An enhanced partial order curve comparison algorithm and its application to analyzing protein folding trajectories.

BMC Bioinformatics
Hong SunYusu Wang

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. 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. 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...Continue Reading

References

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Citations

Feb 19, 2020·Physical Chemistry Chemical Physics : PCCP·Duc Duy NguyenGuo-Wei Wei

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Methods Mentioned

BETA
protein folding
NMR

Software Mentioned

POSA
MC
MAMMOTH
MSTA
POA
MixData
CE
Multiprot
EPO
ME

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