Integrating structural and dynamic information at various scales is essential for understanding complex biological processes. GRAL, the Grenoble Alliance for Integrated Structural & Cell Biology, places emphasis on the dynamics of biological systems, including for example the assembly of protein complexes, their integration into functional operating systems, the kinetics of interactions between host and pathogens and the self-organization of cells into multicellular architectures such as tissues or organoids. Overall, GRAL is divided into two main programmes: 1) “Molecular Machines and Dynamics” and 2) “Self-organization of Biological Systems”.
1. Molecular Machines, Dynamics and assemblies:
The objective of this programme is the comprehensive analysis of molecular machines (protein, DNA, RNA etc.) focused, but not limited to, the following processes: (i) virus host-pathogen interactions, (ii) microbial host-pathogen interactions, (iii) immunity and infection, (iv) membrane transport and signalling, or (v) epigenetics, chromatin, and cancer. The development of methods used to study these complex machineries is also in the scope of GRAL. These include among others: NMR, X-ray crystallography, atomic force microscopy, single molecule fluorescence technologies, neutron and X-ray scattering, optical and electron microscopy, native mass spectrometry techniques, and/or molecular dynamics simulations.
2. Self-organization of Biological systems:
A central property of living systems is their capacity to self-organize. The objective of this programme is the study of the dynamic properties of self-organization during morphogenesis and signalling in response to environmental cues in different organisms such as bacteria, yeast, microalgae, flies, human cells or plants. The programme includes and is not restricted to the following: (i) multicellular assemblies (organoids, tissues etc.), (ii) dynamics of protein complexes, (iii) biogenesis, function and dynamics of subcellular architectures (membranes, organelles, etc.).
Read the full description and expected outcomes of GRAL.