Application of agent-based modelling to assess single-molecule transport across the cell envelope of E. coli

An agent-based model for studying the temperature changes on environments exposed to magnetic fluid hyperthermia

Magnetic fluid hyperthermia (MFH) is a technique whose results show promise in the treatment against cancer, but which still faces obstacles such as controlling the spatial distribution of temperature. The present study developed an agent-based model in order to simulate the temperature changes in an aqueous environment submitted to the magnetic fluid hyperthermia technique. The developed model was built with its parameters based on the clinical treatment protocol for glioblastoma multiforme (GBM). Using thermodynamic properties of magnetic fluid and tissues, we define a specific thermal parameter (α) and evaluate its influence, together with the intensity of the external magnetic field (H), on the dynamics of the temperature of the cancer environment. The temperature evolution generated by the model was in accordance with experimental results known from the subject literature. The parameters evaluation indicates that the temperature stabilization of the tumor environment during MFH treatment is due to the local interactions of energy diffusion, as well as indicating that the α-parameter is a key factor for controlling the temperature and heating speed.

Computational resources and strategies to assess single-molecule dynamics of the translation process in S. cerevisiae

This work provides a systematic and comprehensive overview of available resources for the molecular-scale modelling of the translation process through agent-based modelling. The case study is the translation in Saccharomyces cerevisiae, one of the most studied yeasts. The data curation workflow encompassed structural information about the yeast (i.e. the simulation environment), and the proteins, ribonucleic acids and other types of molecules involved in the process (i.e. the agents). Moreover, it covers the main process events, such as diffusion (i.e. motion of molecules in the environment) and collision efficiency (i.e. interaction between molecules). Data previously determined by wet-lab techniques were preferred, resorting to computational predictions/extrapolations only when strictly necessary. The computational modelling of the translation processes is of added industrial interest, since it may bring forward knowledge on how to control such phenomena and enhance the production of proteins of interest in a faster and more efficient manner.