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BIONT
Modeling Program for the Complex Biochemical Systems

BIONT is the program for simulation and analysis of biochemical kinetics, membrane transport kinetics and volume changes in complex multicompartment systems like Mitochondrial Permeability Transition system. BIONT is written in MatLab 5.11 environment, which provides excellent tools for handling large data matrixes and good possibilities for graphical data representation.

We prefer to write BIONT, instead of using other available biochemical simulation programs, due to necessity to manage some distinctive properties of compiled MPT model, not readily handled simultaneously by the most of convenient programs:

Simultaneous electrogenic membrane transport processes and membrane potential-dependent processes  (e.g. ion transporters, respiratory chain, and ANT)
Varying compartments' volumes (e.g. mitochondrial matrix, intermembrane space)
Multicompartment and multimembrane system
Various reactions' kinetics, often not coincided with widespread types.
Very large number of first-order differential equations (in perspective - arbitrary first-order differential equations) and variables - about several hundreds and more.

Calculation principles used in BIONT

Uniform additive variables

We use uniform additive variables which could represent any of the following parameters in the similar way:

Substances' concentrations
Enzymes' concentrations
Transmembrane charge
Media's volumes

First order differential equations

We use for calculations uniform 4-parameter first order non-linear differential equations. (4 parameters: forward rate constant, reverse rate constant, charge transferred, electrogenic reaction type) 
(In perspective - arbitrary first order differential equations, build-in standard kinetics types)
During integration program performs continuous estimation of membrane(s)' potential(s) and compartments' volumes and, according to the values corrects reactions' rates and substances' concentrations.
(In perspective - continuous estimation of osmolarity, ionic force and pH control: for ...-dependent reactions)
Modified Rosenbrock formula of order 2 for stiff systems was used for numerical integration
(In perspective - various integration methods)
Calculation algorithm can use adaptive time step size, according to the fastest reaction rate

Program features

Models handling

Multiple substances number (up to 10000 - limited by RAM mainly)
Multiple compartments
Multiple charged membranes
Varying compartments' volumes
Varying membranes' charges
(Sub)models creation, changing (add/remove substances and/or reactions), extraction, combining, deletion, saving, loading
Direct table values edition
Conveniences complex (e.g. substances-reactions-calculation-plotting synchronization, automatic reaction rate/equilibrium constant/rate value preview)

Behavior calculation

Adaptive/fixed time periods
Automatic curve groups calculation at some parameter change (e.g. number of concentration/time curves at different reaction rates)
Intermediate steps saving (on HDD) and recall
Metabolic control analysis suit
Control coefficients
Elasticity coefficients

Visualization

Multiple plots
Using calculated values buffer (no need to recalculate for replotting)
Parameter/time curves
Parameter/parameter curves
Built-in parameters' functions set (ln, statistical, special reaction rate functions - dG, partial rate etc.)
Custom functions calculation and plotting

Parameters optimization

Various optimization criteria 
any parameter's arbitrary or built-in functions' value/minimum/maximum (e.g. reaction rate should be 5 nmol/min, or substance concentration should be as maximal as possible)
interparameter dependencies' curves shape (e.g. S-type dependence according to experimental curve shape)
multiple simultaneous optimization criteria (e.g. reaction rate should be 5 nmol/min and at the same time some substance concentration should be as maximal as possible)
selective multiple optimizable parameters (e.g. find out concentrations' values giving maximum reaction rate)
synchronous/free parameters optimization (e.g. we have fixed reactions' rates ratio but need to fit absolute values)
fixed/free optimization ranges
Various optimization methods
Gradient
Multigradient
Simplex
Genetic
Random search
Optimization conveniences set

Statistical estimation

Statistical analysis suit
Dispersion of multiple model parameters
Normal/uniform dispersion
Dispersion range customizable for each parameter
Synchronous/free parameters dispersion
Various statistical parameters estimation and appropriate graphical representation tools
Average
Standard deviation
Correlation
Normality
Histogram
Asymmetry, Excess, Box plot, etc.
Statistical estimation of any custom or built-in parameters' functions

Elements of Metabolic Control Analysis

Metabolic control analysis suit:
Elasticity coefficient estimation
Control coefficient estimation
Additional combined parameters

Program screenshots:

(Click to enlarge)

Main program window: Plots window:

Your comments or questions are welcome!

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