Simmune consists of three components: the Simmune modeler
(short: 'simmod'), the simulator (short: 'simmune') and the signaling
network browser.
Here, we provide a brief overview of the Simmune package which comes with
extensive documentation and tutorial movies. To request Simmune (executables
for Windows (tm), MacOS (tm) and most Unix (tm) platforms) send an email
to software@simmune.org. Simmune is free for non-commercial research.
Licenses for commercial research can be obtained as well. Commercial
licenses will currently be handled by NIAID's Office of Technology
Development.
The Simmune Modeler
The Simmune modeler, Simmod, has five main windows for the definition
of
At the fundamental scale (in the molecule window), the modeler defines
molecules by specifying their types (receptors, enzymes, adaptors etc.)
and their properties, such as the number of binding sites,
enzymatically active sites and diffusion coefficients. Simmod then creates graphical
representations of the molecules and allows the modeler to define
interactions between their binding sites simply by using the mouse to
draw connections between them. Once a connection (binding possibility)
is established, the modeler can define the association and dissociation
rates of the interaction
(screenshot).
In addition to defining the interaction kinetics the modeler can specify whether
a binding or debinding event induces changes in the properties of the interacting
molecules. The classical example for such a situation is the induction of
conformational changes to the cytoplasmic domain of a receptor upon ligation by
its extracellular ligand. Such changes then render certain binding sites
(like, e.g., the enzymatically active domains of RTKs (receptor tyrosine kinases))
more or less available for their binding partners.
By defining these interactions (plus enzymatic transformations, described below)
between pairs of molecules the modeler provides the information the software needs
to construct the full network of all molecular complexes that are possible in the system.
At the next scale, the scale of molecular complexes, the modeler uses the
graphical molecule symbols from the molecule definition window to 'build' those
molecule complexes that should be tracked in space and time during simulations
and / or that have enzymatic activity. Complexes are build simply by double-clicking
the binding possibilities indicated by lines between binding sites
(screenshot).
Important note: Based on the modeler's definition of molecular binding possibilities
and enzymatic transformations Simmune automatically builds the complete network of
molecules, molecule complexes and their reactions. If, for example, the modeler has specified
a binding possibility between a molecule A and a molecule B the software will automatically
include the formation (and dissociation) of the complex A:B into the construction of the reaction network.
The network is constructed upon user request or, automatically, during a simulation. The definition
of molecule complexes 'by hand' is necessary only for those complexes for which i) the modeler wishes to investigate
concentrations and locations during simulations and/or for which ii) the modeler wishes to define enzymatic
action on other molecular species.
The molecule complex symbols created in the complex window are used in the cell definition
window to specify the initial biochemistry (distribution of complexes in the membrane and the cytosol)
of cells. This completes the biochemistry part of the model. Based on the user's inputs the software
can calculate - during a simulation run, see below - the time evolution of the concentrations and
spatial distributions of all complexes. It also can automatically generate graphical representations of the
signaling network (see below) and show how the concentrations of its components and the reaction flows
in the different regions of a simulated cell change over time.
Mechanisms of cellular behavior
Models of cellular behavior may incorporate components on multiple spatial and temporal scales.
A model of a collection of interacting cells could, for example, be simulated with a detailed
simulation of signaling processes leading to the activation and translocation to the nucleus of messengers
that induce cell division. One the other hand, one might, in the model's context, perhaps not be interested
in the details of the division process itself, just in the result: a delayed appearance of an additional
cell in the system. To make such scale-hybrid models and simulations possible Simmune allows the modeler
to connect the detailed intracellular biochemistry to 'stimulus-response' mechanisms: Presence or absence of
threshold amounts of user-defined molecular complexes can be defined as conditions ('stimulus') for the cell
to perform actions ('response') like division, expression of additional molecules (intracellularly) or on the
membrane, directed secretion of molecules, directed movement or death. In this case, the biochemical details of
how the actions themselves are executed need not be simulated - only the build-up of stimuli and the
consequences are.
Extracellular space
With Simmune, cells can be simulated in 2D space, pseudo 2D (a thin slice of 3D space that eliminates most of
the artifacts 2D models suffer from) and 3D space. Currently, only rectangular pieces of space with variable dimensions
can be defined as the extracellular compartment. We are working on the possibility to define more complex topologies.
Defining simulations
After the model components have been defined, the parameters for the simulations of the model can be specified
in the simulation definition window. Besides being an interface for technical settings (like random generator seed etc.)
this window allows the modeler to specify protocols for simulated experiments: when and at which space points should
cells and molecules be introduced to the simulated system. While Simmune makes it possible to run fully interactive simulations
during which the modeler can add, modify or inspect agents at any time (see below) simulation protocols make it possible to
study the behavior of the simulated model through sequences of exactly defined (and easily reproducible) manipulations.
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The Simmune Simulator
Once the model and the simulation parameters have been defined the model can be investigated
through simulation with the Simmune simulator ('simmune'). The simulator is usually started from
the simulation definition window of Simmod. It offers three different views of the simulated
extracellular space: i) a concentration over time view that lists all extracellular
agent types (molecule types, cells) and how their (spatial) average concentration or total
number changes as the simulated time progresses, ii) a pseudo 3D view of the simulated
extracellular compartment with (depending on their types, differently colored) dots representing
the cells in the system, and iii) a 'slice' view that shows a 2D cut through the extracellular
compartment and in addition to being able to visualize molecule concentration gradients
(screenshot)
can be used to select single cells for
detailed inspections of their intracellular biochemistry
(screenshot).
The single-cell inspection mode also allows the user to save the time course of the biochemistry of
the selected cells for inspection with the network browser (see below).
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The Network Browser
Usually, software for the construction of signaling pathways requires the modeler to specify each single
reaction between the molecular complexes involved in the model and then perform a layout of the graphical
representation of the pathway by hand.
As described above, Simmune automatically constructs the complete
signaling network of interacting complexes based on the specifications of bi-molecular binding possibilities.
Moreover, during a simulation of the behavior of cells that contain such signaling networks the modeler can save
the detailed behavior of the cellular biochemistry. The modeler can then use the network browser to investigate
the dynamics of the signaling processes with the help of automatically generated graphical representations of the
networks (screenshot).
These graphical representations use color saturation levels to indicate the relative concentrations of molecular species
and visualize the reaction flows between them. The modeler can 'replay' the simulated experiment and follow the
dynamics of the signal flow far easier and more intuitively than with conventional approaches. At the same time, the
browser offers full access to the quantitative details: clicking on molecular complex symbol allows the modeler to
query all relevant properties (molecular components, binding sites involved in formation of the complex etc.)
and the exact concentration at any point in time and at different locations in the simulated cell.
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