Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies

Abstract

Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.

Keywords: anticancer drug discovery; clinical trials; computational drug design; drug design; molecular dynamics; natural product.

Figure 1

Various therapeutic strategies for cancer treatment.

Figure 2

Natural compounds from various sources exhibit anti-cancer activity.

Figure 3

Mode of action and molecular targets of natural compounds involved in cancer development. The molecular targets are BCL-1, MCL-1, Caspase-2, CDK, p53, VEGF (Vesicular Endothelial Growth Factor), NF-kB, TGFB1, NRF2, MMP, Fatty Acid Synthase, Tellomarase, P13, AKT, mTOR, EGFR, Histone Demthylase, PRAP, and Topoisomease.

Figure 4

The discovery of natural compounds undergoes various stages, which include computational methods and the validation. The computational methods follow sequential steps that involve retrieval of natural compounds, molecular modelling, pharmacophore modelling, QSAR analysis, virtual screening and molecular dynamic simulation. Based on the binding scores, the top natural compounds against the molecular target will be further validated under the in vitro and in vivo cancer model.