A comprehensive map of molecular drug targets

Therapeutic Target Identification and Drug Discovery Driven by Chemical Proteomics

Throughout the human lifespan, from conception to the end of life, small molecules have an intrinsic relationship with numerous physiological processes. The investigation into small-molecule targets holds significant implications for pharmacological discovery. The determination of the action sites of small molecules provide clarity into the pharmacodynamics and toxicological mechanisms of small-molecule drugs, assisting in the elucidation of drug off-target effects and resistance mechanisms. Consequently, innovative methods to study small-molecule targets have proliferated in recent years, with chemical proteomics standing out as a vanguard development in chemical biology in the post-genomic age. Chemical proteomics can non-selectively identify unknown targets of compounds within complex biological matrices, with both probe and non-probe modalities enabling effective target identification. This review attempts to summarize methods and illustrative examples of small-molecule target identification via chemical proteomics. It delves deeply into the interactions between small molecules and human biology to provide pivotal directions and strategies for the discovery and comprehension of novel pharmaceuticals, as well as to improve the evaluation of drug safety.

Nuclear receptor Rev-erbα role in fine-tuning erythropoietin gene expression

ABSTRACT

The regulation of red blood cell (RBC) homeostasis by erythropoietin (EPO) is critical for O2 transport and maintaining the adequate number of RBCs in vertebrates. Therefore, dysregulation in EPO synthesis results in disease conditions such as polycythemia in the case of excessive EPO production and anemia, which occurs when EPO is inadequately produced. EPO plays a crucial role in treating anemic patients; however, its overproduction can increase blood viscosity, potentially leading to fatal heart failure. Consequently, the identification of druggable transcription factors and their associated ligands capable of regulating EPO offers a promising therapeutic approach to address EPO-related disorders. This study unveils a novel regulatory mechanism involving 2 pivotal nuclear receptors (NRs), Rev-ERBA (Rev-erbα, is a truncation of reverse c-erbAa) and RAR-related orphan receptor A (RORα), in the control of EPO gene expression. Rev-erbα acts as a cell-intrinsic negative regulator, playing a vital role in maintaining erythropoiesis at the correct level. It accomplishes this by directly binding to newly identified response elements within the human and mouse EPO gene promoter, thereby repressing EPO production. These findings are further supported by the discovery that a Rev-erbα agonist (SR9011) effectively suppresses hypoxia-induced EPO expression in mice. In contrast, RORα functions as a positive regulator of EPO gene expression, also binding to the same response elements in the promoter to induce EPO production. Finally, the results of this study revealed that the 2 NRs, Rev-erbα and RORα, influence EPO synthesis in a negative and positive manner, respectively, suggesting that the modulating activity of these 2 NRs could provide a method to target disorders linked with EPO dysregulation.

Engineered Branaplam Aptamers Exploit Structural Elements from Natural Riboswitches

Drug candidates that fail in clinical trials for efficacy reasons might still have favorable safety and bioavailability characteristics that could be exploited. A failed drug candidate could be repurposed if a receptor, such as an aptamer, were created that binds the compound with high specificity. Branaplam is a small molecule that was previously in development to treat spinal muscular atrophy and Huntington's disease. Here, we report the development of a small (48-nucleotide) RNA aptamer for branaplam with a dissociation constant of ∼150 nM. Starting with a combinatorial RNA pool integrating the secondary and tertiary structural scaffold of a Guanine-I riboswitch aptamer interspersed with regions of random sequence, in vitro selection yielded aptamer candidates for branaplam. Reselection and rational design were employed to improve binding of a representative branaplam aptamer candidate. A resulting variant retains the pseudoknot and two of the paired elements (P2 and P3) from the scaffold but lacks the enclosing paired element (P1) that is essential for the function of the natural Guanine-I riboswitch aptamer. A second combinatorial RNA pool based on the scaffold for TPP (thiamin pyrophosphate) riboswitches also yielded a candidate offering additional opportunities for branaplam aptamer development.

One-Step Synthesis and Oriented Immobilization of Strep-Tag II Fused PDGFRβ for Screening Intracellular Domain-Targeted Ligands

Accurate orientations and stable conformations of membrane receptor immobilization are particularly imperative for accurate drug screening and ligand-protein affinity analysis. However, there remain challenges associated with (1) traditional recombination, purification, and immobilization of membrane receptors, which are time-consuming and labor-intensive; (2) the orientations on the stationary phase are not easily controlled. Herein, a novel one-step synthesis and oriented-immobilization membrane-receptor affinity chromatography (oSOMAC) method was developed to realize high-throughput and accurate drug screening targeting specific domains of membrane receptors. We employed Strep-tag II as a noncovalent immobilization tag fused into platelet-derived growth factor receptor β (PDGFRβ) through CFPS, and meanwhile, the Strep-Tactin-modified monolithic columns are prepared in batches. The advantages of oSOMAC are as follows: (1) targeted membrane receptors can be expressed independent of living cell within 1-2 h; (2) orientation of membrane receptors can be flexibly controlled and active sites can expose accurately; and (3) targeted membrane receptors can be synthesized, purified, and orientation-immobilized on monolithic columns in one step. Accordingly, three potential PDGFRβ intracellular domain targeted ligands: tanshinone IIA (Tan IIA), hydroxytanshinone IIA, and dehydrotanshinone IIA were successfully screened out from Salvia miltiorrhiza extract through oSOMAC. Pharmacological experiments and molecular docking further demonstrated that Tan IIA could attenuate hepatic stellate cells activation by targeting the protein kinase domain of PDGFRβ with a KD value of 9.7 μM. Ultimately, the novel oSOMAC method provides an original insight for accurate drug screening and interaction analysis which can be applied in other membrane receptors.

Nematode Extracellular Protein Interactome Expands Connections between Signaling Pathways

Multicellularity was accompanied by the emergence of new classes of cell surface and secreted proteins. The nematode C. elegans is a favorable model to study cell surface interactomes, given its well-defined and stereotyped cell types and intercellular contacts. Here we report our C. elegans extracellular interactome dataset, the largest yet for an invertebrate. Most of these interactions were unknown, despite recent datasets for flies and humans, as our collection contains a larger selection of protein families. We uncover new interactions for all four major axon guidance pathways, including ectodomain interactions between three of the pathways. We demonstrate that a protein family known to maintain axon locations are secreted receptors for insulins. We reveal novel interactions of cystine-knot proteins with putative signaling receptors, which may extend the study of neurotrophins and growth-factor-mediated functions to nematodes. Finally, our dataset provides insights into human disease mechanisms and how extracellular interactions may help establish connectomes.

Advancing membrane-associated protein docking with improved sampling and scoring in Rosetta

The oligomerization of protein macromolecules on cell membranes plays a fundamental role in regulating cellular function. From modulating signal transduction to directing immune response, membrane proteins (MPs) play a crucial role in biological processes and are often the target of many pharmaceutical drugs. Despite their biological relevance, the challenges in experimental determination have hampered the structural availability of membrane proteins and their complexes. Computational docking provides a promising alternative to model membrane protein complex structures. Here, we present Rosetta-MPDock, a flexible transmembrane (TM) protein docking protocol that captures binding-induced conformational changes. Rosetta-MPDock samples large conformational ensembles of flexible monomers and docks them within an implicit membrane environment. We benchmarked this method on 29 TM-protein complexes of variable backbone flexibility. These complexes are classified based on the root-mean-square deviation between the unbound and bound states (RMSDUB) as: rigid (RMSDUB <1.2 Å), moderately-flexible (RMSDUB ∈ [1.2, 2.2) Å), and flexible targets (RMSDUB > 2.2 Å). In a local docking scenario, i.e. with membrane protein partners starting ≈10 Å apart embedded in the membrane in their unbound conformations, Rosetta-MPDock successfully predicts the correct interface (success defined as achieving 3 near-native structures in the 5 top-ranked models) for 67% moderately flexible targets and 60% of the highly flexible targets, a substantial improvement from the existing membrane protein docking methods. Further, by integrating AlphaFold2-multimer for structure determination and using Rosetta-MPDock for docking and refinement, we demonstrate improved success rates over the benchmark targets from 64% to 73%. Rosetta-MPDock advances the capabilities for membrane protein complex structure prediction and modeling to tackle key biological questions and elucidate functional mechanisms in the membrane environment. The benchmark set and the code is available for public use at github.com/Graylab/MPDock.

Leveraging Machine Learning-Guided Molecular Simulations Coupled with Experimental Data to Decipher Membrane Binding Mechanisms of Aminosterols

Understanding the molecular mechanisms of the interactions between specific compounds and cellular membranes is essential for numerous biotechnological applications, including targeted drug delivery, elucidation of the drug mechanism of action, pathogen identification, and novel antibiotic development. However, estimation of the free energy landscape associated with solute binding to realistic biological systems is still a challenging task. In this work, we leverage the Time-lagged Independent Component Analysis (TICA) in combination with neural networks (NN) through the Deep-TICA approach for determining the free energy associated with the membrane insertion processes of two natural aminosterol compounds, trodusquemine (TRO), and squalamine (SQ). These compounds are particularly noteworthy because they interact with the outer layer of neuron membranes, protecting them from the toxic action of misfolded proteins involved in neurodegenerative disorders, in both their monomeric and oligomeric forms. We demonstrate how this strategy could be used to generate an effective collective variable for describing solute absorption in the membrane and for estimating free energy landscape of translocation via on-the-fly probability enhanced sampling (OPES) method. In this context, the computational protocol allowed an exhaustive characterization of the aminosterol entry pathway into a neuron-like lipid bilayer. Furthermore, it provided accurate prediction of membrane binding affinities, in close agreement with the experimental binding data obtained by using fluorescently labeled aminosterols and large unilamellar vesicles (LUVs). The findings contribute significantly to our understanding of aminosterol entry pathways and aminosterol-lipid membrane interactions. Finally, the computational methods deployed in this study further demonstrate considerable potential for investigating membrane binding processes.

Advancing drug discovery through assay development: a survey of tool compounds within the human solute carrier superfamily

With over 450 genes, solute carriers (SLCs) constitute the largest transporter superfamily responsible for the uptake and efflux of nutrients, metabolites, and xenobiotics in human cells. SLCs are associated with a wide variety of human diseases, including cancer, diabetes, and metabolic and neurological disorders. They represent an important therapeutic target class that remains only partly exploited as therapeutics that target SLCs are scarce. Additionally, many small molecules reported in the literature to target SLCs are poorly characterized. Both features may be due to the difficulty of developing SLC transport assays that fulfill the quality criteria for high-throughput screening. Here, we report one of the main limitations hampering assay development within the RESOLUTE consortium: the lack of a resource providing high-quality information on SLC tool compounds. To address this, we provide a systematic annotation of tool compounds targeting SLCs. We first provide an overview on RESOLUTE assays. Next, we present a list of SLC-targeting compounds collected from the literature and public databases; we found that most data sources lacked specificity data. Finally, we report on experimental tests of 19 selected compounds against a panel of 13 SLCs from seven different families. Except for a few inhibitors, which were active on unrelated SLCs, the tested inhibitors demonstrated high selectivity for their reported targets. To make this knowledge easily accessible to the scientific community, we created an interactive dashboard displaying the collected data in the RESOLUTE web portal (https://re-solute.eu). We anticipate that our open-access resources on assays and compounds will support the development of future drug discovery campaigns for SLCs.

Shining a Light on Venom-Peptide Receptors: Venom Peptides as Targeted Agents for In Vivo Molecular Imaging

Molecular imaging has revolutionised the field of biomedical research by providing a non-invasive means to visualise and understand biochemical processes within living organisms. Optical fluorescent imaging in particular allows researchers to gain valuable insights into the dynamic behaviour of a target of interest in real time. Ion channels play a fundamental role in cellular signalling, and they are implicated in diverse pathological conditions, making them an attractive target in the field of molecular imaging. Many venom peptides exhibit exquisite selectivity and potency towards ion channels, rendering them ideal agents for molecular imaging applications. In this review, we illustrate the use of fluorescently-labelled venom peptides for disease diagnostics and intraoperative imaging of brain tumours and peripheral nerves. Finally, we address challenges for the development and clinical translation of venom peptides as nerve-targeted imaging agents.

Discovery of a CCR2-targeting pepducin therapy for chronic pain

Targeting the CCL2/CCR2 chemokine axis has been shown to be effective at relieving pain in rodent models of inflammatory and neuropathic pain, therefore representing a promising avenue for the development of non-opioid analgesics. However, clinical trials targeting this receptor for inflammatory conditions and painful neuropathies have failed to meet expectations and have all been discontinued due to lack of efficacy. To overcome the poor selectivity of CCR2 chemokine receptor antagonists, we generated and characterized the function of intracellular cell-penetrating allosteric modulators targeting CCR2, namely pepducins. In vivo, chronic intrathecal administration of the CCR2-selective pepducin PP101 was effective in alleviating neuropathic and bone cancer pain. In the setting of bone metastases, we found that T cells infiltrate dorsal root ganglia (DRG) and induce long-lasting pain hypersensitivity. By acting on CCR2-expressing DRG neurons, PP101 attenuated the altered phenotype of sensory neurons as well as the neuroinflammatory milieu of DRGs, and reduced bone cancer pain by blocking CD4+ and CD8+ T cell infiltration. Notably, PP101 demonstrated its efficacy in targeting the neuropathic component of bone cancer pain, as evidenced by its anti-nociceptive effects in a model of chronic constriction injury of the sciatic nerve. Importantly, PP101-induced reduction of CCR2 signaling in DRGs did not result in deleterious tumor progression or adverse behavioral effects. Thus, targeting neuroimmune crosstalk through allosteric inhibition of CCR2 could represent an effective and safe avenue for the management of chronic pain.

A small-molecule activation mechanism that directly opens the KCNQ2 channel

Pharmacological activation of voltage-gated ion channels by ligands serves as the basis for therapy and mainly involves a classic gating mechanism that augments the native voltage-dependent open probability. Through structure-based virtual screening, we identified a new scaffold compound, Ebio1, serving as a potent and subtype-selective activator for the voltage-gated potassium channel KCNQ2 and featuring a new activation mechanism. Single-channel patch-clamp, cryogenic-electron microscopy and molecular dynamic simulations, along with chemical derivatives, reveal that Ebio1 engages the KCNQ2 activation by generating an extended channel gate with a larger conductance at the saturating voltage (+50 mV). This mechanism is different from the previously observed activation mechanism of ligands on voltage-gated ion channels. Ebio1 caused S6 helices from residues S303 and F305 to perform a twist-to-open movement, which was sufficient to open the KCNQ2 gate. Overall, our findings provide mechanistic insights into the activation of KCNQ2 channel by Ebio1 and lend support for KCNQ-related drug development.

Bridging the gap between target-based and phenotypic-based drug discovery

INTRODUCTION

The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed.

AREAS COVERED

This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process.

EXPERT OPINION

The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.

High-throughput BCRP inhibitors screening system based on styrene maleic acid polymer membrane protein stabilization strategy and surface plasmon resonance biosensor

Multidrug resistance (MDR) is a dominant challenge in cancer chemotherapy failure. The over-expression of breast cancer resistance protein (BCRP) in tumorous cells, along with its extensive substrate profile, is a leading cause of tumor MDR. Herein, on the basis of styrene maleic acid (SMA) polymer membrane protein stabilization strategy and surface plasmon resonance (SPR) biosensor, a novel high-throughput screening (HTS) system for BCRP inhibitors has been established. Firstly, LLC-PK1 and LLC-PK1/BCRP cell membranes were co-incubated with SMA polymers to construct SMA lipid particles (SMALPs). PK1-SMALPs were thus immobilized in channel 1 of the L1 chip as the reference channel, and BCRP-SMALPs were immobilized in channel 2 as the detection channel to establish the BCRP-SMALPs-SPR screening system. The methodological investigation demonstrated that the screening system was highly specific and stable. Three active compounds were screened out from 26 natural products and their affinity constants with BCRP were determined. The KD of xanthotoxin, bergapten, and naringenin were 5.14 μM, 4.57 μM, and 3.72 μM, respectively. The in vitro cell verification experiments demonstrated that xanthotoxin, bergapten, and naringenin all significantly increased the sensitivity of LLC-PK1/BCRP cells to mitoxantrone with possessing reversal BCRP-mediated MDR activity. Collectively, the developed BCRP-SMALPs-SPR screening system in this study has the advantages of rapidity, efficiency, and specificity, providing a novel strategy for the in-depth screening of BCRP inhibitors with less side effects and higher efficacy.

Establishment and evaluation of targeted molecular screening model for the ryanodine receptor or sarco/endoplasmic reticulum calcium ATPase

BACKGROUD

Endoplasmic reticulum/sarcoplasmic reticulum (ER/SR) is crucial for maintaining intracellular calcium homeostasis due to the calcium-signaling-related proteins on its membrane. While ryanodine receptors (RyR) on insect ER/SR membranes are well-known as targets for diamide insecticides, little is known about other calcium channels. Given the resistance of diamide insecticides, the establishment of molecular screening models targeting RyR or sarco/endoplasmic reticulum calcium ATPase (SERCA) is conducive to the discovery of new insecticidal molecules.

RESULTS

The morphological features of Mythimna separata SR have closed vesicles with integrity and high density. The 282 proteins in the SR component contained RyR and SERCA. A measurement model for the release and uptake of calcium was successfully established by detecting calcium ions outside the SR membrane using a fluorescence spectrophotometer. In vitro testing systems using SR vesicles found that diamide insecticides could activate dose-dependently RyR, with EC50 values of 0.14 μM (Chlorantraniliprole), 0.21 μM (Flubendiamide), and 0.57 μM (Cyantraniliprole), respectively. However, dantrolene inhibited RyR-mediated calcium release with an IC50 value of 353.9 μM, suggesting that dantrolene can weakly antagonize RyR. Moreover, cyclopiazonic acid significantly reduced the enzyme activity and calcium uptake capacity of SERCA. On the contrary, CDN1163 markedly activated the enzyme activity and improved the calcium transport capacity of SERCA.

CONCLUSIONS

SR vesicles can be used to study the function of unknown proteins on the SR membranes, as well as for high-throughput screening of highly active compounds targeting RyR or SERCA. © 2024 Society of Chemical Industry.

The state of the art in secondary pharmacology and its impact on the safety of new medicines

Secondary pharmacology screening of investigational small-molecule drugs for potentially adverse off-target activities has become standard practice in pharmaceutical research and development, and regulatory agencies are increasingly requesting data on activity against targets with recognized adverse effect relationships. However, the screening strategies and target panels used by pharmaceutical companies may vary substantially. To help identify commonalities and differences, as well as to highlight opportunities for further optimization of secondary pharmacology assessment, we conducted a broad-ranging survey across 18 companies under the auspices of the DruSafe leadership group of the International Consortium for Innovation and Quality in Pharmaceutical Development. Based on our analysis of this survey and discussions and additional research within the group, we present here an overview of the current state of the art in secondary pharmacology screening. We discuss best practices, including additional safety-associated targets not covered by most current screening panels, and present approaches for interpreting and reporting off-target activities. We also provide an assessment of the safety impact of secondary pharmacology screening, and a perspective on opportunities and challenges in this rapidly developing field.

Brainwide silencing of prion protein by AAV-mediated delivery of an engineered compact epigenetic editor

Prion disease is caused by misfolding of the prion protein (PrP) into pathogenic self-propagating conformations, leading to rapid-onset dementia and death. However, elimination of endogenous PrP halts prion disease progression. In this study, we describe Coupled Histone tail for Autoinhibition Release of Methyltransferase (CHARM), a compact, enzyme-free epigenetic editor capable of silencing transcription through programmable DNA methylation. Using a histone H3 tail-Dnmt3l fusion, CHARM recruits and activates endogenous DNA methyltransferases, thereby reducing transgene size and cytotoxicity. When delivered to the mouse brain by systemic injection of adeno-associated virus (AAV), Prnp-targeted CHARM ablates PrP expression across the brain. Furthermore, we have temporally limited editor expression by implementing a kinetically tuned self-silencing approach. CHARM potentially represents a broadly applicable strategy to suppress pathogenic proteins, including those implicated in other neurodegenerative diseases.

Structural and Computational Insights into Dynamics and Intermediate States of Orexin 2 Receptor Signaling

Orexin 2 receptor (OX2R) is a G protein-coupled receptor (GPCR) whose activation is crucial to regulation of the sleep-wake cycle. Recently, inactive and active state structures were determined from X-ray crystallography and cryo-electron microscopy single particle analysis, and the activation mechanisms have been discussed based on these static data. GPCRs have multiscale intermediate states during activation, and insights into these dynamics and intermediate states may aid the precise control of intracellular signaling by ligands in drug discovery. Molecular dynamics (MD) simulations are used to investigate dynamics induced in response to thermal perturbations, such as structural fluctuations of main and side chains. In this study, we proposed collective motions of the TM domain during activation by performing 30 independent microsecond-scale MD simulations for various OX2R systems and applying relaxation mode analysis. The analysis results suggested that TM3 had a vertical structural movement relative to the membrane surface during activation. In addition, we extracted three characteristic amino acid residues on TM3, i.e., Q1343.32, V1423.40, and R1523.50, which exhibited large conformational fluctuations. We quantitatively evaluated the changes in their equilibrium during activation in relation to the movement of TM3. We also discuss the regulation of ligand binding recognition and intracellular signal selectivity by changes in the equilibrium of Q1343.32 and R1523.50, respectively, according to MD simulations and GPCR database. Additionally, the OX2R-Gi signaling complex is stabilized in the conformation resembling a non-canonical (NC) state, which was previously proposed as an intermediate state during activation of neurotensin 1 receptor. Insights into the dynamics and intermediate states during activation gained from this study may be useful for developing biased agonists for OX2R.

Drug-target interaction prediction using knowledge graph embedding

The prediction of drug-target interactions (DTIs) is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. Computational approaches to predicting DTIs can provide important insights into drug mechanisms of action. However, current methods for predicting DTIs based on the structural information of the knowledge graph may suffer from the sparseness and incompleteness of the knowledge graph and neglect the latent type information of the knowledge graph. In this paper, we propose TTModel, a knowledge graph embedding model for DTI prediction. By exploiting biomedical text and type information, TTModel can learn latent text semantics and type information to improve the performance of representation learning. Comprehensive experiments on two public datasets demonstrate that our model outperforms the state-of-the-art methods significantly on the task of DTI prediction.

RNATACs: Multispecific small molecules targeting RNA by induced proximity

RNA-targeting small molecules (rSMs) have become an attractive modality to tackle traditionally undruggable proteins and expand the druggable space. Among many innovative concepts, RNA-targeting chimeras (RNATACs) represent a new class of multispecific, induced proximity small molecules that act by chemically bringing RNA targets into proximity with an endogenous RNA effector, such as a ribonuclease (RNase). Depending on the RNA effector, RNATACs can alter the stability, localization, translation, or splicing of the target RNA. Although still in its infancy, this new modality has the potential for broad applications in the future to treat diseases with high unmet need. In this review, we discuss potential advantages of RNATACs, recent progress in the field, and challenges to this cutting-edge technology.

Identification of drug targets for Sjögren's syndrome: multi-omics Mendelian randomization and colocalization analyses

Background

Targeted therapy for Sjögren's syndrome (SS) has become an important focus for clinicians. Multi-omics-wide Mendelian randomization (MR) analyses have provided new ideas for identifying potential drug targets.

Methods

We conducted summary-data-based Mendelian randomization (SMR) analysis to evaluate therapeutic targets associated with SS by integrating DNA methylation, gene expression and protein quantitative trait loci (mQTL, eQTL, and pQTL, respectively). Genetic associations with SS were derived from the FinnGen study (discovery) and the GWAS catalog (replication). Colocalization analyses were employed to determine whether two potentially relevant phenotypes share the same genetic factors in a given region. Moreover, to delve deeper into potential regulation among DNA methylation, gene expression, and protein abundance, we conducted MR analysis to explore the causal relationship between candidate gene methylation and expression, as well as between gene expression and protein abundance. Drug prediction and molecular docking were further employed to validate the pharmacological activity of the candidate drug targets.

Results

Upon integrating the multi-omics data, we identified three genes associated with SS risk: TNFAIP3, BTN3A1, and PLAU. The methylation of cg22068371 in BTN3A1 was positively associated with protein levels, consistent with the negative effect of cg22068371 methylation on the risk of SS. Additionally, positive correlations were observed between the gene methylation of PLAU (cg04939496) and expression, as well as between expression and protein levels. This consistency elucidates the promotional effects of PLAU on SS risk at the DNA methylation, gene expression, and protein levels. At the protein level, genetically predicted TNFAIP3 (OR 2.47, 95% CI 1.56-3.92) was positively associated with SS risk, while BTN3A1 (OR 2.96E-03, 95% CI 2.63E-04-3.33E-02) was negatively associated with SS risk. Molecular docking showed stable binding for candidate drugs and target proteins.

Conclusion

Our study reveals promising therapeutic targets for the treatment of SS, providing valuable insights into targeted therapy for SS. However, further validation through future experiments is warranted.

Remapping the Chemical Space and the Pharmacological Space of Drugs: What Can We Expect from the Road Ahead?

This work examines the current landscape of drug discovery and development, with a particular focus on the chemical and pharmacological spaces. It emphasizes the importance of understanding these spaces to anticipate future trends in drug discovery. The use of cheminformatics and data analysis enabled in silico exploration of these spaces, allowing a perspective of drugs, approved drugs after 2020, and clinical candidates, which were extracted from the newly released ChEMBL34 (March 2024). This perspective on chemical and pharmacological spaces enables the identification of trends and areas to be occupied, thereby creating opportunities for more effective and targeted drug discovery and development strategies in the future.

Unraveling the role of plasma proteins in dementia: insights from two cohort studies in the UK, with causal evidence from Mendelian randomization

Population-based proteomics offer a groundbreaking avenue to predict dementia onset. This study employed a proteome-wide, data-driven approach to investigate protein-dementia associations in 229 incident all-cause dementia (ACD) among 3,249 participants from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up, then validated in 1,506 incident ACD among 52,745 individuals from the UK Biobank (UKB) over median 13.7 years. NEFL and RPS6KB1 were robustly associated with incident ACD; MMP12 was associated with vascular dementia in ELSA. Additional markers EDA2R and KIM1 (HAVCR1) were identified from sensitivity analyses. Combining NEFL and RPS6KB1 with other factors yielded high predictive accuracy (area under the curve (AUC)=0.871) for incident ACD. Replication in the UKB confirmed associations between identified proteins with various dementia subtypes. Results from reverse Mendelian Randomization also supported the role of several proteins as early dementia biomarkers. These findings underscore proteomics' potential in identifying novel risk screening targets for dementia.

GPCR Screening Reveals that the Metabolite Receptor HCAR3 Regulates Epithelial Proliferation, Migration, and Cellular Respiration

Epithelial cells in the skin and other tissues rely on signals from their environment to maintain homeostasis and respond to injury, and GPCRs play a critical role in this communication. A better understanding of the GPCRs expressed in epithelial cells will contribute to understanding the relationship between cells and their niche and could lead to developing new therapies to modulate cell fate. This study used human primary keratinocytes as a model to investigate the specific GPCRs regulating epithelial cell proliferation and differentiation. We identified 3 key receptors-HCAR3, LTB4R, and GPR137-and found that knockdown of these receptors led to changes in numerous gene networks that are important for maintaining cell identity and promoting proliferation while inhibiting differentiation. Our study also revealed that the metabolite receptor HCAR3 regulates keratinocyte migration and cellular metabolism. Knockdown of HCAR3 led to reduced keratinocyte migration and respiration, which could be attributed to altered metabolite use and aberrant mitochondrial morphology caused by the absence of the receptor. This study contributes to understanding the complex interplay between GPCR signaling and epithelial cell fate decisions.

Development and therapeutic implications of small molecular inhibitors that target calcium-related channels in tumor treatment

Calcium ion dysregulation exerts profound effects on various physiological activities such as tumor proliferation, migration, and drug resistance. Calcium-related channels play a regulatory role in maintaining calcium ion homeostasis, with most channels being highly expressed in tumor cells. Additionally, these channels serve as potential drug targets for the development of antitumor medications. In this review, we first discuss the current research status of these pathways, examining how they modulate various tumor functions such as epithelial-mesenchymal transition (EMT), metabolism, and drug resistance. Simultaneously, we summarize the recent progress in the study of novel small-molecule drugs over the past 5 years and their current status.

Pharmacological potential of cyclic nucleotide signaling in immunity

Cyclic nucleotides are important signaling molecules that play many critical physiological roles including controlling cell fate and development, regulation of metabolic processes, and responding to changes in the environment. Cyclic nucleotides are also pivotal regulators in immune signaling, orchestrating intricate processes that maintain homeostasis and defend against pathogenic threats. This review provides a comprehensive examination of the pharmacological potential of cyclic nucleotide signaling pathways within the realm of immunity. Beginning with an overview of the fundamental roles of cAMP and cGMP as ubiquitous second messengers, this review delves into the complexities of their involvement in immune responses. Special attention is given to the challenges associated with modulating these signaling pathways for therapeutic purposes, emphasizing the necessity for achieving cell-type specificity to avert unintended consequences. A major focus of the review is on the recent paradigm-shifting discoveries regarding specialized cyclic nucleotide signals in the innate immune system, notably the cGAS-STING pathway. The significance of cyclic dinucleotides, exemplified by 2'3'-cGAMP, in controlling immune responses against pathogens and cancer, is explored. The evolutionarily conserved nature of cyclic dinucleotides as antiviral agents, spanning across diverse organisms, underscores their potential as targets for innovative immunotherapies. Findings from the last several years have revealed a striking diversity of novel bacterial cyclic nucleotide second messengers which are involved in antiviral responses. Knowledge of the existence and precise identity of these molecules coupled with accurate descriptions of their associated immune defense pathways will be essential to the future development of novel antibacterial therapeutic strategies. The insights presented herein may help researchers navigate the evolving landscape of immunopharmacology as it pertains to cyclic nucleotides and point toward new avenues or lines of thinking about development of therapeutics against the pathways they regulate.

Advancing Drug-Target Interaction prediction with BERT and subsequence embedding

Exploring the relationship between proteins and drugs plays a significant role in discovering new synthetic drugs. The Drug-Target Interaction (DTI) prediction is a fundamental task in the relationship between proteins and drugs. Unlike encoding proteins by amino acids, we use amino acid subsequence to encode proteins, which simulates the biological process of DTI better. For this research purpose, we proposed a novel deep learning framework based on Bidirectional Encoder Representation from Transformers (BERT), which integrates high-frequency subsequence embedding and transfer learning methods to complete the DTI prediction task. As the first key module, subsequence embedding allows to explore the functional interaction units from drug and protein sequences and then contribute to finding DTI modules. As the second key module, transfer learning promotes the model learn the common DTI features from protein and drug sequences in a large dataset. Overall, the BERT-based model can learn two kinds features through the multi-head self-attention mechanism: internal features of sequence and interaction features of both proteins and drugs, respectively. Compared with other methods, BERT-based methods enable more DTI-related features to be discovered by means of attention scores which associated with tokenized protein/drug subsequences. We conducted extensive experiments for the DTI prediction task on three different benchmark datasets. The experimental results show that the model achieves an average prediction metrics higher than most baseline methods. In order to verify the importance of transfer learning, we conducted an ablation study on datasets, and the results show the superiority of transfer learning. In addition, we test the scalability of the model on the dataset in unseen drugs and proteins, and the results of the experiments show that it is acceptable in scalability.

GPCR kinase subtype requirements for arrestin-2 and -3 translocation to the cannabinoid CB1 receptor and the consequences on G protein signalling

Arrestins are key negative regulators of G Protein-Coupled Receptors (GPCRs) through mediation of G protein desensitisation and receptor internalisation. Arrestins can also contribute to signal transduction by scaffolding downstream signalling effectors for activation. GPCR kinase (GRK) enzymes phosphorylate the intracellular C-terminal domain, or intracellular loop regions of GPCRs to promote arrestin interaction. There are seven different GRK subtypes, which may uniquely phosphorylate the C-terminal tail in a type of 'phosphorylation barcode,' potentially differentially contributing to arrestin translocation and arrestin-dependent signalling. Such contributions may be exploited to develop arrestin-biased ligands. Here, we examine the effect of different GRK subtypes on the ability to promote translocation of arrestin-2 and arrestin-3 to the cannabinoid CB1 receptor (CB1) with a range of ligands. We find that most GRK subtypes (including visual GRK1) can enhance arrestin-2 and -3 translocation to CB1, and that GRK-dependent changes in arrestin-2 and arrestin-3 translocation were broadly shared for most agonists tested. GRK2/3 generally enhanced arrestin translocation more than the other GRK subtypes, with some small differences between ligands. We also explore the interplay between G protein activity and GRK2/3-dependent arrestin translocation, highlighting that high-efficacy G protein agonists will cause GRK2/3 dependent arrestin translocation. This study supports the hypothesis that arrestin-biased ligands for CB1 must engage GRK5/6 rather than GRK2/3, and G protein-biased ligands must have inherently low efficacy.

Association between Human Blood Proteome and the Risk of Myocardial Infarction

Background

The objective of this study is to estimate the causal relationship between plasma proteins and myocardial infarction (MI) through Mendelian randomization (MR), predict potential target-mediated side effects associated with protein interventions, and ensure a comprehensive assessment of clinical safety.

Methods

From 3 proteome genome-wide association studies (GWASs) involving 9775 European participants, 331 unique blood proteins were screened and chosed. The summary data related to MI were derived from a GWAS meta-analysis, incorporating approximately 61,000 cases and 577,000 controls. The assessment of associations between blood proteins and MI was conducted through MR analyses. A phenome-wide MR (Phe-MR) analysis was subsequently employed to determine the potential on-target side effects of protein interventions.

Results

Causal mediators for MI were identified, encompassing cardiotrophin-1 (CT-1) (odds ratio [OR] per SD increase: 1.16; 95% confidence interval [CI]: 1.13-1.18; p = 1.29 × 10 - 31 ), Selenoprotein S (SELENOS) (OR: 1.16; 95% CI: 1.13-1.20; p = 4.73 × 10 - 24 ), killer cell immunoglobulin-like receptor 2DS2 (KIR2DS2) (OR: 0.93; 95% CI: 0.90-0.96; p = 1.08 × 10 - 5 ), vacuolar protein sorting-associated protein 29 (VPS29) (OR: 0.92; 95% CI: 0.90-0.94; p = 8.05 × 10 - 13 ), and histo-blood group ABO system transferase (NAGAT) (OR: 1.05; 95% CI: 1.03-1.07; p = 1.41 × 10 - 5 ). In the Phe-MR analysis, memory loss risk was mediated by CT-1, VPS29 exhibited favorable effects on the risk of 5 diseases, and KIR2DS2 showed no predicted detrimental side effects.

Conclusions

Elevated genetic predictions of KIR2DS2 and VPS29 appear to be linked to a reduced risk of MI, whereas an increased risk is associated with CT-1, SELENOS, and NAGAT. The characterization of side effect profiles aids in the prioritization of drug targets. Notably, KIR2DS2 emerges as a potentially promising target for preventing and treating MI, devoid of predicted detrimental side effects.

Ion channel inhibition by targeted recruitment of NEDD4-2 with divalent nanobodies

Targeted recruitment of E3 ubiquitin ligases to degrade traditionally undruggable proteins is a disruptive paradigm for developing new therapeutics. Two salient limitations are that <2% of the ~600 E3 ligases in the human genome have been exploited to produce proteolysis targeting chimeras (PROTACs), and the efficacy of the approach has not been demonstrated for a vital class of complex multi-subunit membrane proteins- ion channels. NEDD4-1 and NEDD4-2 are physiological regulators of myriad ion channels, and belong to the 28-member HECT (homologous to E6AP C-terminus) family of E3 ligases with widespread roles in cell/developmental biology and diverse diseases including various cancers, immunological and neurological disorders, and chronic pain. The potential efficacy of HECT E3 ligases for targeted protein degradation is unexplored, constrained by a lack of appropriate binders, and uncertain due to their complex regulation by layered intra-molecular and posttranslational mechanisms. Here, we identified a nanobody that binds with high affinity and specificity to a unique site on the N-lobe of the NEDD4-2 HECT domain at a location physically separate from sites critical for catalysis- the E2 binding site, the catalytic cysteine, and the ubiquitin exosite- as revealed by a 3.1 Å cryo-electron microscopy reconstruction. Recruiting endogenous NEDD4-2 to diverse ion channel proteins (KCNQ1, ENaC, and CaV2.2) using a divalent (DiVa) nanobody format strongly reduced their functional expression with minimal off-target effects as assessed by global proteomics, compared to simple NEDD4-2 overexpression. The results establish utility of a HECT E3 ligase for targeted protein downregulation, validate a class of complex multi-subunit membrane proteins as susceptible to this modality, and introduce endogenous E3 ligase recruitment with DiVa nanobodies as a general method to generate novel genetically-encoded ion channel inhibitors.

Chloride ions in health and disease

Chloride is a key anion involved in cellular physiology by regulating its homeostasis and rheostatic processes. Changes in cellular Cl- concentration result in differential regulation of cellular functions such as transcription and translation, post-translation modifications, cell cycle and proliferation, cell volume, and pH levels. In intracellular compartments, Cl- modulates the function of lysosomes, mitochondria, endosomes, phagosomes, the nucleus, and the endoplasmic reticulum. In extracellular fluid (ECF), Cl- is present in blood/plasma and interstitial fluid compartments. A reduction in Cl- levels in ECF can result in cell volume contraction. Cl- is the key physiological anion and is a principal compensatory ion for the movement of the major cations such as Na+, K+, and Ca2+. Over the past 25 years, we have increased our understanding of cellular signaling mediated by Cl-, which has helped in understanding the molecular and metabolic changes observed in pathologies with altered Cl- levels. Here, we review the concentration of Cl- in various organs and cellular compartments, ion channels responsible for its transportation, and recent information on its physiological roles.

AI approaches for the discovery and validation of drug targets

Artificial intelligence (AI) holds immense promise for accelerating and improving all aspects of drug discovery, not least target discovery and validation. By integrating a diverse range of biological data modalities, AI enables the accurate prediction of drug target properties, ultimately illuminating biological mechanisms of disease and guiding drug discovery strategies. Despite the indisputable potential of AI in drug target discovery, there are many challenges and obstacles yet to be overcome, including dealing with data biases, model interpretability and generalisability, and the validation of predicted drug targets, to name a few. By exploring recent advancements in AI, this review showcases current applications of AI for drug target discovery and offers perspectives on the future of AI for the discovery and validation of drug targets, paving the way for the generation of novel and safer pharmaceuticals.

Causal relationship between anti-inflammatory drugs and cancer: a pan-cancer study with Mendelian randomization

Background

Numerous epidemiological studies have elucidated the intricate connection between inflammation and cancer, highlighting how sustained inflammatory responses can fuel carcinogenesis by fostering proliferation, angiogenesis, and metastasis, while dampening immune responses and sensitivity to chemotherapy. Previous clinical investigations have underscored the potential of anti-inflammatory medications in either preventing or mitigating tumor formation. Here, the causal relationship between anti-inflammatory drugs and cancer was further explored through Mendelian randomization studies.

Methods

Employing Mendelian randomization, we scrutinized the causal links between three anti-inflammatory drugs-NSAIDs, Aspirin, and Anilide-and 37 types of cancer. We primarily utilized inverse variance weighting (IVW) as the primary analytical approach to delineate the causal association between these drugs and cancer types. Concurrently, sensitivity analyses were conducted to ascertain the absence of horizontal pleiotropy and heterogeneity.

Results

Our investigation revealed a discernible causal relationship between certain anti-inflammatory drugs and a subset of cancers, albeit without a pervasive impact across all cancer types. Specifically, NSAIDs exhibited a risk-reducing effect on non-small cell lung cancer (OR: 0.76, 95% CI: 0.59-0.97, p-value: 0.03) and gastric cancer (OR: 0.57, 95% CI: 0.34-0.98, p-value: 0.04). Conversely, aspirin was associated with an increased risk of oral malignant tumors (OR: 2.18, 95% CI: 1.13-4.21, p-value: 0.02). Notably, no statistically significant findings were observed for anilide drugs (p < 0.05).

Conclusion

We identified several cancers with potential causal links to NSAIDs, including non-small cell lung cancer and gastric cancer. Despite our extensive analysis, we did not identify a substantial causal relationship between the use of anti-inflammatory drugs and the development of various cancers.

Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases

Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.

Deep learning of left atrial structure and function provides link to atrial fibrillation risk

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Advancements in clinical RNA therapeutics: Present developments and prospective outlooks

RNA molecules have emerged as promising clinical therapeutics due to their ability to target "undruggable" proteins or molecules with high precision and minimal side effects. Nevertheless, the primary challenge in RNA therapeutics lies in rapid degradation and clearance from systemic circulation, the inability to traverse cell membranes, and the efficient intracellular delivery of bioactive RNA molecules. In this review, we explore the implications of RNAs in diseases and provide a chronological overview of the development of RNA therapeutics. Additionally, we summarize the technological advances in RNA-screening design, encompassing various RNA databases and design platforms. The paper then presents an update on FDA-approved RNA therapeutics and those currently undergoing clinical trials for various diseases, with a specific emphasis on RNA medicine and RNA vaccines.

Chemical manipulation of an activation/inhibition switch in the nuclear receptor PXR

Nuclear receptors are ligand-activated transcription factors that can often be useful drug targets. Unfortunately, ligand promiscuity leads to two-thirds of receptors remaining clinically untargeted. PXR is a nuclear receptor that can be activated by diverse compounds to elevate metabolism, negatively impacting drug efficacy and safety. This presents a barrier to drug development because compounds designed to target other proteins must avoid PXR activation while retaining potency for the desired target. This problem could be avoided by using PXR antagonists, but these compounds are rare, and their molecular mechanisms remain unknown. Here, we report structurally related PXR-selective agonists and antagonists and their corresponding co-crystal structures to describe mechanisms of antagonism and selectivity. Structural and computational approaches show that antagonists induce PXR conformational changes incompatible with transcriptional coactivator recruitment. These results guide the design of compounds with predictable agonist/antagonist activities and bolster efforts to generate antagonists to prevent PXR activation interfering with other drugs.

Effects of SPI1-mediated transcriptome remodeling on Alzheimer's disease-related phenotypes in mouse models of Aβ amyloidosis

SPI1 was recently reported as a genetic risk factor for Alzheimer's disease (AD) in large-scale genome-wide association studies. However, it is unknown whether SPI1 should be downregulated or increased to have therapeutic benefits. To investigate the effect of modulating SPI1 levels on AD pathogenesis, we performed extensive biochemical, histological, and transcriptomic analyses using both Spi1-knockdown and Spi1-overexpression mouse models. Here, we show that the knockdown of Spi1 expression significantly exacerbates insoluble amyloid-β (Aβ) levels, amyloid plaque deposition, and gliosis. Conversely, overexpression of Spi1 significantly ameliorates these phenotypes and dystrophic neurites. Further mechanistic studies using targeted and single-cell transcriptomics approaches demonstrate that altered Spi1 expression modulates several pathways, such as immune response pathways and complement system. Our data suggest that transcriptional reprogramming by targeting transcription factors, like Spi1, might hold promise as a therapeutic strategy. This approach could potentially expand the current landscape of druggable targets for AD.

Diffusion and Oligomerization States of the Muscarinic M1 Receptor in Live Cells─The Impact of Ligands and Membrane Disruptors

G protein-coupled receptors (GPCRs) are a major gateway to cellular signaling, which respond to ligands binding at extracellular sites through allosteric conformational changes that modulate their interactions with G proteins and arrestins at intracellular sites. High-resolution structures in different ligand states, together with spectroscopic studies and molecular dynamics simulations, have revealed a rich conformational landscape of GPCRs. However, their supramolecular structure and spatiotemporal distribution is also thought to play a significant role in receptor activation and signaling bias within the native cell membrane environment. Here, we applied single-molecule fluorescence techniques, including single-particle tracking, single-molecule photobleaching, and fluorescence correlation spectroscopy, to characterize the diffusion and oligomerization behavior of the muscarinic M1 receptor (M1R) in live cells. Control samples included the monomeric protein CD86 and fixed cells, and experiments performed in the presence of different orthosteric M1R ligands and of several compounds known to change the fluidity and organization of the lipid bilayer. M1 receptors exhibit Brownian diffusion characterized by three diffusion constants: confined/immobile (∼0.01 μm2/s), slow (∼0.04 μm2/s), and fast (∼0.14 μm2/s), whose populations were found to be modulated by both orthosteric ligands and membrane disruptors. The lipid raft disruptor C6 ceramide led to significant changes for CD86, while the diffusion of M1R remained unchanged, indicating that M1 receptors do not partition in lipid rafts. The extent of receptor oligomerization was found to be promoted by increasing the level of expression and the binding of orthosteric ligands; in particular, the agonist carbachol elicited a large increase in the fraction of M1R oligomers. This study provides new insights into the balance between conformational and environmental factors that define the movement and oligomerization states of GPCRs in live cells under close-to-native conditions.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors for a wide range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed "DrugMap," an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF-κB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF-κB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription-factor activity.

Phosphatidylinositol (4,5)-bisphosphate drives the formation of EGFR and EphA2 complexes

Receptor tyrosine kinases (RTKs) regulate many cellular functions and are important targets in pharmaceutical development, particularly in cancer treatment. EGFR and EphA2 are two key RTKs that are associated with oncogenic phenotypes. Several studies have reported functional interplay between these receptors, but the mechanism of interaction is still unresolved. Here we utilize a time-resolved fluorescence spectroscopy called PIE-FCCS to resolve EGFR and EphA2 interactions in live cells. We tested the role of ligands and found that EGF, but not ephrin A1 (EA1), stimulated hetero-multimerization between the receptors. To determine the effect of anionic lipids, we targeted phospholipase C (PLC) activity to alter the abundance of phosphatidylinositol (4,5)-bisphosphate (PIP 2 ). We found that higher PIP 2 levels increased homo-multimerization of both EGFR and EphA2, as well as hetero-multimerization. This study provides a direct characterization of EGFR and EphA2 interactions in live cells and shows that PIP 2 can have a substantial effect on the spatial organization of RTKs.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Using automated patch clamp electrophysiology platforms in ion channel drug discovery: an industry perspective

INTRODUCTION

Automated patch clamp (APC) is now well established as a mature technology for ion channel drug discovery in academia, biotech and pharma companies, and in contract research organizations (CRO), for a variety of applications including channelopathy research, compound screening, target validation and cardiac safety testing.

AREAS COVERED

Ion channels are an important class of drugged and approved drug targets. The authors present a review of the current state of ion channel drug discovery along with new and exciting developments in ion channel research involving APC. This includes topics such as native and iPSC-derived cells in ion channel drug discovery, channelopathy research, organellar and biologics in ion channel drug discovery.

EXPERT OPINION

It is our belief that APC will continue to play a critical role in ion channel drug discovery, not only in 'classical' hit screening, target validation and cardiac safety testing, but extending these applications to include high throughput organellar recordings and optogenetics. In this way, with advancements in APC capabilities and applications, together with high resolution cryo-EM structures, ion channel drug discovery will be re-invigorated, leading to a growing list of ion channel ligands in clinical development.

Insights into membrane interactions and their therapeutic potential

Recent research into membrane interactions has uncovered a diverse range of therapeutic opportunities through the bioengineering of human and non-human macromolecules. Although the majority of this research is focussed on fundamental developments, emerging studies are showcasing promising new technologies to combat conditions such as cancer, Alzheimer's and inflammatory and immune-based disease, utilising the alteration of bacteriophage, adenovirus, bacterial toxins, type 6 secretion systems, annexins, mitochondrial antiviral signalling proteins and bacterial nano-syringes. To advance the field further, each of these opportunities need to be better understood, and the therapeutic models need to be further optimised. Here, we summarise the knowledge and insights into several membrane interactions and detail their current and potential uses therapeutically.

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction

BACKGROUND

Ischemic heart disease is one of the leading causes of mortality worldwide, and thus calls for development of more effective therapeutic strategies. This study aimed to identify potential therapeutic targets for coronary heart disease (CHD) and myocardial infarction (MI) by investigating the causal relationship between plasma proteins and these conditions.

METHODS

A two-sample Mendelian randomization (MR) study was performed to evaluate more than 1600 plasma proteins for their causal associations with CHD and MI. The MR findings were further confirmed through Bayesian colocalization, Summary-data-based Mendelian Randomization (SMR), and Transcriptome-Wide Association Studies (TWAS) analyses. Further analyses, including enrichment analysis, single-cell analysis, MR analysis of cardiovascular risk factors, phenome-wide Mendelian Randomization (Phe-MR), and protein-protein interaction (PPI) network construction were conducted to verify the roles of selected causal proteins.

RESULTS

Thirteen proteins were causally associated with CHD, seven of which were also causal for MI. Among them, FES and PCSK9 were causal proteins for both diseases as determined by several analytical methods. PCSK9 was a risk factor of CHD (OR = 1.25, 95% CI: 1.13-1.38, P = 7.47E-06) and MI (OR = 1.36, 95% CI: 1.21-1.54, P = 2.30E-07), whereas FES was protective against CHD (OR = 0.68, 95% CI: 0.59-0.79, P = 6.40E-07) and MI (OR = 0.65, 95% CI: 0.54-0.77, P = 5.38E-07). Further validation through enrichment and single-cell analysis confirmed the causal effects of these proteins. Moreover, MR analysis of cardiovascular risk factors, Phe-MR, and PPI network provided insights into the potential drug development based on the proteins.

CONCLUSIONS

This study investigated the causal pathways associated with CHD and MI, highlighting the protective and risk roles of FES and PCSK9, respectively. FES. Specifically, the results showed that these proteins are promising therapeutic targets for future drug development.

Ligand efficacy shifts a nuclear receptor conformational ensemble between transcriptionally active and repressive states

Nuclear receptors (NRs) are thought to dynamically alternate between transcriptionally active and repressive conformations, which are stabilized upon ligand binding. Most NR ligand series exhibit limited bias, primarily consisting of transcriptionally active agonists or neutral antagonists, but not repressive inverse agonists-a limitation that restricts understanding of the functional NR conformational ensemble. Here, we report a NR ligand series for peroxisome proliferator-activated receptor gamma (PPARγ) that spans a pharmacological spectrum from repression (inverse agonism) to activation (agonism) where subtle structural modifications switch compound activity. While crystal structures provide snapshots of the fully repressive state, NMR spectroscopy and conformation-activity relationship analysis reveals that compounds within the series shift the PPARγ conformational ensemble between transcriptionally active and repressive conformations that are populated in the apo/ligand-free ensemble. Our findings reveal a molecular framework for minimal chemical modifications that enhance PPARγ inverse agonism and elucidate their influence on the dynamic PPARγ conformational ensemble.

IQGAP3 Is an Important Mediator of Skin Inflammatory Diseases

IQGAP3 (IQ Motif Containing GTPase Activating Protein 3) is member of the IQGAP family of scaffold proteins, which are essential for assembling multiprotein complexes that coordinate various intracellular signaling pathways. Previous research has shown that IQGAP3 is overexpressed in psoriatic skin lesions. Given its involvement in processes like cell proliferation and chemokine signaling, we sought to explore its molecular role in driving the psoriatic phenotype of keratinocytes. By conducting transcriptome profiling of HaCaT keratinocytes, we identified numerous psoriasis-associated pathways that were affected when IQGAP3 was knocked down. These included alterations in NFkB signaling, EGFR signaling, activation of p38/MAPK and ERK1/ERK2, lipid metabolism, cytokine production, and the response to inflammatory cytokine stimulation. Real-time analysis further revealed changes in cell growth dynamics, including proliferation and wound healing. The balance between cell proliferation and apoptosis was altered, as were skin barrier functions and the production of IL-6 and IFNγ. Despite these significant findings, the diversity of the alterations observed in the knockdown cells led us to conclude that IQGAP3 may not be the best target for the therapeutic inhibition to normalize the phenotype of keratinocytes in psoriasis.

Comprehensive Research on Druggable Proteins: From PSSM to Pre-Trained Language Models

Identification of druggable proteins can greatly reduce the cost of discovering new potential drugs. Traditional experimental approaches to exploring these proteins are often costly, slow, and labor-intensive, making them impractical for large-scale research. In response, recent decades have seen a rise in computational methods. These alternatives support drug discovery by creating advanced predictive models. In this study, we proposed a fast and precise classifier for the identification of druggable proteins using a protein language model (PLM) with fine-tuned evolutionary scale modeling 2 (ESM-2) embeddings, achieving 95.11% accuracy on the benchmark dataset. Furthermore, we made a careful comparison to examine the predictive abilities of ESM-2 embeddings and position-specific scoring matrix (PSSM) features by using the same classifiers. The results suggest that ESM-2 embeddings outperformed PSSM features in terms of accuracy and efficiency. Recognizing the potential of language models, we also developed an end-to-end model based on the generative pre-trained transformers 2 (GPT-2) with modifications. To our knowledge, this is the first time a large language model (LLM) GPT-2 has been deployed for the recognition of druggable proteins. Additionally, a more up-to-date dataset, known as Pharos, was adopted to further validate the performance of the proposed model.

Graph-based algorithms to dissect long-distance water-mediated H-bond networks for conformational couplings in GPCRs

Changes in structure and dynamics elicited by agonist ligand binding at the extracellular side of G protein coupled receptors (GPCRs) must be relayed to the cytoplasmic G protein binding side of the receptors. To decipher the role of water-mediated hydrogen-bond networks in this relay mechanism, we have developed graph-based algorithms and analysis methodologies applicable to datasets of static structures of distinct GPCRs. For a reference dataset of static structures of bovine rhodopsin solved at the same resolution, we show that graph analyses capture the internal protein-water hydrogen-bond network. The extended analyses of static structures of rhodopsins and opioid receptors suggest a relay mechanism whereby inactive receptors have in place much of the internal core hydrogen-bond network required for long-distance relay of structural change, with extensive local H-bond clusters observed in structures solved at high resolution and with internal water molecules.