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BioMed Research International
Volume 2015, Article ID 769471, 12 pages
http://dx.doi.org/10.1155/2015/769471
Research Article

Agent-Based Spatiotemporal Simulation of Biomolecular Systems within the Open Source MASON Framework

1Escuela Superior de Ingeniería Informática (ESEI), Edificio Politécnico, Universidad de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
2LEPABE, Department of Chemical Engineering, Faculty of Engineering, University of Porto, Rúa Dr. Roberto Frias, 4200-465 Porto, Portugal
3Centre of Biological Engineering (CEB), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal

Received 19 August 2014; Accepted 30 October 2014

Academic Editor: Juan F. De Paz

Copyright © 2015 Gael Pérez-Rodríguez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Agent-based modelling is being used to represent biological systems with increasing frequency and success. This paper presents the implementation of a new tool for biomolecular reaction modelling in the open source Multiagent Simulator of Neighborhoods framework. The rationale behind this new tool is the necessity to describe interactions at the molecular level to be able to grasp emergent and meaningful biological behaviour. We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis. Enzymes may display high specificity for their substrates and this information is crucial to the engineering and optimisation of bioprocesses. Simulation results demonstrate that molecule distributions, reaction rate parameters, and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of realistic cell environments. While higher percentage of collisions with occurrence of reaction increases the affinity of the enzyme to the substrate, a faster reaction (i.e., turnover number) leads to a smaller number of time steps. Slower diffusion rates and molecular crowding (physical hurdles) decrease the collision rate of reactants, hence reducing the reaction rate, as expected. Also, the random distribution of molecules affects the results significantly.