Toshifumi Mori

We report structural adjustments for single-substituted diarylaminoanthracenes to balance charge-transfer-assisted colour tuning with narrow bandwidth and high photoluminescence quantum yield (PLQY).

In complex molecular systems, the reaction coordinate (RC) that characterizes transition pathways is essential to understand underlying molecular mechanisms. This review surveys a framework for identifying the RC by applying deep learning to the committor, which provides the most reliable measure of the progress along a transition path. The inputs to the neural network are collective variables (CVs) expressed as functions of atomic coordinates of the system, and the corresponding RC is predicted as the output by training the network on the committor as the learning target. Because deep-learning models typically operate in a black-box manner, it is difficult to determine which input variables govern the predictions. The incorporation of explainable artificial intelligence techniques enables quantitative assessment of the contributions of individual input variables to the predictions. This approach allows the identification of CVs that play dominant roles and demonstrates that the committor distribution on the surface using important CVs is separated by well-defined boundaries. The framework provides an explainable deep learning strategy for assigning a molecular mechanism from the RC and is applicable to a wide range of complex molecular systems.

Strong triphosphate anchoring and diffuse adenine shielding cooperatively drive ATP's concentration-dependent hydrotropic action and conformational expansion of α-synuclein.

We propose the integral-equation formalism of population dynamics (IEPDYN) to describe the population dynamics of distinct configurational states. According to classical reaction dynamics theory, the probability density associated with a given state obeys the Liouville equation, including influx from and efflux to neighboring states. By introducing a Markov approximation for the crossing of boundaries separating the states, tractable integral equations governing the state populations are derived. Once the time-dependent quantities appearing in these equations are evaluated, the population dynamics on long timescales can be obtained. Because these quantities depend only on a few states in the local neighborhood of a given state, they can be computed using a set of short-timescale molecular dynamics (MD) simulations. The IEPDYN method is formulated in continuous time and therefore does not rely on a coarse-grained timescale (lag time). Consequently, kinetic quantities obtained from IEPDYN are free from lag-time dependence, which has been discussed as a limitation in other approaches. We apply the IEPDYN method to the binding and unbinding kinetics of CH4/CH4, Na+/Cl−, and 18-crown-6-ether (crown ether)/K+ in water. For both kinetics, the time constants estimated from the IEPDYN method are comparable to those obtained from brute-force MD simulations. The required timescale of each MD trajectory in the IEPDYN method is approximately two orders of magnitude shorter than that in the brute-force MD approach in the crown ether/K+ system. This reduction in the trajectory timescale enables applications to complex binding and unbinding systems whose characteristic timescales are far beyond those directly accessible by brute-force MD simulations.

The association and dissociation of ion pairs in water are fundamental to physical chemistry, yet their reaction coordinates are complex, involving not only interionic distance but also solvent-mediated hydration structures. These processes are often represented by free-energy landscapes constructed from collective variables (CVs), such as interionic distance and water-bridging structures; however, it remains uncertain whether such representations reliably capture the transition pathways between the associated and dissociated states. In this study, we employ deep learning to identify reaction coordinates for NaCl ion pair association and dissociation in water, using the committor as a quantitative measure of progress along the transition pathway through the transition state. The solvent environment surrounding the ions is encoded through descriptors based on atom-centered symmetry functions (ACSFs), which serve as input variables for the neural network. In addition, SHapley Additive exPlanations analysis, as an explainable artificial intelligence technique, is applied to identify ACSFs that contribute to the reaction coordinate. A comparative analysis of their correlation with CVs representing water-bridging structures, such as interionic water density and the number of water molecules coordinating both ions, further provides a molecular-level interpretation of the ion association–dissociation mechanism in water.

The myosin superfamily encompasses over 70 classes, each with multiple subclasses, and exhibits substantial diversity in properties such as velocity, ATPase activity, duty ratio, and directionality. This functional diversity enables the specialized roles of each myosin in various organisms, organs, and cell types. Beyond these well-characterized parameters, a newly recognized property has recently come into focus: Certain myosins drive actin filaments along chiral curved trajectories. However, this newly identified property remains largely unexplored. Here, we investigated this chiral motion in vitro using Chara corallina myosin XI ( Cc XI), which drives fast clockwise (CW) movement of actin filaments. This chiral motion arises from asymmetric displacement at the filament’s leading tip, and its curvature depends on the myosin density. Surprisingly, at elevated actin concentrations, filaments exhibiting chiral curved motion undergo collective dynamics, spontaneously forming a ring-shaped structure—termed the actin chiral ring (ACR)—that exhibits persistent CW rotation. ACRs display remarkable stability, continuing to rotate at their formation site until ATP is depleted, while maintaining their structure even after rotation ceases. This stability has not been reported among reported collective motions of cytoskeletal proteins driven by various motors. Our findings demonstrate that myosins with chiral activity can autonomously organize actin filaments into stable, chiral structures through collective motion, providing insights into actin self-organization by unconventional myosins. This paradigm offers a mechanistic basis for how motor-driven molecular asymmetry can give rise to coherent structural chirality at the cellular scale—an essential step in the emergence of cell chirality and asymmetry during development.

KaiC, a cyanobacterial circadian clock protein with autokinase activity, catalyzes the dual phosphorylation of its own S431 and T432 residues in a circadian manner in the presence of KaiA and KaiB. Priming phosphorylation at T432 is a key step that promotes secondary phosphorylation at S431. Although KaiA binding is considered essential for KaiC phosphorylation, the mechanisms underlying the activation and inactivation of priming phosphorylation remain elusive. We found that although the priming phosphorylation is autoinhibited within KaiC, it actually proceeds at a rate constant of 0.019 h−1 even in the absence of KaiA. The autoinhibition of KaiC and the mechanism underlying the release from autoinhibition by KaiA were examined by KaiC structural analysis and by classical molecular dynamics and quantum mechanics/molecular mechanics simulations. We found that the side chain of T432 adopts two rotamers in dephosphorylated KaiC, one of which places T432 in a position suitable for a nucleophilic attack on the terminal phosphate of adenosine triphosphate. However, the nucleophilicity of T432 was insufficient to overcome an energy barrier of ∼21 kcal mol−1 because the catalytic function of a nearby base, E318, was self-suppressed by hydrogen bonding to positively charged R385. Biochemical assays of KaiC mutants showed that the autoinhibition of KaiC autokinase activity is attenuated by conferring T432 high nucleophilicity through the KaiA-assisted release of R385 from E318 to E352. During the circadian cycle, R385 switches interacting partners to inactivate/activate the autokinase function and to ensure the unidirectionality of the KaiC phosphorylation cycle.

The myosin superfamily comprises over 70 classes, each with multiple subclasses, and shows substantial diversity in properties such as velocity, ATPase activity, duty ratio, and directionality. This functional diversity enables the specialized roles of each myosin in various organisms, organs, and cell types. Recent studies have revealed that certain myosins induce chiral curved motions of actin filaments. However, this newly identified property remains largely unexplored. Here, we investigated this chiral motion in vitro using Chara corallina myosin XI ( Cc XI), which drives fast counterclockwise (CCW) movement of actin filaments. This chiral motion arises from asymmetric displacement at the filament’s leading tip, and its curvature depends on the surface density of myosin. Surprisingly, at near-physiological actin concentrations, actin filaments exhibiting chiral curved motion undergo collective motion, spontaneously forming a novel structure—termed the actin chiral ring (ACR)—that exhibits persistent CCW rotation. ACRs display remarkable stability, continuing to rotate at their formation site until ATP is depleted, while maintaining their structure even after rotation ceases. This stability is unprecedented among reported collective motions of cytoskeletal proteins driven by various motors. Our findings demonstrate that myosins with chiral activity can autonomously organize actin filaments into stable, chiral structures through collective motion, providing new insights into actin self-organization by unconventional myosins. This study advances our understanding of the diverse functional roles of unconventional myosins and introduces a new paradigm for cytoskeletal organization. Significance Statement: Myosins are motor proteins that move along actin filaments and support various intracellular functions. Recently, some myosins have been found to drive actin filaments along chiral curved paths, but the mechanisms and significance of this behavior remain poorly understood. Here, we analyzed this activity and discovered that it not only drives chiral curved motion of single actin filaments, but also organizes them into stable, unidirectionally rotating ring structures through collective motion. These rings, termed actin chiral rings (ACRs), spontaneously emerge at near-physiological actin concentrations. Our findings uncover a previously unrecognized organizing principle of actin self-assembly driven by myosin with chiral activity and provide a new framework for understanding how cytoskeletal chirality is made.