequences of biomedical interest.

Kinases are pivotal cell signaling regulators and prominent drug targets. Short peptide substrates are widely used in kinase activity assays essential for investigating kinase biology and drug discovery. However, designing substrates with high activity and specificity remains challenging. Here, we present Subtimizer (substrate optimizer), a streamlined computational pipeline for structure-guided kinase peptide substrate design using AlphaFold-Multimer for structure modeling, ProteinMPNN for sequence design, and AlphaFold2-based interface evaluation. Applied to five kinases, four showed substantially improved activity (up to 350%) with designed peptides. Kinetic analyses revealed >2-fold reductions in Michaelis constant (Km), indicating improved enzyme-substrate affinity. Two designed peptides exhibited >5-fold improvement in selectivity. This study demonstrates AI-driven structure-guided protein design as an effective approach for developing potent and selective kinase substrates, facilitating assay development for drug discovery and functional investigation of the kinome.

Endogenous phospholipids influence the conformational equilibria of G protein-coupled receptors, regulating their ability to bind drugs and form signaling complexes. However, most studies of GPCR-lipid interactions have been carried out in mixed micelles or lipid nanodiscs. Though useful, these membrane mimetics do not fully replicate the physical properties of native cellular membranes associated with large assemblies of lipids. We investigated the conformational equilibria of the human A2A adenosine receptor (A2AAR) in phospholipid vesicles using 19F solid-state magic angle spinning NMR (SSNMR). By applying an optimized sample preparation workflow and experimental conditions, we were able to obtain 19F-SSNMR spectra for both antagonist- and agonist-bound complexes with sensitivity and linewidths closely comparable to those achieved using solution NMR. This facilitated a direct comparison of the A2AAR conformational equilibria across detergent micelle, lipid nanodisc, and lipid vesicle preparations. While antagonist-bound A2AAR showed a similar conformational equilibria across all membrane and membrane mimetic systems, the conformational equilibria of agonist-bound A2AAR exhibited differences among different environments. This suggests that the conformational equilibria of GPCRs may be influenced not only by specific receptor-lipid interactions but also by the membrane properties found in larger lipid assemblies.

Modification-dependent and -independent biomolecular interactions (BIs), including protein-protein, protein-DNA/RNA and protein-lipid, play crucial roles in all cellular processes. Dysregulation of BIs or malfunction of the associated enzymes results in various diseases, thus they are attractive targets for therapies. High-throughput screening (HTS) can greatly facilitate the discovery of drugs for these targets. Here we describe a HTS drug discovery method, called compartmentalization of enhanced biomolecular interactions in test tubes (CEBIT). CEBIT uses selective recruitment of biomolecules into phase separated compartments harboring their cognate binding partners as readouts. CEBIT were tailored to detect various BIs and associated modifying enzymes. Using CEBIT-based HTS assays, we successfully identified known inhibitors of the p53/MDM2 interaction and of SUV39H1 from a compound library. CEBIT is simple and versatile, and is likely to become a powerful tool for drug discovery and basic biomedical research.

Protein binders that detect, activate, inhibit or otherwise modulate their targets are pivotal for biomedical applications. With the increasing accuracy and accessibility of de novo protein design, faster and cheaper experimental screening methods would democratize and accelerate the identification of high-affinity binders. Here we present Cell-Free Two-Hybrid (CF2H), a rapid and sensitive method for detecting high-affinity protein-protein interactions (PPI) that does not require cloning, protein purification nor high-end laboratory equipment. CF2H uses a dimerization-activated DNA binding domain (DBD) fused to prey and bait proteins to trigger transcription upon protein-protein interaction. We demonstrate that CF2H enables the detection of interactions between various types of target and binder proteins such as single-domain antibodies, DARPins and de novo designed binders. We benchmark CF2H as a screening platform by validating previously reported binders for Mdm2 and discover high-affinity binders targeting the checkpoint inhibitor PD-L1 in less than 24 hours. Finally, we show that CF2H can be used to characterize small-molecules modulators of PPI and detect protein biomarkers, opening the door for a new class of cell-free biosensors.

Calmodulin (CaM) is a eukaryotic multifunctional, calcium-modulated protein that regulates the activity of numerous effector proteins involved in a variety of physiological processes. Calmidazolium (CDZ) is a potent small molecule antagonist of CaM and one the most widely used inhibitors of CaM in cell biology. Here, we report the structural characterization of CaM:CDZ complexes using combined SAXS, X-ray crystallography, HDX-MS and NMR approaches. Our results provide molecular insights into the CDZ-induced dynamics and structural changes of CaM leading to its inhibition. CDZ-binding induces an open-to-closed conformational change of CaM and results in a strong stabilization of its structural elements associated with a reduction of protein dynamics over a large time range. These CDZ-triggered CaM changes mimic those induced by CaM-binding peptides derived from protein targets, despite their distant chemical nature. CaM residues in close contact with CDZ and involved in the stabilization of the CaM:CDZ complex have been identified. These results open the way to rationally design new CaM-selective drugs. Figure and text for the Table of Contents (ToC) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/474921v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@b0c76org.highwire.dtl.DTLVardef@15f462forg.highwire.dtl.DTLVardef@1f8e57forg.highwire.dtl.DTLVardef@1a33575_HPS_FORMAT_FIGEXP M_FIG C_FIG Calmidazolium is a potent and widely used inhibitor of calmodulin, a major mediator of calcium-signaling in eukaryotic cells. Structural characterization of calmidazolium-binding to calmodulin reveals that it triggers open-to-closed conformational changes similar to those induced by calmodulin-binding peptides derived from enzyme targets. These results open the way to rationally design new and more selective inhibitors of calmodulin.

The estimation of the biological sex of archeological remains is crucial information in bioarchaeology and forensic anthropology. In recent years, proteomics based on molecular sexual dimorphism have emerged as a preferred method, particularly because of its minimally-invasive approach to extracting amelogenin X and Y proteins from tooth enamel. However, there is an increasing demand to accelerate this process while facilitating the analysis of large archaeological assemblages. This study presents a novel high-throughput targeted paleoproteomics method for biological sex estimation using MALDI-CASI-FTICR mass spectrometry. This approach combines the strengths of existing methods, including ultra-high resolution, significantly reduced processing times, targeted analysis, and scalability to large archaeological sample sets. The method was initially validated on modern individuals with known sex and subsequently applied to 130 adult and juvenile individuals from medieval Great Moravia (present-day Czech Republic). Biological sex was successfully estimated for all but one of the individuals. The results not only provide a more efficient biological sex estimation but also help to resolve a few errors in sex assessment previously encountered with osteomorphological and tooth morphometric techniques. The implementation of this method significantly improves the accuracy and efficiency of biological sex estimation, offering a powerful tool for anthropological research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/706309v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1ede7e6org.highwire.dtl.DTLVardef@13d2f5org.highwire.dtl.DTLVardef@17ee44dorg.highwire.dtl.DTLVardef@1be9dd9_HPS_FORMAT_FIGEXP M_FIG C_FIG

DNA-encoded library (DEL) technology has become a powerful tool in modern drug discovery. Fully harnessing its potential requires the use of extensive computational methodologies, which are often available only through proprietary software. This restricts accessibility for small teams lacking robust informatics support, hindering the growth of the technology. Here, we present DELi, an open-source DEL informatics platform designed for library design, NGS decoding and calling, and enrichment analysis. DELi supports a simple and easy to understand configuration setup to present a straightforward user interface. To showcase its capabilities, we used DELi to design an in-house custom, benzimidazole-based DEL (UNC DEL006), and performed proof-of-concept selection experiments against Bromodomain-containing Protein 4 (BRD4). The DELi decoding and analysis modules identified top-performing compounds, leading to the off-DNA synthesis of UNC11951, which was confirmed as a nanomolar BRD4 binder via isothermal titration calorimetry (ITC) and differential scanning fluorimetry (DSF). These results demonstrate DELi as an effective tool for DEL design and analysis. Furthermore, its open-source nature will promote ongoing development and contributions from the DEL community to expand its applications and capabilities, making DEL technology more widely accessible. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/640184v3_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1d4ca88org.highwire.dtl.DTLVardef@13cb4feorg.highwire.dtl.DTLVardef@8ea7ecorg.highwire.dtl.DTLVardef@1b294fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

P2X7 receptors are important drug targets involved in pathologies ranging from psychiatric disorders to cancer. Being membrane embedded receptors, they are challenging for structural characterisation and at present we only have a small number of X-ray and cryoEM structures for P2X7 bound to antagonists. We demonstrate that Saturation Transfer Difference (STD) NMR on live mammalian cells (on-cell STD NMR) overexpressing P2X7 receptors allows further structural insight on the complexes of P2X7 with two potent negative allosteric modulators, namely AZ10606120 and JNJ-47465567, via the determination of the binding epitope mapping of the interactions e.g. the main region of contact between the ligand and the binding pocket. This approach, reported for the first time on membrane-embedded ion channels, in combination with molecular docking, allows us to propose the first NMR-validated 3D molecular models for two antagonists as bound to human P2X7 receptors, and to correlate the structural knowledge acquired with the pharmacology data. We highlight the transformative potential of this application to aid drug design efforts in a less resource-demanding fashion than X-ray crystallography and cryo-EM and we envisage on-cell STD NMR to fast become an asset for structure-activity-relationship studies helping knowledge-based development of efficient drugs targeting P2X7 and other ion channels/membrane-embedded proteins.

We report a novel formulation approach for development of a thermostable oral insulin tablet. Using freeze drying to form a heat stable tablet in a single-step process, we demonstrate hydroxypropyl beta cyclodextrin (HP-{beta}-CD) encapsulated lipophilic ion-pair complex of insulin using bile salt achieves intestinal absorption and sustained glucose levels. The tablets produced using this simple approach with only two excipients offer protection from enzymatic and stomach acid degradation and facilitate insulin uptake, without any need for specialized drug manufacturing or enteric coating. Insulin in this innovative formulation is thermotolerant, capable of maintaining stability even under heat stress at 30-40{degrees}C/65-75% RH. The convenient presentation of insulin as a thermostable oral tablet presents a low-cost scalable manufacturing method that simplifies the logistics of storage, transport, and distribution in any setting, including areas where cold storage maybe limited or unavailable. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/635377v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@16b4b64org.highwire.dtl.DTLVardef@122c11forg.highwire.dtl.DTLVardef@b50c0borg.highwire.dtl.DTLVardef@29bf28_HPS_FORMAT_FIGEXP M_FIG Our unique formulation approach protects insulin from stomach and temperature induced degradation, improves intestinal permeability providing a sustained release of insulin for glycemic control. The freeze dried tablet product format is easily scalable and flexible, increasing accessibility across all populations. C_FIG