Introduction
This thematic issue aims to highlight recent advances in the integration of computational methodologies and experimental validation strategies in phytopharmacology for cancer therapeutics. Natural products and phytochemicals continue to serve as valuable sources for the discovery of novel anticancer agents; however, efficient translation into clinically relevant therapeutics requires multidisciplinary approaches combining artificial intelligence, molecular modeling, systems pharmacology, bioinformatics, and experimental oncology. This issue will focus on emerging computational platforms for target identification, prediction of pharmacological activities, network-based mechanistic analyses, molecular docking, omics-driven approaches, and machine learning-assisted drug discovery, together with in vitro, in vivo, and translational validation studies. The issue will further emphasize precision oncology, phytochemical-mediated modulation of tumor microenvironment, overcoming therapeutic resistance, nanotechnology-enabled delivery systems, and clinical translation of phytopharmaceuticals for cancer prevention and therapy.
Keywords
Computational Phytopharmacology, Anticancer Phytochemicals, Molecular Docking, Systems Pharmacology, Machine Learning Drug Discovery, Precision Oncology, Nanotechnology Drug Delivery
Sub-topics
- AI-Driven Discovery and Virtual Screening of Anticancer Phytochemicals
- Molecular Docking, Molecular Dynamics, and Systems Pharmacology Approaches in Phytopharmacology
- Multi-Omics and Bioinformatics Approaches for Phytochemical Target Identification
- Experimental Validation of Phytochemical-Mediated Anticancer Mechanisms
- Phytochemicals Targeting Cancer Stem Cells, EMT, proliferation, metastasis, and Tumor Microenvironment
- Nanotechnology-Based Delivery Systems for Phytochemical Therapeutics
- Translational and Clinical Perspectives of Computational Phytopharmacology in Cancer Therapy
