Motion-Planning Based Techniques for Modeling & Simulating Molecular Motions

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NUMBER: 0830753INSTITUTION: Texas Engineering Experiment StationPI: Amato, Nancy & Rauchwerger, LawrenceTITLE: Motion-Planning Based Techniques for Modeling & Simulating Molecular MotionsMolecular motions play an essential role in many biochemical processes. Since it is difficult to experimentally observe molecular motions, computational methods for studying such issues are essential. This research investigates a novel computational method for studying molecular motions that the investigators have developed and validated against experimental data in preliminary work. The research has the potential to provide insight into a number of important questions related to protein folding, stability, and solubility. For example, protein misfolding and aggregation is associated with devastating neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, prion diseases, and related diseases. In addition to publications, results generated by the research are shared with the community in a publicly available database of molecular motions. The protein folding server also allows scientists to submit their own proteins which will be analyzed for them: http://parasol.tamu.edu/foldingserver/.The new computational method invested in this research represents a trade-off between methods such as molecular dynamics and Monte Carlo simulations that provide detailed individual folding trajectories and techniques such as statistical mechanical methods that provide global folding landscape statistics. This method builds a graph (roadmap) corresponding to an approximate map of the molecule's energy landscape that encodes many (typically thousands) folding pathways. Though the individual pathways produced are not as detailed as trajectories generated from a molecular dynamics simulation, they can be used to study properties such as secondary structure formation order and folding kinetics. The major research goals of this project include the development of new and/or improved metrics and analysis techniques for conformations and roadmaps that can be applied in protein stability and kinetics studies and the development of strategies for employing high-performance computing to increase the size and complexity of the systems that can be studied. The investigators validate and apply these new techniques to folding core identification, amyloid formation, kinetics studies, and comparative analysis of proteins.