Volume 50, Number 2, April-June 2016
Special issue: Recent Advances in Operations Research in Computational Biology, Bioinformatics and Medicine
|Page(s)||401 - 411|
|Published online||28 March 2016|
Petri nets formalism facilitates analysis of complex biomolecular structural data
1 Institute of Physics, Faculty of
Physics, Astronomy and Informatics, Nicolaus Copernicus University,
Grudziadzka 5, 87-100
2 Faculty of Mathematics and Computer Science, Nicolaus Copernicus University ul. Chopina 12/18, 87-100 Torun, Poland.
Accepted: 21 September 2015
Molecular dynamics (MD) simulation is a popular method of protein and nucleic acids research. Current MD output trajectories are huge files and therefore they are hard to analyze. Petri nets (PNs) is a mathematical modeling language that allows for concise, graphical representation of complex data. We have developed a few algorithms for PNs generation from such large MD trajectories. One of them, called the One Place One Conformation (OPOC) algorithm, is presented in a greater detail. In the OPOC algorithm one biomolecular conformation corresponds to one PN place and a transition occurring in PN graph is related to a change between biomolecules conformations. As case studies three simulations are analyzed: an enforced steered MD (SMD) dissociation of a transthyretin protein tetramer into dimers, the SMD dissociation of an antibody-antigen complex and a classical MD simulation of transthyretin. We show that PNs reproduce events hidden in MD trajectories and enable observations of the conformational space features hard-to-see by the other clustering methods. Thus, a fundamental process of biomolecular data classification may be optimized using the PN approach.
Mathematics Subject Classification: 90B10 / 68W99 / 92-08
Key words: Data mining / Petri net / molecular dynamic simulations / clustering / conformational space / graphs
© EDP Sciences, ROADEF, SMAI 2016
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