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Impact of proposed work


The algorithmic and software infrastructure for molecular dynamics and sampling of biomolecular systems proposed here will overcome the wide range of length and time scales inherent in such systems, while preserving the atomic resolution of the biological models. It achieves this goal through a combination of original concepts (mollified long time step integrators and cheap approximations of the modified Hamiltonian), and incorporation and extension of other techniques (time scale splitting, semi-implicit integrators, and constrained dynamics) in such a way as to create an integrated simulation methodology. This will allow for the predictive study of large systems and slow processes of biomedical interest. For example, the study of potassium channel dynamics and function is not only interesting in itself, but is also representative of a larger class of problems where this methodology can be applied.

The algorithms will be disseminated in PROTOMOL, a program that is freely available because it is open source. The proposed easy-to-use-interface, achieved through a combination of intuitive user interfaces (like a haptic interface that gives force feedback), and automated empirical optimization of software, will make the algorithms resulting from this research accessible to the scientific community at large. The scalability of the software makes it suitable for different levels of sophistication and computational requirements, ranging from intensive scientific research to computer-aided education at all levels, particularly at the high school and college level. It is exciting that the software runs already on Unix parallel computers and Windows platforms, and efforts will be taken to make it run on Macintosh computers, since the latter is a popular platform for biologists.

The collaborative applications in computational molecular biology, which include the co-advising of biology students, and the course on computational methods for biomolecular modeling are practical ways of educating life scientists in the development and use of more powerful tools that will be sorely needed in the fields of proteomics and drug design, especially with the abundance of data provided by the human genome project. Conversely, it will allow mathematical and computational scientists, such as the graduate students who would be supported by this project, Mr. Qun Ma, Mr. Hong Hu, and Mr. Thomas Slabach, to learn about this exciting field first hand.

The development of this algorithmic and software platform will continue to benefit many students and junior researchers, as evidenced by an already vigorous research program that encompasses eight undergraduates, seven graduate students, and one postdoctoral research associate. A significant effort will be made by the PI to reach out towards minorities. Concrete steps in these directions have been taken, such as advising the society for Hispanic engineers at Notre Dame, and inviting students from Latin America and especially Mexico to attend Notre Dame.

Besides research supervision of these students, synergy between this research project and teaching will occur at several levels. There will be an enhancement in the materials offered for undergraduate and graduate courses developed by the PI on biomolecular modeling, data structures and applied algorithms, and numerical methods. As part of this effort, materials for the newly funded Learning Center at Notre Dame will permit students to interact with biomolecules through haptic devices, using software interfaces that the PI has already developed. For example, this will enable chemical engineering students to understand functioning of proteins for the creation of reactors and computer scientists to understand visualization and computational needs of computational molecular biology. The course on biomolecular modeling will be expanded to include more examples of realistic simulations, and to link results from simulations to experiments to the extent possible.

Finally, this project may seed the creation of an NIH sponsored biocomplexity center, which the PI is already seeking to establish in collaboration with professors from multiple departments at the University of Notre Dame. This initiative has received significant momentum through the award of an NSF biocomplexity grant to three PIs at Notre Dame, of which this PI is Co-PI, for modeling organ growth development from cellular models.


next up previous
Next: Problems and proposed solutions Up: Introduction Previous: Objectives of proposal
Jesus Izaguirre 2001-07-27