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 potentialdependent
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 firstorder differential equations (in perspective
 arbitrary firstorder 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 4parameter first order nonlinear differential equations. (4
parameters: forward rate constant, reverse rate constant, charge
transferred, electrogenic reaction type)
(In perspective  arbitrary first order differential equations, buildin
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. substancesreactionscalculationplotting
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
  Builtin 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 builtin 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. Stype 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 builtin 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!
