Exploring the Target Genes of Fucosylated Chondroitin Sulfate in Treating Lung Adenocarcinoma Based on the Integration of Bioinformatics Analysis, Molecular Docking, and Experimental Verification

ACS Omega, Journal Year: 2024, Volume and Issue: 9(46), P. 46312 - 46322

Published: Nov. 9, 2024

Fucosylated chondroitin sulfate (FCS), extracted from sea cucumbers' body walls, has been found to inhibit the proliferation of lung adenocarcinoma (LUAD) cells. However, there have few studies associated drug targets. This study combined bioinformatics analysis and molecular docking screen main targets FCS intervention in LUAD. Moreover, an experimental validation was performed. First, we downloaded LUAD gene data set The Cancer Genome Atlas (TCGA) database cisplatin (DDP) resistance A549 cells Gene Expression Omnibus (GEO) database. Nine significant genes (PLK1, BUB1, CDK1, CDC20, CCNB1, BUB1B, KIF11, CCNB2, DLAGP5) were identified by analysis, these nine overlapped both sets. Then, results showed that had a better affinity with target proteins BUB1 PLK1. Further verification revealed inhibited growth increased sensitivity DDP. Quantitative real-time polymerase chain reaction (qRT-PCR) treated exhibited down-regulated PLK1 mRNA expression. At same time, FCS+DDP treatment resulted more reduction expression than DDP or alone. These findings reveal potential for provide clues development as anticancer agent.

Language: Английский

Computational Advancements in Cancer Combination Therapy Prediction

Published: July 20, 2023

As cancer remains resistant to several modes of treatment, novel therapeutics are still under active investigation overcome treatment inefficacy in cancer. Given the high attrition rate de novo drug discovery, screening, and repurposing have offered time- cost-effective alternative strategies for identification potentially effective therapeutics. In contrast large-scale screens, computational approaches leverage increasing amounts biomedical data predict candidate therapeutic agents prior testing biological models. Current studies therapy prediction increasingly focused on combination therapies, as therapies numerous advantages over monotherapies. These include increased effect from synergistic interactions, reduced toxicity lowered doses, a risk resistance due multiple non-overlapping mechanisms action. This review provides summary classes methods used research, including networks, regression-based machine learning, classifier learning models, deep approaches, with goal presenting current progress field, particularly non-computational biologists. We conclude by discussing need further advancements technologies that incorporate disease mechanisms, characteristics, multi-omics data, clinical considerations generate patient-specific combinations, holistic integration will inevitably result optimal targeted

Language: Английский

In vitro and in silico antibacterial evaluation of nitrocatechol chalcone and pyrazoline derivatives

Results in Chemistry, Journal Year: 2023, Volume and Issue: 6, P. 101194 - 101194

Published: Nov. 7, 2023

The aim of this study was to determine the in vitro antibacterial activity nitrocatechol chalcone and pyrazoline derivatives previously synthesised by our research group against Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii aerogenes, create validate a pharmacophore model using data. enrichment factor (EF10%) area under receiver operating characteristic (ROC-AUC) curve were used model. Using validated novel designed synthesised, whereafter these also determined susceptible bacteria. After initial screening, only had S. with compound 2a, 2b 1b (1 - 2 µg/ml) having comparable tetracycline (2 µg/ml). A common feature (max. fit: 4, rank score: 84.02) able accurately identify active chalcones within decoy test set. best performing model, i.e., hypothesis 9 (EF10%: 6.7, ROC-AUC: 0.85 ± 0.00) indicated that four hydrogen bond acceptors are important for activity. This guide design synthesis which both resistant aureus strains determined. most compounds 3i (0.5 3c strain respectively, more than tetracycline.

Language: Английский