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Application of Combination High‐Throughput Phenotypic Screening and Target Identification Methods for the Discovery of Natural Product‐Based Combination Drugs

机译:结合高通量表型筛选和目标鉴定方法在发现天然产物的组合药物中的应用

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Abstract 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.
机译:摘要现代药物发现努力随着发展成本的增加,平庸的成功率,这鼓励制药科学家寻求创新的方法。最近,随着系统生物学和代谢组织领域的崛起,网络药理学(NP)已经开始成为药物发现中的一个新的范例,重点关注治疗疾病的多种靶点和药物组合。药物组合益处的研究为药物发现中的天然产物进行了重新聚焦的基础。天然产物由多种成分组成,可以对身体中的各种靶标作用,以诱导药效学反应,该反应可以一起终止于添加剂或协同治疗效果。虽然天然产品不能获得专利,但它们可以用作发现有效组合治疗剂的起点。通过表型筛选可以确定天然产物中生物活性成分的最佳混合物。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机制,并通过实施反向药代动力学方法。该审查文章提供了支持基于天然产品的组合药物的潜在益处的证据,并总结了可以应用于这类药物的药物发现方法。

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