Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism

Wang, Tianyi; Sun, Jianqiang; Zhao, Qi

doi:10.1016/j.compbiomed.2022.106464

Cited by 110 publications

(64 citation statements)

References 56 publications

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“…In addition, several bioinformatics tools provide an important contribution to tumor metabolism analysis and drug development. A bioinformatics tool, named graph convolutional network with graph attention network (GCNAT), is able to predict hERG channel blockers in the early stages of drug discovery [ 52 ]. The metabolite-disease associations predicted by the graph convolutional network with graph attention network (GCNAT) method have also been experimentally validated [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

et al. 2023

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Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan–Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model’s reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS’ correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.

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Section: Discussionmentioning

confidence: 99%

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

et al. 2023

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“…The authors have cited additional references within the Supporting Information. [51][52][53][54][55][56][57][58][59][60][61][62][63] The additional information contains the mathematical equations of the external validation criteria, The score of different parameters of the hypotheses pharmacopore generated, and also the results of docking, MMGBSA and for the whole data set.…”

Section: Discussionmentioning

confidence: 99%

Computational Exploration of the Structural Requirements of Triazole Derivatives as Colchicine Binding Site Inhibitors

et al. 2023

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Colchicine inhibits microtubule assembly by preventing tubulin polymerization, making the colchicine binding site a promising target against cancer. The present study focuses on the 3D‐QSAR analysis of 31 triazole analogs. The atom‐based and field‐based QSAR models exhibit significant statistical results for internal and external validations, with the atom‐based 3D‐QSAR model showing a Q2 of 0.658 and R2 of 0.998, and the field‐based 3D‐QSAR model showing a Q2 of 0.658 and R2 of 0.998. The 3D‐QSAR atom‐based pharmacophore model explains biological activity using a six‐point hypothesis (AHHRRR.1), while the field‐based 3D‐QSAR model explains activity based on steric, electrostatic, hydrophobic, and hydrogen bond donor/acceptor fields. Based on the 3D contour maps generated, five new compounds were designed and their ADME/Tox properties predicted. The results suggested that these compounds possess potent pharmacological characteristics. The results of the molecular docking analysis showed that Pred01 and Pred02 had higher docking scores (−6.2417Kcal/mol and −6.5049Kcal/mol, respectively) than compound 15, and they formed notable hydrogen bonds and hydrophobic interactions with active site residues. The MMGBSA results confirmed these findings and emphasized the essential role of van der Waals energy in the binding energy. Moreover, the dynamic stability of the complexes was further supported by MD simulations.

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“…Some new analytical methods can also be selected to further analyze FXR1 molecules by statistical analysis of the relationship between FXR1 and other molecules, such as GCNCRF, DMFGAM, scRNA-seq, GCNAT, DCAMCP, NDALMA. [61][62][63][64][65][66][67] Additionally, to validate these hypotheses, further in vitro and in vivo experiments are needed to validate the hypothesis that FXR1 may be a diagnostic/prognostic biomarker for certain cancers and a target for immunotherapy. Lastly, extensive clinical sample data collection and analysis is necessary to fully utilize FXR1 as a predictive biomarker for different cancers.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive bioinformatics analysis of FXR1 across pan-cancer: Unraveling its diagnostic, prognostic, and immunological significance

Xiao,

Ullah,

Yang

et al. 2023

Medicine

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Fragile X-related protein 1 (FXR1) is an RNA-binding protein that belongs to the fragile X-related (FXR) family. Studies have shown that FXR1 plays an important role in cancer cell proliferation, invasion and migration and is differentially expressed in cancers. This study aimed to gain a comprehensive and systematic understanding of the analysis of FXR1’s role in cancers. This would lead to a better understanding of how it contributes to the development and progression of various malignancies. this study conducted through The Cancer Genome Atlas (TCGA), GTEx, cBioPortal, TISIDB, GEPIA2 and HPA databases to investigated FXR1’s role in cancers. For data analysis, various software platforms and web platforms were used, such as R, Cytoscape, hiplot plateform. A significant difference in FXR1 expression was observed across molecular and immune subtypes and across types of cancer. FXR1 expression correlates with disease-specific survival (DSS), and overall survival (OS) in several cancer pathways, further in progression-free interval (PFI) in most cancers. Additionally, FXR1 showed a correlation with genetic markers of immunomodulators in different cancer types. Our study provides insights into the role of FXR1 in promoting, inhibiting, and treating diverse cancers. FXR1 has the potential to serve as a diagnostic and prognostic biomarker for cancer, with therapeutic value in immune-based, targeted, or cytotoxic treatments. Further clinical validation and exploration of FXR1 in cancer treatment is necessary.

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Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism

Cited by 110 publications

References 56 publications

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

Computational Exploration of the Structural Requirements of Triazole Derivatives as Colchicine Binding Site Inhibitors

Comprehensive bioinformatics analysis of FXR1 across pan-cancer: Unraveling its diagnostic, prognostic, and immunological significance

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