The use of genomic variants to drive drug repurposing for chronic hepatitis B

BackgroundOne of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB.MethodThe genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)).ResultsA total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores.ConclusionThrough the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.     

Joint mode selection and user association in D2D enabled multitier C-RAN

Cluster Computing - The device-to-device D-2-D Communication empowered Cloud Radio Access Network (CRAN) which is examined to be auspicious system model, gives energy efficiency and high data rate....     

Graphene-Based Plasmonic Waveguides: a Mini Review

Plasmonics - Graphene plasmonics is one of the most explored fields since the successful experimental discovery of the graphene due to its unprecedented properties. The dynamical modulation and...     

Simple and Improved Plasmonic Sensor Configuration Established on MIM Waveguide for Enhanced Sensing Performance

Plasmonics - Herein, two simple configurations of Fano resonance-based plasmonic sensors are proposed for temperature and biosensing applications. The device optimization and sensing performance...     

Caecal microbiota could effectively increase chicken growth performance by regulating fat metabolism

It has been established that gut microbiota influences chicken growth performance and fat metabolism. However, whether gut microbiota affects chicken growth performance by regulating fat metabolism remains unclear. Therefore, seven-week-old chickens with high or low body weight were used in the present study. There were significant differences in body weight, breast and leg muscle indices, and cross-sectional area of muscle cells, suggesting different growth performance. The relative abundance of gut microbiota in the caecal contents at the genus level was compared by 16S rRNA gene sequencing. The results of LEfSe indicated that high body weight chickens contained Microbacterium and Sphingomonas more abundantly (P < 0.05). In contrast, low body weight chickens contained Slackia more abundantly (P < 0.05). The results of H & E, qPCR, IHC, WB and blood analysis suggested significantly different fat metabolism level in serum, liver, abdominal adipose, breast and leg muscles between high and low body weight chickens. Spearman correlation analysis revealed that fat metabolism positively correlated with the relative abundance of Microbacterium and Sphingomonas while negatively correlated with the abundance of Slackia. Furthermore, faecal microbiota transplantation was performed, which verified that transferring faecal microbiota from adult chickens with high body weight into one-day-old chickens improved growth performance and fat metabolism in liver by remodelling the gut microbiota. Overall, these results suggested that gut microbiota could affect chicken growth performance by regulating fat metabolism.     

Synthesis and urease inhibitory potential of benzophenone sulfonamide hybrid in vitro and in silico

This study deals with the synthesis of benzophenone sulfonamides hybrids (1–31) and screening against urease enzyme in vitro. Studies showed that several synthetic compounds were found to have good urease enzyme inhibitory activity. Compounds 1 (N′-((4′-hydroxyphenyl)(phenyl)methylene)-4′′-nitrobenzenesulfonohydrazide), 2 (N′-((4′-hydroxyphenyl)(phenyl)methylene)-3′′-nitrobenzenesulfonohydrazide), 3 (N′-((4′-hydroxyphenyl)(phenyl)methylene)-4′′-methoxybenzenesulfonohydrazide), 4 (3′′,5′′-dichloro-2′′-hydroxy-N′-((4′-hydroxyphenyl)(phenyl)methylene)benzenesulfonohydrazide), 6 (2′′,4′′-dichloro-N′-((4′-hydroxyphenyl)(phenyl)methylene)benzenesulfonohydrazide), 8 (5-(dimethylamino)-N′-((4-hydroxyphenyl)(phenyl)methylene)naphthalene-1-sulfono hydrazide), 10 (2′′-chloro-N′-((4′-hydroxyphenyl)(phenyl)methylene)benzenesulfonohydrazide), 12 (N′-((4′-hydroxyphenyl)(phenyl)methylene)benzenesulfonohydrazide) have found to be potently active having an IC₅₀ value in the range of 3.90–17.99?µM. These compounds showed superior activity than standard acetohydroxamic acid (IC₅₀?=?29.20?±?1.01?µM). Moreover, in silico studies on most active compounds were also performed to understand the binding interaction of most active compounds with active sites of urease enzyme. Structures of all the synthetic compounds were elucidated by ¹H NMR, ¹³C NMR, EI-MS and FAB-MS spectroscopic techniques.