Ibrutinib as a potential therapeutic for cocaine use disorder

IUPHAR review - Data-driven computational drug repurposing approaches for opioid use disorder

Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by the misuse of opioid drugs, causing significant morbidity and mortality in the United States. Existing medications for OUD are limited, and there is an immediate need to discover treatments with enhanced safety and efficacy. Drug repurposing aims to find new indications for existing medications, offering a time-saving and cost-efficient alternative strategy to traditional drug discovery. Computational approaches have been developed to further facilitate the drug repurposing process. In this paper, we reviewed state-of-the-art data-driven computational drug repurposing approaches for OUD and discussed their advantages and potential challenges. We also highlighted promising repurposed candidate drugs for OUD that were identified by computational drug repurposing techniques and reviewed studies supporting their potential mechanisms of action in treating OUD.

Artificial Intelligence/Machine Learning-Driven Small Molecule Repurposing via Off-Target Prediction and Transcriptomics

The process of discovering small molecule drugs involves screening numerous compounds and optimizing the most promising ones, both in vitro and in vivo. However, approximately 90% of these optimized candidates fail during trials due to unexpected toxicity or insufficient efficacy. Current concepts with respect to drug-protein interactions suggest that each small molecule interacts with an average of 6-11 targets. This implies that approved drugs and even discontinued compounds could be repurposed by leveraging their interactions with unintended targets. Therefore, we developed a computational repurposing framework for small molecules, which combines artificial intelligence/machine learning (AI/ML)-based and chemical similarity-based target prediction methods with cross-species transcriptomics information. This repurposing methodology incorporates eight distinct target prediction methods, including three machine learning methods. By using multiple orthogonal methods for a "dataset" composed of 2766 FDA-approved drugs targeting multiple therapeutic target classes, we identified 27,371 off-target interactions involving 2013 protein targets (i.e., an average of around 10 interactions per drug). Relative to the drugs in the dataset, we identified 150,620 structurally similar compounds. The highest number of predicted interactions were for drugs targeting G protein-coupled receptors (GPCRs), enzymes, and kinases with 10,648, 4081, and 3678 interactions, respectively. Notably, 17,283 (63%) of the off-target interactions have been confirmed in vitro. Approximately 4000 interactions had an IC50 of <100 nM for 1105 FDA-approved drugs and 1661 interactions had an IC50 of <10 nM for 696 FDA-approved drugs. Together, the confirmation of numerous predicted interactions and the exploration of tissue-specific expression patterns in human and animal tissues offer insights into potential drug repurposing for new therapeutic applications.

Relating the Biogenesis and Function of P Bodies in Drosophila to Human Disease

Drosophila has been a premier model organism for over a century and many discoveries in flies have furthered our understanding of human disease. Flies have been successfully applied to many aspects of health-based research spanning from behavioural addiction, to dysplasia, to RNA dysregulation and protein misfolding. Recently, Drosophila tissues have been used to study biomolecular condensates and their role in multicellular systems. Identified in a wide range of plant and animal species, biomolecular condensates are dynamic, non-membrane-bound sub-compartments that have been observed and characterised in the cytoplasm and nuclei of many cell types. Condensate biology has exciting research prospects because of their diverse roles within cells, links to disease, and potential for therapeutics. In this review, we will discuss processing bodies (P bodies), a conserved biomolecular condensate, with a particular interest in how Drosophila can be applied to advance our understanding of condensate biogenesis and their role in disease.

Genetic and genomic analyses of Drosophila melanogaster models of chromatin modification disorders

Switch/sucrose nonfermentable (SWI/SNF)-related intellectual disability disorders (SSRIDDs) and Cornelia de Lange syndrome are rare syndromic neurodevelopmental disorders with overlapping clinical phenotypes. SSRIDDs are associated with the BAF (Brahma-Related Gene-1 associated factor) complex, whereas CdLS is a disorder of chromatin modification associated with the cohesin complex. Here, we used RNA interference in Drosophila melanogaster to reduce the expression of six genes (brm, osa, Snr1, SMC1, SMC3, vtd) orthologous to human genes associated with SSRIDDs and CdLS. These fly models exhibit changes in sleep, activity, startle behavior (a proxy for sensorimotor integration), and brain morphology. Whole genome RNA sequencing identified 9,657 differentially expressed genes (FDR < 0.05), 156 of which are differentially expressed in both sexes in SSRIDD- and CdLS-specific analyses, including Bap60, which is orthologous to SMARCD1, an SSRIDD-associated BAF component. k-means clustering reveals genes co-regulated within and across SSRIDD and CdLS fly models. RNAi-mediated reduction of expression of six genes co-regulated with focal genes brm, osa, and/or Snr1 recapitulated changes in the behavior of the focal genes. Based on the assumption that fundamental biological processes are evolutionarily conserved, Drosophila models can be used to understand underlying molecular effects of variants in chromatin-modification pathways and may aid in the discovery of drugs that ameliorate deleterious phenotypic effects.

Perspectives on the Drosophila melanogaster Model for Advances in Toxicological Science

The use of Drosophila melanogaster for studies of toxicology has grown considerably in the last decade. The Drosophila model has long been appreciated as a versatile and powerful model for developmental biology and genetics because of its ease of handling, short life cycle, low cost of maintenance, molecular genetic accessibility, and availability of a wide range of publicly available strains and data resources. These features, together with recent unique developments in genomics and metabolomics, make the fly model especially relevant and timely for the development of new approach methodologies and movements toward precision toxicology. Here, we offer a perspective on how flies can be leveraged to identify risk factors relevant to environmental exposures and human health. First, we review and discuss fundamental toxicologic principles for experimental design with Drosophila. Next, we describe quantitative and systems genetics approaches to resolve the genetic architecture and candidate pathways controlling susceptibility to toxicants. Finally, we summarize the current state and future promise of the emerging field of Drosophila metabolomics for elaborating toxic mechanisms. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Genetic and Genomic Analyses of Drosophila melanogaster Models of Chromatin Modification Disorders

Switch/Sucrose Non-Fermentable (SWI/SNF)-related intellectual disability disorders (SSRIDDs) and Cornelia de Lange syndrome are rare syndromic neurodevelopmental disorders with overlapping clinical phenotypes. SSRIDDs are associated with the BAF (Brahma-Related Gene-1 Associated Factor) complex, whereas CdLS is a disorder of chromatin modification associated with the cohesin complex. Here, we used RNA interference in Drosophila melanogaster to reduce expression of six genes (brm, osa, Snr1, SMC1, SMC3, vtd) orthologous to human genes associated with SSRIDDs and CdLS. These fly models exhibit changes in sleep, activity, startle behavior (a proxy for sensorimotor integration) and brain morphology. Whole genome RNA sequencing identified 9,657 differentially expressed genes (FDR < 0.05), 156 of which are differentially expressed in both sexes in SSRIDD- and CdLS-specific analyses, including Bap60, which is orthologous to SMARCD1, a SSRIDD-associated BAF component, k-means clustering reveals genes co-regulated within and across SSRIDD and CdLS fly models. RNAi-mediated reduction of expression of six genes co-regulated with focal genes brm, osa, and/or Snr1 recapitulated changes in behavior of the focal genes. Based on the assumption that fundamental biological processes are evolutionarily conserved, Drosophila models can be used to understand underlying molecular effects of variants in chromatin-modification pathways and may aid in discovery of drugs that ameliorate deleterious phenotypic effects.

FDA-Approved Kinase Inhibitors in Preclinical and Clinical Trials for Neurological Disorders

Cancers and neurological disorders are two major types of diseases. We previously developed a new concept termed "Aberrant Cell Cycle Diseases" (ACCD), revealing that these two diseases share a common mechanism of aberrant cell cycle re-entry. The aberrant cell cycle re-entry is manifested as kinase/oncogene activation and tumor suppressor inactivation, which are hallmarks of both tumor growth in cancers and neuronal death in neurological disorders. Therefore, some cancer therapies (e.g., kinase inhibition, tumor suppressor elevation) can be leveraged for neurological treatments. The United States Food and Drug Administration (US FDA) has so far approved 74 kinase inhibitors, with numerous other kinase inhibitors in clinical trials, mostly for the treatment of cancers. In contrast, there are dire unmet needs of FDA-approved drugs for neurological treatments, such as Alzheimer's disease (AD), intracerebral hemorrhage (ICH), ischemic stroke (IS), traumatic brain injury (TBI), and others. In this review, we list these 74 FDA-approved kinase-targeted drugs and identify those that have been reported in preclinical and/or clinical trials for neurological disorders, with a purpose of discussing the feasibility and applicability of leveraging these cancer drugs (FDA-approved kinase inhibitors) for neurological treatments.