In silico investigation of the efficacy of benzopyrazine derivatives on breast cancer by VEGFR2 inhibition using ML/DL based CADD software

Angiogenesis is a critical pathway for cancer; The formation of new blood vessels is essential for the growth and metastasis of tumors. VEGF and its receptor VEGFR also play important roles in angiogenesis. VEGFR2 stands out as an important therapeutic target for breast cancer treatment. In this study, the interaction between benzopyrazine derivatives and VEGFR2 was evaluated using computer-based drug design (CADD) models, bioinformatics analyses and complementary computational methods. Biological activity predictions were made by developing the interaction data of 49 benzopyrazine-derived compounds in a virtual environment and by developing a QSAR model. Binding stability of proteins in newly designed structures was demonstrated with molecular dynamics simulations. ADMET predictions reveal that these tables have appropriate pharmacokinetic metabolism. Synthesizability of compounds with the best docking scores was calculated with artificial intelligence using the Retroscheme software. For compound number 46, which has the highest potential, molecular dynamics simulation data for 500 ns were calculated via the Desmond interface and its binding was interpreted. The study particularly shows that compound 46 may be an effective VEGFR2 inhibitor in the treatment of breast cancer.