Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:1.6.5.2 (NQO1)
 6,196 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Potential drug target identification and mechanism of action is an important step in drug discovery process, which can be achieved by biochemical methods, genetic interactions or computational conjectures. Sometimes more than one approach is implemented to mine out the potential drug target and characterize the on-target or off-target effects. A novel anticancer agent RH1 is designed as pro-drug to be activated by NQO1, an enzyme overexpressed in many types of tumors. However, increasing data show that RH1 can affect cells in NQO1-independent fashion. Here, we implemented the bioinformatics approach of modeling and molecular docking for search of RH1 targets among protein kinase species. We have examined 129 protein kinases in total where 96 protein kinases are in complexes with their inhibitor, 11 kinases were in the unbound state with any ligand and for 22 protein kinases 3D structure were modeled. Comparison of calculated free energy of binding of RH1 with indigenous kinase inhibitors binding efficiency as well as alignment of their pharmacophoric maps let us predict and ranked protein kinases such as KIT, CDK2, CDK6, MAPK1, NEK2 and others as the most prominent off-targets of RH1. Our finding opens new avenues in search of protein targets that might be responsible for curing cancer by new promising drug RH1 in NQO1-independent way.
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PMID:Molecular modeling and structure-based drug discovery approach reveals protein kinases as off-targets for novel anticancer drug RH1. 2887 92

The study aimed to clarify the potential immune-related targets and mechanisms of Qingyihuaji Formula (QYHJ) against pancreatic cancer (PC) through network pharmacology and weighted gene co-expression network analysis (WGCNA). Active ingredients of herbs in QYHJ were identified by the TCMSP database. Then, the putative targets of active ingredients were predicted with SwissTargetPrediction and the STITCH databases. The expression profiles of GSE32676 were downloaded from the GEO database. WGCNA was used to identify the co-expression modules. Besides, the putative targets, immune-related targets, and the critical module genes were mapped with the specific disease to select the overlapped genes (OGEs). Functional enrichment analysis of putative targets and OGEs was conducted. The overall survival (OS) analysis of OGEs was investigated using the Kaplan-Meier plotter. The relative expression and methylation levels of OGEs were detected in UALCAN, human protein atlas (HPA), Oncomine, DiseaseMeth version 2.0 and, MEXPRESS database, respectively. Gene set enrichment analysis (GSEA) was conducted to elucidate the key pathways of highly-expressed OGEs further. OS analyses found that 12 up-regulated OGEs, including CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 that could be utilized as potential diagnostic indicators for PC. Further, methylation analyses suggested that the abnormal up-regulation of these OGEs probably resulted from hypomethylation, and GSEA revealed the genes markedly related to cell cycle and proliferation of PC. This study identified CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 might be used as reliable immune-related biomarkers for prognosis of PC, which may be essential immunotherapies targets of QYHJ.
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PMID:Integrated Analyses Identify Immune-Related Signature Associated with Qingyihuaji Formula for Treatment of Pancreatic Ductal Adenocarcinoma Using Network Pharmacology and Weighted Gene Co-Expression Network. 3253 71