基因组挖掘指导天然药物分子的发现

Genome mining-directed discovery for natural medicinal products

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。

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.