In silico screening of chalcone derivatives as promising EGFR-TK inhibitors for the clinical treatment of cancer.

ABSTRACT: Epidermal growth factor receptor (EGFR) promotes tumorigenic characteristics and activates cancer-associated signaling pathways such as Wnt/-catenin, transforming growth factor (TGF-β), and phosphoinositide-3-kinase (PI3K). Several inhibitors have been reported to suppress the activity of EGFR and are being used in cancer treatment. However, patients in the malignant stage of cancer show resistance to those inhibitors, opening a wide space for research to discover novel inhibitors. Therefore, we carried out machine learning and virtual screening to discover novel inhibitors with high affinity against EGFR-TK. Initially, a library of 2640 chalcones were screened out using a machine-learning model developed based on the random forest algorithm, exhibiting high sensitivity and a Receiver Oper

SUBMITTER: Mathpal S 

PROVIDER: S-EPMC10730483 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature