Literature Review : Perbandingan Aktivitas Senyawa Kimia Yang Berpotensi Sebagai Kandidat Obat Kanker Payudara Oral Menggunakan Metode In Silico - Akifah, Muthia Nur; Damara , Dandy Satria; Putri , Indah Syah; Utami , Marshah Rahmawati (Journal of Pharmaceutical and Sciences, 2025)
Breast cancer is a type of cancer with a high prevalence rate, especially in women, which contributes significantly to the global death rate from cancer. This disease is characterized by abnormal cell growth that attacks body tissues and is often difficult to treat due to the limitations of effective treatment and minimal side effects. Although treatments such as chemotherapy, surgery, and radiation therapy are available, significant side effects, including impaired patients' quality of life, remain a major challenge. Therefore, a new approach is needed to find drug candidates with high efficacy and lower side effects.  This study aims to compare the activity of chemical compounds that have the potential to be used as a breast cancer drug using the in silico method. The method involves computer simulations to evaluate molecular interactions with cancer receptors, such as ER-α and HER-2, as well as verify their pharmacokinetic feasibility through compliance with Lipinski's rules. This review literature draws on eight relevant recent studies, showing that some compounds have significant activity against cancer receptors and meet pharmacokinetic criteria for oral administration. The results of the analysis revealed that Longipinocarvone compounds had the best affinity for ER-α receptors (-8.20 kcal/mol), while Galagin showed the best affinity for HER-2 (-7.79 kcal/mol). Both also meet Lipinski's rule, indicating the potential to be developed into an oral drug. This in silico simulation provides efficient and cost-effective initial insight into the drug discovery process. The study concluded that both compounds have the potential to be promising breast cancer drug candidates, although further validation through in vitro and in vivo trials is needed to support these results.