This is a part of a joint project of the CADD Group with several groups at the Department of Defense (DoD), with the title Computational platforms for transforming small molecules into investigational new drugs. The projects lead PI on the DoD side is Dr. S. Anders Wallqvist, Tri-Service Biotechnology High-Performance Computing Software Applications Institute for Force Health Protection (BHSAI), Telemedicine and Advanced Technology Research Center (TATRC), U.S. Army Medical Research and Materiel Command (USAMRMC), 2405 Whittier Drive, Suite 200, Frederick, MD 217602. Other participating groups are at the Department of Biochemistry, Walter Reed Army Institute of Research (WRAIR), and the Department of Cell Biology and Biochemistry, U.S. Army Medical Research Institute for Infectious Diseases (USAMRIID).
The aim of the overall project is to integrate three fundamental aspects of the preclinical drug development phase, i.e., structure-based drug design, analysis and prediction of pharmacological data, and the prediction of adverse and off-target effects from chemical structures. As a specific initial target, this project in general, and Dr. Pugliese in the CADD Group in specific, will apply structure-based inhibitor design approaches to several enzymes of a specific pathogen. Dr. Pugliese will apply approaches such as homology modeling, docking, pharmacophore searches, ADME/Tox prediction programs, metabolic profiling and other computational tools useful in CADD work to the pathogens target(s) to identify small molecules as candidates that could ultimately lead to drugs against this and other pathogens employing similar enzymes. The most important aspect of Dr. Pugliese's work will concern metabolism and metabolites. The work having effectively started in early 2010, Dr. Pugliese has begun to implement a resource for successful prediction of metabolism and metabolites of drug-like small molecules as part of our computer-aided drug design capabilities. The first phase of this project, consisting of canvassing the field for predictive computer tools as well as data sets that can be used to test these tools and develop (better) predictive models, is nearing completion. Both commercial and free resources have been compiled or are in the process of being acquired. A comparison and benchmark study with appropriate publication is in the works. In this initial phase of the project, we are focusing on (prediction of) metabolic stability data such as half-life values in Human Liver Microsome or Human Hepatocyte assays. It is planned to broaden the scope of properties studied to prediction of type of metabolization reaction and metabolization site as well as of metabolites;and cytochrome P450 metabolization profiles including prediction whether a compound is an inhibitor or an inducer of a specific isozyme. While the initial test and application of these resources will occur in the context of the pathogen of interest to DoD, the general capability of predicting metabolic stability, metabolization profile and specific metabolites of a small molecule will be applicable to all types of drug development, and therefore be very useful in the development of anti-cancer therapeutics aiming at molecular targets of high interest to NCI, as well as in, e.g., NCI's anti-HIV drug design projects.
