Targeting p53 misfolding conundrum by stabilizing agents and their analogs in breast cancer therapy: a comprehensive computational analysis - Haq, Burhan Ul; Qayoom, Hina; Sofi, Shazia; Jan, Nusrat; Shabir, Aisha; Ahmad, Irshad; Ahmad, Fuzail; Almilaibary, Abdullah; Mir, Manzoor A. (Frontiers in Pharmacology, 2024)
Cancer continues to be a major global public health concern and one of the foremost causes of death. Delays in the diagnosis and cure may cause an uptick in advanced stage disease and mortality. Particular to females currently, the most common cancer is breast carcinoma. The breast carcinoma has surpassed lung carcinoma and currently represents the chief type of cancer diagnosed (2.3 million new cases, which amount to 11.7% of all cancer cases). In addition, by 2040, the incidence will increase by more than 46% as per the estimates of GLOBOCAN. TNBC represents the highly aggressive and invasive subtype of breast cancer characterized by rapid progression, short response time to the available treatment and poor clinical results. Thus, it is very crucial to develop novel diagnostic tools and therapeutics with good efficacy. Majority of cancers display malfunction along the p53 pathway. Moreover, p53 not only loses its function but is prone to misfolding and aggregation, leading to formation of amyloid aggregates as well. Research is being carried out to locate ways to restore the normal action and expression of p53. Here we have explored PhiKan-083 for its possible stabilizing effect over p53, to address the problem with its misfolding. Thus, examining analogues of PhiKan-083 that display roles in p53 stability will help update our understanding of cancer progression and may expedite the progress of new anticancer treatments. We anticipate that the drug molecules and their analogues targeting p53 aggregation may be used in combination with other anticancer compounds to solve the problem with p53 aggregation. In this study, by employing ADMET analysis the compounds were screened and further examined the chosen compounds with the help of molecular docking. By utilising databases like UALCAN, TIMER, GEPIA, PredictProtein etc we investigated TP53's expression pattern and prognostic relevance in various cancer settings.