Instructors- Information Technologies in Medicine and Biology,Graduate Program,Bioinformatics,Medical Informatics

	Cournia Zoe Researcher (Lecturer Level) Instit.: BRFAA Tel: (+30) 210-6597195 e-mail: zcournia [at] bioacademy.gr
Personal Web Page: http://www.bioacademy.gr/faculty-details/H80/zoe?lang=gr
Short Bio:
Zoe Cournia graduated from the Chemistry Department in the University of Athens and subsequently pursued doctoral studies in the University of Heidelberg, Germany, with Dr. Jeremy Smith. She obtained the Ph.D. degree in 2006 in the field of computational biophysical chemistry. Cournia then joined Dr. Bill Jorgensen's lab in the Department of Chemistry, Yale University to perform post-doctoral studies in computer-aided drug design. At Yale, she focused on the design and discovery of novel anti-cancer agents using computational techniques. Her research, sponsored by the American Association for Cancer Research Fellowship in Angiogenesis, focused on the protein Macrophage Migration Inhibitory Factor (MIF), which has been recently identified as a pro-oncogenic and pro-inflammatory factor. Aided by state of the art computational methods, her work led to the discovery of several small-molecule inhibitors of MIF-receptor binding, which are now employed in pre-clinical studies at the Yale School of Medicine. Dr. Cournia became a Lecturer in Yale College in 2009 where she taught the course "Computer Modeling of Biomolecules". During 2007-2008 she served as a co-President of the Yale Pharmaceutical and Biotechnology Society and in 2009 she was also honored with the "Women of Innovation Award" from the Connecticut Technology Council. Since October 2009 she is a member of BRFAA, where as a researcher (Lecturer Level) she works on targeting the mutated cancerous PI3Kα protein with small molecule inhibitors, inhibition of the c-Myc-Max interaction with small molecule inhibitors, and the design of small molecule inhibitors of the Arp2/3 complex in order to discover new anti-cancer agents. For these studies the Cournia lab employs a combination of MD simulations, virtual screening, de novo drug design, free energy perturbation calculations, pharmacological property prediction and Monte Carlo simulations.

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