ACD/NNMR
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Quickly and accurately predict 15N NMR chemical shifts and coupling constants for almost any organic chemical structure. |
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Many fine chemicals, natural products, along with over 80% of all drugs contain nitrogen. While collecting 15N NMR data can assist in the identification of these compounds, a variety of reasons prevent it from being collected on a routine basis:
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Low natural abundance and sensitivity of 15N result in poor quality spectra and slow acquisition times. |
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Acquisition range is broad and knowledge of 15N chemical shift behavior is required, making the experimental setup more demanding than 1H and 13C NMR (especially in 2D experiments). |
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Interpretation of coupling constant and chemical shifts can be challenging. |
ACD/NNMR is a 15N prediction package that can help simplify the complex routines mentioned above by predicting chemical shifts and coupling constants to aid in interpretation. It can also be used to narrow down the experimental acquisition range to reduce instrument time.
Chemical structures, imported from a variety of formats (including SDfiles, molfiles, SMILES, InChI, etc.) or drawn directly with our renowned ACD/ChemSketch package, can be used to predict 15N NMR chemical shifts and coupling constants in a matter of seconds. Add-ins for ISIS and ChemDraw provide access to our predictions directly from alternative drawing packages.
In addition to prediction of chemical shifts and coupling constants, you can build databases of experimental chemical shifts from your own compounds and novel structures to improve your predictions.
Attention existing users: In order to generate the most accurate predictions (in particular for compounds that exhibit stereochemistry), please review the technical note entitled, "How to Draw Structures for Accurate NMR Predictions".
For more information on the capabilities of this product refer to the overview links on the side panel of this page.
The separate ACD/NNMR DB software module provides you with access to browse the complete 15N NMR database used for the predictions.
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