Computational approaches to natural products-based lead discovery

Abstract

Innovative bioactive agents fuel drug discovery and the development of new medicines. Future success in chemical biology and pharmaceutical research will fundamentally rely on the combination of advanced synthetic and analytical technologies that are embedded in a theoretical framework that provides a rationale for the interplay between chemical structure and biological effect. A driving role in this setting falls on computer-assisted molecular design and engineering, by providing real-time access to a virtually infinite source of novel tool compounds and lead structures, and guiding experimental screening campaigns. We will present concepts and ideas for the representation of molecular structure, predictive models of structure-activity relationships, the de-orphaning of bioactive compounds, and discuss de novo design approaches that have proven their usefulness in drug discovery. Emphasis will be put on bioactive natural products as templates for computational lead discovery. We will showcase new methods for natural-product inspired molecular design and macromolecular target prediction.