Simulating the structure and dynamics of large numbers of proteins and their complexes is a large task by any reckoning - just a small or average-sized protein such as protein-L could take several years of computational time. To compare computational results with experimental results, a more immediate solution is desirable, so a new simulation approach to the study of proteins was developed together with colleagues at the University of Pittsburgh Medical School, Polymer Research Center of Bogazici University, and the National Institutes of Health. The resulting Gaussian Network Model (GNM) technique was first presented in the 3 publications below (highly cited according to ISIhighlycited.com).
GNM is considered a breakthrough for simulation of protein molecules and describes the dynamic characteristics of proteins such as domain motions and folding patterns. HIV-1 has been accurately identified using this modeling technique, improving our understanding of its functionality and stability. Currently, GNM is also being applied to understand and predict the binding mechanisms of biological assemblies and their interactions with drugs. Other mathematical tools for computational modeling are being developed and include model testing and validation in collaboration with theoretical and experimental scientists at other universities and institutions. He is collaborating with Jorge Sofo (Physics Department) on simulation of protein structures on confined synthetic environments such as gold and silica surfaces.
The design of inexpensive and sensitive biodetection devices that can be used in the doctor's office or at home for identifying diseases such as influenza as well as biotoxins are some of the applications guided by his computational efforts. Currently he is working with a potential industrial partner on a microfluidics-based device to detect pathogens, which he hopes will be another breakthrough.
A New Bio-Nano Lab, New Course Development - and Research
In addition to building his new Biomolecular Materials Laboratory, Professor Demirel has been a primary user of the Penn State Lion-XM PC Cluster, a cost-effective, high-performance parallel computing system that enables faculty and other researchers to run complex computer simulation programs. Professor Demirel also has been charged with developing 2 new graduate-level courses on bio-nano materials as part of a new nano minor being proposed by Stephen Fonash (Kunkle Chair, Professor of Engineering Sciences, and Director of the Center for Nanotechnology Education and Utilization). With Reka Albert (Physics Department), he has started a quantitative bioscience group that meets 2 or 3 times a month to hear presentations by researchers at Penn State and other institutions, followed by discussion. And last, but not least, he is currently preparing a chapter for a book on bio-MEMS, is working on several papers, and has a grant proposal out for simulation and design of biomolecular materials. After just 6 months at Penn State, Melik Demirel "has a lot on his plate."