Novel Antimalarial Drug Candidates Generated In Silico by Analysis of Public HTS Data
Poster Sep 24, 2012
Robert Fraczkiewicz, Michael S. Lawless, Robert D. Clark, and Walter S. Woltosz
The World Health Organization has estimated that over 200 million people suffered from malaria in 2010 and that over 600,000 people died from it that year. Growing problems with resistance to existing anti-malarial drugs makes identification of new drugs a high priority. We applied a series of state-of-the-art In Silico tools to publicly available activity data from screens carried out on intact Plasmodium falciparum parasites to yield a handful of candidate molecules predicted to combine potency with good absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Here we describe the overall process used to design these molecules and report encouraging results for their activity against the parasite in culture. We also show that the ADMET properties predicted for them generally compare well to the experimentally determined values.
We utilized paired synthetic crRNAs coupled with our synthetic tracrRNA in cells transduced with lentiviral Cas9 to perform a functional knockout on hsa-miR-221. This three-part system (crRNA, tracrRNA and Cas9) has demonstrated efficient gene editing when used with only one guide RNA, but the goal was to use two crRNAs to remove the entire stem-loop.READ MORE
During early drug discovery, the study of metabolism plays an essential role in determining which drug candidates move forward into development and later stages. As an alternative to traditional Data Dependent Acquisition (DDA), the use of MSE/All Ions Fragmentation (AIF) has become common in metabolite identification workflows for the analysis of metabolic hot spots. Here we present a solution for analysis of MSE/AlF in metID studies.READ MORE