Rational Genome Mining for Anti-Chagas Disease Agents

• Applicant: Dr. Lena Keller
• Subject Area: Pharmacy ; Biochemistry
• Term: from 2016 to 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 329128825

Natural products have indisputably played a major role in the development of small molecule drug therapy. Nevertheless, as rich and productive as this approach has been, genome mining efforts of microorganisms have revealed that they possess untapped wealth in terms of biosynthetic capacity to produce structurally diverse natural products. As a result, genome mining has been heralded as a renaissance for the field of natural products drug discovery; however, this promise has not been realized and so far, genome mining approaches have fallen short of expectations.While there are a multitude of potential problems that have contributed to this lack of productivity, a central drawback has been the irrationality of the search process; that is, in most cases it is not possible to deduce anything about the pharmacological properties of a molecule based on the gene structure of its biosynthetic pathway. Therefore, this proposal outlines another approach, based on computational methods, by which to make genome mining for useful natural products a more targeted and rational enterprise. Genome sequence data from marine cyanobacteria (blue-green algae) will be employed to predict the therapeutic potential of a compound before it is even isolated. Marine cyanobacteria are particularly suitable for this study since they have been shown to possess an enormous potential to produce structurally diverse natural products that exhibit a broad spectrum of potent biological activities. Being neglected by natural product scientists until the 1980s, cyanobacteria are now recognized as a promising yet underexplored source for novel natural products.As a first step, genomic sequence data will be matched with metabolomics data to identify the expressed metabolome and to collect all available information about the metabolites. This information will be used to predict hypothetic structures that will be tested in an inverse virtual screening effort with a set of target proteins. The set consists of ten validated target proteins in the parasitic agent of Chagas disease, a disease with a devastating chronic course. Compounds will be prioritized for the isolation process based on their potential binding activity and their structures will be elucidated using detailed NMR analysis. A set of enzymatic and whole cell assays will be run to verify the predicted bioactivity data.A successful implementation of this approach would highly increase the chances to discover bioactive natural products and to focus the laboratory work on bioactive compounds. With the dedication to new natural products that target Chagas, this work might also contribute to the development of drugs that help to prevent the chronic course of the disease. Furthermore, the developed approach could be transferred to other natural product producers as well as different target structures and would therefore provide the basis for further studies.

• DFG Programme: Research Fellowships
• International Connection: USA
• Host: Professor William H. Gerwick, Ph.D.