Mesoscale modelling with Fluctuating Finite Element Analysis (FFEA)

There is a community consensus that "Structural biology is transitioning from a largely molecular perspective to a much wider range of length scales", as a result of developments in 3D cellular imaging tools such as cryo-Electron Microscopy and Tomography. Fluctuating Finite Element Analysis (FFEA) is a novel mesoscale biomolecular simulation tool developed by our research team at Leeds which is specifically designed for biomolecular modelling based on structural data from cryo-EM and cryo-ET. Through this travel grant I will build collaborations with key computational (Amaro), experimental (Chiu and Fire) and theoretical (Benham) groups to broaden the range of biological questions addressable with FFEA by performing preliminary calculations on cytoplasmic dynein and extrachromosomal DNA (eccDNA). The aim is to build an international community of FFEA users by ensuring usability and compatibility with other codes.

There is a community consensus that "Structural biology is transitioning from a largely molecular perspective to a much wider range of length scales", as a result of developments in . To gain a mechanistic understanding of the new biomolecular regime being revealed by 3D cellular imaging tools such as cryo-Electron Microscopy and Tomography (cryo-EM/ET), we will need simulation tools both for hypothesis testing and to integrate different types of biophysical data.

FFEA provides a new modelling method for simulating soft matter and biomolecular structures using volumetric data (e.g. from the EMDB), as opposed to atomistic data (e.g from the PDB), as input to the calculations. This will enable experimentalists to interpret the data from low resolution (10-100nm) structural studies, such as cryoEM or SAXS, for example, by providing a means to infer mechanical properties by matching the observed variations in configuration with simulation. It can also be used by soft-matter physicists studying the effect of crowding on protein diffusion; by nanotechnologists wishing to construct a complex biofluid with bespoke mechanical properties; or to study the interactions of new bionanomaterials with proteins in a cellular context, and reveal how diffusion and flexibility influence biomolecular interactions.

Proteomics and systems biology have shown that biochemical and metabolic processes are often regulated by way of signal cascades involving complex networks of interacting macromolecules. However, most current in silico drug design strategies simply aim to screen for small molecule inhibitors against a particular pair of binding partners, whereas the higher order consequences of this intervention is often beyond the scope of the methodology. Since FFEA makes it possible to construct a fully hierarchical computer model, it becomes possible to predict the mesoscale mechanical consequences of inhibiting (or stabilising) a particular atomistic interaction, for example during the inhibition of a molecular motor such as dynein. FFEA can be therefore be used more generally to model how the complex physical organisation of the environment surrounding a particular drug target might affect the response, or how changes to the mechanics of proteins might affect their function at the mesoscale. The method also has implications for the future design of drug delivery vehicles that hope to increase drug efficacy by providing an environment for the drug that guides it towards its target, since it enables far more realistic cellular and subcellular organisation to be included in the models.