In Silico‐Guided Strategies for the Discovery and Rationalization of Bioactive Natural Products

Abstract

The identification of bioactive natural products is a multidisciplinary research field. One methodology used in this research environment is the application of computational (virtual) screening. In silico screening allows for focusing experimental efforts on promising plant material and constituents. Starting from the chemical structures of natural products in the form of 3D multiconformational databases, virtual screening methods predict potentially active compounds within the screened database. For this task docking, pharmacophore‐based screening, 2D similarity searches, quantitative structure–activity relationship (QSAR) modeling, and neural networks can be employed. A procedure for selecting the most promising virtual hits for further analyses is described. In addition, bioactivity profiling and activity rationalization strategies are shown. Finally, also the limits of the virtual approaches are discussed. This chapter gives an overview of virtual screening applications in the field of natural product research. In addition, selected examples and strategies are described in detail.