title: An enhanced partial order curve comparison algorithm and its application to analyzing protein folding trajectories.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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. The EPO algorithm addresses several new challenges presented by comparing high dimensional curves coming from folding trajectories. A detailed case study on miniprotein Trp-cage 1 demonstrates that our algorithm can detect similarities at rather low level, and extract biologically meaningful folding events.
  
  
  CONCLUSIONS
  The EPO algorithm is general and applicable to a wide range of applications. We demonstrate its generality and effectiveness by applying it to aligning multiple protein structures with low similarities. For user's convenience, we provide a web server for the algorithm at http://db.cse.ohio-state.edu/EPO.
authors: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA. sun.82@osu.edu
authors: Hong
authors: H
authors: Sun
authors: Hakan
authors: H
authors: Ferhatosmanoglu
authors: Motonori
authors: M
authors: Ota
authors: Yusu
authors: Y
authors: Wang
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D009038:Motion; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*
chemical_list: D011506:Proteins