Computational Discovery of Novel Herbal Phytoconstituents for Lung Cancer Treatment

Lung cancer is the leading cause of cancer-related death worldwide due to late diagnosis and limited treatment interventions. The adverse effects and therapeutic resistance development are among the most potent clinical issues for lung cancer treatment. In the present investigation, we used advanced computational tools and techniques to identify and evaluate potential herbal phytoconstituents that could target VEGFR. We collected the phytochemical constituents from web servers such as PubChem, zinc15, and Drug Bank using a systemic literature survey. We have downloaded the protein 3D structure using a protein data bank (PDB) to the local computer. The downloaded structure was prepared using software like Auto Dock vina 1.2.0 version 2021. and Discovery visualizer. In the present work, we have used computational techniques like molecular docking between target and ligands to measure the binding affinity generated. For docking and lead findings, we have used software like Pyrex and Auto Dock Vina. The selected ligands were further analyzed for their systemic properties; we have used several web servers provided by govt. of Switzerland. The present work carried out on lung cancer produced several phytoconstituents with both drug-like properties and can come out as potential therapeutic agents. The authors of the study strongly recommend that wet laboratory experiments to be conducted for the listed phytoconstituents