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NMRPredict:
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NMRPredict Overview
NMRPredict
NMRPredict version 1 was released in the summer of 2004. Version 2 was released in November 2005 and updated in June 2006.
Version 3 was released in September 2006 and Version 4 in January 2008 and updated to version 4.7 in January 2010.
We believe NMRPredict is the most accurate NMR prediction program available. The accuracy of the carbon predictions was discussed in 2007 and the proton predictions were dramatically improved by 40% in early 2008, and further improved in 2009.
While the Windows interface for NMRPredict is new, the science behind the program certainly is not and includes over 100 man years of development from four of the world leaders in their respective fields:
- Professor Wolfgang Robien of the University of Vienna has been working in the area of Carbon 13 NMR prediction and databases
for nearly 30 years. He and his co-workers have built up a database of over 193,000 C13 and 31,000 X-Nuclei data and he is the developer of the CSEARCH C13 and X-Nuclei prediction program
which is included in NMRPredict
- Professor Ray Abraham of the University of Liverpool is renowned as one of the world leaders in proton NMR prediction and has published over 20 papers on the subject over the past 30 years.
He is the developer of the CHARGE proton NMR prediction program which is included in NMRPredict
- Professor Ernö Pretsch of ETH, Zürich is known as one of undoubted world leaders in NMR prediction as has published many books
on the subject over the last 30 years
- Dr Kevin Gilbert of Serena Software has been working in the field of Geometry optimization and Conformational searching using molecule mechanics force fields for over 25 years.
He is the developer of PC Model and GMMX. GMMX is included as part of NMRPredict
Some of the features of NMRpredict are:
- It is so easy to use that you can learn the program in minutes
- You can enter your query structures using the drawing program you use every day - either ISIS Draw, ChemDraw, Symyx Draw or ChemSketch
- It not only gives reliable predictions but is not a "black box". You are informed when and why predictions can be relied upon, and when you need to take care
- It is priced remarkably reasonably for both industrial and academic users
In Carbon 13 NMR Prediction NMRPredict:
- Uses an enhanced HOSE Code algorithm to make predictions against a database of 193,352 of the most highly verified data available.
An optional additional 185,517 data from Chemical Concepts are also available. This database of over 378,000 records is the largest commercial collection in the world
- Also uses a highly sophisticated Neural Network algorithm to help predict molecules which are not well represented in the database
- Automatically selects a "Best" C13 prediction for each atom from the two prediction methods
- Is able to differentiate its predictions based on the stereochemistry in the molecule. No other prediction program is able to do this so reliably
- Offers an optional database building module which allows you to build your own C13 NMR databases for prediction
In Proton NMR Prediction NMRPredict:
- Makes predictions based on functional groups which have been parametrised by Professor Abraham.
- Generates 3D conformers from a 2D structure using force field calculations prior to prediction.
Spectra are predicted for each conformer. A weighted average spectrum is also calculated
- Also includes the substituent chemical shifts approach developed by Professor Ernö Pretsch of ETH, Zürich. This routine has recently been enhanced to make use of 3D structures.
- Automatically selects a "Best" proton prediction for each atom from the two prediction methods
- Offers an optional database building module which allows you to assign your own proton user databases for prediction
Try NMRPredict
It is possible to try NMRPredict for yourself at no charge. Contact Jeff Seymour at jeff@modgraph.co.uk.
NMRPredict and Mestelab Research
Modgraph and Mestelab Research have collaborated to integrate NMRPredict within
the world famous Mnova NMR processing package. Now you can open your real experimental data and, from within the same package, compare the predicted with the experimental spectrum.
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