MCell

Category Cross-Omics>Agent-Based Modeling/Simulation/Tools

Abstract MCell is a general Monte Carlo simulator of cellular microphysiology.

MCell may be used for the study of biological signal transactions, namely the microphysiology of synaptic transmission, and other areas, including: statistical chemistry, molecular diffusion, single channel or multi-channel simulation, data analysis, noise analysis, Markov processes, and other molecule dynamic applications.

MCell simulations take place on a sub-cellular biological scale. In areas of computational neurobiology, sub-cellular communication is based on a wide variety of chemical signaling pathways.

A process like synaptic transmission encompasses neurotransmitter and neuromodulator molecules, proteins involved in exo- and endocytosis, receptor proteins, transport proteins, and oxidative and hydrolytic enzymes.

MCell makes it possible to incorporate high resolution ultra-structure into models of ligand diffusion and signaling, and to provide highly realistic 3D simulations of sub-cellular architecture and physiology.

MCell Overview of Features/capabilities --

Typical events that occur during an MCell simulation include the release of ligand molecules from a structure (e.g., a vesicle), de novo creation or destruction of ligand molecules (e.g., synthesis, hydrolysis, or redox reactions), ligand diffusion within spaces defined by arbitrary surfaces (e.g., pre- and postsynaptic membranes, or a cell membrane with attached patch clamp micropipette), and chemical reactions undergone by ligand and “effector” (e.g., receptor or enzyme) molecules.

Ligands, effectors, reaction mechanisms, 3D surfaces, and other simulation components are specified using a simple programming language, or Model Description Language (MDL), that was designed with biologically-oriented users in mind.

When a simulation is run, one or more MDL input files are interpreted (parsed) to create the simulation objects and then execution begins for a specified number of iterations.

Each iteration corresponds to one Monte Carlo time-step. A wide variety of numerical and imaging results can be output from the run, and, in addition, simulations can be stopped and subsequently restarted from user-specified “checkpoints”.

Each time that a simulation restarts, updated information can be read from the input MDL file(s).

Check-pointing is thus an advanced and general way to change run-time parameters such as the time-step, reaction rate constants, and surface positions, and can also be used to split long simulations into segments that are run sequentially.

MCell's Monte Carlo algorithms simulate ligand diffusion using 3D random walk movements for individual molecules.

The positions of surfaces and effector sites are mapped in space, and “encounters” with diffusing ligand molecules are detected at points of intersection with the ligands motion.

The final outcome of each encounter is decided by comparing the value of a random number to the probability of each possible outcome. Different possible outcomes depend on the properties of the surface.

For example, at the point of intersection, the surface may be reflective, transparent, absorptive, or occupied by an effector site with an associated chemical reaction mechanism.

Random numbers are also used to decide between all other possible reaction mechanism transitions that might occur during each time-step. For example, bound ligand molecules may unbind, and effector sites may change from one defined state to another, simulating a protein conformational change.

The numerical accuracy of MCell's algorithms has been rigorously tested, and because of unique optimizations, the time required for simulations does Not depend on the complexity of included surfaces.

In other words, simulation of a large-scale tissue reconstruction (e.g. hundreds of thousands of polygons) requires about the same amount of time as simulation of a highly simplified structure.

The effective speed-up introduced by the manufacturer’s code optimizations thus amounts to many orders of magnitude, and can literally save months of computer time.

MCell simulation results --

MCell can export the simulation results in a variety of data formats: 2D numerical data, 3D animation data, and "C" style language data. There are also several popular visualization data format available for the user's convenience.

To define 3D visualization outputs, just select the right output mode in the MCell visual data output statement.

The available visualization modes in MCell are DX (IBM’s open source, DataExplorer), IRIT (open source, irit), RAYSHADE (open source, rayshade), POVRAY (open source, povray) and RENDERMAN (open source, Pixar's Renderman).

It is also possible to export numerical results and “C” language format results from a MCell simulation, and display them in various ways (MATLAB, Mathematica...).

MCell and DReAMM --

MCell - MCell (as stated above...) is a General Monte Carlo Simulator of Microcellular Physiology, and simulations can easily include hundreds of polygon mesh surfaces, sometimes containing millions of triangles, and thousands to millions of diffusing or stationary molecules.

DReAMM - DReAMM is a visualization and analysis program designed to read MCell visualization output of virtually unlimited size, and then let you choose what to render and with what level of detail.

The most important advantage of DReAMM’s design is fast interactive flexibility.

This requires a large amount of RAM for anything but the simplest MCell models (refer to the DReAMM User’s Guide for further details).

Visualizing Large Models - By default, newly imported data is Not rendered until selected, which avoids memory overruns and other difficulties incurred by very large models.

In addition, the default rendering properties assigned to newly chosen objects are designed to minimize memory use and computational load. Finally, you can also “clip” imported data, so that only a specified portion is rendered.

DReAMM Projects and Customizations - Imported MCell visualization data and associated DReAMM settings (selected objects, clipping, camera and animation, lighting, shading, and so forth) constitute a DReAMM project, which can be saved in a project configuration file for subsequent reuse.

While working with a DReAMM project, you can customize hundreds of rendering and animation settings, which can be saved in separate customization files.

These files can subsequently be shared between different DReAMM projects, for example, a complex camera trajectory might be reused for multiple animations, or a complex set of surface coloring and shading properties might be reused for multiple models.

Note: MCell was initially designed for computational neurobiology but it is Not limited to that area. It can also be applied to a wide range of micro-studies (as stated above...) such as diffusion-reaction applications, molecular dynamics, and computational chemistry.

The MCell team is working to add electronic physiology into the simulation in future versions.

Note: According to the Manufacturer, CellBlender (an additional program) is replacing PSC_DX and DReAMM as the primary tool to visualize MCell simulations. As such, PSC_DX and DReAMM are No longer under active development, but will remain available for download.

System Requirements

Contact manufacturer(s).

Manufacturer

Manufacturer Web Site MCell, DReAMM

Price Contact manufacturer.

G6G Abstract Number 20620

G6G Manufacturer Number 104221