Sahana Soumitra, Sarkar Jyotirmay, Mandal Sourav, Chatterjee Indranil, Dhar Susmita, Datta Samaresh, Mondal Sumanta
Department of Pharmacognosy, Birbhum Pharmacy School, Kolkata, West Bengal, India.
Faculty of Pharmacy, C. V. Raman Global University, Bhubaneswar, Odisha, India.
Funct Integr Genomics. 2025 Jun 19;25(1):132. doi: 10.1007/s10142-025-01645-7.
The field of natural product (NPs) discovery has significantly evolved with the advent of multi-omics approaches, encompassing genomics, transcriptomics, proteomics, and metabolomics. This review highlighting targeted isolation strategies and the comprehensive applications of omics in investigating natural products. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools that revolutionize the traditional methods of natural product discovery. This review delves into the integration of multi-omics technology in the isolation and discovery of natural product. Omics applications in natural product investigation have revolutionized the field by enabling high-throughput screening, rapid identification of novel compounds, and understanding the complex interactions within biological systems. For instance, metabolomics gives insights into the metabolic profiles of organisms under different conditions, aiding in the discovery of unique NPs with potential therapeutic applications. Genomics has facilitated the mining of microbial genomes for biosynthetic gene clusters, leading to the discovery of new antibiotics and carcinopreventive agents. Transcriptomics and proteomics provide insights into gene expression and protein synthesis, revealing the dynamics of NPs biosynthesis under various conditions. Despite these limitations, the future prospects of multi-omics in natural product discovery are promising. Advances in omics technologies, coupled with machine learning and artificial intelligence, are expected to enhance data integration and predictive modeling, accelerating the discovery and development of innovative drugs. Furthermore, the continuous improvement in analytical techniques and the establishment of comprehensive databases will facilitate the identification and characterization of NPs, ultimately contributing to the development of new therapeutic agents. Collaborative efforts across disciplines and the integration of environmental and ecological data will further enhance our understanding of NP biosynthesis and lead to more effective and sustainable drug discovery strategies.
随着多组学方法的出现，包括基因组学、转录组学、蛋白质组学和代谢组学，天然产物（NP）发现领域发生了重大演变。本综述重点介绍了靶向分离策略以及组学在天然产物研究中的综合应用。组学技术，包括基因组学、转录组学、蛋白质组学和代谢组学，已成为强大的工具，彻底改变了天然产物发现的传统方法。本综述深入探讨了多组学技术在天然产物分离和发现中的整合。组学在天然产物研究中的应用通过实现高通量筛选、快速鉴定新化合物以及理解生物系统内的复杂相互作用，彻底改变了该领域。例如，代谢组学可深入了解不同条件下生物体的代谢谱，有助于发现具有潜在治疗应用的独特天然产物。基因组学促进了对微生物基因组中生物合成基因簇的挖掘，从而发现了新的抗生素和防癌剂。转录组学和蛋白质组学提供了对基因表达和蛋白质合成的见解，揭示了不同条件下天然产物生物合成的动态过程。尽管存在这些局限性，多组学在天然产物发现中的未来前景依然广阔。组学技术的进步，再加上机器学习和人工智能，有望加强数据整合和预测建模，加速创新药物的发现和开发。此外，分析技术的不断改进和综合数据库的建立将有助于天然产物的鉴定和表征，最终推动新治疗剂的开发。跨学科的合作努力以及环境和生态数据的整合将进一步加深我们对天然产物生物合成的理解，并带来更有效和可持续的药物发现策略。
