Symposium3

Cooperation of Real-World Modeling with Simulation toward the Problem “What is Life?”

Living matter is manipulating large number of different molecules to create spatio-temporal self-organization. Currently, many numerical studies have been carried out to shed light on the underlying mechanisms of life. Sometimes, these studies remain as a possible explanatory interpretation because of the complexity of actual living systems. In the present talk, I would like to show some examples of real-world modeling, which help us to obtain deeper understanding in biological systems. 1) Emergence of cell-like structure and function under crowding condition with macromolecules. 2) Self-organization of cellular assembly. 3) Self-generation of macroscopic regular motion for the assembly of nano-scaled self-propelling objects.

The mechanical genome

In addition to the classical layer of genetic information, DNA molecules also carry other layers of information. Two possible layers are discussed. One is a mechanical layer, namely that the base pair sequence influences the mechanical and geometrical properties of the DNA molecules which in turn might guide their packing inside the cell. A second possible layer is the speed of translation in the protein-producing ribosomes where the speed influences the quality of the protein product. We demonstrate that the degeneracy

Water on the DNA Surface: Microscopic Insight from Molecular Dynamics Simulations

Water on the DNA surface exhibits characteristic behavior such as ice-like water network along the narrow groove of DNA. By using molecular dynamics simulations, we obtained detailed picture for such water; our characterization fully describes the water network patterns and their sequence variation [Biophys. J. 97, 1138 (2009)]. Analysis on such water network further revealed microscopic origin of the slow water-exchange kinetics [Biophys. Chem. 160, 54 (2012)]. As another relevant topic, I will also mention a relation with DNA damage production. Our recent study [Chem. Phys. Lett. 749, 137441 (2020)] found that site-dependent water accessibility for DNA backbone is well correlated with the probabilities of DNA damage production by OH radical attacking. This suggests that the site-dependent hydration property is a key factor for DNA damage production.

Visualization of Dose Rate Distribution around Fukushima Daiichi Nuclear Power Plant using Artificial Neural Networks.

This study proposes a method of visualizing the ambient dose rate distribution using artificial neural networks (ANN) from airborne radiation monitoring results. The ANN method was applied to the results of the airborne radiation monitoring which was conducted around the Fukushima Daiichi Nuclear Power Plant by an unmanned aerial vehicle. The ANN was constructed by training data consisting of input variable dataset (radiation count rate, altitude, topographic data, photographic RGB data) and objective variable dataset (the air dose rate data at 1 m above the ground level). The reliability of the ANN method was evaluated by comparison with the ground-based survey data. The dose rate map created by the ANN method reproduced ground-based survey results better than traditional methods.