Phenotype selection due to mutational robustness.

The mutation-selection mechanism of Darwinian evolution gives rise not only to adaptation to environmental conditions but also to the enhancement of robustness against mutations. When two or more phenotypes have the same fitness value, the robustness distribution for different phenotypes can vary. Thus, we expect that some phenotypes are favored in evolution and that some are hardly selected because of a selection bias for mutational robustness.

Evolution enhances mutational robustness and suppresses the emergence of a new phenotype: A new computational approach for studying evolution.

The aim of this paper is two-fold. First, we propose a new computational method to investigate the particularities of evolution. Second, we apply this method to a model of gene regulatory networks (GRNs) and explore the evolution of mutational robustness and bistability.

Emergence of cooperative bistability and robustness of gene regulatory networks.

Gene regulatory networks (GRNs) are complex systems in which many genes regulate mutually to adapt the cell state to environmental conditions. In addition to function, the GRNs possess several kinds of robustness. This robustness means that systems do not lose their functionality when exposed to disturbances such as mutations or noise, and is widely observed at many levels in living systems.

The interplay of intrinsic disorder and macromolecular crowding on α-synuclein fibril formation.

α-synuclein (α-syn) is an intrinsically disordered protein which is considered to be one of the causes of Parkinson's disease. This protein forms amyloid fibrils when in a highly concentrated solution. The fibril formation of α-syn is induced not only by increases in α-syn concentration but also by macromolecular crowding.

Numerous but rare: an exploration of magic squares.

How rare are magic squares? So far, the exact number of magic squares of order n is only known for n ≤ 5. For larger squares, we need statistical approaches for estimating the number. For this purpose, we formulated the problem as a combinatorial optimization problem and applied the Multicanonical Monte Carlo method (MMC), which has been developed in the field of computational statistical physics.

Nucleotide-dependent structural fluctuations and regulation of microtubule-binding affinity of KIF1A.

Molecular motors such as kinesin regulate affinity to a rail protein during the ATP hydrolysis cycle. The regulation mechanism, however, is yet to be determined. To understand this mechanism, we investigated the structural fluctuations of the motor head of the single-headed kinesin called KIF1A in different nucleotide states using molecular dynamics simulations of a Gō-like model.

Structural flexibility of intrinsically disordered proteins induces stepwise target recognition.

An intrinsically disordered protein (IDP) lacks a stable three-dimensional structure, while it folds into a specific structure when it binds to a target molecule. In some IDP-target complexes, not all target binding surfaces are exposed on the outside, and intermediate states are observed in their binding processes. We consider that stepwise target recognition via intermediate states is a characteristic of IDP binding to targets with "hidden" binding sites.

Frustration-induced protein intrinsic disorder.

Spontaneous folding into a specific native structure is the most important property of protein to perform their biological functions within organisms. Spontaneous folding is understood on the basis of an energy landscape picture based on the minimum frustration principle. Therefore, frustration seemingly only leads to protein functional disorder.

Free-energy landscape of kinesin by a realistic lattice model.

Structural fluctuations in the thermal equilibrium of the kinesin motor domain are studied using a lattice protein model with Gō interactions. By means of the multi-self-overlap ensemble Monte Carlo method and the principal component analysis, the free-energy landscape is obtained. It is shown that kinesins have two subdomains that exhibit partial folding/unfolding at functionally important regions: one is located around the nucleotide binding site and the other includes the main microtubule binding site.

Structural change and nucleotide dissociation of Myosin motor domain: dual go model simulation.

We investigated the structural relaxation of myosin motor domain from the pre-power stroke state to the near-rigor state using molecular dynamics simulation of a coarse-grained protein model. To describe the spontaneous structural change, we propose a dual Gō-model-a variant of the Gō-like model that has two reference structures. The nucleotide dissociation process is also studied by introducing a coarse-grained nucleotide in the simulation.