Version 2018.1
User-Defined Reactions
- Identify a greater number of metabolites, impurities, and/or degradants through addition of User-Defined Reactions
- Simply specify a generic reaction mechanism, for example conversion of C=O → C-OH, and generate any relevant metabolites formed by this process
Cross-Species Experiments
- Conveniently distinguish experimental data from distinct species (human, mouse, rat, dog) by designating species type during processing set-up
- Differentiate cross-species data in the Project Summary: [+]
- View an updated Global Biotransformation Map, which now includes all components detected in any species
- Display component detection by species in the Species Summary table
Customizable Data Reporting Template
- Easily create customized PDF templates for MetaSense project reporting [+]
- Report templates are compiled in ChemSketch, and all relevant project elements are available for inclusion: Overall Biotransformation Map, Kinetic Plot, Table of Species Summary, etc.
- Plus, includes the ability to display additional identifying elements and metadata: company logo, project description, analysts involved, etc.
Data Import & Processing
- Input and process data more efficiently with the Setup Wizard
- Analyze cross-species samples together. Designate a Sample Name for the collective dataset, and indicate a Species Type (Rat, Human, Mouse, Dog) for each sample
- Easier data tracking through preset naming conventions for experiments; specify a label in the Naming Pattern input to apply it across experiments
- Further differentiate experiment types with addition of "Blank", "Control", and "t0" categories to the Experiment Time dropdown menu [+]
- Streamline data processing through automatic subtraction of Blank baseline absorbance values from other experiments
- Customize data input by setting instrument mass accuracy and assigning separate tolerance thresholds for parent and metabolite retention times (to account for retention time lag between experiments) [+]
- Adapt processing further by adjusting parameters related to Unexpected Components, and/or customizing the various Advanced Settings [+]
Data Import
We continue to improve and support all major instrument vendor data formats. This version includes enhancements to the following:
Support of the new Agilent DAD data format, through import of *.sqlite files from instrument *.D folders
Improved support for XCalibur (Thermo Fisher Scientific), NetCDF, Agilent LC/MS 6000 (*.bin), Agilent LC/MS TOF (*.wiff), and Shimadzu LC/MS-IT-TOF (*.lcd) files
Data Display
Easily access data on metabolites filtered out of further analysis through the Filtered Metabolites table [+]
LC/UV/MS Data Processing & Analysis
Learn more about tools for processing and analysis of LC/UV/MS data and general tools for multi-technique, vendor agnostic data handling [+]
Data Analysis
Intelligent Component Recognition
- Employ the Intelligent Component Recognition workflow (IXCR 2.0) to streamline identification of "known unknowns" in mixtures through spectral searching.
- Characterize chromatographic components by searching their associated MSn spectra against public and/or user-created spectral databases (*.nd9 or *.cfd formats)
- Screen GC/MS data using MS1 spectra, and LC/MS data using MS2 spectra (recommended)
- Conveniently review the top result for each component in tabulated view
- Evaluate hit quality via mass difference (Da, mDa, or ppm units), and numeric MS Match values
- Right-click to expand the structure candidate list for each component, with the ability to customize the total number of hits displayed
- Easily evaluate top structure hits using mirrored plot comparisons of experimental and database MS spectra
Intelligent Component Extraction—IntelliXtract
- Manually adjust the mass accuracy (Da) specified for assignment
- Differentiate between isobaric ions or isomers that partially co-elute
Targeted Component Recognition—IntelliTarget
- Track any formulae/structures that are not found by IntelliTarget (which detects compounds that are specified prior to spectral deconvolution) by choosing to include them in tabulated view.
- Compounds not assigned to peaks are labeled "Not Found" in the MS Match column
Metabolite Identification—User-Defined Reactions
- Identify a greater number of metabolites and degradants through addition of User-Defined Reactions. Simply specify a generic reaction mechanism, for example conversion of C=O → C-OH, and generate any relevant metabolites formed by this process
Peak Tracking
- Track peaks more efficiently by transferring unique entity names from the Table of Peaks to the Table of Components
Data Display
- Visualize multiple MSn spectra simultaneously through improved MS Tree control
- All spectra, or only selected spectra, can be displayed
- Easily interpret MSn spectra by grouping display panels and performing collective zoom
Zoom Applied
MetaSense also contains spectral processing capabilities for a variety of spectroscopic techniques.
Click on each technique to read about what has been added.
Improvements to peak detection algorithm for more comprehensive processing of chromatographic data
- Complete automated detection of peak riders and shoulders based on user-defined 'signal to noise ratio' thresholds.
- Greater flexibility in data processing through a variety of peak integration methods
Peak integration options available for chromatographic data analysis
- Achieve greater accuracy in peak area calculations through the capability to manually adjust the baseline
Refined processing options deliver the most relevant information from chromatographic data
- Define selected areas of a chromatogram for analysis by excluding 'dark regions'
- Refine processing routines with flexible settings based on time intervals
- Define integration method
- Fine-tune peak detection thresholds
- Inclusion of negative peaks
Known Structure Identification Add-On
Simplify unknown compound identification/dereplication by determining whether the compounds' experimental 13C resonances match the predicted signals of known structures. Uses ACD/Labs leading, proprietary NMR prediction neural network algorithms.
- Uses a database of ~98 million known structures collected from open chemistry databases (e.g. PubChem) with predicted 13C NMR spectra
- Rapidly search using individual 13C, HSQC, or HMBC NMR spectra
- Conveniently view results in terms of the average chemical shift deviation between experimental and predicted spectra and their structure and database ID
Search results for the 13C NMR spectrum of Retrorsine. The query spectrum is green and offset vertically from the hit spectrum, which is shown in red. The list of hits is shown in the window below the spectra.
Data Analysis
Enhanced 1D NMR Mixture Analysis Tools:
- Conveniently compare spectra with automatic peak height and chemical shift offset scaling
- Automatically rank hits within a spectral search region
- Easily control the offset between a query spectrum and its respective hits
The new "Optimize Hit" feature can be seen in the spectra comparison menu on the left-hand side of the figure. The query spectrum is shown in green, the original hit is shown in red, and the blue line is the optimized hit curve.
Multiple tools and improvements have been added to version 2018.1. The highlights include:
- Improved peak picking and multiplet assignment accuracy of fluorinated molecules
- Automatically assign Homonuclear coupling partners, in some cases potentially eliminating the need for a COSY Spectrum
- Easily view connected 1H assignments and their coupling constants on the proposed structure
Additional tools have been added to improve spectral processing, 1D and 2D structure assignments, automated structure verification, data visualization, and software usability
Ease of Use
- Easily share custom solvent information
- Save structure data files (*.sdf) to a predefined folder
- Option to manually set the spectrum type
- Option to set display order according to Bruker Expno parameter
Data Analysis
- Simplify analyses by breaking a single curve into several curves with respect to temperature sweeps
- Analyze curves with ill-defined temperature gradients and plateaus
