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.
Keywords: Pharmacophore modeling, virtual screening, natural products, natural product databases, parallel screening
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