Inhibition of EZH2 transactivation function sensitizes solid tumors to genotoxic stress.

Drugs that block the activity of the methyltransferase EZH2 are in clinical development for the treatment of non-Hodgkin lymphomas harboring EZH2 gain-of-function mutations that enhance its polycomb repressive function. We have previously reported that EZH2 can act as a transcriptional activator in castration-resistant prostate cancer (CRPC). Now we show that EZH2 inhibitors can also block the transactivation activity of EZH2 and inhibit the growth of CRPC cells. Gene expression and epigenomics profiling of cells treated with EZH2 inhibitors demonstrated that in addition to derepressing gene expression, these compounds also robustly down-regulate a set of DNA damage repair (DDR) genes, especially those involved in the base excision repair (BER) pathway. Methylation of the pioneer factor FOXA1 by EZH2 contributes to the activation of these genes, and interaction with the transcriptional coactivator P300 via the transactivation domain on EZH2 directly turns on the transcription. In addition, CRISPR-Cas9-mediated knockout screens in the presence of EZH2 inhibitors identified these BER genes as the determinants that underlie the growth-inhibitory effect of EZH2 inhibitors. Interrogation of public data from diverse types of solid tumors expressing wild-type EZH2 demonstrated that expression of DDR genes is significantly correlated with EZH2 dependency and cellular sensitivity to EZH2 inhibitors. Consistent with these findings, treatment of CRPC cells with EZH2 inhibitors dramatically enhances their sensitivity to genotoxic stress. These studies reveal a previously unappreciated mechanism of action of EZH2 inhibitors and provide a mechanistic basis for potential combination cancer therapies.

Deep learning identifies explainable reasoning paths of mechanism of action for drug repurposing from multilayer biological network.

The discovery and repurposing of drugs require a deep understanding of the mechanism of drug action (MODA). Existing computational methods mainly model MODA with the protein-protein interaction (PPI) network. However, the molecular interactions of drugs in the human body are far beyond PPIs. Additionally, the lack of interpretability of these models hinders their practicability. We propose an interpretable deep learning-based path-reasoning framework (iDPath) for drug discovery and repurposing by capturing MODA on by far the most comprehensive multilayer biological network consisting of the complex high-dimensional molecular interactions between genes, proteins and chemicals. Experiments show that iDPath outperforms state-of-the-art machine learning methods on a general drug repurposing task. Further investigations demonstrate that iDPath can identify explicit critical paths that are consistent with clinical evidence. To demonstrate the practical value of iDPath, we apply it to the identification of potential drugs for treating prostate cancer and hypertension. Results show that iDPath can discover new FDA-approved drugs. This research provides a novel interpretable artificial intelligence perspective on drug discovery.

Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication.

Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects.

Advances in Nucleoside and Nucleotide Analogues in Tackling Human Immunodeficiency Virus and Hepatitis Virus Infections.

Nucleoside and nucleotide analogues are structurally similar antimetabolites and are promising small-molecule chemotherapeutic agents against various infectious DNA and RNA viruses. To date, these analogues have not been documented in-depth as anti-human immunodeficiency virus (HIV) and anti-hepatitis virus agents, these are at various stages of testing ranging from pre-clinical, to those withdrawn from trials, or those that are approved as drugs. Hence, in this review, the importance of these analogues in tackling HIV and hepatitis virus infections is discussed with a focus on the viral genome and the mechanism of action of these analogues, both in a mutually exclusive manner and their role in HIV/hepatitis coinfection. This review encompasses nucleoside and nucleotide analogues from 1987 onwards, starting with the first nucleoside analogue, zidovudine, and going on to those in current clinical trials and even the drugs that have been withdrawn. This review also sheds light on the prospects of these nucleoside analogues in clinical trials as a treatment option for the COVID-19 pandemic.

Targeting astrocytes in bipolar disorder.

Astrocytes are homeostatic cells of the central nervous system, which are critical for development and maintenance of synaptic transmission and hence of synaptically connected neuronal ensembles. Astrocytic densities are reduced in bipolar disorder, and therefore deficient astroglial function may contribute to overall disbalance in neurotransmission and to pathological evolution. Classical anti-bipolar drugs (lithium salts, valproic acid and carbamazepine) affect expression of astroglial genes and modify astroglial signalling and homeostatic cascades. Many effects of both antidepressant and anti-bipolar drugs are exerted through regulation of glutamate homeostasis and glutamatergic transmission, through K(+) buffering, through regulation of calcium-dependent phospholipase A2 (that controls metabolism of arachidonic acid) or through Ca(2+) homeostatic and signalling pathways. Sometimes anti-depressant and anti-bipolar drugs exert opposite effects, and some effects on gene expression in drug treated animals are opposite in neurones vs. astrocytes. Changes in the intracellular pH induced by anti-bipolar drugs affect uptake of myo-inositol and thereby signalling via inositoltrisphosphate (InsP3), this being in accord with one of the main theories of mechanism of action for these drugs.

Targeting astrocytes in major depression.

Astrocytes represent a highly heterogeneous population of neural cells primarily responsible for the homeostasis of the CNS. Astrocytes express multiple receptors for neurotransmitters, including the serotonin 5-HT2B receptors and interact with neurones at the synapse. Astroglia contribute to neurological diseases through homeostatic response, neuroprotection and reactivity. In major depression, astrocytes show signs of degeneration and are decreased in numbers, which may lead to a misbalance in neurotransmission and aberrant synaptic connectivity. In this review, we summarize astroglia-specific effects of major antidepressants and outline future strategies for astroglia-specific therapy in neuropsychiatric disorders.

Historeceptomic Fingerprints for Drug-Like Compounds.

Most drugs exert their beneficial and adverse effects through their combined action on several different molecular targets (polypharmacology). The true molecular fingerprint of the direct action of a drug has two components: the ensemble of all the receptors upon which a drug acts and their level of expression in organs/tissues. Conversely, the fingerprint of the adverse effects of a drug may derive from its action in bystander tissues. The ensemble of targets is almost always only partially known. Here we describe an approach improving upon and integrating both components: in silico identification of a more comprehensive ensemble of targets for any drug weighted by the expression of those receptors in relevant tissues. Our system combines more than 300,000 experimentally determined bioactivity values from the ChEMBL database and 4.2 billion molecular docking scores. We integrated these scores with gene expression data for human receptors across a panel of human tissues to produce drug-specific tissue-receptor (historeceptomics) scores. A statistical model was designed to identify significant scores, which define an improved fingerprint representing the unique activity of any drug. These multi-dimensional historeceptomic fingerprints describe, in a novel, intuitive, and easy to interpret style, the holistic, in vivo picture of the mechanism of any drug's action. Valuable applications in drug discovery and personalized medicine, including the identification of molecular signatures for drugs with polypharmacologic modes of action, detection of tissue-specific adverse effects of drugs, matching molecular signatures of a disease to drugs, target identification for bioactive compounds with unknown receptors, and hypothesis generation for drug/compound phenotypes may be enabled by this approach. The system has been deployed at drugable.org for access through a user-friendly web site.