title: Rule-based modeling and simulations of the inner kinetochore structure.
abstract: BACKGROUND
  Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins.
  
  
  RESULTS
  Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts.
  
  
  CONCLUSIONS
  Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores.
authors.affiliation: Bio Systems Analysis Group, Institute of Computer Science, Jena Centre for Bioinformatics and Friedrich Schiller University, Jena, Germany. Electronic address: sergej.tschernyschkow@uni-jena.de.
authors.forename: Sergej
authors.initials: S
authors.lastname: Tschernyschkow
authors.forename: Sabine
authors.initials: S
authors.lastname: Herda
authors.forename: Gerd
authors.initials: G
authors.lastname: Gruenert
authors.forename: Volker
authors.initials: V
authors.lastname: Döring
authors.forename: Dennis
authors.initials: D
authors.lastname: Görlich
authors.forename: Antje
authors.initials: A
authors.lastname: Hofmeister
authors.forename: Christian
authors.initials: C
authors.lastname: Hoischen
authors.forename: Peter
authors.initials: P
authors.lastname: Dittrich
authors.forename: Stephan
authors.initials: S
authors.lastname: Diekmann
authors.forename: Bashar
authors.initials: B
authors.lastname: Ibrahim
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D003198:Computer Simulation; D018386:Kinetochores / Q000737:chemistry* / Q000648:ultrastructure*; D008954:Models, Biological; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation
keywords: 3D space; Chromatin structure; Kinetochore; Modeling; Rule-based; SRSim software; Simulation