VEGAS as a Platform for Facile Directed Evolution in Mammalian Cells.

Directed evolution, artificial selection toward designed objectives, is routinely used to develop new molecular tools and therapeutics. Successful directed molecular evolution campaigns repeatedly test diverse sequences with a designed selective pressure. Unicellular organisms and their viral pathogens are exceptional for this purpose and have been used for decades. However, many desirable targets of directed evolution perform poorly or unnaturally in unicellular backgrounds. Here, we present a system for facile directed evolution in mammalian cells. Using the RNA alphavirus Sindbis as a vector for heredity and diversity, we achieved 24-h selection cycles surpassing 10-3 mutations per base. Selection is achieved through genetically actuated sequences internal to the host cell, thus the system's name: viral evolution of genetically actuating sequences, or "VEGAS." Using VEGAS, we evolve transcription factors, GPCRs, and allosteric nanobodies toward functional signaling endpoints each in less than 1 weeks' time.

Gut-Brain Cross-Talk in Metabolic Control.

Because human energy metabolism evolved to favor adiposity over leanness, the availability of palatable, easily attainable, and calorically dense foods has led to unprecedented levels of obesity and its associated metabolic co-morbidities that appear resistant to traditional lifestyle interventions. However, recent progress identifying the molecular signaling pathways through which the brain and the gastrointestinal system communicate to govern energy homeostasis, combined with emerging insights on the molecular mechanisms underlying successful bariatric surgery, gives reason to be optimistic that novel precision medicines that mimic, enhance, and/or modulate gut-brain signaling can have unprecedented potential for stopping the obesity and type 2 diabetes pandemics.

Combination Cancer Therapy Can Confer Benefit via Patient-to-Patient Variability without Drug Additivity or Synergy.

Combination cancer therapies aim to improve the probability and magnitude of therapeutic responses and reduce the likelihood of acquired resistance in an individual patient. However, drugs are tested in clinical trials on genetically diverse patient populations. We show here that patient-to-patient variability and independent drug action are sufficient to explain the superiority of many FDA-approved drug combinations in the absence of drug synergy or additivity. This is also true for combinations tested in patient-derived tumor xenografts. In a combination exhibiting independent drug action, each patient benefits solely from the drug to which his or her tumor is most sensitive, with no added benefit from other drugs. Even when drug combinations exhibit additivity or synergy in pre-clinical models, patient-to-patient variability and low cross-resistance make independent action the dominant mechanism in clinical populations. This insight represents a different way to interpret trial data and a different way to design combination therapies.

Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.

Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems.

Radiotheranostics in oncology: Making precision medicine possible.

A quintessential setting for precision medicine, theranostics refers to a rapidly evolving field of medicine in which disease is diagnosed followed by treatment of disease-positive patients using tools for the therapy identical or similar to those used for the diagnosis. Against the backdrop of only-treat-when-visualized, the goal is a high therapeutic index with efficacy markedly surpassing toxicity. Oncology leads the way in theranostics innovation, where the approach has become possible with the identification of unique proteins and other factors selectively expressed in cancer versus healthy tissue, advances in imaging technology able to report these tissue factors, and major understanding of targeting chemicals and nanodevices together with methods to attach labels or warheads for imaging and therapy. Radiotheranostics-using radiopharmaceuticals-is becoming routine in patients with prostate cancer and neuroendocrine tumors who express the proteins PSMA (prostate-specific membrane antigen) and SSTR2 (somatostatin receptor 2), respectively, on their cancer. The palpable excitement in the field stems from the finding that a proportion of patients with large metastatic burden show complete and partial responses, and this outcome is catalyzing the search for more radiotheranostics approaches. Not every patient will benefit from radiotheranostics; but, for those who cross the target-detected line, the likelihood of response is very high.

A tamoxifen receptor within a voltage-gated sodium channel.

Voltage-gated sodium channels are targets for many analgesic and antiepileptic drugs whose therapeutic mechanisms and binding sites have been well characterized. We describe the identification of a previously unidentified receptor site within the NavMs voltage-gated sodium channel. Tamoxifen, an estrogen receptor modulator, and its primary and secondary metabolic products bind at the intracellular exit of the channel, which is a site that is distinct from other previously characterized sodium channel drug sites. These compounds inhibit NavMs and human sodium channels with similar potencies and prevent sodium conductance by delaying channel recovery from the inactivated state. This study therefore not only describes the structure and pharmacology of a site that could be leveraged for the development of new drugs for the treatment of sodium channelopathies but may also have important implications for off-target health effects of this widely used therapeutic drug.

Neuropathic Pain: From Mechanisms to Treatment.

Neuropathic pain caused by a lesion or disease of the somatosensory nervous system is a common chronic pain condition with major impact on quality of life. Examples include trigeminal neuralgia, painful polyneuropathy, postherpetic neuralgia, and central poststroke pain. Most patients complain of an ongoing or intermittent spontaneous pain of, for example, burning, pricking, squeezing quality, which may be accompanied by evoked pain, particular to light touch and cold. Ectopic activity in, for example, nerve-end neuroma, compressed nerves or nerve roots, dorsal root ganglia, and the thalamus may in different conditions underlie the spontaneous pain. Evoked pain may spread to neighboring areas, and the underlying pathophysiology involves peripheral and central sensitization. Maladaptive structural changes and a number of cell-cell interactions and molecular signaling underlie the sensitization of nociceptive pathways. These include alteration in ion channels, activation of immune cells, glial-derived mediators, and epigenetic regulation. The major classes of therapeutics include drugs acting on α2δ subunits of calcium channels, sodium channels, and descending modulatory inhibitory pathways.

Translational In Vivo Assays in Behavioral Biology.

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Development of synthetic lipoxin-A4 mimetics (sLXms): New avenues in the treatment of cardio-metabolic diseases.

Resolution of inflammation is a complex, dynamic process consisting of several distinct processes, including inhibition of endothelial activation and leukocyte trafficking; promotion of inflammatory cell apoptosis and subsequent non-phlogistic scavenging and degradation; augmentation of pathogen phagocytosis; modulation of stromal cell phenotype coupled to the promotion of tissue regeneration and repair. Among these tightly regulated processes, the clearance and degradation of apoptotic cells without eliciting an inflammatory response is a crucial allostatic mechanism vital to developmental processes, host defence, and the effective resolution of inflammation. These efferocytic and subsequent effero-metabolism processes can be carried out by professional and non-professional phagocytes. Defective removal or inadequate processing of apoptotic cells leads to persistent unresolved inflammation, which may promote insidious pathologies including scarring, fibrosis, and eventual organ failure. In this manuscript, the well-established role of endothelial activation and leukocyte extravasation, as classical vascular targets of the 'inflammation pharmacology', will be briefly reviewed. The main focus of this work is to bring attention to a less explored aspect of the 'resolution pharmacology', aimed at tackling defective efferocytosis and inefficient effero-metabolism, as key targeted mechanisms to prevent or pre-empt vascular complications in cardio-metabolic diseases. Despite the use of gold standard lipid-lowering drugs or glucose-lowering drugs, none of them are able to tackle the so called residual inflammatory risk and/or the metabolic memory. In this review, the development of synthetic mimetics of endogenous mediators of inflammation is highlighted. Such molecules finely tune key components across the whole inflammatory process, amongst various other novel therapeutic paradigms that have emerged over the past decade, including anti-inflammatory therapy. More specifically, FPR2-agonists in general, and Lipoxin analogues in particular, greatly enhance the reprogramming and cross-talk between classical and non-classical innate immune cells, thus inducing both termination of the pro-inflammatory state as well as promoting the subsequent resolving phase, which represent pivotal mechanisms in inflammatory cardio-metabolic diseases.

Subcellular activation of ß-adrenergic receptors using a spatially restricted antagonist.

Gprotein-coupled receptors (GPCRs) regulate several physiological and pathological processes and represent the target of approximately 30% of Food and Drug Administration-approved drugs. GPCR-mediated signaling was thought to occur exclusively at the plasma membrane. However, recent studies have unveiled their presence and function at subcellular membrane compartments. There is a growing interest in studying compartmentalized signaling of GPCRs. This requires development of tools to separate GPCR signaling at the plasma membrane from the ones initiated at intracellular compartments. We leveraged the structural and pharmacological information available for ß-adrenergic receptors (ßARs) and focused on ß1AR as exemplary GPCR that functions at subcellular compartments, and rationally designed spatially restricted antagonists. We generated a cell-impermeable ßAR antagonist by conjugating a suitable pharmacophore to a sulfonate-containing fluorophore. This cell-impermeable antagonist only inhibited ß1AR on the plasma membrane. In contrast, a cell-permeable ßAR antagonist containing a nonsulfonated fluorophore efficiently inhibited both the plasma membrane and Golgi pools of ß1ARs. Furthermore, the cell-impermeable antagonist selectively inhibited the phosphorylation of PKA downstream effectors near the plasma membrane, which regulate sarcoplasmic reticulum (SR) Ca2+ release in adult cardiomyocytes, while the ß1AR Golgi pool remained active. Our tools offer promising avenues for investigating compartmentalized ßAR signaling in various contexts, potentially advancing our understanding of ßAR-mediated cellular responses in health and disease. They also offer a general strategy to study compartmentalized signaling for other GPCRs in various biological systems.

Acceleration of infectious disease drug discovery and development using a humanized model of drug metabolism.

A key step in drug discovery, common to many disease areas, is preclinical demonstration of efficacy in a mouse model of disease. However, this demonstration and its translation to the clinic can be impeded by mouse-specific pathways of drug metabolism. Here, we show that a mouse line extensively humanized for the cytochrome P450 gene superfamily ("8HUM") can circumvent these problems. The pharmacokinetics, metabolite profiles, and magnitude of drug-drug interactions of a test set of approved medicines were in much closer alignment with clinical observations than in wild-type mice. Infection with Mycobacterium tuberculosis, Leishmania donovani, and Trypanosoma cruzi was well tolerated in 8HUM, permitting efficacy assessment. During such assessments, mouse-specific metabolic liabilities were bypassed while the impact of clinically relevant active metabolites and DDI on efficacy were well captured. Removal of species differences in metabolism by replacement of wild-type mice with 8HUM therefore reduces compound attrition while improving clinical translation, accelerating drug discovery.

Emerging Pharmacotherapies for Obesity: A Systematic Review.

The history of anti-obesity pharmacotherapies is marked by disappointments, often entangled with societal pressure promoting weight loss and the conviction that excess body weight signifies a lack of willpower. However, categories of emerging pharmacotherapies generate hope to reduce obesity rates. This systematic review of phase 2 and phase 3 trials in adults with overweight/obesity investigates the effect of novel weight loss pharmacotherapies, compared to placebo/control or Food and Drug Administration-approved weight loss medication, through searching Medline, Embase, and ClinicalTrials.gov (2012-2024). We identified 53 phase 3 and phase 2 trials, with 36 emerging anti-obesity drugs or combinations thereof and four withdrawn or terminated trials. Oral semaglutide 50 mg is the only medication that has completed a phase 3 trial. There are 14 ongoing phase 3 trials on glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) (ecnoglutide, orforglipron, TG103), GLP-1 RA/amylin agonist (CagriSema), GLP-1/glucagon RAs (mazdutide, survodutide), GLP-1/glucose-dependent insulinotropic polypeptide and glucagon RA (retatrutide), dapagliflozin, and the combination sibutramine/topiramate. Completed phase 2 trials on incretin-based therapies showed a mean percent weight loss of 7.4-24.2%. Almost half of the drugs undergoing phase 2 trials were incretin analogs. The obesity drug pipeline is expanding rapidly, with the most promising results reported with incretin analogs. Data on mortality and obesity-related complications, such as cardio-renal-metabolic events, are needed. Moreover, long-term follow-up data on the safety and efficacy of weight maintenance with novel obesity pharmacotherapies, along with studies focused on under-represented populations, cost-effectiveness assessments, and drug availability, are needed to bridge the care gap for patients with obesity. Significance Statement Obesity is the epidemic of the 21st century. Except for the newer injectable medications, drugs with suboptimal efficacy have been available in the clinician's armamentarium. However, emerging alternatives of novel agents and combinations populate the obesity therapeutic pipeline. This systematic review identifies the state and mechanism of action of emerging pharmacotherapies undergoing or having completed phase 2 and phase 3 clinical trials. The information provided herein furthers the understanding of obesity management, implying direct clinical implications and stimulating research initiatives.

Promising tools for future drug discovery and development in antiarrhythmic therapy.

Arrhythmia refers to irregularities in the rate and rhythm of the heart, with symptoms spanning from mild palpitations to life-threatening arrhythmias and sudden cardiac death (SCD). The complex molecular nature of arrhythmias complicates the selection of appropriate treatment. Current therapies involve the use of antiarrhythmic drugs (class I-IV) with limited efficacy and dangerous side effects and implantable pacemakers and cardioverter-defibrillators with hardware-related complications and inappropriate shocks. The number of novel antiarrhythmic drug in the development pipeline has decreased substantially during the last decade and underscores uncertainties regarding future developments in this field. Consequently, arrhythmia treatment poses significant challenges, prompting the need for alternative approaches. Remarkably, innovative drug discovery and development technologies show promise in helping advance antiarrhythmic therapies. Here, we review unique characteristics and the transformative potential of emerging technologies that offer unprecedented opportunities for transitioning from traditional antiarrhythmics to next-generation therapies. We assess stem cell technology, emphasizing the utility of innovative cell profiling using multi-omics, high-throughput screening, and advanced computational modeling in developing treatments tailored precisely to individual genetic and physiological profiles. We offer insights into gene therapy, peptide and peptibody approaches for drug delivery. We finally discuss potential strengths and weaknesses of such techniques in reducing adverse effects and enhancing overall treatment outcomes, leading to more effective, specific, and safer therapies. Altogether, this comprehensive overview introduces innovative avenues for personalized rhythm therapy, with particular emphasis on drug discovery, aiming to advance the arrhythmia treatment landscape and the prevention of SCD. Significance Statement Arrhythmias and sudden cardiac death account for 15-20% of deaths worldwide. However, current antiarrhythmic therapies are ineffective and with dangerous side effects. Here, we review the field of arrhythmia treatment underscoring the slow progress in advancing the cardiac rhythm therapy pipeline and the uncertainties regarding evolution of this field. We provide information on how emerging technological and experimental tools can help accelerate progress and address the limitations of antiarrhythmic drug discovery.

Innovation in cancer pharmacotherapy through integrative consideration of germline and tumor genomes.

Precision cancer medicine is widely established, and numerous molecularly targeted drugs for various tumor entities are approved or in development. Personalized pharmacotherapy in oncology has so far been based primarily on tumor characteristics, e.g., somatic mutations. However, the response to drug treatment also depends on pharmacological processes summarized under the term ADME (absorption, distribution, metabolism, and excretion). Variations in ADME genes have been the subject of intensive research for more than five decades, considering individual patients' genetic makeup, referred to as pharmacogenomics (PGx). The combined impact of a patient's tumor and germline genome is only partially understood and often not adequately considered in cancer therapy. This may be attributed, in part, to the lack of methods for combined analysis of both data layers. Optimized personalized cancer therapies should, therefore, aim to integrate molecular information about the tumor and the germline, taking into account existing PGx guidelines for drug therapy. Moreover, such strategies should provide the opportunity to consider genetic variants of previously unknown functional significance. Bioinformatic analysis methods and corresponding algorithms for data interpretation need to be developed to consider PGx data in interdisciplinary molecular tumor boards, where cancer patients are discussed to provide evidence-based recommendations for clinical management based on individual tumor profiles. Significance Statement The era of personalized oncology has seen the emergence of drugs tailored to genetic variants associated with cancer biology. However, full potential of targeted therapy remains untapped due to the predominant focus on acquired tumor-specific alterations. Optimized cancer care must integrate tumor and patient genomes, guided by pharmacogenomic principles. An essential prerequisite for realizing truly personalized drug treatment of cancer patients is the development of bioinformatic tools for comprehensive analysis of all data layers generated in modern precision oncology programs.

Drug discovery in the era of cryo-electron microscopy.

Structure-based drug discovery (SBDD) is an indispensable approach for the design and optimization of new therapeutic agents. Here, we highlight the rapid progress that has turned cryo-electron microscopy (cryoEM) into an exceptional SBDD tool, and the wealth of new structural information it is providing for high-value pharmacological targets. We review key advantages of a technique that directly images vitrified biomolecules without the need for crystallization; both in terms of a broader array of systems that can be studied and the different forms of information it can provide, including heterogeneity and dynamics. We discuss near- and far-future developments, working in concert towards achieving the resolution and throughput necessary for cryoEM to make a widespread impact on the SBDD pipeline.

Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.

Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.

Novel systems biology experimental pipeline reveals matairesinol's antimetastatic potential in prostate cancer: an integrated approach of network pharmacology, bioinformatics, and experimental validation.

Matairesinol (MAT), a plant lignan renowned for its anticancer properties in hormone-sensitive cancers like breast and prostate cancers, presents a promising yet underexplored avenue in the treatment of metastatic prostate cancer (mPC). To elucidate its specific therapeutic targets and mechanisms, our study adopted an integrative approach, amalgamating network pharmacology (NP), bioinformatics, GeneMANIA-based functional association (GMFA), and experimental validation. By mining online databases, we identified 27 common targets of mPC and MAT, constructing a MAT-mPC protein-protein interaction network via STRING and pinpointing 11 hub targets such as EGFR, AKT1, ERBB2, MET, IGF1, CASP3, HSP90AA1, HIF1A, MMP2, HGF, and MMP9 with CytoHuba. Utilizing DAVID, Gene Ontology (GO) analysis highlighted metastasis-related processes such as epithelial-mesenchymal transition, positive regulation of cell migration, and key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cancer, prostate cancer, PI3K-Akt, and MAPK signaling, while the web resources such as UALCAN and GEPIA2 affirmed the clinical significance of the top 11 hub targets in mPC patient survival analysis and gene expression patterns. Our innovative GMFA enrichment method further enriched network pharmacology findings. Molecular docking analyses demonstrated substantial interactions between MAT and 11 hub targets. Simulation studies confirmed the stable interactions of MAT with selected targets. Experimental validation in PC3 cells, employing quantitative real-time reverse-transcription PCR and various cell-based assays, corroborated MAT's antimetastatic effects on mPC. Thus, this exhaustive NP analysis, complemented by GMFA, molecular docking, molecular dynamics simulations, and experimental validations, underscores MAT's multifaceted role in targeting mPC through diverse therapeutic avenues. Nevertheless, comprehensive in vitro validation is imperative to solidify these findings.

Integrating network pharmacology and in silico analysis deciphers Withaferin-A's anti-breast cancer potential via hedgehog pathway and target network interplay.

This study examines the remarkable effectiveness of Withaferin-A (WA), a withanolide obtained from Withania somnifera (Ashwagandha), in encountering the mortiferous breast malignancy, a global peril. The predominant objective is to investigate WA's intrinsic target proteins and hedgehog (Hh) pathway proteins in breast cancer targeting through the application of in silico computational techniques and network pharmacology predictions. The databases and webtools like Swiss target prediction, GeneCards, DisGeNet and Online Mendelian Inheritance in Man were exploited to identify the common target proteins. The culmination of the WA network and protein-protein interaction network were devised using Stitch and String web tools, through which the drug-target network of 30 common proteins was constructed employing Cytoscape-version 3.9. Enrichment analysis was performed by incorporating Gprofiler, Metascape and Cytoscape plugins. David compounded the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and enrichment was computed through bioinformatics tools. The 20 pivotal proteins were docked harnessing Glide, Schrodinger Suite 2023-2. The investigation was governed by docking scores and affinity. The shared target proteins underscored the precise Hh and WA network roles with the affirmation enrichment P-value of <0.025. The implications for hedgehog and cancer pathways were profound with enrichment (P < 0.01). Further, the ADMET and drug-likeness assessments assisted the claim. Robust interactions were noticed with docking studies, authenticated through molecular dynamics, molecular mechanics generalized born surface area scores and bonds. The computational investigation emphasized WA's credible anti-breast activity, specifically with Hh proteins, implying stem-cell-level checkpoint restraints. Rigorous testament is imperative through in vitro and in vivo studies.

Dual-channel hypergraph convolutional network for predicting herb-disease associations.

Herbs applicability in disease treatment has been verified through experiences over thousands of years. The understanding of herb-disease associations (HDAs) is yet far from complete due to the complicated mechanism inherent in multi-target and multi-component (MTMC) botanical therapeutics. Most of the existing prediction models fail to incorporate the MTMC mechanism. To overcome this problem, we propose a novel dual-channel hypergraph convolutional network, namely HGHDA, for HDA prediction. Technically, HGHDA first adopts an autoencoder to project components and target protein onto a low-dimensional latent space so as to obtain their embeddings by preserving similarity characteristics in their original feature spaces. To model the high-order relations between herbs and their components, we design a channel in HGHDA to encode a hypergraph that describes the high-order patterns of herb-component relations via hypergraph convolution. The other channel in HGHDA is also established in the same way to model the high-order relations between diseases and target proteins. The embeddings of drugs and diseases are then aggregated through our dual-channel network to obtain the prediction results with a scoring function. To evaluate the performance of HGHDA, a series of extensive experiments have been conducted on two benchmark datasets, and the results demonstrate the superiority of HGHDA over the state-of-the-art algorithms proposed for HDA prediction. Besides, our case study on Chuan Xiong and Astragalus membranaceus is a strong indicator to verify the effectiveness of HGHDA, as seven and eight out of the top 10 diseases predicted by HGHDA for Chuan-Xiong and Astragalus-membranaceus, respectively, have been reported in literature.

Pro-resolving therapies as potential adjunct treatment for infectious diseases: Evidence from studies with annexin A1 and angiotensin-(1-7).

Infectious diseases, once believed to be an eradicable public health threat, still represent a leading cause of death worldwide. Environmental and social changes continuously favor the emergence of new pathogens and rapid dissemination around the world. The limited availability of anti-viral therapies and increased antibiotic resistance has made the therapeutic management of infectious disease a major challenge. Inflammation is a primordial defense to protect the host against invading microorganisms. However, dysfunctional inflammatory responses contribute to disease severity and mortality during infections. In recent years, a few studies have examined the relevance of resolution of inflammation in the context of infections. Inflammation resolution is an active integrated process transduced by several pro-resolving mediators, including Annexin A1 and Angiotensin-(1-7). Here, we examine some of the cellular and molecular circuits triggered by pro-resolving molecules and that may be beneficial in the context of infectious diseases.