A aplicação das ferramentas in silico no desenvolvimento de quimioterápicos

This article explores the use of in silico tools in the development of chemotherapeutics, highlighting their ability to accelerate the discovery and optimization of new cancer treatments. Through techniques such as molecular docking, molecular dynamics, QSAR, and machine learning, researchers can simulate molecular interactions, enabling the identification and refinement of selective kinase inhibitors and other molecules with therapeutic potential. The studies cited demonstrate how these approaches contribute to more effective and personalized treatments, reducing both the costs and the time of drug development. Moreover, the integration of these techniques promises to revolutionize anticancer therapies, moving the field of oncology into an era of precision medicine.