Biophysics and physicobiology最新文献

Tauopathy is a spectrum of diseases characterized by fibrillary tau aggregate formation in neurons and glial cells in the brain. Tau aggregation originates in the brainstem and entorhinal cortex and then spreads throughout the brain in Alzheimer's disease (AD), which is the most prevalent type of tauopathy. Understanding the mechanism by which locally developed tau pathology propagates throughout the brain is crucial for comprehending AD pathogenesis. Therefore, a novel model of tau pathology that artificially induces tau aggregation in targeted cells at specific times is essential. This study describes a novel optogenetic module, OptoTau, which is a human tau with the P301L mutation fused with a photosensitive protein CRY2olig, inducing various forms of tau according to the temporal pattern of blue light illumination pattern. Continuous blue light illumination for 12 h to Neuro2a cells that stably express OptoTau (OptoTauKI cells) formed clusters along microtubules, many of which eventually accumulated in aggresomes. Conversely, methanol-resistant tau aggregation was formed when alternating light exposure and darkness in 30-min cycles for 8 sets per day were repeated over 8 days. Methanol-resistant tau was induced more rapidly by repeating 5-min illumination followed by 25-min darkness over 24 h. These results indicate that OptoTau induced various tau aggregation stages based on the temporal pattern of blue light exposure. Thus, this technique exhibits potential as a novel approach to developing specific tau aggregation in targeted cells at desired time points.

Intracellular positional information is crucial for the precise control of biological phenomena, including cell division, polarity, and motility. Intracellular reaction-diffusion (iRD) waves are responsible for regulating positional information within cells as morphogens in multicellular tissues. However, iRD waves are explained by the coupling of biochemical reactions and molecular diffusion which indicates nonlinear systems under far from equilibrium conditions. Because of this complexity, experiments using defined elements rather than living cells containing endogenous factors are necessary to elucidate their pattern formation mechanisms. In this review, we summarize the effectiveness of artificial cell systems for investigating iRD waves derived from their high controllability and ability to emulate cell-size space effects. We describe how artificial cell systems reveal the characteristics of iRD waves, including the mechanisms of wave generation, mode selection, and period regulation. Furthermore, we introduce remaining open questions and discuss future challenges even in Min waves and in applying artificial cell systems to various iRD waves.

Computerized molecular docking methodologies are pivotal in in-silico screening, a crucial facet of modern drug design. ChooseLD, a docking simulation software, combines structure- and ligand-based drug design methods with empirical scoring. Despite advancements in computerized molecular docking methodologies, there remains a gap in optimizing the predictive capabilities of docking simulation software. Accordingly, using the docking scores output by ChooseLD, we evaluated its performance in predicting the bioactivity of G-protein coupled receptor (GPCR) and kinase bioactivity, specifically focusing on Ki and IC₅₀ values. We evaluated the accuracy of our algorithm through a comparative analysis using force-field-based predictions from AutoDock Vina. Our findings suggested that the modified ChooseLD could accurately predict the bioactivity, especially in scenarios with a substantial number of known ligands. These findings highlight the importance of selecting algorithms based on the characteristics of the prediction targets. Furthermore, addressing partial model fitting with database knowledge was demonstrated to be effective in overcoming this challenge. Overall, these findings contribute to the refinement and optimization of methodologies in computer-aided drug design, ultimately advancing the efficiency and reliability of in-silico screening processes.