The overall colors palette can be changed from the 'Properties' window (double click on the spectra or go to the main menu ‘Edit’/Properties') by changing the starting colour of the Stacked /Hue Color (in this case it has been changed into red) If the script runs properly you should obtain something like this: Stacked Item Set Visualization into View= “Superimpose”, Palette=“Hue” and click ‘Ok’.Fill the “Data Folder” field, pointing to the pathway where spectra are stored (click on “preview file” to check which spectra would be included in the stacked).On the menu select Script/Import/Directory Spectra Stack to automatically open and stack a serie of spectra located under the same folder. You can also rename the page (right click ’Edit Page Title’) or delete pages containing individual spectra. Then click on the icon highlighted below in order to superimpose selected items (alternatively the same command is located in the main menu 'Stack/Superimpose Items').įinally the stacked plot is created in a new page, as the second page after the first selected spectrum of the stack. Selection can be done either by doing right click ’Select all’, or pressing SHIFT while selecting. Once spectra are opened in Mnova select all pages containing the desired spectra. Use the 'Data Browser' panel (it has to be activated from main menu 'View/Panel Data Browser').Īlso, with the “+” button you can add the path where your data are located.Īs in the first option, select the folders containing raw data and drag&drop them into Mnova. from “1” to “9”) and drag and drop them into Mnova.
There a couple of ways to load your data into Mnova: Create a stacked plot manuallyįirst you need to selecting your raw data manually. This tutorial intends to guide you through the main steps of your chemical shift perturbation analysis. Mnova Binding automatically processes 2D HSQC type of protein-ligand titration spectra, tracks the peak movement, and computes the Kd‘s for multiple peaks. This powerful tool has been designed to carry out chemical shift perturbation analysis for fragment-based drug discovery.