Tracking Internal Frames of Reference for Consistent Molecular Distribution Functions

From complex data to clear insights: visualizing molecular dynamics trajectories

Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

VIAMD: a Software for Visual Interactive Analysis of Molecular Dynamics

The typical workflow in molecular dynamics (MD) analysis requires several separate tools, often resulting in a lack of synergy and interaction between the individual analysis steps. This article presents VIAMD, an application designed to address this issue by integrating a 3D visualization of molecular trajectories with flexible analysis components. VIAMD uses an interactive scripting interface, allowing for property definition and evaluation. The application provides context-aware suggestions and expression feedback through information and visualizations. The user-defined properties can be explored and analyzed through the various components. This enables correlation with spatial conformations, statistical analysis of distributions, and powerful aggregation of multidimensional properties such as spatial distribution functions. VIAMD has the potential to advance research in many scientific disciplines and is a promising solution for improving the workflow of MD visualization and analysis.

Distinct Heterocyclic Moieties Govern the Selectivity of Thiophene-Vinylene-Based Ligands Towards Aβ or Tau Pathology in Alzheime's Disease

Distinct aggregated proteins are correlated with numerous neurodegenerative diseases and the development of ligands that selectively detect these pathological hallmarks is vital. Recently, the synthesis of thiophene-based optical ligands, denoted bi-thiophene-vinyl-benzothiazoles (bTVBTs), that could be utilized for selective assignment of tau pathology in brain tissue with Alzheime's disease (AD) pathology, was reported. Herein, we investigate the ability of these ligands to selectively distinguish tau deposits from aggregated amyloid-β (Aβ), the second AD associated pathological hallmark, when replacing the terminal thiophene moiety with other heterocyclic motifs. The selectivity for tau pathology was reduced when introducing specific heterocyclic motifs, verifying that specific molecular interactions between the ligands and the aggregates are necessary for selective detection of tau deposits. In addition, ligands having certain heterocyclic moieties attached to the central thiophene-vinylene building block displayed selectivity to aggregated Aβ pathology. Our findings provide chemical insights for the development of ligands that can distinguish between aggregated proteinaceous species consisting of different proteins and might also aid in creating novel agents for clinical imaging of tau pathology in AD.

Metabolite-induced in vivo fabrication of substrate-free organic bioelectronics

Interfacing electronics with neural tissue is crucial for understanding complex biological functions, but conventional bioelectronics consist of rigid electrodes fundamentally incompatible with living systems. The difference between static solid-state electronics and dynamic biological matter makes seamless integration of the two challenging. To address this incompatibility, we developed a method to dynamically create soft substrate-free conducting materials within the biological environment. We demonstrate in vivo electrode formation in zebrafish and leech models, using endogenous metabolites to trigger enzymatic polymerization of organic precursors within an injectable gel, thereby forming conducting polymer gels with long-range conductivity. This approach can be used to target specific biological substructures and is suitable for nerve stimulation, paving the way for fully integrated, in vivo-fabricated electronics within the nervous system.