The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this.

Abstract. The information capacity of DNA double-crossover (DX) tiles was successfully increased beyond a binary representation to higher base representations. By controlling the length and the position of DNA hairpins on the DX tile, ternary and senary (base-3 and base-6) digit representations were realized and verified by atomic force microscopy (AFM). Also, normal mode analysis (NMA) was carried out to study the mechanical characteristics of each structure.Online supplementary data available from stacks.iop.org/Nano/XX/XXXXXX/mmedia

The proposed frequency analysis method is a feasible method for understanding DNA nanostructure's vibration characteristics, including both frequencies and mode shapes in atomic detail, adding to the molecular fingerprint provided by the conventional Raman spectrum.

Target-oriented cellular automata with computation are the primary challenge in the field of DNA algorithmic self-assembly in connection with specific rules.

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A foldback intercoil (FBI) DNA nanostructure has important biological functions that are closely related to specific life phenomena, and it has a geometrically unique fourstranded DNA configuration that consists of two folded-back antiparallel DNA double helixes intertwining in the major groove by sharing the same helix axis. However, the geometrical complexity of its unusual FBI configuration has prohibited its in vitro formation from direct contact between B-form DNA duplexes. Although several efforts have been made to investigate its functionalities and configurations, the FBI structures have been rarely constructed (via structural DNA nanotechnology) and simulated (through computational biology) to determine their geometrical stability, experimental validity, and engineering feasibility. In this study, we designed an FBI configuration with a homologous DNA base sequence implemented on either a double-crossover DNA tile or a double-crossover DNA lattice which was observed using an atomic force microscope. In addition, we propose a 3-dimensional FBI structural model and perform a normal-mode analysis based on the mass-weighted chemical elastic network model. These results provide an implementation of a biological simulation in the design of unusual DNA nanostructures, a prediction of their corresponding biological functionality, and an assessment of the feasibility to construct naturally existing biological configurations through synthetic DNA molecules.

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In order to incorporate functionalization into synthesized DNA nanostructures, enhance their production yield, and utilize them in various applications, it is necessary to study their physical stabilities and dynamic characteristics. Although simulation-based analysis used for DNA nanostructures provides important clues to explain their self-assembly mechanism, structural function, and intrinsic dynamic characteristics, few studies have focused on the simulation of DNA supramolecular structures due to the structural complexity and high computational cost. Here, we demonstrated the feasibility of using normal mode analysis for relatively complex DNA structures with larger molecular weights, i.e., finite-size DNA 2D rings and 3D buckyball structures. The normal mode analysis was carried out using the mass-weighted chemical elastic network model (MWCENM) and the symmetry-constrained elastic network model (SCENM), both of which are precise and efficient modeling methodologies. MWCENM considers both the weight of the nucleotides and the chemical bonds between atoms, and SCENM can obtain mode shapes of a whole structure by using only a repeated unit and its connectivity with neighboring units. Our results show the intrinsic vibrational features of DNA ring structures, which experience inner/outer circle and bridge motions, as well as DNA buckyball structures having overall breathing and local breathing motions. These could be used as the fundamental basis for designing and constructing more complicated DNA nanostructures.