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Virtual screening for the discovery of bioactive natural products.

机译：虚拟筛选，发现具有生物活性的天然产物。

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In this survey the impact of the virtual screening concept is discussed in the field of drug discovery from nature. Confronted by a steadily increasing number of secondary metabolites and a growing number of molecular targets relevant in the therapy of human disorders, the huge amount of information needs to be handled. Virtual screening filtering experiments already showed great promise for dealing with large libraries of potential bioactive molecules. It can be utilized for browsing databases for molecules fitting either an established pharmacophore model or a three dimensional (3D) structure of a macromolecular target. However, for the discovery of natural lead candidates the application of this in silico tool has so far almost been neglected. There are several reasons for that. One concerns the scarce availability of natural product (NP) 3D databases in contrast to synthetic libraries; another reason is the problematic compatibility of NPs with modern robotized high throughput screening (HTS) technologies. Further arguments deal with the incalculable availability of pure natural compounds and their often too complex chemistry. Thus research in this field is time-consuming, highly complex, expensive and ineffective. Nevertheless, naturally derived compounds are among the most favorable source of drug candidates. A more rational and economic search for new lead structures from nature must therefore be a priority in order to overcome these problems. Here we demonstrate some basic principles, requirements and limitations of virtual screening strategies and support their applicability in NP research with already performed studies. A sensible exploitation of the molecular diversity of secondary metabolites however asks for virtual screening concepts that are interfaced with well-established strategies from classical pharmacognosy that are used in an effort to maximize their efficacy in drug discovery. Such integrated virtual screening workflows are outlined here and shall help to motivate NP researchers to dare a step towards this powerful in silico tool.
机译：在这项调查中，虚拟筛选概念的影响在自然界发现药物的领域中进行了讨论。面对不断增加的次级代谢产物数量以及与人类疾病治疗相关的越来越多的分子靶标，需要处理大量信息。虚拟筛选过滤实验已经显示出对处理潜在生物活性分子大库的巨大希望。它可用于浏览数据库，以查找适合已建立的药效团模型或大分子靶标的三维（3D）结构的分子。但是，对于发现天然铅候选物，迄今为止几乎忽略了这种计算机软件工具的应用。有几个原因。一个问题是与合成库相比，天然产品（NP）3D数据库的稀缺性;另一个原因是NP与现代机器人化高通量筛选（HTS）技术之间的兼容性问题。进一步的论点涉及纯天然化合物的不可估量的可用性及其经常过于复杂的化学反应。因此，该领域的研究是耗时，高度复杂，昂贵且无效的。尽管如此，天然衍生的化合物仍是候选药物的最有利来源。因此，为了克服这些问题，必须优先考虑从自然界中寻找新的铅结构的更为合理和经济的方法。在这里，我们演示了虚拟筛选策略的一些基本原理，要求和局限性，并通过已进行的研究支持了它们在NP研究中的适用性。然而，对次生代谢物分子多样性的合理利用要求虚拟筛选概念与经典生药学中已建立的策略相联系，以最大程度地发挥其在药物发现中的功效。此处概述了这种集成的虚拟筛选工作流程，这将有助于激励NP研究人员敢于迈向这一强大的计算机软件工具。

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