Abstract
Quinazoline derivatives have shown promising pharmacological activities against various diseases, including cancer, inflammation, and cardiovascular disorders. Computational studies have become an important tool in the discovery and optimization of new quinazoline derivatives. In this chapter, the importance and application of computational studies in finding new active quinazoline derivatives were discussed. The various computational techniques, such as molecular docking, molecular dynamics simulations, quantum mechanics calculations, and machine learning algorithms, which have been used to predict the biological activities and optimize the structures of quinazoline derivatives, were described. Examples of successful applications of computational studies in the discovery of new quinazoline derivatives with improved pharmacological activities were added. Overall, computational studies have proven to be valuable in the development of new quinazoline derivatives and have the potential to accelerate the drug discovery process.