AI-Driven Scientific Prompting and Sequential Discovery Pipeline for AKT1-Targeted Predictive Modelling and Therapeutic Insights in Breast Cancer Using Curcumin from Turmeric

Abstract

Breast cancer remains one of the most prevalent malignancies worldwide and represents a major cause of cancerrelated mortality among women. Despite substantial progress in early detection and treatment strategies, the disease continues to pose significant clinical challenges due to its molecular heterogeneity, metastatic potential, and resistance to therapeutic interventions. Among the numerous molecular pathways involved in breast cancer development, the phosphatidylinositol-3-kinase/protein kinase B (PI3K–AKT) signaling pathway plays a central role in regulating tumor cell proliferation, survival, metabolism, and angiogenesis. AKT1, a serine/threonine kinase belonging to the AKT protein family, is one of the most critical components of this pathway and has been extensively investigated as a therapeutic target in cancer research. In recent years, artificial intelligence (AI) has emerged as a powerful tool capable of transforming drug discovery and biomedical research. AI-based computational models enable researchers to analyze large biological datasets, predict molecular interactions, and identify potential therapeutic compounds with high efficiency. The concept of AI-driven scientific prompting has recently gained attention as a structured approach for guiding artificial intelligence systems to perform complex scientific analyses, including target identification, molecular docking, predictive modelling, and drug optimization. Curcumin, the principal bioactive compound of turmeric (Curcuma longa), has attracted significant interest in cancer research due to its diverse pharmacological activities. Numerous studies have demonstrated that curcumin exhibits anti-inflammatory, antioxidant, and anticancer properties through modulation of multiple molecular pathways, including PI3K–AKT, NF-κB, and MAPK signaling pathways. Curcumin has been shown to suppress tumor cell proliferation, induce apoptosis, inhibit angiogenesis, and reduce metastatic potential in several types of cancers, including breast cancer. The integration of artificial intelligence with phytochemical research offers a promising strategy for accelerating the discovery of novel therapeutic agents targeting key oncogenic proteins such as AKT1. AI-driven discovery pipelines combine computational approaches such as network pharmacology, molecular docking, machine learning predictive modelling, and systems biology analysis to evaluate potential drug candidates and understand their mechanisms of action. This review article provides a comprehensive overview of the role of AKT1 in breast cancer progression and highlights the therapeutic potential of curcumin as a natural inhibitor of AKT signaling. Furthermore, the review discusses the emerging role of artificial intelligence in drug discovery and explores how AI-driven scientific prompting can facilitate the identification and optimization of natural compounds for cancer therapy.