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.

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.

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.

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.

Distinct mouse models of Stargardt disease display differences in pharmacological targeting of ceramides and inflammatory responses.

Mutations in many visual cycle enzymes in photoreceptors and retinal pigment epithelium (RPE) cells can lead to the chronic accumulation of toxic retinoid byproducts, which poison photoreceptors and the underlying RPE if left unchecked. Without a functional ATP-binding cassette, sub-family A, member 4 (ABCA4), there is an elevation of all-trans-retinal and prolonged buildup of all-trans-retinal adducts, resulting in a retinal degenerative disease known as Stargardt-1 disease. Even in this monogenic disorder, there is significant heterogeneity in the time to onset of symptoms among patients. Using a combination of molecular techniques, we studied Abca4 knockout (simulating human noncoding disease variants) and Abca4 knock-in mice (simulating human misfolded, catalytically inactive protein variants), which serve as models for Stargardt-1 disease. We compared the two strains to ascertain whether they exhibit differential responses to agents that affect cytokine signaling and/or ceramide metabolism, as alterations in either of these pathways can exacerbate retinal degenerative phenotypes. We found different degrees of responsiveness to maraviroc, a known immunomodulatory CCR5 antagonist, and to the ceramide-lowering agent AdipoRon, an agonist of the ADIPOR1 and ADIPOR2 receptors. The two strains also display different degrees of transcriptional deviation from matched WT controls. Our phenotypic comparison of the two distinct Abca4 mutant-mouse models sheds light on potential therapeutic avenues previously unexplored in the treatment of Stargardt disease and provides a surrogate assay for assessing the effectiveness for genome editing.

Dual-pocket inhibition of Nav channels by the antiepileptic drug lamotrigine.

Voltage-gated sodium (Nav) channels govern membrane excitability, thus setting the foundation for various physiological and neuronal processes. Nav channels serve as the primary targets for several classes of widely used and investigational drugs, including local anesthetics, antiepileptic drugs, antiarrhythmics, and analgesics. In this study, we present cryogenic electron microscopy (cryo-EM) structures of human Nav1.7 bound to two clinical drugs, riluzole (RLZ) and lamotrigine (LTG), at resolutions of 2.9 Å and 2.7 Å, respectively. A 3D EM reconstruction of ligand-free Nav1.7 was also obtained at 2.1 Å resolution. RLZ resides in the central cavity of the pore domain and is coordinated by residues from repeats III and IV. Whereas one LTG molecule also binds to the central cavity, the other is found beneath the intracellular gate, known as site BIG. Therefore, LTG, similar to lacosamide and cannabidiol, blocks Nav channels via a dual-pocket mechanism. These structures, complemented with docking and mutational analyses, also explain the structure-activity relationships of the LTG-related linear 6,6 series that have been developed for improved efficacy and subtype specificity on different Nav channels. Our findings reveal the molecular basis for these drugs' mechanism of action and will aid the development of novel antiepileptic and pain-relieving drugs.

Pharmacological Management of Cardiac Arrhythmias in the Fetal and Neonatal Periods: A Scientific Statement From the American Heart Association: Endorsed by the Pediatric & Congenital Electrophysiology Society (PACES).

Disorders of the cardiac rhythm may occur in both the fetus and neonate. Because of the immature myocardium, the hemodynamic consequences of either bradyarrhythmias or tachyarrhythmias may be far more significant than in mature physiological states. Treatment options are limited in the fetus and neonate because of limited vascular access, patient size, and the significant risk/benefit ratio of any intervention. In addition, exposure of the fetus or neonate to either persistent arrhythmias or antiarrhythmic medications may have yet-to-be-determined long-term developmental consequences. This scientific statement discusses the mechanism of arrhythmias, pharmacological treatment options, and distinct aspects of pharmacokinetics for the fetus and neonate. From the available current data, subjects of apparent consistency/consensus are presented, as well as future directions for research in terms of aspects of care for which evidence has not been established.

DrugAI: a multi-view deep learning model for predicting drug-target activating/inhibiting mechanisms.

Understanding the mechanisms of candidate drugs play an important role in drug discovery. The activating/inhibiting mechanisms between drugs and targets are major types of mechanisms of drugs. Owing to the complexity of drug-target (DT) mechanisms and data scarcity, modelling this problem based on deep learning methods to accurately predict DT activating/inhibiting mechanisms remains a considerable challenge. Here, by considering network pharmacology, we propose a multi-view deep learning model, DrugAI, which combines four modules, i.e. a graph neural network for drugs, a convolutional neural network for targets, a network embedding module for drugs and targets and a deep neural network for predicting activating/inhibiting mechanisms between drugs and targets. Computational experiments show that DrugAI performs better than state-of-the-art methods and has good robustness and generalization. To demonstrate the reliability of the predictive results of DrugAI, bioassay experiments are conducted to validate two drugs (notopterol and alpha-asarone) predicted to activate TRPV1. Moreover, external validation bears out 61 pairs of mechanism relationships between natural products and their targets predicted by DrugAI based on independent literatures and PubChem bioassays. DrugAI, for the first time, provides a powerful multi-view deep learning framework for robust prediction of DT activating/inhibiting mechanisms.

TCMFP: a novel herbal formula prediction method based on network target's score integrated with semi-supervised learning genetic algorithms.

Traditional Chinese medicine (TCM) has accumulated thousands years of knowledge in herbal therapy, but the use of herbal formulas is still characterized by reliance on personal experience. Due to the complex mechanism of herbal actions, it is challenging to discover effective herbal formulas for diseases by integrating the traditional experiences and modern pharmacological mechanisms of multi-target interactions. In this study, we propose a herbal formula prediction approach (TCMFP) combined therapy experience of TCM, artificial intelligence and network science algorithms to screen optimal herbal formula for diseases efficiently, which integrates a herb score (Hscore) based on the importance of network targets, a pair score (Pscore) based on empirical learning and herbal formula predictive score (FmapScore) based on intelligent optimization and genetic algorithm. The validity of Hscore, Pscore and FmapScore was verified by functional similarity and network topological evaluation. Moreover, TCMFP was used successfully to generate herbal formulae for three diseases, i.e. the Alzheimer's disease, asthma and atherosclerosis. Functional enrichment and network analysis indicates the efficacy of targets for the predicted optimal herbal formula. The proposed TCMFP may provides a new strategy for the optimization of herbal formula, TCM herbs therapy and drug development.