VisualEnzymics present you with a custom visual interface. No more tedious wizards and results files. With VisualEnzymics, you see curve fits in real time. All the equations and graphs are linked. All the standard graph transforms are programmed. Change equations and fit data with the click of a button. Display a different data set with the click of a button. Create a layout with the click of a button. VisualEnzymics is built to give you interactive control.
Fitting Panel
The Fitting Panel is the central component of VisualEnzymics. From the Fitting Panel, you perform data analysis and access other linked windows in VisualEnzymics. There are nine tabs in the Fitting Panel. Each tab takes you to the equations for a specific type of analysis, including one substrate, one substrate one inhibitor, pH, exponentials, response curves, two substrate, one substrate one activator, binding and tight binding analysis. From the Fitting Panel, you also access data tables, graphs, ANOVA, and the report window. Data tables allow you to enter your kinetic data in terms of substrate, inhibitor, activator, velocity, and standard deviation of the velocity. Data tables are directly linked to the Fitting Panel. The graph window displays your kinetic data and gives you control over how you view the results of your analysis. Graphs are automatically linked to the Fitting Panel. The Report window gives you a record of the statistics for each fit. You can print out the results from the optimized fit from the report window. The layout window provides a blank canvas for you to compose publication quality figures from multiple graphs of different data sets.
Graph Window
VisualEnzymics supports a graph window for each type of analysis in the Fitting Panel. Each graph window provides an interactive visualization of your analysis. Since there are nine tabs corresponding to the nine types of analysis in VisualEnzymics, there are nine graph windows linked to the Fitting Panel. Each graph window displays up to 10 data sets and contains three tabs to control the data display. The data selection tab provides controls to display the raw data, the fit estimate curve, the final fit curve, the error bars, and the residuals from the individual fits. The scaling/transform tab provides one-click buttons to scale data on linear or log scales, or to generate automatic data transforms to Lineweaver-Burk, Hanes-Woolf, Woolf-Hofstee, or Eadie-Scatchard formats. The outputs tab offers one-click buttons to generate independent copies of the graph that are not linked to the Fitting Panel. An unlimited number of independent graphs can be generated from the graph window, and each can be customized for export to publication or electronic presentation programs. You have complete control over all the graphic elements of independent graphs.
Report Window
VisualEnzymics provides a report window to record the results of data fits to various equations. After fitting data to a kinetic equation, click the report button to generate the statistical output for the fit. The report will include the parameter settings of the fit, the initial parameter estimates, the final fitted parameters, the standard error and confidence interval for the parameters, the correlation matrix, and a copy of the original data. From this record you can always go back and recreate the fit, if necessary. The report can be printed for hardbound notebooks, or you can copy and paste reports into other programs. Alternatively, you can copy and paste fit results into a VisualEnzymics layout along with the final graph including the best fitting model line. The report window is generated in an Igor Pro notebook window that functions like all other notebook windows in Igor Pro, i.e. as a full fledged document editor. The notebook window can be named and saved as a separate file. Later it can be opened as part of any VisualEnzymics experiment. Also, graphs and tables can be pasted into the notebook window, as well as images or graphics from any outside source. The report window can be used to provide full documentation of the experiment, including data, results, graphs, procedures, and discussion.
Layout Window
VisualEnzymics includes automatic layout windows to combine graphs and statistical output from data fits. The output tab in the graph windows provides one click buttons to generate a basic layout that includes the current graph and residuals plot from the graph window. From this basic layout, additional graphs and text can be added to create a visual record of the experimental results. Any independent graph that has been generated from the graph window can be added to the layout. All VisualEnzymics graphs that are included in a layout are automatically updated whenever you change anything in the original graph, including colors, text sizing, symbol sizing, and annotations. Images or graphics from other programs can be pasted into the layout. Each layout page has a graphics layer and a drawing layer. The graphics layer can contain graphs, tables, and text from VisualEnzymics. The drawing layer can be used to create elements with the built-in drawing tools. Objects in the layout can be positioned precisely with the alignment guides that display object coordinates as they are moved within the layout. Layouts can be printed for hardbound notebooks, or can be exported as graphic objects to presentation programs or publishable documents. Layouts can be closed and saved. VisualEnzymics records a layout macro to recreate the layout and all its style elements. Saved layouts can be used as style macros for new layouts by opening a saved layout, and replacing the graphs in the layout with new graphs. An unlimited number of layouts can be saved in VisualEnzymics.
ANOVA Window
VisualEnzymics offers ANOVA for comparison of two model fits to the same kinetic data. ANOVA provides a method for determining whether or not a more complex model yields a significantly better fit to your data than a simpler model. After fitting your data to one model, you can transfer the fit statistics to the ANOVA panel under the section labeled Model A. Then return to the Fitting Panel, select a more complex model with more parameters, and fit the data to the more complex model. Usually, a more complex model with more parameters will give you a slightly better fit. The question is whether or not the improvement means that the more complex model is the true model. After fitting the data, transfer the fit statistics to the ANOVA panel under the section labeled Model B. Then run the F test to compare nested models, and the Akaike Information Criteria to compare non-nested models. The F test will yield a p value that provides the level of significance for any improvement in the fit to the more complex model. The lower the p value, the more likely it is that the more complex model represents the true kinetic model. For non-nested models, the smaller AIC value indicates which model is likely to be the true model.
Inhibition Calculator
VisualEnzymics provides you with a unique inhibition calculator that calculates the percent inhibition for seven different steady state inhibition models given a set of inhibition constants and reactant concentrations. When you design an enzyme inhibition experiment, you must select inhibitor concentrations that will yield significant enzyme inhibition over the range of substrate concentrations in the experiment. The inhibition calculator was created to help you design these experiments. For instance, if you suspect that a potential inhibitor may yield competitive inhibition, and you know the kcat and Km for your enzyme, you can calculate the degree of inhibition for any combination of Ki and inhibitor concentration over a range of substrate concentrations. This determines whether you might need more or less inhibitor in your experiment to observe significant inhibition at a specific Ki. By entering the same Ki and inhibitor concentration for various inhibition mechanisms, you can compare the potential inhibition profiles for other mechanisms. This type of comparison also is important for experimental design in testing large chemical libraries, sometimes up to a million compounds, in drug discovery. Since the type of potential inhibition is unknown for any compound in the library, the design of the experiment will be weighted to detecting certain types of inhibition at the chosen substrate and inhibitor concentration. In the design of the experiment, if you assume that you want to be able to detect competitive inhibitors with a Ki of 10 uM or less, and that your assay signal window will reliably detect 50% inhibition or greater, the inhibition calculator will calculate the substrate concentration needed to achieve this level of inhibition. This can reveal hidden technical problems, and can lead to more effective experimental designs.
Monte Carlo Fits
VisualEnzymics provides a Monte Carlo algorithm for brute force data fitting when the kinetic parameter estimates are largely unknown. Finding good initial parameter estimates often is easy for simple kinetic models with only two or three parameters. For more complex models, however, finding good initial estimates may be difficult, and the standard Levenberg-Marquardt fitting algorithm may fail to converge. In this case, the Monte Carlo method can be used to test millions of random parameter combinations in a matter of a few seconds or minutes. The parameter bounds then can be narrowed and another round of Monte Carlo optimization can be performed to refine the parameters. With several rounds of optimization, good initial estimates can be obtained for use with the Levenberg-Marquardt fitting algorithm. The Monte Carlo method also may be used to check whether or not the Levenberg-Marquardt algorithm has found a true minimum in the fit.
Binding Calculator
VisualEnzymics provides a binding calculator for calculating the concentrations of free and bound species in a one step binding reaction when at least three of the species concentrations are known, or two species and the Kd are known . The calculator also provides a graph of the binding curve over any specified range of ligand concentrations. The calculator can be used to plan binding experiments by entering various possibilities for the Kd, the enzyme concentration, and the ligand concentration. The calculated binding curve will show the shape of the curve, and will demonstrate whether or not the potential experimental conditions will yield binding saturation. By varying the input parameters, it is possible to visualize the effects of increasing or decreasing the enzyme concentration, or to see the effects of varying any of the species concentrations in a one step binding mechanism.
Software Link :
VisualEnzymics - Enzyme Kinetics Analysis software
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