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The prediction of protein–ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying interactions as well as to provide a measure for ligand affinity or differentiate between active and inactive ligands. Various studies have revealed that most docking software packages reliably predict the binding mode, although scoring remains a challenge. Here, a diverse benchmark data set of 99 matched molecular pairs (3D-MMPs) with experimentally determined X-ray structures and corresponding binding affinities is introduced. This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicability of the 3D-MMP data set as a valuable tool for benchmarking scoring functions.
Background: Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine‐learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain.
Methods: Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine‐learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analysed by means of computational functional genomics in the Gene Ontology knowledgebase.
Results: Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signalling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research.
Conclusions: The present computational functional genomics‐based approach provided a computational systems‐biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine‐learned methods provide innovative approaches to knowledge discovery from previous evidence.
Significance: We show that knowledge discovery in genetic databases and contemporary machine‐learned techniques can identify relevant biological processes involved in Persitent pain.
The bile acid activated transcription factor farnesoid X receptor (FXR) regulates numerous metabolic processes and is a rising target for the treatment of hepatic and metabolic disorders. FXR agonists have revealed efficacy in treating non-alcoholic steatohepatitis (NASH), diabetes and dyslipidemia. Here we characterize imatinib as first-in-class allosteric FXR modulator and report the development of an optimized descendant that markedly promotes agonist induced FXR activation in a reporter gene assay and FXR target gene expression in HepG2 cells. Differential effects of imatinib on agonist-induced bile salt export protein and small heterodimer partner expression suggest that allosteric FXR modulation could open a new avenue to gene-selective FXR modulators.
While interleukin (IL)-1β is a potent pro-inflammatory cytokine involved in host defense, high levels can cause life-threatening sterile inflammation including systemic inflammatory response syndrome. Hence, the control of IL-1β secretion is of outstanding biomedical importance. In response to a first inflammatory stimulus such as lipopolysaccharide, pro-IL-1β is synthesized as a cytoplasmic inactive pro-form. Extracellular ATP originating from injured cells is a prototypical second signal for inflammasome-dependent maturation and release of IL-1β. The human anti-protease alpha-1 antitrypsin (AAT) and IL-1β regulate each other via mechanisms that are only partially understood. Here, we demonstrate that physiological concentrations of AAT efficiently inhibit ATP-induced release of IL-1β from primary human blood mononuclear cells, monocytic U937 cells, and rat lung tissue, whereas ATP-independent IL-1β release is not impaired. Both, native and oxidized AAT are active, suggesting that the inhibition of IL-1β release is independent of the anti-elastase activity of AAT. Signaling of AAT in monocytic cells involves the lipid scavenger receptor CD36, calcium-independent phospholipase A2β, and the release of a small soluble mediator. This mediator leads to the activation of nicotinic acetylcholine receptors, which efficiently inhibit ATP-induced P2X7 receptor activation and inflammasome assembly. We suggest that AAT controls ATP-induced IL-1β release from human mononuclear blood cells by a novel triple-membrane-passing signaling pathway. This pathway may have clinical implications for the prevention of sterile pulmonary and systemic inflammation.
Many cancers have the tumor suppressor p53 inactivated by mutation, making reactivation of mutant p53 with small molecules a promising strategy for the development of novel anticancer therapeutics. The oncogenic p53 mutation Y220C, which accounts for approximately 100,000 cancer cases per year, creates an extended surface crevice in the DNA-binding domain, which destabilizes p53 and causes denaturation and aggregation. Here, we describe the structure-guided design of a novel class of small-molecule Y220C stabilizers and the challenging synthetic routes developed in the process. The synthesized chemical probe MB710, an aminobenzothiazole derivative, binds tightly to the Y220C pocket and stabilizes p53-Y220C in vitro. MB725, an ethylamide analogue of MB710, induced selective viability reduction in several p53-Y220C cancer cell lines while being well tolerated in control cell lines. Reduction of viability correlated with increased and selective transcription of p53 target genes such as BTG2, p21, PUMA, FAS, TNF, and TNFRSF10B, which promote apoptosis and cell cycle arrest, suggesting compound-mediated transcriptional activation of the Y220C mutant. Our data provide a framework for the development of a class of potent, non-toxic compounds for reactivating the Y220C mutant in anticancer therapy.
Adult neurogenesis is regulated by stem cell niche-derived extrinsic factors and cell-intrinsic regulators, yet the mechanisms by which niche signals impinge on the activity of intrinsic neurogenic transcription factors remain poorly defined. Here, we report that MEIS2, an essential regulator of adult SVZ neurogenesis, is subject to posttranslational regulation in the SVZ olfactory bulb neurogenic system. Nuclear accumulation of MEIS2 in adult SVZ-derived progenitor cells follows downregulation of EGFR signaling and is modulated by methylation of MEIS2 on a conserved arginine, which lies in close proximity to nested binding sites for the nuclear export receptor CRM1 and the MEIS dimerization partner PBX1. Methylation impairs interaction with CRM1 without affecting PBX1 dimerization and thereby allows MEIS2 nuclear accumulation, a prerequisite for neuronal differentiation. Our results describe a form of posttranscriptional modulation of adult SVZ neurogenesis whereby an extrinsic signal fine-tunes neurogenesis through posttranslational modification of a transcriptional regulator of cell fate.
Impaired NO-cGMP signaling has been linked to several neurological disorders. NO-sensitive guanylyl cyclase (NO-GC), of which two isoforms—NO-GC1 and NO-GC2—are known, represents a promising drug target to increase cGMP in the brain. Drug-like small molecules have been discovered that work synergistically with NO to stimulate NO-GC activity. However, the effects of NO-GC stimulators in the brain are not well understood. In the present study, we used Förster/fluorescence resonance energy transfer (FRET)-based real-time imaging of cGMP in acute brain slices and primary neurons of cGMP sensor mice to comparatively assess the activity of two structurally different NO-GC stimulators, IWP-051 and BAY 41-2272, in the cerebellum, striatum and hippocampus. BAY 41-2272 potentiated an elevation of cGMP induced by the NO donor DEA/NO in all tested brain regions. Interestingly, IWP-051 potentiated DEA/NO-induced cGMP increases in the cerebellum and striatum, but not in the hippocampal CA1 area or primary hippocampal neurons. The brain-region-selective activity of IWP-051 suggested that it might act in a NO-GC isoform-selective manner. Results of mRNA in situ hybridization indicated that the cerebellum and striatum express NO-GC1 and NO-GC2, while the hippocampal CA1 area expresses mainly NO-GC2. IWP-051-potentiated DEA/NO-induced cGMP signals in the striatum of NO-GC2 knockout mice but was ineffective in the striatum of NO-GC1 knockout mice. These results indicate that IWP-051 preferentially stimulates NO-GC1 signaling in brain slices. Interestingly, no evidence for an isoform-specific effect of IWP-051 was observed when the cGMP-forming activity of whole brain homogenates was measured. This apparent discrepancy suggests that the method and conditions of cGMP measurement can influence results with NO-GC stimulators. Nevertheless, it is clear that NO-GC stimulators enhance cGMP signaling in the brain and should be further developed for the treatment of neurological diseases.
Background: Treatment complexity rises in line with the number of drugs, single doses, and administration methods, thereby threatening patient adherence. Patients with multimorbidity often need flexible, individualised treatment regimens, but alterations during the course of treatment may further increase complexity. The objective of our study was to explore medication changes in older patients with multimorbidity and polypharmacy in general practice.
Methods: We retrospectively analysed data from the cluster-randomised PRIMUM trial (PRIoritisation of MUltimedication in Multimorbidity) conducted in 72 general practices. We developed an algorithm for active pharmaceutical ingredients (API), strength, dosage, and administration method to assess changes in physician-reported medication data during two intervals (baseline to six-months: ∆1; six- to nine-months: ∆2), analysed them descriptively at prescription and patient levels, and checked for intervention effects.
Results: Of 502 patients (median age 72 years, 52% female), 464 completed the study. Changes occurred in 98.6% of patients (changes were 19% more likely in the intervention group): API changes during ∆1 and ∆2 occurred in 414 (82.5%) and 338 (67.3%) of patients, dosage alterations in 372 (74.1%) and 296 (59.2%), and changes in API strength in 158 (31.5%) and 138 (27.5%) respectively. Administration method changed in 79 (16%) of patients in both ∆1 and ∆2. Simvastatin, metformin and aspirin were most frequently subject to alterations.
Conclusion: Medication regimens in older patients with multimorbidity and polypharmacy changed frequently. These are mostly due to discontinuations and dosage alterations, followed by additions and restarts. These findings cast doubt on the effectiveness of cross-sectional assessments of medication and support longitudinal assessments where possible.
Trial registration: 1. Prospective registration: Trial registration number: NCT01171339; Name of registry: ClinicalTrials.gov; Date of registration: July 27, 2010; Date of enrolment of the first participant to the trial: August 12, 2010.
2. Peer reviewed trial registration: Trial registration number: ISRCTN99526053; Name of registry: Controlled Trials; Date of registration: August 31, 2010; Date of enrolment of the first participant to the trial: August 12, 2010.
Background: Drugs used to treat gastrointestinal diseases (GI drugs) are widely used either as prescription or over23 the-counter (OTC) medications and belong to both the ten most prescribed and ten most sold OTC medications worldwide. Current clinical practice shows that in many cases, these drugs are administered concomitantly with other drug products. Due to their metabolic properties and mechanisms of action, the drugs used to treat gastrointestinal diseases can change the pharmacokinetics of some co27 administered drugs. In certain cases, these interactions can lead to failure of treatment or to the occurrence of serious adverse events. The mechanism of interaction depends highly on drug properties and differs among therapeutic categories. Understanding these interactions is essential to providing recommendations for optimal drug therapy.
Objective: To discuss the most frequent interactions between GI and other drugs, including identification of the mechanisms behind these interactions, where possible.
Conclusion: Interactions with GI drugs are numerous and can be highly significant clinically. Whilst alterations in bioavailability due to changes in solubility, dissolution rate and metabolic interactions can be (for the most part) easily identified, interactions that are mediated through other mechanisms, such as permeability or microbiota, are less well understood. Future work should focus on characterizing these aspects.