Pharmacophore-Based Screening for the Successful Identification of Bio-Active Natural Products

Abstract

We report on the impact of pharmacophore-based virtual screening in the field of drug discovery from natural products. Confronted by an increasing number of secondary metabolites and an increasing number of biomolecular targets relevant in the therapy of human disorders, there is clearly the need for efficient data management. Filtering of compounds by virtual screening experiments already showed great effect when dealing with large libraries of potential bioactive molecules. Feature-based 3D pharmacophores have been successfully utilized for database mining in order to retrieve potentially bio-active molecules. However, for the discovery of natural lead candidates, the application of such in silico tools has been so far almost neglected. There seems to be several reasons for this. One concerns the scarce availability of natural product (NP) 3D databases in contrast to synthetic/combinatorial compound libraries; another reason might be the problematic compatibility of NPs with modern robotized high-throughput-screening (HTS) technologies. Additionally, the incalculable availability of pure natural compounds and their often too complex chemistry is claimed to hamper such an approach. Thus, research in this field appears time-consuming, highly complex, expensive, and ineffective. Nevertheless, naturally derived compounds are still among the most favorable sources of new drug candidates. A more rational and economic search for new lead structures originating from nature must therefore be a priority in order to overcome these problems.