A comprehensive map of molecular drug targets

A multi-omics target study for glioblastoma multiforme (GBM) based on Mendelian randomization analysis

Background

Glioblastoma multiforme (GBM) is the most frequent type of primary malignant brain tumor. This study utilized Mendelian randomization (MR) analysis to explore the causal link between proteins in plasma and cerebrospinal fluid and GBM.

Aims

This study aimed to identify proteins in both plasma and cerebrospinal fluid (CSF) that could serve as potential therapeutic targets for GBM.

Methods

We employed previously published protein quantitative trait loci (pQTL) data from CSF and plasma as the exposure data, alongside aggregated Genome-Wide Association Study (GWAS) data on GBM for our MR analysis. Furthermore, we conducted Bayesian co-localization analysis and examined the protein-protein interaction (PPI) networks of CSF and plasma proteins related to GBM risk.

Results

MR identified three key proteins linked to GBM risk: ribophorin I (RPN1) in plasma, von Willebrand factor (vWF) and macrophage-stimulating protein (MSP). in CSF. Elevated RPN1 and MSP were associated with decreased GBM risk, while increased vWF was linked to higher risk. External validation confirmed that RPN1 served as a key protein in GBM development. Bayesian co-localization showed a 10.35 % probability of a shared causal variant between RPN1 and GBM. Protein-protein interaction analysis further highlighted related proteins for RPN1.

Conclusions

In summary, the plasma protein RPN1 and the CSF proteins vWF and MSP are causally associated with the risk of GBM. Further research is needed to clarify the roles of these candidate proteins in GBM. Notably, RPN1 may serve as a potential therapeutic target for GBM. Future clinical studies on GBM treatment could explore drugs targeting RPN1.

Research progress in myocardial function and diseases related to muscarinic acetylcholine receptor (Review)

Muscarinic acetylcholine (ACh) receptors (also known as M receptors) are widely distributed in all organs and tissues of the body, mainly playing a role in cholinergic nerve conduction. There are five known subtypes of muscarinic ACh receptors, but their pharmacological mechanisms of action on myocardial function have remained to be clearly defined. Functional myocardial diseases and myocardial injuries, such as arrhythmia, myocardial ischemia, myocarditis and myocardial fibrosis, may be affected by muscarinic ACh receptors. This article reviews the research progress of the regulation of myocardial function by muscarinic ACh receptors and related diseases, with the aim of developing better strategies and providing references for further revealing and clarifying the signal transduction and mechanisms of muscarinic ACh receptors in cardiomyocytes, and finding potential myocardial protective drugs that act on muscarinic ACh receptors.

Genome-wide Mendelian randomization mapping the influence of plasma proteome on major depressive disorder

Plasma proteins play critical roles in a series of biological processes and represent a major source of translational biomarkers and drug targets. In this study, we performed Mendelian randomization (MR) to explore potential causal associations of protein quantitative trait loci (pQTL, n = 54,219) with major depressive disorder (MDD) using summary statistics from the PGC (n = 143,265) and further replicated in FinnGen cohort (n = 406,986). Subsequently, gene expression quantitative trait loci (eQTL) of identified proteins were leveraged to validate the primary findings in both PGC and FinnGen cohorts. We implemented reverse causality detection using bidirectional MR analysis, Steiger test, Bayesian co-localization and phenotype scanning to further strengthen the MR findings. In primary analyses, MR analysis revealed 2 plasma protein significantly associated with MDD risk at Bonferroni correction (P < 3.720 × 10-5), including butyrophilin subfamily 2 member A1 (BTN2A1, OR = 0.860; 95 % CI, 0.825-0.895; P = 1.79 × 10-5) and butyrophilin subfamily 3 member A2 (BTN3A2, OR = 1.071; 95 % CI, 1.056-1.086; P = 3.89 × 10-6). Both the identified proteins had no reverse causality. Bayesian co-localization indicated that BTN2A1 (coloc.abf-PPH4 = 0.620) and BTN3A2 (coloc.abf-PPH4 = 0.872) exhibited a shared variant with MDD, a finding that was subsequently validated by HEIDI test. In the replication stage, BTN2A1 and BTN3A2 were successfully validated in the FinnGen cohort. This study genetically determined BTN2A1 and BTN3A2 were associated with MDD and these findings may have clinical implications for MDD prevention.

Biased agonism in peptide-GPCRs: A structural perspective

G protein-coupled receptors (GPCRs) are dynamic membrane receptors that transduce extracellular signals to the cell interior by forming a ligand-receptor-effector (ternary) complex that functions via allosterism. Peptides constitute an important class of ligands that interact with their cognate GPCRs (peptide-GPCRs) to form the ternary complex. "Biased agonism", a therapeutically relevant phenomenon exhibited by GPCRs owing to their allosteric nature, has also been observed in peptide-GPCRs, leading to the development of selective therapeutics with fewer side effects. In this review, we have focused on the structural basis of signalling bias at peptide-GPCRs of classes A and B, and reviewed the therapeutic relevance of bias at peptide-GPCRs, with the hope of contributing to the discovery of novel biased peptide drugs.

Proteome-Wide Genetic Study in East Asians and Europeans Identified Multiple Therapeutic Targets for Ischemic Stroke

BACKGROUND

Analyses of genomic and proteomics data in prospective biobank studies in diverse populations may discover novel or repurposing drug targets for stroke.

METHODS

We extracted individual cis-protein quantitative trait locus for 2923 proteins measured using Olink Explore panel from a genome-wide association study in prospective China Kadoorie Biobank and UK Biobank, both established ≈20 years ago. These cis-protein quantitative trait loci were used in ancestry-specific 2-sample Mendelian randomization analyses of ischemic stroke (IS) in East Asians (n=22 664 cases) and Europeans (n=62 100 cases). We further undertook colocalization analyses to examine the shared causal variants of cis-protein quantitative trait locus with stroke, along with various downstream analyses (eg, phenome-wide association study, drug development lookups) to clarify mechanisms of action and druggability.

RESULTS

In Mendelian randomization analyses, the genetically predicted plasma levels of 10 proteins were significantly associated with IS in East Asians (n=2) and Europeans (n=9), with 6 proteins (FGF5 [fibroblast growth factor 5], TMPRSS5 [transmembrane protease serine 5], FURIN, F11 [coagulation factor XI], ALDH2 [aldehyde dehydrogenase 2], and ABO) showing positive and 4 (GRK5 [G protein-coupled receptor kinase 5], KIAA0319 [dyslexia-associated protein KIAA0319], PROCR [endothelial protein C receptor], and MMP12 [macrophage metalloelastase 12]) showing inverse associations, all directionally consistent between East Asians and Europeans. Colocalization analyses provided strong evidence (posterior probabilities for the H4 hypothesis ≥0.7) of shared genetic variants with IS for 9 out of 10 proteins (except ABO). Moreover, 8 proteins were also causally associated, in the expected directions, with systolic blood pressure (positive/inverse: 4/2), low-density lipoprotein cholesterol (1 positive), body mass index (1 inverse), type 2 diabetes (2/1), or atrial fibrillation (3/1). Phenome-wide association study analyses and lookups in knock-out mouse models confirmed their importance for IS or stroke-related traits (eg, hematologic phenotypes). Of these 10 proteins, 1 was not druggable (ABO), 3 had known primary (F11) or potentially repurposed (ALDH2, MMP12) drug targets for stroke, and 6 (PROCR, GRK5, FGF5, FURIN, KIAA0319, and TMPRSS5) had no evidence of any drug targets.

CONCLUSIONS

Proteogenomic investigation in diverse ancestry populations identified the causal relevance of 10 proteins for IS, with several being potentially novel or repurposed targets that could be prioritized for further investigation.

From Nuclear Receptors to GPCRs: a Deep Transfer Learning Approach for Enhanced Environmental Estrogen Recognition

Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic estrogen receptors (ERs) to induce genomic effects, as well as to G protein-coupled estrogen receptor (GPER) located on the membrane, thereby inducing downstream nongenomic effects rapidly. However, due to the relatively scarce ligand data, receptor-based or ligand-based screening models for GPER are challenging. Inspired by functional similarity between GPER and ER, this study constructs a deep transfer learning model named GPNET to predict potential GPER-binding ligands by using three-dimensional (3D) molecular surface electrostatic potential point clouds (SepPC) as input. The model retains a part of molecular structural knowledge learned from the ER ligands and then trains the remaining parameters of the model using the GPER ligands, ultimately obtaining the GPNET model, which effectively predicts the binding activity of compounds with GPER. GPNET outperforms From Scratch (nontransfer) model on the small data set, achieving the area under the receiver operating characteristic (ROC) curve (AUCROC) of 0.898 on the validation set and 0.863 on the test set, respectively. Furthermore, by visualizing the critical points and extracting the features from activation points of active ligands, the study provides a more in-depth interpretation of the molecular mechanism of two bisphenol A (BPA) alternatives binding to GPER.

The Orphan Receptor GPR151: Discovery, Expression, and Emerging Biological Significance

G protein-coupled receptors (GPCRs) are among the most prominent druggable targets in the human genome, accounting for approximately 40% of marketed drugs. Despite this, current GPCR-targeted therapies address only about 10% of the GPCRs encoded in the genome. Expanding our knowledge of the remaining "orphan" GPCRs represents a critical frontier in drug discovery. GPR151 emerges as a compelling target due to its distinct expression in the habenula complex, spinal cord neurons, and dorsal root ganglia. This receptor is highly conserved across mammals and possesses orthologs in species such as zebrafish and chickens, underscoring its evolutionarily conserved role in fundamental mammalian processes. Although the precise function of GPR151 remains unknown, it has been strongly implicated in pain modulation and reward-seeking behavior. These attributes position GPR151 as a promising candidate for the development of targeted and specialized pharmacological therapies. This review summarizes the current literature on GPR151, including its discovery, structure, mechanisms, anatomical distribution, and functional roles, while also exploring potential directions for future research.

GPRASP1 deletion in mice abrogates adverse side effects associated with chronic stimulation of Beta2-adrenoceptor

GPCR associated sorting protein 1 (GPRASP1) interacts with numerous GPCRs including the Beta2-adrenoceptor (B2AR) and has been proposed to be involved in adaptations associated with chronic stimulation of those receptors. In clinic, long acting B2AR agonists (LABAs) such as formoterol are used in the treatment of asthma as potent bronchodilators but with adverse side effects including the development of tolerance and airway hyperresponsiveness upon chronic administration. Here, we investigated the role of GPRASP1 on B2AR activity and on B2AR agonists-associated side effects in vitro and in vivo. To this purpose, we set-up a model of chronic formoterol administration in mouse leading to B2AR down-regulation as well as to the development of airway hyperreactivity and bronchodilator tolerance and studied the phenotype of GPRASP1 knockout animals. We show in cells that GPRASP1 expression has no impact on agonist-induced B2AR down-regulation but strongly modulate B2AR-associated signalling. Moreover, wild-type mice chronically treated with formoterol developed airway hyperresponsiveness to methacholine and bronchodilator tolerance to formoterol that were absent in GPRASP1 KO mice while B2AR down-regulation was similar in both genotypes. These adverse side effects were correlated with an increase in the number of cells and in collagen levels in the lungs of wild-type but not of GPRASP1 KO mice. Collectively, our data show that GPRASP1 is critically involved in adaptations to chronic activation of B2AR that leads to lung tissue remodelling, development of bronchial hyperresponsiveness and bronchodilator tolerance to B2AR agonist formoterol and could therefore represent an interesting target to limit side effects associated with LABAs.

Harnessing Nur77's mitochondrial apoptotic pathway: A promising therapeutic strategy for targeted disease intervention

The role of mitochondria in disease development cannot be overlooked, and the targeting of mitochondria for the treatment of disease has emerged as a significant area of research in recent years. Mitochondria are the control center of the intrinsic apoptotic pathway, and their normal functions are finely regulated by a series of complex mechanisms. The nuclear receptor Nur77 is closely related to the functions of the mitochondria and is an active pro-apoptotic member of the nuclear receptor superfamily. The translocation of Nur77 to the mitochondria can promote the conversion of the anti-apoptotic protein Bcl-2 to a pro-apoptotic state, disrupt the balance between mitochondrial fission and fusion, and inhibit mitophagy. These effects lead to irreversible damage to mitochondria and apoptosis, ultimately accelerating the progression of the disease. Here, we review the mechanism and targeted drug development of the mitochondrial apoptosis pathway activated by Nur77 in human diseases, helping to understand the new advances in disease treatment.

Engineered Proteins and Chemical Tools to Probe the Cell Surface Proteome

The cell surface proteome, or surfaceome, is the hub for cells to interact and communicate with the outside world. Many disease-associated changes are hard-wired within the surfaceome, yet approved drugs target less than 50 cell surface proteins. In the past decade, the proteomics community has made significant strides in developing new technologies tailored for studying the surfaceome in all its complexity. In this review, we first dive into the unique characteristics and functions of the surfaceome, emphasizing the necessity for specialized labeling, enrichment, and proteomic approaches. An overview of surfaceomics methods is provided, detailing techniques to measure changes in protein expression and how this leads to novel target discovery. Next, we highlight advances in proximity labeling proteomics (PLP), showcasing how various enzymatic and photoaffinity proximity labeling techniques can map protein-protein interactions and membrane protein complexes on the cell surface. We then review the role of extracellular post-translational modifications, focusing on cell surface glycosylation, proteolytic remodeling, and the secretome. Finally, we discuss methods for identifying tumor-specific peptide MHC complexes and how they have shaped therapeutic development. This emerging field of neo-protein epitopes is constantly evolving, where targets are identified at the proteome level and encompass defined disease-associated PTMs, complexes, and dysregulated cellular and tissue locations. Given the functional importance of the surfaceome for biology and therapy, we view surfaceomics as a critical piece of this quest for neo-epitope target discovery.

The crucial decade that ion channels were proven to exist : The vision of Bertil Hille and Clay Armstrong and how it came through

This retrospective begins with the first recording of the Na+ and K+ currents underlying the action potential in the giant squid axon reported by Hodgkin and Huxley in 1952, which made the question of where ions pass through the membrane more compelling. The notion of channels in the membrane had been around for quite some time but was so vague and contested that even the recording of Na+ and K+ currents through the membrane was not considered sufficient proof of their existence. In fact, Hodgkin and Huxley never referred to ion channels in their papers, only currents and conductances. The word "channel" remained somewhat left out from the scientific debate for almost another two decades, even though its idea was slowly making its way into the minds of discerning scientists. It is precisely this period that the present retrospective focuses on to understand the evolution of the ion channel concept from a speculative functional entity to a physical transmembrane object that serves the efficient and selective passage of ions. In this regard, the fundamental contribution of Bertil Hille and Clay Armstrong in promoting this idea, in the cold attitude, when not open aversion, of much of the scientific community, is fully acknowledged. Mention should also be made of Erwin Neher and Bert Sakmann's patch-clamp technique, which made it possible to directly measure ion currents through individual channels, thus conclusively demonstrating their presence in cell membranes. The retrospective goes on to briefly show how the cloning of ion channels in the 1980s and the first X-ray crystallographic structures at the turn of the century fully confirmed the initial suggestions, and closes by illustrating the relevance of ion channels in biology and medicine.

Therapeutic target prediction for orphan diseases integrating genome-wide and transcriptome-wide association studies

Therapeutic target identification is challenging in drug discovery, particularly for rare and orphan diseases. Here, we propose a disease signature, TRESOR, which characterizes the functional mechanisms of each disease through genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) data, and develop machine learning methods for predicting inhibitory and activatory therapeutic targets for various diseases from target perturbation signatures (i.e., gene knockdown and overexpression). TRESOR enables highly accurate identification of target candidate proteins that counteract disease-specific transcriptome patterns, and the Bayesian optimization with omics-based disease similarities achieves the performance enhancement for diseases with few or no known targets. We make comprehensive predictions for 284 diseases with 4345 inhibitory target candidates and 151 diseases with 4040 activatory target candidates, and elaborate the promising targets using several independent cohorts. The methods are expected to be useful for understanding disease-disease relationships and identifying therapeutic targets for rare and orphan diseases.

Similarity of drug targets to human microbiome metaproteome promotes pharmacological promiscuity

Similarity between candidate drug targets and human proteins is commonly assessed to minimize the occurrence of side effects. Although numerous drugs have been found to disrupt the health of the human microbiome, no comprehensive comparison between established drug targets and the human microbiome metaproteome has yet been conducted. Therefore, herein, sequence and structure alignments between human and pathogen drug targets and representative human gut, oral, and vaginal microbiome metaproteomes were performed. Both human and pathogen drug targets were found to be similar in sequence, function, structure, and drug binding capacity to proteins in diverse pathogenic and non-pathogenic bacteria from all three microbiomes. The gut metaproteome was identified as particularly susceptible overall to off-target effects. Certain symptoms, such as infections and immune disorders, may be more common among drugs that non-selectively target host microbiota. These findings suggest that similarities between human microbiome metaproteomes and drug target candidates should be routinely checked.

Strategies for in Silico Drug Discovery to Modulate Macromolecular Interactions Altered by Mutations

Most human diseases have genetic components, frequently single nucleotide variants (SNVs), which alter the wild type characteristics of macromolecules and their interactions. A straightforward approach for correcting such SNVs-related alterations is to seek small molecules, potential drugs, that can eliminate disease-causing effects. Certain disorders are caused by altered protein-protein interactions, for example, Snyder-Robinson syndrome, the therapy for which focuses on the development of small molecules that restore the wild type homodimerization of spermine synthase. Other disorders originate from altered protein-nucleic acid interactions, as in the case of cancer; in these cases, the elimination of disease-causing effects requires small molecules that eliminate the effect of mutation and restore wild type p53-DNA affinity. Overall, especially for complex diseases, pathogenic mutations frequently alter macromolecular interactions. This effect can be direct, i.e., the alteration of wild type affinity and specificity, or indirect via alterations in the concentration of the binding partners. Here, we outline progress made in methods and strategies to computationally identify small molecules capable of altering macromolecular interactions in a desired manner, reducing or increasing the binding affinity, and eliminating the disease-causing effect. When applicable, we provide examples of the outlined general strategy. Successful cases are presented at the end of the work.

At The Interface: Small-Molecule Inhibitors of Soluble Cytokines

Cytokines are crucial regulators of the immune system that orchestrate interactions between cells and, when dysregulated, contribute to the progression of chronic inflammation, cancer, and autoimmunity. Numerous biologic-based clinical agents, mostly monoclonal antibodies, have validated cytokines as important clinical targets and are now part of the standard of care for a number of diseases. These agents, while impactful, still suffer from limitations including a lack of oral bioavailability, high cost of production, and immunogenicity. Small-molecule cytokine inhibitors are attractive alternatives that can address these limitations. Although targeting cytokine-cytokine receptor complexes with small molecules has been a challenging research endeavor, multiple small-molecule inhibitors have now been identified, with a number of them undergoing clinical evaluation. In this review, we highlight the recent advancements in the discovery and development of small-molecule inhibitors targeting soluble cytokines. The strategies for identifying these novel ligands as well as the structural and mechanistic insights into their activity represent important milestones in tackling these challenging and clinically important protein-protein interactions.

Multi-omics analysis identifies diagnostic circulating biomarkers and potential therapeutic targets, revealing IQGAP1 as an oncogene in gastric cancer

This study employed a multi-omics integration approach to identify circulating biomarkers for gastric cancer (GC). We analyzed plasma and tumor tissue single-cell RNA sequencing data, along with gene and protein quantitative trait loci analyses. Leveraging data from UK Biobank and FinnGen, we investigated genetic associations with GC. Through colocalization, Mendelian Randomization, and various filtering analyses, we identified four genes (IQGAP1, KRTCAP2, PARP1, MLF2) and four proteins (EGFL9 [DLK2], ECM1, PDIA5, TIMP4) as potential GC biomarkers. These were selected based on significant genetic colocation probabilities and significant associations with GC. Seven of these biomarkers demonstrated predictive capability for GC occurrence, with AUC ranging from 0.61 to 0.99. Drug prediction analysis identified seven protein biomarkers as potential targets for immunotherapy, targeted therapies, and tumor chemotherapy. Further scRNA-seq analysis revealed significant expression differences between gastric tumor and normal tissues, particularly the upregulation of IQGAP1, which highlights its role in tumor growth.

NR4A1 Acts as a Novel Regulator of Platelet Activation and Thrombus Formation

BACKGROUND

Mounting evidence indicates that nuclear receptors play a critical regulatory role in platelet pathophysiology and thrombotic disorders. Although NR4A (the nuclear receptor subfamily 4 group A) plays an important role in cardiovascular pathophysiology, the expression profile and biological function of NR4A member 1 (NR4A1) in platelets have never been reported.

METHODS

We evaluated the functions and the underlying mechanisms of NR4A1 in platelet activation and thrombus formation using platelet-specific NR4A1-deficient mice and NR4A1-specific agonists. Using a hyperlipidemic mouse model and platelets from patients with hypercholesterolemia, we explored the influence of hypercholesterolemia on NR4A1 expression and the effects of NR4A1-specific agonists on platelet hyperreactivity induced by hypercholesterolemia.

RESULTS

NR4A1 was expressed in both human and mouse platelets. Platelet-specific NR4A1 deletion accelerated FeCl3-induced carotid arterial occlusive thrombus formation, enhanced collagen/epinephrine-induced pulmonary thromboembolism, and exacerbated microvascular microthrombi obstruction and infarct expansion in an acute myocardial infarction model. NR4A1-deficient platelets exhibited enhanced agonist-induced aggregation responses, integrin αIIbβ3 activation, dense granule release, α-granule release, platelet spreading, and clot retraction. Consistently, pharmacological activation of NR4A1 by specific agonists decreased platelet activation in both mouse and human platelets. Mechanistically, CAP1 (adenylyl cyclase-associated protein 1) was identified as the direct downstream interacting protein of NR4A1. NR4A1 deletion decreased cAMP levels and phosphorylation of VASP (vasodilator-stimulated phosphoprotein), while NR4A1-specific agonists increased cAMP levels and phosphorylation of VASP in platelets. Importantly, NR4A1 expression in platelets was upregulated in the setting of hypercholesterolemia, which was derived from its upregulation in megakaryocytes in a reactive oxygen species-dependent manner. Platelets from hypercholesterolemic patients and mice exhibited hyperreactivity. However, NR4A1-specific agonists significantly inhibited the activation of hypercholesterolemic platelets to the levels of healthy control platelets.

CONCLUSIONS

We provide the first evidence that nuclear receptor NR4A1 negatively regulates platelet activation and thrombus formation. NR4A1 may serve as a novel therapeutic target for managing thrombosis-based cardiovascular diseases, especially with hypercholesterolemia.

Genetically druggable targets for MAPK-activated colorectal cancer by a two-sample mendelian randomization analysis

Colorectal cancer (CRC) is a significant worldwide health issue, ranking second in women and third in men. Predictions estimate a rise to 2.5 million cases by 2035, with CRC being the fourth deadliest cancer due to delayed diagnosis and the scarcity of effective treatment options. Over 60% of CRC cases involve MAPK-activated signal pathways, particularly driven by RAS oncogene mutations, which hinder treatment responses, making them 'undruggable.' This study conducts a two-sample Mendelian randomization protein quantitative trait loci (pQTL) analysis to investigate the causal association between plasma proteins and MAPK-activated CRCs. The study indicates that four plasma proteins-MHC class I polypeptide-related sequence B (MICB), complement C4A, C4B, and interleukin-21 (IL-21) are associated with an increased risk of MAPK-activated CRCs. These findings highlight the possibility of utilizing plasma proteins as therapeutic targets and diagnostic markers to advance the fight against CRCs, indicating promising results for more effective interventions. To ascertain and expand upon these discoveries, further research is imperative to fully harness the potential of these discoveries.

An Estrogen Receptor β Agonist with AR Antagonist Activity from a Modern Asymmetric De Novo Steroid Synthesis

While the androgen receptor (AR) has long been a molecular target of prostate cancer therapeutics, the estrogen receptor β (ERβ) has more recently become of interest in this area of chemotherapeutic space due to its demonstrated role as a tumor suppressor. Here, we report studies that build on our earlier discovery of an exquisitely potent and selective steroidal agonist of ERβ that have resulted in the identification of a synthetic substituted estrane that, in reporter assays, is a potent and selective agonist of ERβ over ERα while also possessing activity as an antagonist of the AR that has potency within 7-fold of enzalutamide. Notably, this discovery was made possible by leveraging the power of our modern asymmetric de novo chemical synthesis of estranes that obviates the typical dependence on semisynthesis (natural product derivatization) for steroid-based medicinal chemistry.

PROTAC Delivery Strategies for Overcoming Physicochemical Properties and Physiological Barriers in Targeted Protein Degradation

Proteolysis targeting chimeras (PROTACs), heterobifunctional molecules that hijack the ubiquitin-proteasome system (UPS) to degrade specific proteins, hold great promise in treating diseases driven by traditionally "undruggable" targets. However, their large molecular weight, high hydrophobicity, and other physicochemical hurdles contribute to their limited bioavailability, suboptimal pharmacokinetics, and attenuated therapeutic efficacy. Consequently, diverse formulation innovations have been investigated to optimize PROTAC delivery. This review examines current challenges and advances in specialized drug delivery approaches designed to bolster PROTAC pharmacological performance. We first outline the fundamental limitations of PROTACs-their low aqueous solubility, poor cell permeability, rapid clearance, and concentration-dependent "hook effect". We then discuss how various enabling formulations address these issues, including polymeric micelles, emulsions, amorphous solid dispersions, lipid-based nanoparticles, liposomes, and exosomes. Collectively, these delivery technologies substantially improve the therapeutic outcomes of PROTACs in preclinical cancer models. Future applications may extend beyond oncology to address other complex diseases using newly emerging heterobifunctional molecules. By integrating advanced formulation science with innovative degrader design, the field stands poised to unlock the clinical potential of PROTACs for protein degradation therapies.

"Living Detergents": an in Situ Detergent Tailoring Strategy for Efficient Membrane Protein Stabilization and Analysis

Detergents are essential molecular tools for membrane protein (MP) research, yet traditional detergents with static properties often fail to address the diverse and evolving needs of MP studies. To this end, this study introduces "living detergents", an innovative class of detergents equipped with functional tags that enable bioorthogonal modifications with externally introduced structural elements. This approach allows for not only the parallel generation of new detergents, but also in situ tuning of MP samples within freshly formed detergents. The efficacy of this strategy was demonstrated through the rapid identification of optimal detergents for high-quality electron microscopy studies of A2AAR. Overall, this flexible and robust platform enables efficient tailoring of detergents, advancing the exploration of detergent structure-function relationships in MP research and opening pathways for more specialized solutions for diverse experimental demands.

Advances in solubilization and stabilization techniques for structural and functional studies of membrane proteins

Membrane proteins (MPs) are indispensable in various biological processes, including material transport, signal transduction, immune response, and cell recognition. Unraveling the intricate interplay between MP structure and function is pivotal for advancing fundamental biology and pharmaceutical research. However, the inherent hydrophobicity and complex lipid interactions of MPs pose significant challenges in determining their three-dimensional configurations. In recent years, cryo-electron microscopy (cryo-EM) has emerged as a powerful alternative for structural elucidation, overcoming the challenges faced by traditional techniques such as X-ray crystallography and nuclear magnetic resonance (NMR). This review centers on advanced solubilization and stabilization techniques for MPs, as well as MP functions and expression systems, highlighting the strengths and limitations of conventional detergents, liposomes, bicelles, and nanodiscs, alongside emerging alternatives like styrene-maleic acid (SMA) and diisobutylene-maleic acid (DIBMA). Notably, SMA and its derivatives provide promising detergent-free alternatives that preserve protein stability and native conformation, which is particularly valuable for accurate cryo-EM characterization of complex MPs. This work is designed to serve as both an updated resource for researchers already immersed in the field and an accessible entry point for those new to MP research. By consolidating recent advancements and highlighting critical gaps, this review aims to inspire future investigations that push the boundaries of MP structural and functional studies, ultimately driving innovations in drug discovery and therapeutic development.

A force-sensitive adhesion GPCR is required for equilibrioception

Equilibrioception (sensing of balance) is essential for mammals to perceive and navigate the three-dimensional world. A rapid mechanoelectrical transduction (MET) response in vestibular hair cells is crucial for detecting position and motion. Here, we identify the G protein-coupled receptor (GPCR) LPHN2/ADGRL2, expressed on the apical membrane of utricular hair cells, as essential for maintaining normal balance. Loss of LPHN2 specifically in hair cells impaired both balance behavior and the MET response in mice. Functional analyses using hair-cell-specific Lphn2-knockout mice and an LPHN2-specific inhibitor suggest that LPHN2 regulates tip-link-independent MET currents at the apical surface of utricular hair cells. Mechanistic studies in a heterologous system show that LPHN2 converts force stimuli into increased open probability of transmembrane channel-like protein 1 (TMC1). LPHN2-mediated force sensation triggers glutamate release and calcium signaling in utricular hair cells. Importantly, reintroducing LPHN2 into the hair cells of Lphn2-deficient mice restores vestibular function and MET response. Our data reveal that a mechanosensitive GPCR is required for equilibrioception.

Allosteric antibodies: a novel paradigm in drug discovery

Allostery represents a fundamental mechanism in protein regulation, enabling modulation of protein function from sites distal to the active site. While traditionally explored in the context of small molecules, allosteric modulation is gaining traction as a main mode of action in the realm of antibodies, which offer enhanced specificity and reduced toxicity. This review delves into the rapidly growing field of allosteric antibodies, highlighting recent therapeutic advancements and novel druggability avenues. We also explore the potential of these antibodies as innovative tools in drug discovery and discuss contemporary strategies for designing novel allosteric antibodies, leveraging state-of-the-art computational approaches.

Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery

G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at their orthosteric binding site. Despite their prominence, predicting the pharmacological effects of novel GPCR-targeting drugs remains challenging due to the complex functional dynamics of these receptors. Recent advances in X-ray crystallography, cryo-electron microscopy, spectroscopic techniques and molecular simulations have enhanced our understanding of receptor conformational dynamics and ligand interactions with GPCRs. These developments have revealed novel ligand-binding modes, mechanisms of action and druggable pockets. In this Review, we highlight such aspects for recently discovered small-molecule drugs and drug candidates targeting GPCRs, focusing on three categories: allosteric modulators, biased ligands, and bivalent and bitopic compounds. Although studies so far have largely been retrospective, integrating structural data on ligand-induced receptor functional dynamics into the drug discovery pipeline has the potential to guide the identification of drug candidates with specific abilities to modulate GPCR interactions with intracellular effector proteins such as G proteins and β-arrestins, enabling more tailored selectivity and efficacy profiles.

Biased signaling in drug discovery and precision medicine

Receptors are crucial for converting chemical and environmental signals into cellular responses, making them prime targets in drug discovery, with about 70% of drugs targeting these receptors. Biased signaling, or functional selectivity, has revolutionized drug development by enabling precise modulation of receptor signaling pathways. This concept is more firmly established in G protein-coupled receptor and has now been applied to other receptor types, including ion channels, receptor tyrosine kinases, and nuclear receptors. Advances in structural biology have further refined our understanding of biased signaling. This targeted approach enhances therapeutic efficacy and potentially reduces side effects. Numerous biased drugs have been developed and approved as therapeutics to treat various diseases, demonstrating their significant therapeutic potential. This review provides a comprehensive overview of biased signaling in drug discovery and disease treatment, highlighting recent advancements and exploring the therapeutic potential of these innovative modulators across various diseases.

GPCR oligomerization across classes: A2AR-mediated regulation of mGlu5R activation

The adenosine A2A receptor (A2AR), a class A GPCR, is a known player in neurological diseases, including Parkinson's disease and Alzheimer's disease, and is also implicated in SARS-CoV-2 infection. Recent studies have revealed its oligomerization with metabotropic glutamate receptor type 5 (mGlu5R), a class C G protein coupled receptor (GPCR) that exists in the homodimeric form. Simultaneous activation of both receptors synergistically enhances mGlu5R-mediated effects in the hippocampus. Despite their importance, the molecular mechanisms governing these interactions remain unclear. In this study, we used molecular modelling techniques, including molecular docking, extensive molecular dynamics (MD) simulations, and detailed analysis, to elucidate the interactions between mGlu5R and A2AR in the inactive and active states. Our findings provide molecular-level insights into the permissive role of A2AR in mGlu5R activation, demonstrating that the inactive A2AR interface within the oligomer blocks the mGlu5R transmembrane helix 6 (TM6), which is crucial for activation. Upon A2AR activation, the oligomer interface undergoes conformational rearrangement, exposing mGlu5R-TM6 and allowing for mGlu5R activation. Furthermore, we identified a pivotal role of the mGlu5R-TM4:A2AR-TM4 interface in facilitating mGlu5R activation. These results highlight the intricate architecture of the mGlu5R:A2AR oligomer, advancing our understanding of GPCR oligomerization and its regulatory mechanisms on receptor activity.

Emerging magic bullet: subcellular organelle-targeted cancer therapy

The therapeutic efficacy of anticancer drugs heavily relies on their concentration and retention at the corresponding target site. Hence, merely increasing the cellular concentration of drugs is insufficient to achieve satisfactory therapeutic outcomes, especially for the drugs that target specific intracellular sites. This necessitates the implementation of more precise targeting strategies to overcome the limitations posed by diffusion distribution and nonspecific interactions within cells. Consequently, subcellular organelle-targeted cancer therapy, characterized by its exceptional precision, have emerged as a promising approach to eradicate cancer cells through the specific disruption of subcellular organelles. Owing to several advantages including minimized dosage and side effect, optimized efficacy, and reversal of multidrug resistance, subcellular organelle-targeted therapies have garnered significant research interest in recent years. In this review, we comprehensively summarize the distribution of drug targets, targeted delivery strategies at various levels, and sophisticated strategies for targeting specific subcellular organelles. Additionally, we highlight the significance of subcellular targeting in cancer therapy and present essential considerations for its clinical translation.

Global analysis of ligand-gated ion channel conservation across Platyhelminthes

Ligand-gated ion channels (LGICs) are critical for neurotransmission, mediating responses to neurotransmitters and hormones, and influencing diverse physiological processes. This study identifies and classifies LGICs across Platyhelminthes, with a particular focus on parasitic neodermatans, which impact human and animal health. Using bioinformatics tools, we analyzed LGICs from 41 neodermatan species and expanded our investigation to encompass vertebrates, other invertebrates, and non-bilaterians to trace LGIC evolutionary pathways across Metazoa. We identified 2,269 putative LGICs within neodermatan species, which we classified into the cys-loop, ASIC/Deg/ENaC, iGluR, and P2X families. Our phylogenetic and clustering analyses reveal lineage-specific patterns with distinct evolutionary trajectories for each LGIC family in neodermatans compared to free-living platyhelminths and other taxa. Notably, the ASIC/Deg/ENaC family displayed the greatest degree of neodermatan-specific divergence, while cys-loop and P2X families were more conserved across taxa. To provide insight into their potential physiological roles, we analyzed LGIC expression patterns in Schistosoma mansoni, revealing widespread expression across neuronal and muscle cell types. The distribution of acid-sensing ion channels (ASICs) in both neurons and muscles suggests a role in neuromuscular signalling, while the P2X receptor (Smp_333600) exhibited sex-specific expression, potentially indicating distinct functional roles in males and females. Additionally, several cys-loop acetylcholine and GABA receptors showed differential neuronal and muscle expression, highlighting their likely contributions to cholinergic and inhibitory neurotransmission. These findings underscore the relevance of LGICs in parasite physiology, particularly in neuromuscular and sensory processes, and suggest potential targets for antiparasitic interventions.

GalNac-siRNA conjugate delivery technology promotes the treatment of typical chronic liver diseases

INTRODUCTION

Nucleic acid-based therapeutics have become a key pillar of the 'third wave' of modern medicine, following the eras of small molecule inhibitors and antibody drugs. Their rapid progress is heavily dependent on delivery technologies, with the development of N-acetylgalactosamine (GalNAc) conjugates marking a breakthrough in targeting liver diseases. This technology has gained significant attention for its role in addressing chronic conditions like chronic hepatitis B (CHB) and nonalcoholic steatohepatitis (NASH), which are challenging to treat with conventional methods.

AREAS COVERED

This review explores the origins, mechanisms, and advantages of GalNAc-siRNA delivery systems, highlighting their ability to target hepatocytes via the asialoglycoprotein receptor (ASGPR). The literature reviewed covers preclinical and clinical advancements, particularly in CHB and NASH. Key developments in stabilization chemistry and conjugation technologies are examined, emphasizing their impact on enhancing therapeutic efficacy and patient compliance.

EXPERT OPINION

GalNAc-siRNA technology represents a transformative advancement in RNA interference (RNAi) therapies, addressing unmet needs in liver-targeted diseases. While significant progress has been made, challenges remain, including restricted targeting scope and scalability concerns. Continued innovation is expected to expand applications, improve delivery efficiency, and overcome limitations, establishing GalNAc-siRNA as a cornerstone for future nucleic acid-based treatments.

Molecular mechanism of the arrestin-biased agonism of neurotensin receptor 1 by an intracellular allosteric modulator

Biased allosteric modulators (BAMs) of G protein-coupled receptors (GPCRs) have been at the forefront of drug discovery owing to their potential to selectively stimulate therapeutically relevant signaling and avoid on-target side effects. Although structures of GPCRs in complex with G protein or GRK in a BAM-bound state have recently been resolved, revealing that BAM can induce biased signaling by directly modulating interactions between GPCRs and these two transducers, no BAM-bound GPCR-arrestin complex structure has yet been determined, limiting our understanding of the full pharmacological profile of BAMs. Herein, we developed a chemical protein synthesis strategy to generate neurotensin receptor 1 (NTSR1) with defined hexa-phosphorylation at its C-terminus and resolved high-resolution cryo-EM structures (2.65-2.88 Å) of NTSR1 in complex with both β-arrestin1 and the BAM SBI-553. These structures revealed a unique "loop engagement" configuration of β-arrestin1 coupling to NTSR1 in the presence of SBI-553, markedly different from the typical "core engagement" configuration observed in the absence of BAMs. This configuration is characterized by the engagement of the intracellular loop 3 of NTSR1 with a cavity in the central crest of β-arrestin1, representing a previously unobserved, arrestin-selective conformation of GPCR. Our findings fill the critical knowledge gap regarding the regulation of GPCR-arrestin interactions and biased signaling by BAMs, which would advance the development of safer and more efficacious GPCR-targeted therapeutics.

Molecule-rich solutions for achieving novel non-opioid analgesics

Despite their efficacy, opioids have long been associated with risks of addiction, tolerance, and dependence, leaving an unmet clinical need for pain treatment. Efforts have been devoted to developing novel classes of pain-relieving medication that outperform current options in terms of pain relief, side-effect profiles, and potential for abuse, but with limited success. Recent advances in the neurobiology of pain have shed light on the potential of targeting non-opioid receptors involved in pain processing. In this review, we identify avenues, ranging from molecular-based approaches to molecule-rich solutions, for effectively identifying non-opioid analgesics free from the side effects associated with opioids.

A Proteomic Signature for Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma Predicts Patients at High Risk of Recurrence

SIGNIFICANCE

HPV+OPSCC incidence is increasing, with heterogeneous treatment outcomes despite favorable prognosis. Current de-escalation strategies show inferior results, highlighting the need for precise risk stratification. Using data-independent acquisition mass spectrometry proteomics, we identified a 26-peptide signature that stratifies patients into risk categories, potentially enabling personalized treatment decisions and optimal patient selection for de-escalation trials.

Lentinan enhances microbiota-derived isoursodeoxycholic acid levels to alleviate hepatic ischemia-reperfusion injury in mice

Hepatic ischemia-reperfusion injury (HIRI) is an essential clinical concern caused by liver transplantation, resection, trauma, and shock that must be addressed immediately. Although the mechanisms underlying HIRI are well-documented, effective prevention and treatment strategies are still lacking. Inflammation is a central mechanism of HIRI, with macrophages playing a crucial role in initiating and amplifying the inflammatory response. Numerous plant polysaccharides exhibit substantial anti-inflammatory and hepatoprotective properties. However, the function of Lentinan (LNT) in HIRI has not been fully explored. Thus, this study aims to investigate the preventive potential of LNT in HIRI. Here, we reveal that oral administration of LNT considerably reduces hepatic inflammation and improves liver pathology in mice with HIRI by modulating gut microbiota. Specifically, LNT considerably increased microbiota-derived isoursodeoxycholic acid (IsoUDCA). Further experiments showed that IsoUDCA alleviates hepatic injury by suppressing macrophage inflammation. Mechanistically, IsoUDCA directly binds to and activates the neuron-derived clone 77 (Nur77) transcription factor, inhibiting the NF-κB signaling pathway in macrophages. Our findings shed light on the significant role of the LNT-microbiota-IsoUDCA-Nur77 axis in attenuating macrophage inflammation during HIRI, offering novel insights into potential therapeutic targets and avenues for preventing HIRI.

Strategy for drug repurposing in fibroadipogenic replacement during muscle wasting: application to duchenne muscular dystrophy

Background

Understanding the cell functionality during disease progression or drugs' mechanism are major challenges for precision medicine. Predictive models describing biological phenotypes can be challenging to obtain, particularly in scenarios where sample availability is limited, such as in the case of rare diseases. Here we propose a new method that reproduces the fibroadipogenic expansion that occurs in muscle wasting.

Methods

We used immortalized fibroadipogenic progenitor cells (FAPs) and differentiated them into fibroblasts or adipocytes. The method successfully identified FAPs cell differentiation fate using accurate measurements of changes in specific proteins, which ultimately constitute a valid cellular in vitro platform for drug screening. Results were confirmed using primary FAPs differentiation as well as comparison with omics data from proteomics and genomic studies.

Results

Our method allowed us to screen 508 different drugs from 2 compounds libraries. Out of these 508, we identified 4 compounds that reduced fibrogenesis and adipogenesis of ≥30% of fibrogenesis and adipogenesis using immortalized cells. After selecting the optimal dose of each compound, the inhibitory effect on FAP differentiation was confirmed by using primary FAPs from healthy subjects (n = 3) and DMD patients (n = 3). The final 4 selected hits reduced fibrogenic differentiation in healthy and DMD samples. The inhibition of adipogenesis was more evident in DMD samples than healthy samples. After creating an inhibitory map of the tested drugs, we validated the signalling pathways more involved in FAPs differentiation analysing data from proteomic and genomic studies.

Conclusion

We present a map of molecular targets of approved drugs that helps in predicting which therapeutic option may affect FAP differentiation. This method allows to study the potential effect of signalling circuits on FAP differentiation after drug treatment providing insights into molecular mechanism of action of muscle degeneration. The accuracy of the method is demonstrated by comparing the signal pathway activity obtained after drug treatment with proteomic and genomic data from patient-derived cells.

A new paradigm for drug discovery in the treatment of complex diseases: drug discovery and optimization

In the past, the drug research and development has predominantly followed a "single target, single disease" model. However, clinical data show that single-target drugs are difficult to interfere with the complete disease network, are prone to develop drug resistance and low safety in clinical use. The proposal of multi-target drug therapy (also known as "cocktail therapy") provides a new approach for drug discovery, which can affect the disease and reduce adverse reactions by regulating multiple targets. Natural products are an important source for multi-target innovative drug development, and more than half of approved small molecule drugs are related to natural products. However, there are many challenges in the development process of natural products, such as active drug screening, target identification and preclinical dosage optimization. Therefore, how to develop multi-target drugs with good drug resistance from natural products has always been a challenge. This article summarizes the applications and shortcomings of related technologies such as natural product bioactivity screening, clarify the mode of action of the drug (direct/indirect target), and preclinical dose optimization. Moreover, in response to the challenges faced by natural products in the development process and the trend of interdisciplinary and multi-technology integration, and a multi-target drug development strategy of "active substances - drug action mode - drug optimization" is proposed to solve the key challenges in the development of natural products from multiple dimensions and levels.

A quantitative analysis of ligand binding at the protein-lipid bilayer interface

The majority of drugs target membrane proteins, and many of these proteins contain ligand binding sites embedded within the lipid bilayer. However, targeting these therapeutically relevant sites is hindered by limited characterization of both the sites and the molecules that bind to them. Here, we introduce the Lipid-Interacting LigAnd Complexes Database (LILAC-DB), a curated dataset of 413 structures of ligands bound at the protein-bilayer interface. Analysis of these structures reveals that ligands binding to lipid-exposed sites exhibit distinct chemical properties, such as higher calculated partition coefficient (clogP), molecular weight, and a greater number of halogen atoms, compared to ligands that bind to soluble proteins. Additionally, we demonstrate that the atomic properties of these ligands vary significantly depending on their depth within and exposure to the lipid bilayer. We also find that ligand binding sites exposed to the bilayer have distinct amino acid compositions compared to other protein regions, which may aid in the identification of lipid-exposed binding sites. This analysis provides valuable guidelines for researchers pursuing structure-based drug discovery targeting underexploited ligand binding sites at the protein-lipid bilayer interface.

Towards a unified molecular mechanism for liganddependent activation of NR4A-RXR heterodimers

A subset of nuclear receptors (NRs) function as permissive heterodimers with retinoid X receptor (RXR), defined by transcriptional activation in response to binding RXR agonist ligands. Permissive NR-RXR activation operates via a classical pharmacological mechanism, where binding of an RXR agonist increases coactivator recruitment to the heterodimer. However, we previously demonstrated that transcriptional activation of permissive Nurr1-RXRα (NR4A2-NR2B1) heterodimers by an RXR ligand set, which included pharmacological RXR agonists and selective Nurr1-RXRα agonists that function as antagonists of RXRα homodimers, occurs via a non-classical mechanism: ligand-binding domain (LBD) heterodimer dissociation (Yu et al., 2023). Here, we extend mechanistic ligand profiling of the same RXR ligand set to Nur77-RXRγ (NR4A1-NR2B3), which is evolutionarily related to Nurr1-RXRα. Biochemical and NMR protein-protein interaction profiling along with cellular transcription studies indicate that the RXR ligand set, which lacks selective Nur77-RXRγ agonists, may influence Nur77-RXRγ transcriptional activation through both classical pharmacological activation and LBD heterodimer dissociation. However, upon reanalyzing our previously published data for Nurr1-RXRα, we found that the inclusion of selective Nurr1-RXRα agonists was essential for elucidating the LBD heterodimer dissociation mechanism. Our findings underscore the need for a more functionally diverse RXR ligand set to explore Nur77-RXRγ activation and unify LBD heterodimer dissociation as a potential targeting mechanism for NR4A-RXR heterodimers in neurodegenerative and inflammatory diseases.

Leveraging Artificial Intelligence and Machine Learning for Characterizing Protein Corona, Nanobiological Interactions, and Advancing Drug Discovery

Proteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), including the protein corona's formation, significantly affect NP behavior, biodistribution, cellular uptake, and toxicity. Comprehending these interactions is pivotal for advancing the design of NPs to augment their efficacy and safety in biomedical applications. While traditional nanomedicine design relies heavily on experimental work, the use of data science and machine learning (ML) is on the rise to predict the synthesis and behavior of nanomaterials (NMs). Nanoinformatics combines computational simulations with laboratory studies, assessing risks and revealing complex nanobio interactions. Recent advancements in artificial intelligence (AI) and ML are enhancing the characterization of the protein corona and improving drug discovery. This review discusses the advantages and limitations of these approaches and stresses the importance of comprehensive datasets for better model accuracy. Future developments may include advanced deep-learning models and multimodal data integration to enhance protein function prediction. Overall, systematic research and advanced computational tools are vital for improving therapeutic outcomes and ensuring the safe use of NMs in medicine.

Epitope-directed selection of GPCR nanobody ligands with evolvable function

Antibodies have the potential to target G protein-coupled receptors (GPCRs) with high receptor, cellular, and tissue selectivity; however, few antibody ligands for GPCRs exist. Here, we describe a generalizable selection method to enrich for GPCR ligands from a synthetic camelid antibody fragment (nanobody) library. Our strategy yielded multiple nanobody ligands for the angiotensin II type I receptor (AT1R), a prototypical GPCR and important drug target. We found that nanobodies readily act as allosteric modulators, encoding selectivity for both the receptor and chemical features of GPCR ligands. We then used structure-guided design to convert two nanobodies from allosteric ligands to competitive AT1R inhibitors through simple mutations. This work demonstrates that nanobodies can encode multiple pharmacological behaviors and have great potential as evolvable scaffolds for the development of next-generation GPCR therapeutics.

Fab-Induced Stabilization of an Ion Channel Receptor Enables Mechanistic Characterization of Small-Molecule Therapeutics

Developing small-molecule (SM) therapeutics that target membrane proteins (MPs) is often challenging, because few biophysical methods can handle the detergents required to maintain target stability. Here, we report a surface plasmon resonance (SPR)-based methodology that enables the characterization of interactions between SMs and an ion channel receptor (MP1) in complex with a stabilizing antibody fragment (Fab) and surfactant. Briefly, a stable MP1-Fab complex was formed by coimmobilizing MP1 with an anti-MP1-Fab within the hydrogel film to study the interactions of MP1 with SMs. The critical micelle concentration (CMC) is the concentration at which 50% of the surfactant monomers are assembled into micelles. Micelles readily absorb compounds resulting in compound-loaded micelles that generate high nonspecific binding and hinder resolution of SM binding responses. This micelle-induced interference was avoided by utilizing a weak detergent at a concentration below its CMC, allowing for the resolution of compound binding to a solvent-exposed pocket. Additional Fab stabilization was required to rescue binding at a second pocket buried within the transmembrane region of MP1. The resulting SPR-based assay proved invaluable during hit-to-lead optimization by progressing structure-activity relationship (SAR) studies and resolving the mechanism of action (MoA).

T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment

There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to accurately predict the binding affinity of small molecules to a protein target in silico enables the rapid identification of candidate inhibitors and facilitates the optimization of on-target potency. In this work, we present T-ALPHA, a novel deep learning model that enhances protein-ligand binding affinity prediction by integrating multimodal feature representations within a hierarchical transformer framework to capture information critical to accurately predicting binding affinity. T-ALPHA outperforms all existing models reported in the literature on multiple benchmarks designed to evaluate protein-ligand binding affinity scoring functions. Remarkably, T-ALPHA maintains state-of-the-art performance when utilizing predicted structures rather than crystal structures, a powerful capability in real-world drug discovery applications where experimentally determined structures are often unavailable or incomplete. Additionally, we present an uncertainty-aware self-learning method for protein-specific alignment that does not require additional experimental data and demonstrate that it improves T-ALPHA's ability to rank compounds by binding affinity to biologically significant targets such as the SARS-CoV-2 main protease and the epidermal growth factor receptor. To facilitate implementation of T-ALPHA and reproducibility of all results presented in this paper, we made all of our software available at https://github.com/gregory-kyro/T-ALPHA.

Evaluating student understanding of pharmacodynamics core concepts

Pharmacodynamics is an essential subdiscipline of pharmacology that underpins safe and effective prescribing and therapeutic decision-making, as well as drug discovery and development. The exponential increase in the number of therapeutic drugs has prompted members of the pharmacology educator community to question existing pharmacology curricula focused on individual drugs and move toward a curriculum focused on conceptual understanding. A first step towards conceptual understanding is to establish what students currently know about pharmacodynamic core concepts. A total of 218 students from 10 universities were invited to complete a questionnaire that assessed their understanding of drug efficacy, drug-target interaction, drug tolerance, and structure-activity relationship. Pairs of pharmacology experts independently assessed each student's response and flagged any misconceptions that arose. The experts then compared their evaluations, achieved a consensus decision, and grouped the misconceptions into themes. Less than 25% of students provided core concept meanings that fully aligned with those of the expert group. By contrast, more than 75% of students could apply the core concept to a novel scenario at least in part. Overall, 480 misconceptions were identified and grouped into 55 misconception themes. The concept of drug efficacy was the core concept with which students struggled most. It is unclear why students were better able to apply their knowledge than to define the core concepts, although this might reflect a focus on active learning in pharmacology courses globally. The deficits in defining and understanding pharmacodynamic core concepts, and the misconceptions revealed in student responses, can be used by educators to guide their efforts.

Protein Drug Targets for Abdominal Aortic Aneurysm and Proteomic Associations Between Modifiable Risk Factors and Abdominal Aortic Aneurysm

BACKGROUND

Abdominal aortic aneurysm (AAA) is a severe aortic disease for which no pharmacological interventions have yet been developed. This investigation focused on identifying protein-based therapeutic targets and assessing how proteins mediate the interplay between modifiable risk factors and AAA development.

METHODS

Causal inferences between plasma proteins and AAA were drawn using 2-sample Mendelian randomization, followed by comprehensive sensitivity testing, colocalization, and replication efforts. Further analyses included database interrogation, single-cell RNA data analysis, enrichment analysis, protein-protein interaction networks, and immunohistochemistry to map the tissue-specific expression of these proteins, their expression within AAA tissues, and their biological roles. Mediation Mendelian randomization was employed to evaluate the mediating effects of AAA-related proteins on the associations between AAA and 3 risk factors: hypertension, smoking, and obesity.

RESULTS

A total of 43 proteins were identified as having causal links to AAA. Colocalization analysis pinpointed 13 proteins with strong evidence of colocalization with AAA. Of these, the causal involvement of 10 proteins was substantiated by external validation data. Consistent evidence for PCSK9 (proprotein convertase subtilisin/kexin type 9), IL6R (interleukin-6R), ECM1 (extracellular matrix protein 1), and ANGPTL4 (angiopoietin-related protein 4) was further validated through tissue immunohistochemistry and blood data. Moreover, Mendelian randomization analysis identified 10 proteins as mediators of the influence of hypertension, smoking, and obesity on AAA development.

CONCLUSIONS

This analysis identifies 4 proteins (PCSK9, IL6R, ECM1, and ANGPTL4) as high-priority therapeutic targets for AAA and emphasizes the intermediary role of plasma proteins in linking hypertension, smoking, obesity, and AAA. Further investigations are needed to clarify the specific roles of these proteins in AAA pathology.

GPCR drug discovery: new agents, targets and indications

G protein-coupled receptors (GPCRs) form one of the largest drug target families, reflecting their involvement in numerous pathophysiological processes. In this Review, we analyse drug discovery trends for the GPCR superfamily, covering compounds, targets and indications that have reached regulatory approval or that are being investigated in clinical trials. We find that there are 516 approved drugs targeting GPCRs, making up 36% of all approved drugs. These drugs act on 121 GPCR targets, one-third of all non-sensory GPCRs. Furthermore, 337 agents targeting 133 GPCRs, including 30 novel targets, are being investigated in clinical trials. Notably, 165 of these agents are approved drugs being tested for additional indications and novel agents are increasingly allosteric modulators and biologics. Remarkably, diabetes and obesity drugs targeting GPCRs had sales of nearly US $30 billion in 2023 and the numbers of clinical trials for GPCR modulators in the metabolic diseases, oncology and immunology areas are increasing strongly. Finally, we highlight the potential of untapped target-disease associations and pathway-biased signalling. Overall, this Review provides an up-to-date reference for the drugged and potentially druggable GPCRome to inform future GPCR drug discovery and development.

Unraveling the role of proteins in dementia: insights from two UK cohorts with causal evidence

Population-based proteomics offers a groundbreaking avenue to predict future disease risks, enhance our understanding of disease mechanisms, and discover novel therapeutic targets and biomarkers. The role of plasma proteins in dementia, however, requires further exploration. This study investigated 276 protein-dementia associations in 229 incident all-cause dementia, 89 Alzheimer's disease, and 41 vascular dementia among 3249 participants (55% women, 97.2% white ethnicity) from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up. We used Cox proportional hazard regression for the analysis. Receiver operating characteristic analyses were conducted to assess the precision of the identified proteins from the fully adjusted Cox regression models in predicting incident all-cause dementia, both individually and in combination with demographic predictors, APOE genotype, and memory score, to estimate the area under the curve. Additionally, the eXtreme Gradient Boosting machine learning algorithm was used to identify the most important features predictive of future all-cause dementia onset. These associations were then validated in 1506 incident all-cause dementia, 732 Alzheimer's disease, 281 vascular dementia, and 111 frontotemporal dementia cases among 52 745 individuals (53.9% women, 93.3% White ethnicity) from the UK Biobank over a median 13.7-year follow-up. Two-sample bi-directional Mendelian randomization and drug target Mendelian randomization were further employed to determine the causal direction between protein concentration and dementia. NEFL (hazard ratio [HR] [95% confidence intervals (CIs)]: 1.54 [1.29, 1.84]) and RPS6KB1 (HR [95% CI]: 1.33 [1.16, 1.52]) were robustly associated with incident all-cause dementia; MMP12 (HR [95% CI]: 2.06 [1.41, 2.99]) was associated with vascular dementia in ELSA, after correcting for multiple testing. Additional markers EDA2R and KIM1 were identified from subgroup and sensitivity analyses. Combining NEFL and RPS6KB1 with other predictors yielded high predictive accuracy (area under the curve = 0.871) for incident all-cause dementia. The eXtreme Gradient Boosting machine learning algorithm also identified RPS6KB1, NEFL, and KIM1 as the most important protein features for predicting future all-cause dementia. Sex difference was evident for the association between RPS6KB1 and all-cause dementia, with stronger association in men (P for interaction = 0.037). Replication in the UK Biobank confirmed the associations between the identified proteins and various dementia subtypes. The results from Mendelian randomization in the reverse direction indicated that several proteins serve as early markers for dementia, rather than being direct causes of the disease. These findings provide insights into putative mechanisms for dementia. Future studies are needed to validate the findings on RPS6KB1 in relation to dementia risk.

Mendelian randomization identifies proteins involved in neurodegenerative diseases

Proteins are involved in multiple biological functions. High-throughput technologies have allowed the measurement of thousands of proteins in population biobanks. In this study, we aimed to identify proteins related to Alzheimer's disease, Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis by leveraging large-scale genetic and proteomic data. We performed a two-sample cis Mendelian randomization study by selecting instrumental variables for the abundance of >2700 proteins measured by either Olink or SomaScan platforms in plasma from the UK Biobank and the deCODE Health Study. We also used the latest publicly available genome-wide association studies for the neurodegenerative diseases of interest. The potentially causal effect of proteins on neurodegenerative diseases was estimated based on the Wald ratio. We tested 13 377 protein-disease associations, identifying 169 associations that were statistically significant (5% false discovery rate). Evidence of co-localization between plasma protein abundance and disease risk (posterior probability > 0.80) was identified for 61 protein-disease pairs, leading to 50 unique protein-disease associations. Notably, 23 of 50 protein-disease associations corresponded to genetic loci not previously reported by genome-wide association studies. The two-sample Mendelian randomization and co-localization analysis also showed that APOE abundance in plasma was associated with three subcortical volumes (hippocampus, amygdala and nucleus accumbens) and white matter hyper-intensities, whereas PILRA and PILRB abundance in plasma was associated with caudate nucleus volume. Our study provided a comprehensive assessment of the effect of the human proteome that is currently measurable through two different platforms on neurodegenerative diseases. The newly associated proteins indicated the involvement of complement (C1S and C1R), microglia (SIRPA, SIGLEC9 and PRSS8) and lysosomes (CLN5) in Alzheimer's disease; the interleukin-6 pathway (CTF1) in Parkinson's disease; lysosomes (TPP1), blood-brain barrier integrity (MFAP2) and astrocytes (TNFSF13) in amyotrophic lateral sclerosis; and blood-brain barrier integrity (VEGFB), oligodendrocytes (PARP1), node of Ranvier and dorsal root ganglion (NCS1, FLRT3 and CDH15) and the innate immune system (CR1, AHSG and WARS) in multiple sclerosis. Our study demonstrates how harnessing large-scale genomic and proteomic data can yield new insights into the role of the plasma proteome in the pathogenesis of neurodegenerative diseases.

RNA aptamer-mediated RNA nanotechnology for potential treatment of cardiopulmonary diseases

Ribonucleic acid (RNA) aptamers are single-stranded RNAs that bind to target proteins or other molecules with high specificity and affinity, modulating biological functions through distinct mechanisms. These aptamers can act n as antagonists to block pathological interactions, agonists to activate signaling pathways, or delivery vehicles for therapeutic cargos such as siRNAs and miRNAs. The advances in RNA nanotechnology further enhances the versatility of RNA aptamers, offering scalable platforms for engineering. In this review, we have summarized recent developments in RNA aptamer-mediated RNA nanotechnology and provide an overview of its potential in treating cardiovascular and respiratory disorders, including atherosclerosis, acute coronary syndromes, heart failure, lung cancer, pulmonary hypertension, asthma, chronic obstructive pulmonary disease (COPD), acute lung injury, viral respiratory infections, and pulmonary fibrosis. By integrating aptamer technologies with innovative delivery systems, RNA aptamers hold the potential to revolutionize the treatment landscape for cardiopulmonary diseases.

Plasma proteomic signatures of social isolation and loneliness associated with morbidity and mortality

The biology underlying the connection between social relationships and health is largely unknown. Here, leveraging data from 42,062 participants across 2,920 plasma proteins in the UK Biobank, we characterized the proteomic signatures of social isolation and loneliness through proteome-wide association study and protein co-expression network analysis. Proteins linked to these constructs were implicated in inflammation, antiviral responses and complement systems. More than half of these proteins were prospectively linked to cardiovascular disease, type 2 diabetes, stroke and mortality during a 14 year follow-up. Moreover, Mendelian randomization (MR) analysis suggested causal relationships from loneliness to five proteins, with two proteins (ADM and ASGR1) further supported by colocalization. These MR-identified proteins (GFRA1, ADM, FABP4, TNFRSF10A and ASGR1) exhibited broad associations with other blood biomarkers, as well as volumes in brain regions involved in interoception and emotional and social processes. Finally, the MR-identified proteins partly mediated the relationship between loneliness and cardiovascular diseases, stroke and mortality. The exploration of the peripheral physiology through which social relationships influence morbidity and mortality is timely and has potential implications for public health.

Design, synthesis, and screening of an RNA optimized fluorinated fragment library

Fragment-based screening is an efficient method for early-stage drug discovery. In this study, we aimed to create a fragment library optimized for producing high hit rates against RNA targets. RNA has historically been an underexplored target, but recent research suggests potential for optimizing small molecule libraries for RNA binding. We extended this concept to fragment libraries to produce an RNA optimized fluorinated fragment library. We then screened this library, alongside two non-RNA optimized fragment libraries, against three RNA targets: the human cytoplasmic A-site and the S. cerevisiae tRNAAsp anticodon stem loop with and without nucleobase modifications. The screens yielded 24, 31, and 20 hits against the respective targets. Importantly, statistical analysis confirmed a significant overrepresentation of hits in our RNA optimized library. Based on these findings, we propose guidelines for developing RNA optimized fragment libraries. We hope the guidelines will help expediting fragment-based ligand discovery for RNA targets and contribute to presenting RNA as a promising target in drug discovery.