Network analysis and ligand-based pharmacophore modeling for discovery of small molecule against glioblastoma multiforme.
Vishnu Vasanthi RadhakrishnanSonu BennyAneesh Thankappan PresannaPublished in: Future medicinal chemistry (2022)
Aim: This study uses network pharmacology to design a c-Src inhibitor followed by pharmacophore modeling to combat glioblastoma multiforme. These in silico approaches are suitable for designing and developing new molecules of interest. Materials & methods: The authors performed virtual screening, pharmacophore analysis and validation of results using various in silico tools and reliable data from different types of literature and databases. Results: The in silico pipeline the authors followed produced reliable chemical information to combat glioblastoma. The authors identified a chemical template against the c-Src protein, which was validated statistically and computationally. Conclusion: The authors have successfully identified a chemical template against c-Src , which will be developed into a promising inhibitor in future studies.
Keyphrases
- molecular docking
- small molecule
- network analysis
- tyrosine kinase
- protein protein
- molecular dynamics simulations
- molecular dynamics
- systematic review
- big data
- molecularly imprinted
- high throughput
- electronic health record
- machine learning
- current status
- binding protein
- healthcare
- mass spectrometry
- artificial intelligence
- health information
- deep learning
- case control