Self-organized emergence of folded protein-like network structures from geometric constraints

The intricate three-dimensional geometries of protein tertiary structures underlie protein function and emerge through a folding process from one-dimensional chains of amino acids. The exact spatial sequence and configuration of amino acids, the biochemical environment and the temporal sequence of distinct interactions yield a complex folding process that cannot yet be easily tracked for all proteins. To gain qualitative insights into the fundamental mechanisms behind the folding dynamics and generic features of the folded structure, we propose a simple model of structure formation that takes into account only fundamental geometric constraints and otherwise assumes randomly paired connections. We find that despite its simplicity, the model results in a network ensemble consistent with key overall features of the ensemble of Protein Residue Networks we obtained from more than 1000 biological protein geometries as available through the Protein Data Base. Specifically, the distribution of the number of interaction neighbors a unit (amino acid) has, the scaling of the structure's spatial extent with chain length, the eigenvalue spectrum and the scaling of the smallest relaxation time with chain length are all consistent between model and real proteins. These results indicate that geometric constraints alone may already account for a number of generic features of protein tertiary structures

Ultrafast structural changes direct the first molecular events of vision

視覚に関わるタンパク質の超高速分子動画 --薄暗いところで光を感じる仕組み--. 京都大学プレスリリース. 2023-03-23.Vision is initiated by the rhodopsin family of light-sensitive G protein-coupled receptors (GPCRs). A photon is absorbed by the 11-cis retinal chromophore of rhodopsin, which isomerizes within 200 femtoseconds to the all-trans conformation, thereby initiating the cellular signal transduction processes that ultimately lead to vision. However, the intramolecular mechanism by which the photoactivated retinal induces the activation events inside rhodopsin remains experimentally unclear. Here we use ultrafast time-resolved crystallography at room temperature to determine how an isomerized twisted all-trans retinal stores the photon energy that is required to initiate the protein conformational changes associated with the formation of the G protein-binding signalling state. The distorted retinal at a 1-ps time delay after photoactivation has pulled away from half of its numerous interactions with its binding pocket, and the excess of the photon energy is released through an anisotropic protein breathing motion in the direction of the extracellular space. Notably, the very early structural motions in the protein side chains of rhodopsin appear in regions that are involved in later stages of the conserved class A GPCR activation mechanism. Our study sheds light on the earliest stages of vision in vertebrates and points to fundamental aspects of the molecular mechanisms of agonist-mediated GPCR activation

The EnMAP imaging spectroscopy mission towards operations

EnMAP (Environmental Mapping and Analysis Program) is a high-resolution imaging spectroscopy remote sensing mission that was successfully launched on April 1st, 2022. Equipped with a prism-based dual-spectrometer, EnMAP performs observations in the spectral range between 418.2 nm and 2445.5 nm with 224 bands and a high radiometric and spectral accuracy and stability. EnMAP products, with a ground instantaneous field-of-view of 30 m x 30 m at a swath width of 30 km, allow for the qualitative and quantitative analysis of surface variables from frequently and consistently acquired observations on a global scale. This article presents the EnMAP mission and details the activities and results of the Launch and Early Orbit and Commissioning Phases until November 1st, 2022. The mission capabilities and expected performances for the operational Routine Phase are provided for existing and future EnMAP users

Sustainable and convenient: Bi-modal public transit systems outperforming the private car

Mobility is an indispensable part of modern human societies, but the dominance of motorized individual traffic (MIV, i.e., the private car) leads to a prohibitive waste of energy as well as other resources. Public transportation with line services, such as light rail, can pool many more passengers, thereby saving resources, but often is less convenient (longer transit times). Door-to-door shuttle services, on the other hand, are convenient but have a limited pooling efficiency due to detours scaling with shuttle occupancy. Combining line services with a fleet of shared shuttles in an integrated so-called bi-modal system may provide on-demand door-to-door service at a service level superior to current public transport with significantly less resource consumption than MIV. Here we introduce a generic model of bi-modal public transit and characterize its critical parameters of operation. We identify the conflicting objectives for optimization, i.e., user convenience and energy consumption, and evaluate the system’s performance in terms of Pareto fronts. By means of simulation and analytical theory, we find that energy consumption can be as low as 20% of MIV, at line service densities typically found in real settings. Road traffic can be reduced to less than 10% of MIV. Surprisingly, we find favorable performance not only in urban, but also in rural settings. We thereby provide a possible answer to the pressing question of designing sustainable future mobility solutions

What geometrically constrained protein models can tell us about real-world protein contact maps

The mechanisms by which a protein's 3D structure can be determined based on its amino acid sequence have long been one of the key mysteries of biophysics. Often simplistic models, e.g. derived from geometric constraints, capture bulk real-world 3D protein--protein properties well. One approach is using protein contact maps to better understand protein's properties. Here, we investigate the emergent behavior of protein contact maps derived from a geometrically constrained random interaction model in comparison to real-world proteins. Deriving an analytical approximation for the distribution of amino acid distances $s$ of a 2D geometric model, by means of a mean-field approach, we present a theoretical basis for the distribution of amino acid distances in proteins. To validate this approximation we compare it to simulations of a 2D and 3D geometrically constrained model, as well as contact maps of real proteins. Using data from the RCSB Protein Data Bank (PDB) and AlphaFold~2 database, the analytical approximation can be accurately fit to both datasets. This holds for protein chain lengths of $L\approx100$, $L\approx200$, and $L\approx300$. While, a universal scaling behavior for the different chain lengths could not be deduced, it seems that the amino acid distance distributions can be attributed to geometric constraints of protein chains in bulk and amino acid sequences only play a secondary role.Comment: 9 pages, 4 figure