基因组挖掘指导天然药物分子的发现

doi:10.12211/2096-8280.2023-086

合成生物学 ›› 2024, Vol. 5 ›› Issue (3): 447-473.DOI: 10.12211/2096-8280.2023-086

基因组挖掘指导天然药物分子的发现

奚萌宇¹^,², 胡逸灵¹, 顾玉诚³, 戈惠明¹

^1.南京大学生命科学学院，医药生物技术全国重点实验室，江苏南京 210023
^2.南京大学化学化工学院，江苏南京 210023
^3.先正达Jealott’s Hill国际研发中心，英国，伯克郡，布拉克内尔 RG42 6EY

收稿日期:2023-11-28 修回日期:2024-02-20 出版日期:2024-06-30 发布日期:2024-07-12
通讯作者: 戈惠明
作者简介:奚萌宇（1995—），女，博士研究生。研究方向为解析放线菌来源天然产物生物合成途径和机制；基因组挖掘发现新颖天然产物。E-mail：dg20240120@smail.nju.edu.cn
胡逸灵（1989—），男，博士，博士后。研究方向为天然产物的基因组挖掘和人工智能在天然产物发现中的应用。E-mail：huyiling10@163.com
戈惠明（1980—），男，教授，博士生导师。研究方向为挖掘微生物中新型药源分子；解析重要微生物活性分子的生物合成途径和机制；工程改造新型生物催化剂；合成生物学智造高值化学品。E-mail：hmge@nju.edu.cn
基金资助:
国家重点研发计划(2018YFA0902000);国家自然科学基金(81925033)

Genome mining-directed discovery for natural medicinal products

Mengyu XI¹^,², Yiling HU¹, Yucheng GU³, Huiming GE¹

^1.State Key Laboratory of Pharmaceutical Biotechnology，School of Life Sciences，Nanjing University，Nanjing 210023，Jiangsu，China
^2.School of Chemistry and Chemical Engineering，Nanjing University，Nanjing 210023，Jiangsu，China
^3.Syngenta Jealott’s Hill International Research Centre，Bracknell RG42 6EY，Berkshire，UK

Received:2023-11-28 Revised:2024-02-20 Online:2024-06-30 Published:2024-07-12
Contact: Huiming GE

摘要/Abstract

摘要：

天然产物是临床药物的主要来源，也是新药研发过程中先导化合物结构设计和优化的灵感源泉。但传统策略天然药源分子的发现却遭遇了瓶颈，新颖天然产物的数量逐渐无法满足现代药物开发的需求和应对全球多药耐药的威胁。随着测序技术的快速迭代，生物学的研究进入了基因组时代，基因组挖掘指导天然产物定向发现的策略得以确立，成功摆脱了传统天然产物发现策略对于生物样本生物量的依赖，极大提高了活性天然产物发现的特异性和成功率。本文简述了基因组挖掘以及相关数据库和生物信息学工具的发展，详细介绍了包括基于核心基因或后修饰基因的经典挖掘手段，自抗性机制、进化理论指导的基因组挖掘和人工智能在活性天然产物发现中的具体应用，并对基因组挖掘在药物发现和多学科交叉领域的影响和发展进行了展望。基因组信息中蕴藏着无可估量的化学潜能，促进基因组挖掘与其他学科间的交叉融合，提升对遗传信息的处理和分析能力，增强下游基因簇表达通量和产物结构预测能力，可实现天然小分子高通量、高新颖性和高效率的发现，为开发具有自主知识产权的新药物、新化学品和新型酶催化剂服务。

关键词: 基因组挖掘, 天然产物, 药物发现, 生物合成, 人工智能, 数据库

Abstract:

Natural products and their derivatives are main sources for lead compounds in drug discovery and development. Canonical natural product discovery relies largely on biological activity-guided or chromatographic identification-oriented screening strategies, which have achieved great success so far. However, the limitations of these methods, such as time consumption, labor intensity, and the noises of abundant natural products, have constrained productivities in discovering novel active natural products for drug development and combating the rising threat of drug resistance. Modern biotechnology, particularly the development of DNA sequencing and computational technology, has made it possible to study the biosynthesis of natural products, enabling us to connect genetic sequences with natural product structures for predicting the potentials of natural products produced by specific biological species at the genetic level. Therefore, genome mining-directed discovery for natural products has emerged. In addition to mining methods dependent on the conservation of genes encoding core enzymes for natural product biosynthesis, recently developed activity-oriented and intelligence-assisted genome mining strategies provide more opportunities for discovering naturally medicinal products. This article reviews the history of genome mining, highlighting advances in related databases, tools, and algorithms, with a focus on recent cases and applications of classic genome mining as well as self-resistance mechanism, evolutionary theory and artificial intelligence guided mining in the discovery of naturally active products. Since genomic information contains enormous chemical potentials, the discovery of natural products with high throughput and efficiency can accelerate the development of new drugs, new chemicals and new catalysts.

Key words: genome mining, natural products, drug discovery, biosynthesis, artificial intelligence, databases

中图分类号:

奚萌宇, 胡逸灵, 顾玉诚, 戈惠明. 基因组挖掘指导天然药物分子的发现[J]. 合成生物学, 2024, 5(3): 447-473.

Mengyu XI, Yiling HU, Yucheng GU, Huiming GE. Genome mining-directed discovery for natural medicinal products[J]. Synthetic Biology Journal, 2024, 5(3): 447-473.

图/表 13

图1 烯二炔类天然产物生物合成基因簇及代表性化合物

Fig. 1 BGCs and representative compounds of enediyne

图2 从细菌天然基因簇的组成中获得启示，发现抗耐药株的新型多黏菌素类分子Macolacin［59］

Fig. 2 Discovery of the antibiotic Macolacin through the syn-BNPs strategy[59]

图3 从放线菌基因组中挖掘活性膦酸盐类天然产物

Fig. 3 Discovery of natural phosphates through the genome mining

图4 针对萜类合酶的基因组挖掘发现八放珊瑚来源的萜类［74］

Fig. 4 Discovery of octocoral terpene cyclases and natural products synthesized by the enzymes through the genome mining[74]

图5 卤代天然产物的基因组挖掘

Fig. 5 Genome mining for the discovery of halogen-containing natural products

图6 通过基因组挖掘发现新型硒代天然产物

Fig. 6 Genome mining for the discovery of selenium-containing metabolites

图7 基因组挖掘含哌嗪酸和二醇二氮𬭩结构单元的天然产物

Fig. 7 Genome mining for the discovery of natural products containing piperazic acid or diazeniumdiolate units

图8 RaS-RiPPs序列相似性网络和对应的交联产物［111-115］（已表征类群的rSAM酶催化形成的交联由红色标注）

Fig. 8 Sequence similarity network analysis of RaS-RiPPs and the discovery of the cross-linked products [111-115](red: new bonds formed by rSAM enzymes)

图9 真菌来源的RiPPs以及催化其环化的酶

Fig. 9 Representative fungal RiPPs and the enzymes responsible for catalyzing their cross-linking

图10 植物分支环肽发掘流程

Fig. 10 Discovery of the side-chain-macrocyclic peptides from plants

图11 自抗性基因导向的基因组挖掘获得活性天然产物

Fig. 11 Self-resistance gene directed natural product discovery

图12 构建系统发育树指导新颖天然产物的发现［143］

Fig. 12 Phylogeny‑guided genome mining for discovering new natural products[143]

图13 人工智能在基因组挖掘中的应用

Fig. 13 AI-assistant and genomics-directed discovery of active natural products

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基因组挖掘指导天然药物分子的发现

Genome mining-directed discovery for natural medicinal products

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