Drug discovery against FGFR2 mutation in lungs cancer approach using NGS and medicinal plant

Lung cancer remains one of the most prevalent and deadly malignancies worldwide, necessitating the development of more effective and targeted therapeutic strategies. The integration of Next-Generation Sequencing (NGS) technologies with traditional medicinal plant-based drug discovery offers a promising avenue for identifying novel bioactive compounds and their molecular targets. This study explores a combinatorial approach where high-throughput NGS data is utilized to decode the transcriptomic and genomic landscapes of lung cancer, enabling the identification of key oncogenes, tumor suppressor genes, and signaling pathways involved in disease progression. Concurrently, bioactive phytochemicals from selected medicinal plants are screened for their potential to modulate these molecular targets. In silico analyses including protein-ligand docking, pharmacokinetic profiling, and toxicity prediction are employed to validate the therapeutic relevance of candidate compounds. Structural modeling and validation using tools like PyMOL, ERRAT, and Ramachandran plot analysis, further ensure the accuracy of target-ligand interactions. This integrative methodology not only accelerates the drug discovery pipeline but also leverages the untapped reservoir of natural compounds in combating non-small cell lung cancer (NSCLC). The findings of this study underscore the potential of combining NGS-based target discovery with phytochemical screening as a cost-effective, precise, and innovative strategy for anti-cancer drug development