Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms.

Journal: Trends in cancer
Published Date:

Abstract

Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anticancer drugs such as Taxol (paclitaxel). Natural products provide diverse mechanisms of action and can be used directly or as prodrugs for further anticancer optimization. Despite the success, major bottlenecks can delay anticancer lead discovery and implementation. Recent advances in sequencing and omics-related technology have provided a mine of information for developing new therapeutics from natural products. Artificial intelligence (AI), including machine learning (ML), has offered powerful techniques for extensive data analysis and prediction-making in anticancer leads discovery. This review presents an overview of current AI-guided solutions to discover anticancer lead compounds, focusing on natural products from plants and associated microorganisms.

Authors

  • Gang Li
    The Centre for Cyber Resilience and Trust, Deakin University, Australia.
  • Ping Lin
    Department of Geriatrics, The Third Hospital of Hangzhou, Hangzhou, Zhejiang, China.
  • Ke Wang
    China Electric Power Research Institute, Haidian District, Beijing 100192, China. wangke1@epri.sgcc.com.cn.
  • Chen-Chen Gu
    Department of Natural Medicinal Chemistry and Pharmacognosy, School of Pharmacy, Qingdao University, Qingdao 266071, People's Republic of China.
  • Souvik Kusari
    Center for Mass Spectrometry, Faculty of Chemistry and Chemical Biology, Technische Universität Dortmund, Dortmund 44227, Germany. Electronic address: souvik.kusari@tu-dortmund.de.