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Agent-based spatiotemporal simulation of biomolecular systems within the open source MASON framework.

Pérez-Rodríguez G, Pérez-Pérez M, Glez-Peña D, Fdez-Riverola F, Azevedo NF, Lourenço A - Biomed Res Int (2015)

Bottom Line: We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis.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.Also, the random distribution of molecules affects the results significantly.

View Article: PubMed Central - PubMed

Affiliation: Escuela Superior de Ingeniería Informática (ESEI), Edificio Politécnico, Universidad de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain.

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.

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Related in: MedlinePlus

Performance of the tool in scenarios of increasing computational complexity.
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fig6: Performance of the tool in scenarios of increasing computational complexity.

Mentions: For this purpose, we run preliminary performance tests to find out the current scalability of our system. Figure 6 summarises performance tests using an Intel I7 (2600) 3.4 GHz processor with 6 GB of RAM and running Windows 8 64-bit. The tests accounted for three possible scenarios, as follows: no action, that is, the agents are created but no diffusion or behavioural rules are executed; without reaction, that is, the agents are created and diffusion rules are activated, but agents do not interact among themselves; and, with reaction, that is, agents are created, can move, and can interact. The three scenarios show a similar performance till the system reaches a population of 1.5E + 05 agents. That is, till this point, the physics governing agent movement and the introduction of behavioural rules do not affect simulation time significantly. Cost resides on creating the system. After that point, the time taken by the simulation of more elaborated scenarios, that is, more agents in motion and more rules to manage, is somewhat aggravated. Over 2.5E + 05 agents, the system becomes computational unviable by a single machine.


Agent-based spatiotemporal simulation of biomolecular systems within the open source MASON framework.

Pérez-Rodríguez G, Pérez-Pérez M, Glez-Peña D, Fdez-Riverola F, Azevedo NF, Lourenço A - Biomed Res Int (2015)

Performance of the tool in scenarios of increasing computational complexity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4385633&req=5

fig6: Performance of the tool in scenarios of increasing computational complexity.
Mentions: For this purpose, we run preliminary performance tests to find out the current scalability of our system. Figure 6 summarises performance tests using an Intel I7 (2600) 3.4 GHz processor with 6 GB of RAM and running Windows 8 64-bit. The tests accounted for three possible scenarios, as follows: no action, that is, the agents are created but no diffusion or behavioural rules are executed; without reaction, that is, the agents are created and diffusion rules are activated, but agents do not interact among themselves; and, with reaction, that is, agents are created, can move, and can interact. The three scenarios show a similar performance till the system reaches a population of 1.5E + 05 agents. That is, till this point, the physics governing agent movement and the introduction of behavioural rules do not affect simulation time significantly. Cost resides on creating the system. After that point, the time taken by the simulation of more elaborated scenarios, that is, more agents in motion and more rules to manage, is somewhat aggravated. Over 2.5E + 05 agents, the system becomes computational unviable by a single machine.

Bottom Line: We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis.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.Also, the random distribution of molecules affects the results significantly.

View Article: PubMed Central - PubMed

Affiliation: Escuela Superior de Ingeniería Informática (ESEI), Edificio Politécnico, Universidad de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain.

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.

Show MeSH
Related in: MedlinePlus