title: Enhanced partial order curve comparison over multiple protein folding trajectories.
abstract: 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-cage(24) demonstrates that our algorithm can detect similarities at rather low level, and extract biologically meaningful folding events.
authors.affiliation: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA. sunh@cse.ohio-state.edu
authors.forename: Hong
authors.initials: H
authors.lastname: Sun
authors.forename: Hakan
authors.initials: H
authors.lastname: Ferhatosmanoglu
authors.forename: Motonori
authors.initials: M
authors.lastname: Ota
authors.forename: Yusu
authors.initials: Y
authors.lastname: Wang
mesh_terms: D001665:Binding Sites; D003198:Computer Simulation; D007700:Kinetics; D008956:Models, Chemical; D008958:Models, Molecular; D009038:Motion; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013499:Surface Properties
chemical_list: D011506:Proteins