Modern drug discovery efforts have had mediocre success rates with increasing developmental costs, and this has encouraged pharmaceutical scientists to seek innovative approaches. Recently with the rise of the fields of systems biology and metabolomics, network pharmacology (NP) has begun to emerge as a new paradigm in drug discovery, with a focus on multiple targets and drug combinations for treating disease. Studies on the benefits of drug combinations lay the groundwork for a renewed focus on natural products in drug discovery. Natural products consist of a multitude of constituents that can act on a variety of targets in the body to induce pharmacodynamic responses that may together culminate in an additive or synergistic therapeutic effect. Although natural products cannot be patented, they can be used as starting points in the discovery of potent combination therapeutics. The optimal mix of bioactive ingredients in natural products can be determined via phenotypic screening. The targets and molecular mechanisms of action of these active ingredients can then be determined using chemical proteomics, and by implementing a reverse pharmacokinetics approach. This review article provides evidence supporting the potential benefits of natural product‐based combination drugs, and summarizes drug discovery methods that can be applied to this class of drugs.

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组合高通量表型筛选和目标识别方法在基于天然产物的组合药物发现中的应用

现代药物发现的努力取得了中等水平的成功率，同时开发成本也不断增加，这鼓励了药物科学家寻求创新方法。最近随着系统生物学和代谢组学，网络药理学领域的兴起（NP）已开始成为药物发现的新范例，重点放在治疗疾病的多种靶标和药物组合上。有关药物组合益处的研究为重新关注药物发现中的天然产物奠定了基础。天然产物由多种成分组成，这些成分可以作用于体内的多种靶标，以诱导药效学反应，这些反应可能最终达到加和或协同的治疗作用。尽管天然产物不能申请专利，但它们可以用作发现有效联合疗法的起点。天然产物中生物活性成分的最佳混合可以通过表型筛选来确定。然后可以使用化学蛋白质组学确定这些活性成分的靶标和分子作用机理，并通过实施反向药代动力学方法。这篇综述文章提供了支持基于天然产物的联合药物潜在益处的证据，并总结了可应用于此类药物的药物发现方法。