Medicine in Omics最新文献

Background

Methods

Results

Conclusion

The present study involves the use of combined network pharmacology and molecular modelling approach for identifying important phytoconstituents that could modulate the functions of multiple therapeutic targets in Alzheimer’s disease. A list of botanicals reported in the literature for their efficacy in Alzheimer’s disease, the phytochemicals present in the botanicals were identified with the help of network pharmacology approach. The pharmacokinetic properties like blood brain barrier penetration and Lipinski’s rule of five for the selected phytoconstituents were analyzed. The major targets involved in the pathogenesis of Alzheimer’s disease were collected from the DisGeNET database. The selected proteins were subjected to topological analysis using Cytoscape software to identify the important targets in the network. The top 7 phytoconstituents and 5 proteins were subjected to molecular docking, MM-GBSA and molecular dynamics studies. A total of 15 plants and 1443 phytoconstituents were identified through a literature survey and from several databases. The pharmacokinetics study revealed that 7 phytoconstituents - glycyrrhisoflavone, eugenol, ferulic acid, methyl jasmonate, geranyl formate, formononetin, and elemicin- exhibited favourable pharmacokinetic properties. Five targets, HMOX1, CNR1, STAT3, HDAC2, and MAOB were found to be important in the network of 3300 proteins based on degree centrality and betweenness centrality. Among the seven phytoconstituents, glycyrrhisoflavone exhibited good dock scores and free energy value. Based on this, the stability of glycyrrhisoflavone with the five selected targets were analyzed using molecular dynamics study. Glycyrrhisoflavone showed good stability with most of the selected therapeutic targets. The current study reveals that the selected phytoconstituents i.e glycyrrhisoflavone, eugenol, ferulic acid, methyl jasmonate, geranyl formate, formononetin, and elemicin could serve as good lead molecules in treatment and management of Alzheimer’s disease through modulation of multiple targets.

Hepatocellular carcinoma (HCC), a type of liver cancer, ranks as the third-leading cause of death due to the lack of definite biomarkers for early-stage detection. HCC progression occurs by the dysregulation of several genes. Though several studies focus on biomarkers for HCC diagnosis, stage-specific marker identification remains elusive. Hence, the present study aims to identify early-stage biomarkers for the detection of HCC through integrated in silico analysis. The differential gene expression was performed using GEO2R for the datasets (GSE14520, GSE63898, GSE121248, GSE124535, GSE94660, and GSE6764) retrieved from Gene Expression Omnibus (GEO) of patients with cirrhotic liver or HCC. The common differentially expressed gene enrichment analysis was performed using Funrich for Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomics (KEGG) gene mapping. The Protein-Protein Interaction (PPI) network was performed using the Search Tool for the Retrieval of Interacting Genes (STRING). The hub genes were identified using the CytoHubba plug-in of Cytoscape software. The identified genes were verified for their prognostic value using the Kaplan-Meier plotter and Immunohistochemistry micrographs obtained from the Human Protein Atlas database. An overall of 243 common differentially expressed genes (DEGs) were identified containing 171 upregulated and 72 downregulated genes. With the help of PPI network construction, ten hub genes were identified as CDK1, AURKA, CCNB1, CCNB2, CENPF, CDC20, TOP2A, BUB1, RRM2, and HMMR, which are dysregulated owing to HCC proliferation, tumorigenesis and poor prognosis in patients. These hub genes are suitable waypoints for the diagnosis and targeted therapy against early-stage HCC.

Clostridium botulinum strain Hall produces potent botulinum neurotoxin type A1, which causes food-borne, infant, and wound botulism in humans. Antibiotics and botulinum antitoxins can control growth and prevent botulinum toxicity. However, limited information on a protein with an unknown function hinders the discovery of new drug targets for this disease. In this study, a combined bioinformatics approach with literature support was applied to predict, assign, and validate operome functions. Our functional annotation scheme was based on sequence motifs, conserved domains, structures, protein folds, and evolutionary relationships. Approximately 14.62 % of the operome exhibited sequence similarity to known proteins, with 6.65 % predicted functions for 293 proteins, including 121 proteins exclusive to C. botulinum. Structural analysis revealed a significant presence of the Rossmann fold (26 %) and miscellaneous folds (43 %) among the operome. Transporters (>85) and transcriptional regulators (>45) were prevalent, underscoring their importance in C. botulinum adaptive strategies. The newly identified operome contributed to the diverse cellular and metabolic processes of this organism. The function of its operome was involved in amino acid metabolism and botulinum neurotoxin biosynthesis. In this study, we identified and characterized 13 new virulence proteins from the operome to determine their structure–function relationships. These new metabolic and virulence proteins allow the organism to colonize and interact with the human gastrointestinal tract. This study provides a quest for new drugs and targets for treating the underlying diseases of C. botulinum in humans.

People who expose to mixture of crude oil products had been reported to show several diseased-symptoms including hypertension, liver failure and chronic complications. The drugs for treating multiple-complex diseases are scarcely available. Cashew nut snack is known to check multiple diseases and easily accessible by indigenous-patients with no lethal-effects. Here, we examined the corrective-measures of roasted-cashew-nut (RCN) against hypertension co-morbidity with liver-failure in male rats on exposure to mixture of fractionated-petroleum-products (MFPP). Seventy (70) male-albino-rats (n = 10) were randomly exposed to MFPP for 14 days. Group 1: control rats were given basal-diet. Group 2 was given basal diet + 0.2 ml/day-MFPP. Group 3 was given 0.2 ml/day-MFPP + 50 mg/kg Atenolol. Group 4 was given 0.2 ml/day-MFPP + 10 % RCN. Group 5 was given 0.2 ml/day-MFPP + 20 % RCN. Group 6 was given 10 % RCN_. Group 7 was given 20 % RCN. We found that high activities of liver-arginase, MAO-A, AChE, ADA, PDE-5¹ and ATP-hydrolytic-enzymes with low-bioavailability of NO-level on exposure to MFPP implicated liver-failure and hypertension. Also, up-regulation of HIF-1, p53, TNF-α, and MCP-1 with reduced-level of 1L-10 were connected to liver-failure and hypertension. However, post-treatment with 10 % RCN and 20 % RCN for 14-days corrected liver-failure and hypertension by inhibiting liver-arginase, MAO-A, AChE, ADA, PDE-5¹ and ATP-hydrolytic-enzymes. Also, liver-failure characterized by vascular-congestion and sinusoidal-dilation on exposure to 0.2 ml/day-MFPP was reversed by 10 % RCN and 20 % RCN via down-regulation of liver HIF-1, p53, TNF-α, MCP-1 with increased 1L-10. We conclude that 10 % RCN and 20 % RCN may be an innovative-snacks against hepatocellular damage co-morbidity with hypertension.

Colorectal cancer (CRC) is the third most prevalent cancer worldwide. Vitamin D receptor (VDR) gene mutations and Vitamin D deficiency contribute to CRC development and progression. Certain long non-coding RNAs (lncRNAs) directly inhibit VDR gene transcription, leading to VDR mutation. Thus, targeting oncogenic lncRNAs and VDR expression is a promising strategy for effective cancer treatment. Here, we green-synthesized Lactobacillus plantarum loaded nickel oxide nanoparticles (LpNiONPs) to assess their anticancer potential in CRC by targeting long non-coding RNA EIF3J- divergent transcript (lncRNA EIF3J-DT) and VDR. The potent bioactive component present in L. plantarum was identified via gas chromatography-mass spectrometry (GC–MS) analysis, and its interaction with VDR, as well as the functional interaction with lncRNA EIF3J-DT, were evaluated using the PyRx program and RPISeq-software, respectively. The LpNiONPs were characterized using UV–Vis spectroscopy, Zeta Potential, dynamic light scattering (DLS), fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) and X-ray diffraction (XRD) techniques. The anticancer potential of LpNiONPs against HT-29 cells was assessed through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, scratch assay, 4′,6-diamidino-2-phenylindole (DAPI)/ acridine orange-ethidium bromide (AO-EtBr) staining experiments, and reverse transcriptase-PCR to evaluate the expression of lncRNA EIF3J-DT/VDR and apoptotic-related genes. The potent bioactive compound Pyrrolo (1,2-a) pyrazine-1,4-dione in L. plantarum strongly interacts with VDR, highlighting its drug design potential. The formation of LpNiONPs was confirmed via UV–Vis spectroscopy with an absorption peak at 394 nm. LpNiONPs were positively charged, monodispersed, and stable square-shaped nanoparticles. LpNiONPs show dose-dependent cytotoxicity and induced apoptosis, confirmed by staining images in HT-29 cells. Moreover, LpNiONPs downregulated lncRNA EIF3J-DT, CYP24-A1 and BCL2 genes while upregulating VDR, cas-3, cas-9 and BAX in HT-29 cells. These findings suggest that LpNiONPs exhibit anticancer activity by promoting VDR-associated apoptosis by inhibiting lncRNA EIF3J-DT in CRC cells.

Tuberculosis (TB) continues to be a global health problem due to its high morbidity and death rates. Standardized regimens have been used in traditional TB treatment methods, frequently leading to less-than-ideal results and the establishment of drug-resistant strains. The development of personalized medicine provides a potentially effective remedy to individual patients' by adjusting therapeutic approaches to particular genotypic and phenotypic traits. Detecting TB strains, drug resistance indicators, and host genetic variants that affect treatment results is made possible by genomic and molecular diagnostic approaches. These developments offer helpful information for predicting therapy outcomes and choosing the best treatment plan for each individual.

Integrating phenotypic data, such as clinical characteristics, immunological state, and comorbidities, improves diagnostic and treatment decision-making accuracy. The use of targeted drug therapies, such as innovative anti-TB medicines and repurposed medications, which have the potential to overcome drug resistance and boost treatment effectiveness, can be guided by personalized therapy. Personalized interventions based on genetic and phenotypic factors can improve patient outcomes by identifying those at risk of treatment failure or disease progression. This article discusses the importance of personalized therapy for TB patients. It specifically highlights the benefits of using “omics” data to enhance therapeutic results and decrease the risk of drug resistance.

In the recent years, the development of so-called omics technologies has greatly contributed to the discovery of new biomarkers and targets, spanning different areas from diagnosis to therapy, and helping to accelerate the progress of precision and personalized medicine. In addition to classic omics, including genomics, transcriptomics, proteomics, and metabolomics, newer-generation omics technologies and related platforms, such as microbiomics and nutrigenomics, are emerging. At the same time, the use of liquid biopsies is becoming established as optimal biological samples, consisting in biological fluids (i.e. blood, saliva, and urine), that are easy to collect, and whose components (cells, nucleic acids, exosome) can be analysed using throughput techniques. In addition, it is becoming attractive, because it consents the extrapolation of big data via multi-omics technologies. Here, we report a brief description and discussion of such technologies, highlighting applications and possible limitations.