An examination of the OMIM database for associating mutation to a consensus reference sequence

Cucurbitacin B targets STAT3 to induce ferroptosis in non-small cell lung cancer

Cucurbitacin B (CuB) is a compound found in plants like Cucurbitaceae that has shown promise in fighting cancer, particularly in lung cancer. However, the specific impact of CuB on ferroptosis and how it works in lung cancer cells has not been fully understood. Our research has discovered that CuB can effectively slow down the growth of non-small cell lung cancer (NSCLC) cells. Even in small amounts, it was able to inhibit the growth of various NSCLC cell lines. This inhibitory effect was reversed when ferroptosis inhibitors DFO, Lip-1 and Fer-1 were introduced. CuB was found to increase the levels of reactive oxygen species (ROS), lipid ROS, MDA, and ferrous ions within H358 lung cancer cells, leading to a decrease in GSH, mitochondrial membrane potential (MMP) and changes in ferroptosis-related proteins in a dose-dependent manner. These findings were also confirmed in A549 lung cancer cells. In A549 cells, different concentrations of CuB induced the accumulation of intracellular lipid ROS, ferrous ions and changes in ferroptosis-related indicators in a concentration-dependent manner. Meanwhile, the cytotoxic effect induced by CuB in A549 cells was counteracted by ferroptosis inhibitors DFO and Fer-1. Through network pharmacology, we identified potential targets related to ferroptosis in NSCLC cells treated with CuB, with STAT3 targets showing high scores. Further experiments using molecular docking and cell thermal shift assay (CETSA) revealed that CuB interacts with the STAT3 protein. Western blot and immunofluorescence staining demonstrated that CuB inhibits the phosphorylation of STAT3 (P-STAT3) in H358 cells. Silencing STAT3 enhanced CuB-induced accumulation of lipid ROS and iron ions, as well as the expression of ferroptosis-related proteins. On the other hand, overexpression of STAT3 reversed the effects of CuB-induced ferroptosis. The results indicate that CuB has the capability to suppress STAT3 activation, resulting in ferroptosis, and could be a promising treatment choice for NSCLC.

Network pharmacology and in vivo experiment-based strategy for investigating the mechanism of chronic prostatitis/chronic pelvic pain syndrome in QianLieJinDan tablets

Background

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common urinary system disease that is prone to recurrence. It typically leads to varying degrees of pelvic pain and discomfort, as well as symptoms related to the urinary system in affected patients. QianLieJinDan tablets (QLJD), a traditional Chinese medicine, have shown promising therapeutic effects on CP/CPPS in clinical practice, but the underlying mechanisms of QLJD in treating CP/CPPS have not been determined.

Objective

To reveal the phytochemical characterization and multitarget mechanism of QLJD on CP/CPPS.

Methods

The concentrations of the components of QLJD were determined using UHPLC-Q Exactive Orbitrap-MS. Utilizing network pharmacology approaches, the potential components, targets, and pathways involved in the treatment of CP/CPPS caused by QLJD were screened. Molecular docking calculations were employed to assess the affinity between the components of the QLJD and potential targets, revealing the optimal molecular conformation and binding site. Finally, the therapeutic efficacy and potential underlying mechanisms of QLJD were investigated through pharmacological experiments.

Results

In this study, a total of 35 components targeting 29 CP-related genes were identified, among which quercetin, baicalin, icariin, luteolin, and gallic acid were the major constituents. Enrichment analysis revealed that the potential targets were involved mainly in the regulation of cytokines, cell proliferation and apoptosis, and the oxidative stress response and were primarily associated with the cytokine‒cytokine receptor interaction pathway, the IL-17 signaling pathway, the Th17 cell differentiation pathway, and the JAK-STAT signaling pathway. In vivo experiments demonstrated that QLJD effectively attenuated the infiltration of CD3+ T cells and the expression of ROS in a CP/CPPS model rat prostate tissue. Furthermore, through the inhibition of IL-6 and STAT3 expression, QLJD reduced the differentiation of Th17 cells, thereby ameliorating pathological injury and prostatic index in prostate tissue.

Conclusion

The potential of QLJD as an anti-CP/CPPS agent lies in its ability to interfere with the expression of IL-6 and STAT3, inhibit Th17 cell differentiation, reduce inflammatory cell infiltration in rat prostate tissue, and alleviate oxidative stress damage through its multi-component, multi-target, and multi-pathway effects.

Unraveling the potential mechanisms of the anti-osteoporotic effects of the Achyranthes bidentata-Dipsacus asper herb pair: a network pharmacology and experimental study

Background: Osteoporosis is a prevalent bone metabolism disease characterized by a reduction in bone density, leading to several complications that significantly affect patients' quality of life. The Achyranthes bidentata-Dipsacus asper (AB-DA) herb pair is commonly used in Traditional Chinese Medicine (TCM) to treat osteoporosis. This study aimed to investigate the therapeutic compounds and potential mechanisms of AB-DA using network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification. Methods: Identified compounds of AB-DA were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicine Information Database (TCM-ID), TCM@Taiwan Database, BATMAN-TCM, and relevant literature. The main bioactive ingredients were screened based on the criteria of "OB (oral bioavailability) ≥ 30, DL (drug-likeness) ≥ 0.18." Potential targets were predicted using the PharmMapper and SwissTargetPrediction websites, while disease (osteoporosis)-related targets were obtained from the GeneCards, DisGeNET, and OMIM databases. The PPI network and KEGG/GO enrichment analysis were utilized for core targets and pathway screening in the STRING and Metascape databases, respectively. A drug-compound-target-pathway-disease network was constructed using Cytoscape software to display core regulatory mechanisms. Molecular docking and dynamics simulation techniques explored the binding reliability and stability between core compounds and targets. In vitro and in vivo validation experiments were utilized to explore the anti-osteoporosis efficiency and mechanism of sitogluside. Results: A total of 31 compounds with 83 potential targets for AB-DA against osteoporosis were obtained. The PPI analysis revealed several hub targets, including AKT1, CASP3, EGFR, IGF1, MAPK1, MAPK8, and MAPK14. GO/KEGG analysis indicated that the MAPK cascade (ERK/JNK/p38) is the main pathway involved in treating osteoporosis. The D-C-T-P-T network demonstrated therapeutic compounds that mainly consisted of iridoids, steroids, and flavonoids, such as sitogluside, loganic acid, and β-ecdysterone. Molecular docking and dynamics simulation analyses confirmed strong binding affinity and stability between core compounds and targets. Additionally, the validation experiments showed preliminary evidence of antiosteoporosis effects. Conclusion: This study identified iridoids, steroids, and flavonoids as the main therapeutic compounds of AB-DA in treating osteoporosis. The underlying mechanisms may involve targeting core MAPK cascade (ERK/JNK/p38) targets, such as MAPK1, MAPK8, and MAPK14. In vivo experiments preliminarily validated the anti-osteoporosis effect of sitogluside. Further in-depth experimental studies are required to validate the therapeutic value of AB-DA for treating osteoporosis in clinical practice.

Exploring the mechanism of Alisma orientale for the treatment of pregnancy induced hypertension and potential hepato-nephrotoxicity by using network pharmacology, network toxicology, molecular docking and molecular dynamics simulation

Background: Pregnancy-induced Hypertension (PIH) is a disease that causes serious maternal and fetal morbidity and mortality. Alisma Orientale (AO) has a long history of use as traditional Chinese medicine therapy for PIH. This study explores its potential mechanism and biosafety based on network pharmacology, network toxicology, molecular docking and molecular dynamics simulation. Methods: Compounds of AO were screened in TCMSP, TCM-ID, TCM@Taiwan, BATMAN, TOXNET and CTD database; PharmMapper and SwissTargetPrediction, GeneCards, DisGeNET and OMIM databases were used to predict the targets of AO anti-PIH. The protein-protein interaction analysis and the KEGG/GO enrichment analysis were applied by STRING and Metascape databases, respectively. Then, we constructed the "herb-compound-target-pathway-disease" map in Cytoscape software to show the core regulatory network. Finally, molecular docking and molecular dynamics simulation were applied to analyze binding affinity and reliability. The same procedure was conducted for network toxicology to illustrate the mechanisms of AO hepatotoxicity and nephrotoxicity. Results: 29 compounds with 78 potential targets associated with the therapeutic effect of AO on PIH, 10 compounds with 117 and 111 targets associated with AO induced hepatotoxicity and nephrotoxicity were obtained, respectively. The PPI network analysis showed that core therapeutic targets were IGF, MAPK1, AKT1 and EGFR, while PPARG and TNF were toxicity-related targets. Besides, GO/KEGG enrichment analysis showed that AO might modulate the PI3K-AKT and MAPK pathways in treating PIH and mainly interfere with the lipid and atherosclerosis pathways to induce liver and kidney injury. The "herb-compound-target-pathway-disease" network showed that triterpenoids were the main therapeutic compounds, such as Alisol B 23-Acetate and Alisol C, while emodin was the main toxic compounds. The results of molecular docking and molecular dynamics simulation also showed good binding affinity between core compounds and targets. Conclusion: This research illustrated the mechanism underlying the therapeutic effects of AO against PIH and AO induced hepato-nephrotoxicity. However, further experimental verification is warranted for optimal use of AO during clinical practice.

Predicting of disease genes for gestational diabetes mellitus based on network and functional consistency

OBJECTIVE

Gestational diabetes mellitus (GDM) is a world-widely prevalent disease with adverse outcomes. This study aims to identify its disease genes through bioinformatics analysis.

STUDY DESIGN

The raw gene expression profiling (ID: GSE19649) was downloaded from Gene Expression Omnibus database, including 3 GDM and 2 healthy control specimens. Then limma package in R was utilized to identify differentially expressed genes (DEGs, criteria: p value <0.05 and |log2 FC|>1). Simultaneously, known disease genes of GDM were downloaded from Online Mendelian Inheritance in Man database. Then, DEGs and known disease genes were uploaded to STRING to investigate their protein-protein interactions (PPIs). Gene pairs with confidence score >0.8 were utilized to construct PPI network. Furthermore, pathway and functional enrichment analyses were performed through KOBAS (criterion: p value <0.05) and DAVID (The Database for Annotation, Visualization and Integrated Discovery) software (criterion: false discovery rate <0.05), respectively.

RESULTS

A total of 404 DEGs were identified, including 273 up-regulated and 131 down-regulated DEGs. Moreover, 68 known disease genes of GDM were obtained. Then, 190 gene pairs were identified to significantly interact with each other. After deleting PPIs between DEGs, PPI network was constructed, consisting of 115 gene pairs. Furthermore, genes in PPI network were significantly enriched in 10 functions and 8 pathways.

CONCLUSION

Based on PPI network and functional consistency, 6 candidate genes of GDM were considered to be candidate disease genes of GDM, including CYP1A1, LEPR, ESR1, GYS2, AGRP, and CACNA1G. However, further studies are required to validate these results.

Personal genomic information management and personalized medicine: challenges, current solutions, and roles of HIM professionals

In recent years, the term personalized medicine has received more and more attention in the field of healthcare. The increasing use of this term is closely related to the astonishing advancement in DNA sequencing technologies and other high-throughput biotechnologies. A large amount of personal genomic data can be generated by these technologies in a short time. Consequently, the needs for managing, analyzing, and interpreting these personal genomic data to facilitate personalized care are escalated. In this article, we discuss the challenges for implementing genomics-based personalized medicine in healthcare, current solutions to these challenges, and the roles of health information management (HIM) professionals in genomics-based personalized medicine.

M2SG: mapping human disease-related genetic variants to protein sequences and genomic loci

SUMMARY

Online Mendelian Inheritance in Man (OMIM) is a manually curated compendium of human genetic variants and the corresponding phenotypes, mostly human diseases. Instead of directly documenting the native sequences for gene entries, OMIM links its entries to protein and DNA sequences in other databases. However, because of the existence of gene isoforms and errors in OMIM records, mapping a specific OMIM mutation to its corresponding protein sequence is not trivial. Combining computer programs and extensive manual curation of OMIM full-text descriptions and original literature, we mapped 98% of OMIM amino acid substitutions (AASs) and all SwissProt Variant (SwissVar) disease-related AASs to reference sequences and confidently mapped 99.96% of all AASs to the genomic loci. Based on the results, we developed an online database and interactive web server (M2SG) to (i) retrieve the mapped OMIM and SwissVar variants for a given protein sequence; and (ii) obtain related proteins and mutations for an input disease phenotype. This database will be useful for analyzing sequences, understanding the effect of mutations, identifying important genetic variations and designing experiments on a protein of interest.

AVAILABILITY AND IMPLEMENTATION

The database and web server are freely available at http://prodata.swmed.edu/M2S/mut2seq.cgi.