3DSpineMFE
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
Modelling and simulation
SDA: Simulation of Diffusional Association
SDA7 can be used to carry out Brownian dynamics simulations of the diffusional association in a continuum aqueous solvent of two solute molecules, e.g. proteins, or of a solute molecule to an inorganic surface. SDA7 can also be used to simulate the diffusion of multiple proteins, in dilute or concentrated solutions, e.g., to study the effects of macromolecular crowding.
If the 3D structure of the bound complex is unknown, SDA can be used for rigid-body docking to predict the structure of the diffusional encounter complex or the orientation in which a protein binds to a surface. The configurations obtained from SDA can subsequently be refined by running molecular dynamics simulations to obtain structures for fully bound complexes.
If the 3D structure of the bound complex is known, SDA can be used to calculate bimolecular association rate constants. It can also be used to record Brownian dynamics trajectories or encounter complexes and to calculate bimolecular electron transfer rate constants.
While these Brownian dynamics simulations are usually carried out with rigid solutes, in SDA7 we give a possibility to assign more than one conformation to each solute molecule. This allows some large-scale internal dynamics of macromolecules to be considered in the simulations.
In this SDA distribution, there is a single executable, sda_flex, which will execute different types of simulation:
- Compute the bimolecular diffusional association rate constant for 2 solutes using a user-defined set of intermolecular contact distances as reaction criteria
- Compute the rate constants for electron transfer from the relative diffusion of two proteins
- Perform rigid-body docking of two macromolecules
- Perform rigid-body docking of a solute and a surface
- Calculate the time during which user-defined contacts are maintained; this gives an approximation for the lifetimes of a complex. The starting configurations may be from a crystal structure or recorded from a simulation
- Re-calculate energies for a recorded set of configurations
- Compute PMFs for protein/surface binding
- Perform simulations of the diffusion of multiple proteins
The simulations can be run in serial or in parallel mode on a shared-memory computer architecture.
Other software
All softwareArbor
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks. Arbor is written from the ground up with many-cpu and gpu architectures in mind, to help neuroscientists effectively use contemporary and future HPC systems to meet their simulation needs. Arbor supports NVIDIA and AMD GPUs as well as explicit vectorization on CPUs from Intel (AVX, AVX2 and AVX512) and ARM (Neon and SVE). When coupled with low memory overheads, this makes Arbor an order of magnitude faster than the most widely-used comparable simulation software. Arbor is open source and openly developed, and we use development practices such as unit testing, continuous integration, and validation.
Modelling and simulationCellular level simulation
BioExcel Building Blocks
BioExcel Building Blocks Workflows is a collection of biomolecular workflows to explore the flexibility and dynamics of macromolecules, including signal transduction proteins or molecules related to the Central Nervous System. Molecular dynamics setup for protein and protein-ligand complexes are examples of workflows available as Jupyter Notebooks. The workflows are built using the BioBB software library, developed in the framework of the BioExcel Centre of Excellence. BioBBis a collection of Python wrappers on top of popular biomolecular simulation tools, offering a layer of interoperability between the wrapped tools, which make them compatible and prepared to be directly interconnected to build complex biomolecular workflows.
Modelling and simulationMolecular and subcellular simulation