University of Innsbruck, Institute of Pharmacy, Department of Pharmaceutical Chemistry, Innsbruck, Austria.
Curr Pharm Des. 2010 May;16(15):1666-81. doi: 10.2174/138161210791164072.
Natural products have been exposed to a long selection process to interact with biological targets and are therefore a valuable source for ideas for novel chemical entities in drug development. However, the process to determine activities of natural products is mainly based on serendipity, and can thus become time- and cost-intensive. In this review we present strategies on how modern in-silico molecular modeling techniques can be used to make this process more efficient and discuss how to discover and optimize drug candidates inspired by nature. Focusing on 3D pharmacophore modeling techniques, we provide an overview of virtual screening and modeling methods, review available in silico databases as sources for chemical structures of natural products, discuss techniques for biological activity profiling, and summarize recent success stories for the combination of in-silico approaches and pharmacognosy.
天然产物经过长期的生物靶标相互作用选择过程,因此是药物开发中新型化学实体的宝贵来源。然而,确定天然产物活性的过程主要基于偶然发现,因此可能会变得耗时且昂贵。在这篇综述中,我们介绍了如何使用现代计算分子建模技术来提高这个过程的效率,并讨论了如何发现和优化受自然启发的药物候选物。本文重点介绍了 3D 药效团建模技术,提供了虚拟筛选和建模方法的概述,回顾了可用于天然产物化学结构的现有计算数据库,讨论了生物活性谱分析技术,并总结了计算方法与生药学相结合的最新成功案例。