Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples

In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. Here, we integrate two tools, LIANA and Tensor-cell2cell, which, when combined, can deploy multiple existing methods and resources to enable the robust and flexible identification of cell-cell communication programs across multiple samples. In this work, we show how the integration of our tools facilitates the choice of method to infer cell-cell communication and subsequently perform an unsupervised deconvolution to obtain and summarize biological insights. We explain how to perform the analysis step by step in both Python and R and provide online tutorials with detailed instructions available at https://ccc-protocols.readthedocs.io/. This workflow typically takes ∼1.5 h to complete from installation to downstream visualizations on a graphics processing unit-enabled computer for a dataset of ∼63,000 cells, 10 cell types, and 12 samples.

Spatial transcriptomics reveals prognosis-associated cellular heterogeneity in the papillary thyroid carcinoma microenvironment

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common malignant endocrine tumour, and its incidence and prevalence are increasing considerably. Cellular heterogeneity in the tumour microenvironment is important for PTC prognosis. Spatial transcriptomics is a powerful technique for cellular heterogeneity study.

METHODS

In conjunction with a clinical pathologist identification method, spatial transcriptomics was employed to characterise the spatial location and RNA profiles of PTC-associated cells within the tissue sections. The spatial RNA-clinical signature genes for each cell type were extracted and applied to outlining the distribution regions of specific cells on the entire section. The cellular heterogeneity of each cell type was further revealed by ContourPlot analysis, monocle analysis, trajectory analysis, ligand-receptor analysis and Gene Ontology enrichment analysis.

RESULTS

The spatial distribution region of tumour cells, typical and atypical follicular cells (FCs and AFCs) and immune cells were accurately and comprehensively identified in all five PTC tissue sections. AFCs were identified as a transitional state between FCs and tumour cells, exhibiting a higher resemblance to the latter. Three tumour foci were shared among all patients out of the 13 observed. Notably, tumour foci No. 2 displayed elevated expression levels of genes associated with lower relapse-free survival in PTC patients. We discovered key ligand-receptor interactions, including LAMB3-ITGA2, FN1-ITGA3 and FN1-SDC4, involved in the transition of PTC cells from FCs to AFCs and eventually to tumour cells. High expression of these patterns correlated with reduced relapse-free survival. In the tumour immune microenvironment, reduced interaction between myeloid-derived TGFB1 and TGFBR1 in tumour focus No. 2 contributed to tumourigenesis and increased heterogeneity. The spatial RNA-clinical analysis method developed here revealed prognosis-associated cellular heterogeneity in the PTC microenvironment.

CONCLUSIONS

The occurrence of tumour foci No. 2 and three enhanced ligand-receptor interactions in the AFC area/tumour foci reduced the relapse-free survival of PTC patients, potentially leading to improved prognostic strategies and targeted therapies for PTC patients.

Biological and mutational analyses of CXCR4-antagonist interactions and design of new antagonistic analogs

The chemokine receptor CXCR4 has become an attractive therapeutic target for HIV-1 infection, hematopoietic stem cell mobilization, and cancer metastasis. A wide variety of synthetic antagonists of CXCR4 have been developed and studied for a growing list of clinical applications. To compare the biological effects of different antagonists on CXCR4 functions and their common and/or distinctive molecular interactions with the receptor, we conducted head-to-head comparative cell-based biological and mutational analyses of the interactions with CXCR4 of eleven reported antagonists, including HC4319, DV3, DV1, DV1 dimer, V1, vMIP-II, CVX15, LY2510924, IT1t, AMD3100, and AMD11070 that were representative of different structural classes of D-peptides, L-peptide, natural chemokine, cyclic peptides, and small molecules. The results were rationalized by molecular modeling of CXCR4-antagonist interactions from which the common as well as different receptor binding sites of these antagonists were derived, revealing a number of important residues such as W94, D97, H113, D171, D262, and E288, mostly of negative charge. To further examine this finding, we designed and synthesized new antagonistic analogs by adding positively charged residues Arg to a D-peptide template to enhance the postulated charge-charge interactions. The newly designed analogs displayed significantly increased binding to CXCR4, which supports the notion that negatively charged residues of CXCR4 can engage in interactions with moieties of positive charge of the antagonistic ligands. The results from these mutational, modeling and new analog design studies shed new insight into the molecular mechanisms of different types of antagonists in recognizing CXCR4 and guide the development of new therapeutic agents.

Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions

As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.

Substance P analogs devoid of key residues fail to activate human mast cells via MRGPRX2

Mast cells play an important role in disease pathogenesis by secreting immunomodulatory molecules. Mast cells are primarily activated by the crosslinking of their high affinity IgE receptors (FcεRI) by antigen bound immunoglobulin (Ig)E antibody complexes. However, mast cells can also be activated by the mas related G protein-coupled receptor X2 (MRGPRX2), in response to a range of cationic secretagogues, such as substance P (SP), which is associated with pseudo-allergic reactions. We have previously reported that the in vitro activation of mouse mast cells by basic secretagogues is mediated by the mouse orthologue of the human MRGPRX2, MRGPRB2. To further elucidate the mechanism of MRGPRX2 activation, we studied the time-dependent internalization of MRGPRX2 by human mast cells (LAD2) upon stimulation with the neuropeptide SP. In addition, we performed computational studies to identify the intermolecular forces that facilitate ligand-MRGPRX2 interaction using SP. The computational predictions were tested experimentally by activating LAD2 with SP analogs, which were missing key amino acid residues. Our data suggest that mast cell activation by SP causes internalization of MRGPRX2 within 1 min of stimulation. Hydrogen bonds (h-bonds) and salt bridges govern the biding of SP to MRGPRX2. Arg1 and Lys3 in SP are key residues that are involved in both h-bonding and salt bridge formations with Glu164 and Asp184 of MRGPRX2, respectively. In accordance, SP analogs devoid of key residues (SP1 and SP2) failed to activate MRGPRX2 degranulation. However, both SP1 and SP2 caused a comparable release of chemokine CCL2. Further, SP analogs SP1, SP2 and SP4 did not activate tumor necrosis factor (TNF) production. We further show that SP1 and SP2 limit the activity of SP on mast cells. The results provide important mechanistic insight into the events that result in mast cell activation through MRGPRX2 and highlight the important physiochemical characteristics of a peptide ligand that facilitates ligand-MRGPRX2 interactions. The results are important in understanding activation through MRGPRX2, and the intermolecular forces that govern ligand-MRGPRX2 interaction. The elucidation of important physiochemical properties within a ligand that are needed for receptor interaction will aid in designing novel therapeutics and antagonists for MRGPRX2.

Receptor-ligand pair typing and prognostic risk model of response or resistance to immune checkpoint inhibitors in lung adenocarcinoma

Introduction

Currently, programmed cell death-1 (PD-1)-targeted treatment is ineffective for a sizable minority of patients, and drug resistance still cannot be overcome.

Methods

To explore the mechanisms of immunotherapy and identify new therapeutic opportunities in lung adenocarcinoma (LUAD), data from patients who did and did not respond to the anti-PD-1 treatment were evaluated using single-cell RNA sequencing, and bulk RNA sequencing were collected.

Results

We investigated the gene expression that respond or not respond to immunotherapy in diverse cell types and revealed transcriptional characteristics at the single-cell level. To ultimately explore the molecular response or resistance to anti-PD-1 therapy, cell-cell interactions were carried out to identify the different LRIs (ligand-receptor interactions) between untreated patients vs. no-responders, untreated patients vs. responders, and responders vs. non-responders. Next, two molecular subgroups were proposed based on 73 LRI genes, and subtype 1 had a poor survival status and was likely to be the immunosuppressive tumor subtype. Furthermore, based on the LASSO Cox regression analysis results, we found that TNFSF13, AXL, KLRK1, FAS, PROS1, and CDH1 can be distinct prognostic biomarkers, immune infiltration levels, and responses to immunotherapy in LUAD.

Discussion

Altogether, the effects of immunotherapy were connected to LRIs scores, indicating that potential medications targeting these LRIs could contribute to the clinical benefit of immunotherapy. Our integrative omics analysis revealed the mechanisms underlying the anti-PD-1 therapy response and offered abundant clues for potential strategies to improve precise diagnosis and immunotherapy.

PlantPhoneDB: A manually curated pan-plant database of ligand-receptor pairs infers cell-cell communication

Ligand-receptor pairs play important roles in cell-cell communication for multicellular organisms in response to environmental cues. Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) provides unprecedented opportunities to investigate cellular communication based on ligand-receptor expression. However, so far, no reliable ligand-receptor interaction database is available for plant species. In this study, we developed PlantPhoneDB (https://jasonxu.shinyapps.io/PlantPhoneDB/), a pan-plant database comprising a large number of high-confidence ligand-receptor pairs manually curated from seven resources. Also, we developed a PlantPhoneDB R package, which not only provided optional four scoring approaches that calculate interaction scores of ligand-receptor pairs between cell types but also provided visualization functions to present analysis results. At the PlantPhoneDB web interface, the processed datasets and results can be searched, browsed, and downloaded. To uncover novel cell-cell communication events in plants, we applied the PlantPhoneDB R package on GSE121619 dataset to infer significant cell-cell interactions of heat-shocked root cells in Arabidopsis thaliana. As a result, the PlantPhoneDB predicted the actively communicating AT1G28290-AT2G14890 ligand-receptor pair in atrichoblast-cortex cell pair in Arabidopsis thaliana. Importantly, the downstream target genes of this ligand-receptor pair were significantly enriched in the ribosome pathway, which facilitated plants adapting to environmental changes. In conclusion, PlantPhoneDB provided researchers with integrated resources to infer cell-cell communication from scRNA-seq datasets.

Dendrites use mechanosensitive channels to proofread ligand-mediated neurite extension during morphogenesis

Ligand-receptor interactions guide axon navigation and dendrite arborization. Mechanical forces also influence guidance choices. However, the nature of such mechanical stimulations, the mechanosensor identity, and how they interact with guidance receptors are unknown. Here, we demonstrate that mechanosensitive DEG/ENaC channels are required for dendritic arbor morphogenesis in Caenorhabditis elegans. Inhibition of DEG/ENaC channels causes reduced dendritic outgrowth and branching in vivo, a phenotype that is alleviated by overexpression of the mechanosensitive channels PEZO-1/Piezo or YVC1/TrpY1. DEG/ENaCs trigger local Ca²⁺ transients in growing dendritic filopodia via activation of L-type voltage-gated Ca²⁺ channels. Anchoring of filopodia by dendrite ligand-receptor complexes is required for the mechanical activation of DEG/ENaC channels. Therefore, mechanosensitive channels serve as a checkpoint for appropriate chemoaffinity by activating Ca²⁺ transients required for neurite growth.

Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens

Cancer immunotherapy targets the interplay between immune and cancer cells. In particular, interactions between cytotoxic T lymphocytes (CTLs) and cancer cells, such as PD-1 (PDCD1) binding PD-L1 (CD274), are crucial for cancer cell clearance. However, immune checkpoint inhibitors targeting these interactions are effective only in a subset of patients, requiring the identification of novel immunotherapy targets. Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening in either cancer or immune cells has been employed to discover regulators of immune cell function. However, CRISPR screens in a single cell type complicate the identification of essential intercellular interactions. Further, pooled screening is associated with high noise levels. Herein, we propose intercellular CRISPR screens, a computational approach for the analysis of genome-wide CRISPR screens in every interacting cell type for the discovery of intercellular interactions as immunotherapeutic targets. We used two publicly available genome-wide CRISPR screening datasets obtained while triple-negative breast cancer (TNBC) cells and CTLs were interacting. We analyzed 4825 interactions between 1391 ligands and receptors on TNBC cells and CTLs to evaluate their effects on CTL function. Intercellular CRISPR screens discovered targets of approved drugs, a few of which were not identifiable in single datasets. To evaluate the method's performance, we used data for cytokines and costimulatory molecules as they constitute the majority of immunotherapeutic targets. Combining both CRISPR datasets improved the recall of discovering these genes relative to using single CRISPR datasets over two-fold. Our results indicate that intercellular CRISPR screens can suggest novel immunotherapy targets that are not obtained through individual CRISPR screens. The pipeline can be extended to other cancer and immune cell types to discover important intercellular interactions as potential immunotherapeutic targets.

Ligand-receptor promiscuity enables cellular addressing

In multicellular organisms, secreted ligands selectively activate, or "address," specific target cell populations to control cell fate decision-making and other processes. Key cell-cell communication pathways use multiple promiscuously interacting ligands and receptors, provoking the question of how addressing specificity can emerge from molecular promiscuity. To investigate this issue, we developed a general mathematical modeling framework based on the bone morphogenetic protein (BMP) pathway architecture. We find that promiscuously interacting ligand-receptor systems allow a small number of ligands, acting in combinations, to address a larger number of individual cell types, defined by their receptor expression profiles. Promiscuous systems outperform seemingly more specific one-to-one signaling architectures in addressing capability. Combinatorial addressing extends to groups of cell types, is robust to receptor expression noise, grows more powerful with increases in the number of receptor variants, and is maximized by specific biochemical parameter relationships. Together, these results identify design principles governing cellular addressing by ligand combinations.

GPR35 in Intestinal Diseases: From Risk Gene to Function

Diet and gut microbial metabolites mediate host immune responses and are central to the maintenance of intestinal health. The metabolite-sensing G-protein coupled receptors (GPCRs) bind metabolites and trigger signals that are important for the host cell function, survival, proliferation and expansion. On the contrary, inadequate signaling of these metabolite-sensing GPCRs most likely participate to the development of diseases including inflammatory bowel diseases (IBD). In the intestine, metabolite-sensing GPCRs are highly expressed by epithelial cells and by specific subsets of immune cells. Such receptors provide an important link between immune system, gut microbiota and metabolic system. Member of these receptors, GPR35, a class A rhodopsin-like GPCR, has been shown to be activated by the metabolites tryptophan-derived kynurenic acid (KYNA), the chemokine CXCL17 and phospholipid derivate lysophosphatidic acid (LPA) species. There have been studies on GPR35 in the context of intestinal diseases since its identification as a risk gene for IBD. In this review, we discuss the pharmacology of GPR35 including its proposed endogenous and synthetic ligands as well as its antagonists. We elaborate on the risk variants of GPR35 implicated in gut-related diseases and the mechanisms by which GPR35 contribute to intestinal homeostasis.

Computational Analysis of the Crystal and Cryo-EM Structures of P-Loop Channels with Drugs

The superfamily of P-loop channels includes various potassium channels, voltage-gated sodium and calcium channels, transient receptor potential channels, and ionotropic glutamate receptors. Despite huge structural and functional diversity of the channels, their pore-forming domain has a conserved folding. In the past two decades, scores of atomic-scale structures of P-loop channels with medically important drugs in the inner pore have been published. High structural diversity of these complexes complicates the comparative analysis of these structures. Here we 3D-aligned structures of drug-bound P-loop channels, compared their geometric characteristics, and analyzed the energetics of ligand-channel interactions. In the superimposed structures drugs occupy most of the sterically available space in the inner pore and subunit/repeat interfaces. Cationic groups of some drugs occupy vacant binding sites of permeant ions in the inner pore and selectivity-filter region. Various electroneutral drugs, lipids, and detergent molecules are seen in the interfaces between subunits/repeats. In many structures the drugs strongly interact with lipid and detergent molecules, but physiological relevance of such interactions is unclear. Some eukaryotic sodium and calcium channels have state-dependent or drug-induced π-bulges in the inner helices, which would be difficult to predict. The drug-induced π-bulges may represent a novel mechanism of gating modulation.

Nanoscale FasL Organization on DNA Origami to Decipher Apoptosis Signal Activation in Cells

Cell signaling is initiated by characteristic protein patterns in the plasma membrane, but tools to decipher their molecular organization and activation are hitherto lacking. Among the well-known signaling pattern is the death inducing signaling complex with a predicted hexagonal receptor architecture. To probe this architecture, DNA origami-based nanoagents with nanometer precise arrangements of the death receptor ligand FasL are introduced and presented to cells. Mimicking different receptor geometries, these nanoagents act as signaling platforms inducing fastest time-to-death kinetics for hexagonal FasL arrangements with 10 nm inter-molecular spacing. Compared to naturally occurring soluble FasL, this trigger is faster and 100× more efficient. Nanoagents with different spacing, lower FasL number or higher coupling flexibility impede signaling. The results present DNA origami as versatile signaling scaffolds exhibiting unprecedented control over molecular number and geometry. They define molecular benchmarks in apoptosis signal initiation and constitute a new strategy to drive particular cell responses.

A complex immune response to flagellin epitope variation in commensal communities

Immune systems restrict microbial pathogens by identifying "non-self" molecules called microbe-associated molecular patterns (MAMPs). It is unclear how immune responses are tuned to or by MAMP diversity present in commensal microbiota. We systematically studied the variability of commensal peptide derivatives of flagellin (flg22), a MAMP detected by plants. We define substantial functional diversity. Most flg22 peptides evade recognition, while others contribute to evasion by manipulating immunity through antagonism and signal modulation. We establish a paradigm of signal integration, wherein the sequential signaling outputs of the flagellin receptor are separable and allow for reprogramming by commensal-derived flg22 epitope variants. Plant-associated communities are enriched for immune evading flg22 epitopes, but upon physiological stress that represses the immune system, immune-activating flg22 epitopes become enriched. The existence of immune-manipulating epitopes suggests that they evolved to either communicate or utilize the immune system for host colonization and thus can influence commensal microbiota community composition.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.

Mutational Analysis of the Putative Anti-Müllerian Hormone (AMH) Binding Interface on its Type II Receptor, AMHR2

Anti-Müllerian hormone (AMH) or Müllerian inhibiting substance is a unique member of the TGF-β family responsible for development and differentiation of the reproductive system. AMH signals through its own dedicated type II receptor, anti-Müllerian hormone receptor type II (AMHR2), providing an exclusive ligand-receptor pair within the broader TGF-β family. In this study, we used previous structural information to derive a model of AMH bound to AMHR2 to guide mutagenesis studies to identify receptor residues important for AMH signaling. Nonconserved mutations were introduced in AMHR2 and characterized in an AMH-responsive cell-based luciferase assay and native PAGE. Collectively, our results identified several residues important for AMH signaling within the putative ligand binding interface of AMHR2. Our results show that AMH engages AMHR2 at a similar interface to how activin and BMP class ligands bind the type II receptor, ACVR2B; however, there are significant molecular differences at the ligand interface of these 2 receptors, where ACVR2B is mostly hydrophobic and AMHR2 is predominately charged. Overall, this study shows that although the location of ligand binding on the receptor is similar to ACVR2A, ACVR2B, and BMPR2; AMHR2 uses unique ligand-receptor interactions to impart specificity for AMH.

Cell-Free Expression of Sodium Channel Domains for Pharmacology Studies. Noncanonical Spider Toxin Binding Site in the Second Voltage-Sensing Domain of Human Nav1.4 Channel

Voltage-gated sodium (Na_V) channels are essential for the normal functioning of cardiovascular, muscular, and nervous systems. These channels have modular organization; the central pore domain allows current flow and provides ion selectivity, whereas four peripherally located voltage-sensing domains (VSDs-I/IV) are needed for voltage-dependent gating. Mutations in the S4 voltage-sensing segments of VSDs in the skeletal muscle channel Na_V1.4 trigger leak (gating pore) currents and cause hypokalemic and normokalemic periodic paralyses. Previously, we have shown that the gating modifier toxin Hm-3 from the crab spider Heriaeus melloteei binds to the S3-S4 extracellular loop in VSD-I of Na_V1.4 channel and inhibits gating pore currents through the channel with mutations in VSD-I. Here, we report that Hm-3 also inhibits gating pore currents through the same channel with the R675G mutation in VSD-II. To investigate the molecular basis of Hm-3 interaction with VSD-II, we produced the corresponding 554-696 fragment of Na_V1.4 in a continuous exchange cell-free expression system based on the Escherichia coli S30 extract. We then performed a combined nuclear magnetic resonance (NMR) and electron paramagnetic resonance spectroscopy study of isolated VSD-II in zwitterionic dodecylphosphocholine/lauryldimethylamine-N-oxide or dodecylphosphocholine micelles. To speed up the assignment of backbone resonances, five selectively ¹³C,¹⁵N-labeled VSD-II samples were produced in accordance with specially calculated combinatorial scheme. This labeling approach provides assignment for ∼50% of the backbone. Obtained NMR and electron paramagnetic resonance data revealed correct secondary structure, quasi-native VSD-II fold, and enhanced ps-ns timescale dynamics in the micelle-solubilized domain. We modeled the structure of the VSD-II/Hm-3 complex by protein-protein docking involving binding surfaces mapped by NMR. Hm-3 binds to VSDs I and II using different modes. In VSD-II, the protruding ß-hairpin of Hm-3 interacts with the S1-S2 extracellular loop, and the complex is stabilized by ionic interactions between the positively charged toxin residue K24 and the negatively charged channel residues E604 or D607. We suggest that Hm-3 binding to these charged groups inhibits voltage sensor transition to the activated state and blocks the depolarization-activated gating pore currents. Our results indicate that spider toxins represent a useful hit for periodic paralyses therapy development and may have multiple structurally different binding sites within one Na_V molecule.

A strategy for the selection of monovalent antibodies that span protein dimer interfaces

Ligand-induced dimerization is the predominant mechanism through which secreted proteins activate cell surface receptors to transmit essential biological signals. Cytokines are a large class of soluble proteins that dimerize transmembrane receptors into precise signaling topologies, but there is a need for alternative, engineerable ligand scaffolds that specifically recognize and stabilize these protein interactions. Recombinant antibodies can potentially serve as robust and versatile platforms for cytokine complex stabilization, and their specificity allows for tunable modulation of dimerization equilibrium. Here, we devised an evolutionary strategy to isolate monovalent antibody fragments that bridge together two different receptor subunits in a cytokine-receptor complex, precisely as the receptors are disposed in their natural signaling orientations. To do this, we screened a naive antibody library against a stabilized ligand-receptor ternary complex that acted as a "molecular cast" of the natural receptor dimer conformation. Our selections elicited "stapler" single-chain variable fragments (scFvs) of antibodies that specifically engage the interleukin-4 receptor heterodimer. The 3.1 Å resolution crystal structure of one such stapler revealed that, as intended, this scFv recognizes a composite epitope between the two receptors as they are positioned in the complex. Extending our approach, we evolved a stapler scFv that specifically binds to and stabilizes the interface between the interleukin-2 cytokine and one of its receptor subunits, leading to a 15-fold enhancement in interaction affinity. This demonstration that scFvs can be selected to recognize epitopes that span protein interfaces presents new opportunities to engineer structurally defined antibodies for a broad range of research and therapeutic applications.

Simultaneous Ligand and Receptor Tracking through NMR Spectroscopy Enabled by Distinct 19F Labels

To probe ligand-receptor binding at the atomic-level, a frequent approach involves multidimensional nuclear magnetic resonance (NMR) spectroscopy experiments relying on ¹³C- and/or ¹⁵N-enrichment alongside ¹H. Alternatively, the lack of fluorine in biomolecules may be exploited through specific incorporation of ¹⁹F nuclei into a sample. The ¹⁹F nucleus is highly sensitive to environmental changes and allows for one-dimensional NMR spectroscopic study, with perturbation to chemical shift and spin dynamics diagnostic of structural change, ligand binding, and modified conformational sampling. This was applied to the apelinergic system, which comprises a rhodopsin-like G protein-coupled receptor (the apelin receptor (AR)/APJ) and two families of cognate ligands, the apelin and apela (ELABELA/toddler) peptides. Specifically, AR fragments consisting of either the N-terminal tail and first transmembrane (TM) α-helix (AR55) or the first three transmembrane α-helices (TM1-3) were prepared with biosynthetic fluorotryptophan incorporation. Interactions of each AR fragment with a high-affinity, 2,4,5-trifluorophenylalanine labeled apelin analogue were compared by ¹⁹F NMR. Distinct ranges of ¹⁹F chemical shifts for ligand and receptor provide unambiguous tracking of both species, with distinct binding behaviour observed for each AR fragment implying that AR55 is not sufficient to recapitulate the physiological binding event. Site-specific perturbation was also apparent for the apelin analogue as a function of substitution site, indicating an orientational binding preference. As a whole, this strategy of distinctive ¹⁹F labelling for ligand and receptor provides a relatively fast (i.e., employing 1D NMR experiments) and highly sensitive method to simultaneously and definitively track binding in both species.

Predicting Molecular Targets for Small-Molecule Drugs with a Ligand-Based Interaction Fingerprint Approach

The computational prediction of molecular targets for small-molecule drugs remains a great challenge. Herein we describe a ligand-based interaction fingerprint (LIFt) approach for target prediction. Together with physics-based docking and sampling methods, we assessed the performance systematically by modeling the polypharmacology of 12 kinase inhibitors in three stages. First, we examined the capacity of this approach to differentiate true targets from false targets with the promiscuous binder staurosporine, based on native complex structures. Second, we performed large-scale profiling of kinase selectivity on the clinical drug sunitinib by means of computational simulation. Third, we extended the study beyond kinases by modeling the cross-inhibition of bromodomain-containing protein 4 (BRD4) for 10 well-established kinase inhibitors. On this basis, we made prospective predictions by exploring new kinase targets for the anticancer drug candidate TN-16, originally known as a colchicine site binder and microtubule disruptor. As a result, p38α was highlighted from a panel of 187 different kinases. Encouragingly, our prediction was validated by an in vitro kinase assay, which showed TN-16 as a low-micromolar p38α inhibitor. Collectively, our results suggest the promise of the LIFt approach in predicting potential targets for small-molecule drugs.

Cell surface expression of the Alzheimer disease-related presenilin proteins

The presenilin proteins PS-1 and PS-2 are crucially involved in Alzheimer disease (AD), but their molecular functions are not known. They are integral membrane proteins, but whether they can be expressed at the surface of cells has been in dispute. Here we show by immunofluorescence experiments, using anti-peptide antibodies specific for either PS-1 or PS-2, that live cultured DAMI cells and differentiated human NT2N neuronal cells are specifically immunolabeled for their endogenous as well as transfected presenilins, although the cells cannot be immunolabeled for their intracellular tubulin, unless they are first fixed and permeabilized. These and other results establish that portions of the presenilins are indeed expressed at the surfaces of these cells. These findings support our previous proposal that the presenilins on the surface of a cell engage in intercellular interactions with the beta-amyloid precursor protein on the surface of a neighboring cell, as a critical step in the molecular and cellular mechanisms that lead to AD.