Virtual Screening for the Discovery of Active Principles from Natural Products

Computational methods are a powerful knowledge-based a approach that helps to select plant material or natural products (NP) with an increased likelihood for biological activity. These methods enable the rationalization of biological activities of NP and contribute to putative protein-ligand binding characteristics of these molecules. In this way, focusing on information about highly ranked virtual hits from properly validated in silico models is a rationale to streamline experimental efforts. In silico approaches can focus on well-known constituents of herbal remedies as well as on any natural compound with relevant biological effects directly retrieved from the literature. They might further be helpful for the selection of promising starting material for an experimental work-up. This chapter provides a general overview to students and researchers, who will step in this emerging and exciting field of science. It gives a brief introduction into the field of cheminformatics and presents different virtual screening strategies implemented in pharmacognostic workflows to point out opportunities and challenges in NP-based drug discovery.