News & Events

Lindsay Caesar

Posted on February 20, 2019

When

Date - February 20, 2019
1:00 pm - 2:00 pm


What

PhD Defense
Faculty Advisor: Dr. Nadja Cech
Talk Title: Bioinformatics Strategies to Understand the Complexities of Medicinal Natural Product Mixtures

Abstract:

Compounds from natural sources, as well as those inspired by them, represent the majority of small molecule drugs on the market today. Plants, owing to their complex biosynthetic pathways, are poised to synthesize diverse secondary metabolites that selectively target biological macromolecules. Despite the vast chemical landscape of botanicals and other natural products, drug discovery programs from these sources have diminished due to the costly and time-consuming nature of standard practices and high rates of compound rediscovery. Bioinformatics tools can be used to integrate biological and chemical datasets, allowing researchers to predict active constituents early in the fractionation process and to tailor isolation efforts towards the most biologically relevant compounds. A recent validation study has demonstrated the applicability of this approach for predicting antimicrobial compounds from complex mixtures, in addition to identifying the method’s limitations and opportunities. Often, analytical tools aimed to assess biological mixtures ascribe the activity to a few known components. Although researchers recognize this as an oversimplification, research methodologies to address this problem have not been developed. We have recently conceived of a new approach, Simplify, that can both identify mixture components that contribute to biological activity and characterize the nature of their interactions prior to their isolation. As a test case, this approach has been applied to correctly identify both additive and synergistic compounds from a botanical medicine. These findings illustrate the efficacy of this approach for understanding how natural product mixtures work in concert, and are expected to serve as a launching point for the comprehensive evaluation of mixtures in future studies.