RESUMO
Glioblastoma (GBM) is a highly aggressive and lethal type of brain tumor with complex and diverse molecular signaling pathways involved that are in its development and progression. Despite numerous attempts to develop effective treatments, the survival rate remains low. Therefore, understanding the molecular mechanisms of these pathways can aid in the development of targeted therapies for the treatment of glioblastoma. Nanomedicines have shown potential in targeting and blocking signaling pathways involved in glioblastoma. Nanomedicines can be engineered to specifically target tumor sites, bypass the blood-brain barrier (BBB), and release drugs over an extended period. However, current nanomedicine strategies also face limitations, including poor stability, toxicity, and low therapeutic efficacy. Therefore, novel and advanced nanomedicine-based strategies must be developed for enhanced drug delivery. In this review, we highlight risk factors and chemotherapeutics for the treatment of glioblastoma. Further, we discuss different nanoformulations fabricated using synthetic and natural materials for treatment and diagnosis to selectively target signaling pathways involved in GBM. Furthermore, we discuss current clinical strategies and the role of artificial intelligence in the field of nanomedicine for targeting GBM.
Assuntos
Glioblastoma , Humanos , Glioblastoma/patologia , Nanomedicina , Inteligência Artificial , Barreira Hematoencefálica/metabolismo , Transdução de SinaisRESUMO
Breast cancer invasive 2.3 million women worldly and second prominent factor of cancer-related mortality. Finding a new site-specific and safe small molecule is a current need in this field. With the aid of deep learning Algorithms, we analyzed the published big database from cancer CBioportal to find the best target protein. Further, Multi-omics analysis such as enrichment analysis, scores of molecular, RNA biological function at a cellular level, and protein domain were obtained and matched to find the better hit molecules. The gene analysis output shows nucleolar protein 6 plays a significant responsibility in breast carcinoma and 354 natural and synthetic lead molecules are docked inside the active site. Docking result gave the output hit molecule falavan-3-ols with a binding score of -5.325 (Kcal/mol) and interaction analysis illustrates, 13 active amino acids favoring the binding interaction with functional groups of the hit molecule compared to the standard molecule Abemacilib (-2.857 (Kcal/mol)). Best docked complex of flavan-3-ols and NOL6 protein subjected to dynamic simulation 100â¯ns to study the stability. The results proved that π-π stacked, carbonhydrogen and electrostatic interactions are stable throughout the 100â¯ns simulation. The overall results conclude the hit molecule flavan-3-ol will be a safe and potent lead molecule to generate and treat breast carcinoma patients.