Antrafenine is a drug initially designed for anti-inflammation uses. In this work we have synthesized a library of its structural analogs and tested the anti-influenza activities. These analogs belong to a group of 2-(quinolin-4-yl)amino benzamides or 2-(quinolin-4-yl)amino benzoate derivatives. Best performers were identified, namely 12, 34, 41, with IC against A/WSN/33 (H1N1) of 5.53, 3.21 and 6.73 μM respectively. These chemicals were also effective against A/PR/8/34 (H1N1), A/HK/1/68 (H3N2) and B/Florida/04/2006 viruses. Time-of-addition study and minigenome luciferase reporter assay both supported that the compounds act on the ribonucleoprotein (RNP) components. Using 34 and 41 as representative compounds, we determined by microscale thermophoresis that this group of compounds bind to both PA C-terminal domain and the nucleoprotein (NP) which is the most abundant subunit of the RNP. Taken together, we have identified a new class of anti-influenza compounds with dual molecular targets and good potential to be further developed. IMPORTANCE: The influenza viruses, especially influenza A and B subtypes, cause many deaths each year. The high mutation rate of the virus renders available therapeutics less effective with time. In this work we identify a new class of compounds, structurally similar to the anti-inflammation drug antrafenine, with good potency against influenza A strains. The IC of the best performers are within low micromolar range and thus have good potential for further development.
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http://dx.doi.org/10.1016/j.ejmech.2023.115775 | DOI Listing |
J Mol Model
January 2025
Hubei Key Laboratory·for High-Efficiency-Utilization of Solar Energy and Operation, Control of Energy-Storage System, Hubei-University of Technology, Wuhan, 430068, China.
Context: Ionization and adsorption in gas discharge are similar to electrophilic and nucleophilic reactions. The molecular descriptors characterizing reactions such as electrostatic potential descriptors are useful in predicting the electrical strength of environmentally friendly gases. In this study, descriptors of 73 molecules are employed for correlation analysis with electrical strength.
View Article and Find Full Text PDFClin Rheumatol
January 2025
Department of Public Health, University of Murcia, Campus de Ciencias de la Salud, Murcia, 30120, Spain.
Introduction: Therapeutic drug monitoring (TDM) in inflammatory rheumatic diseases (RMDs) is gaining interest. However, there are unresolved questions about the best practices for implementing TDM effectively in clinical settings.
Objective: The primary objective of this study was to evaluate whether early TDM of adalimumab predicts drug survival at 52 weeks in patients with RMDs.
Biomech Model Mechanobiol
January 2025
Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, 84112, USA.
When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limited information about the incident is available in such cases, and witness statements are not always reliable. In this study, we introduce a novel, data-driven approach to predict fall parameters that lead to skull fractures in infants in order to aid in determinations of abusive head trauma.
View Article and Find Full Text PDFPediatr Cardiol
January 2025
Department of Infectious Disease, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, No. 1678 Dongfang Road, Pudong New Area, Shanghai, 200127, China.
Kawasaki disease (KD) is a febrile vasculitis disorder, with coronary artery lesions (CALs) being the most severe complication. Early detection of CALs is challenging due to limitations in echocardiographic equipment (UCG). This study aimed to develop and validate an artificial intelligence algorithm to distinguish CALs in KD patients and support diagnostic decision-making at admission.
View Article and Find Full Text PDFMamm Genome
January 2025
Universidade Professor Edson Antônio Velano (UNIFENAS), Rodovia 179, Km 0, Alfenas, MG, 37132440, Brasil.
This study aimed to identify splicing quantitative trait loci (cis-sQTL) in Nelore cattle muscle tissue and explore the involvement of spliced genes (sGenes) in immune system-related biological processes. Genotypic data from 80 intact male Nelore cattle were obtained using SNP-Chip technology, while RNA-Seq analysis was performed to measure gene expression levels, enabling the integration of genomic and transcriptomic datasets. The normalized expression levels of spliced transcripts were associated with single nucleotide polymorphisms (SNPs) through an analysis of variance using an additive linear model with the MatrixEQTL package.
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