Enhanced Partial Order Curve Comparison Over Multiple Protein Folding Trajectories

Hong Sun*, Hakan Ferhatosmanoglu, Motonori Ota, Yusu Wang

Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA. sunh@cse.ohio-state.edu

Proc LSS Comput Syst Bioinform Conf. August, 2007. Vol. 6, p. 299-310. Full-Text PDF

*To whom correspondence should be addressed.

Understanding how proteins fold is essential to our quest in discovering how life works at the molecular level. Current computation power enables researchers to produce a huge amount of folding simulation data. Hence there is a pressing need to be able to interpret and identify novel folding features from them. In this paper, we model each folding trajectory as a multi-dimensional curve. We then develop an effective multiple curve comparison (MCC) algorithm, called the enhanced partial order (EPO) algorithm, to extract features from a set of diverse folding trajectories, including both successful and unsuccessful simulation runs. Our EPO algorithm addresses several new challenges presented by comparing high dimensional curves coming from folding trajectories. A detailed case study of applying our algorithm to a miniprotein Trp-cage²⁴ demonstrates that our algorithm can detect similarities at rather low level, and extract biologically meaningful folding events.