; void 0;){kind=small}
A Publication Comparing NMR Prediction Approaches
Posted by: Antony Williams in ChemSpider ChemistryCopyright©2007 Antony Williams
Those of you frequenting this blog might have read my highly opinionated views of what was originally entitled “Open Notebook Science NMR” (1,2). My views around that work were very strong…in fact I didn’t really “get it”. I didn’t get why GIAO approaches for NMR prediction (with all of the stated limitations) would be done to prove that you could validate NMR assignments by comparing predictions with assignments made experimentally . It’s known that NMR prediction can validate structures – it’s done on a daily basis in commercial software tools. I was involved in building tools like that for over a decade so what was to prove?
The work concluded, as I understand it, with the examination and “validation” of about 500 structures over a month, but with a limited set of elements, no flexible side chains and a limited Mw range. Meanwhile, chemists are doing it on a daily basis across industry in a few seconds using one button click (1,2). For one of the most impressive overviews of verification technology in the lab see this talk by Phil Keyes from Lexicon Pharmaceuticals.
I get that there is value in validating assignments extracted from the literature as was finally declared as the focus for the work…actually BEFORE they are put in the literature. But, to clarify, that’s not about prediction so much as workflow…prediction and validation has been proven for many years. It’s not perfect but really good. That will be reviewed in our future publication “The Performance Validation of Neural Network Based 13C NMR Prediction Using a Publicly Available Data Source” presently in review at JCIM. This paper will review neural network prediction applied to NMRShiftDB. Just as a reminder from previous posts…the ENTIRE dataset of over 200,000 shifts were calculated in less than 5 minutes…no limitations re. flexible chains, Mw limits etc.
With these comments as an intro I am pointing interested readers to an article that found its way onto JCIM ASAP Articles yesterday. This reviews the Neural Network prediction as well as other approaches. I will confess that the Neural Network approach far exceeded my own expectations of performance. But hey, that’s why we do research…we have opinions, expectations and hypotheses…and go off to prove them. And if we can’t something fresh and exciting can show up anyway!
Toward More Reliable 13C and 1H Chemical Shift Prediction: A Systematic Comparison of Neural-Network and Least-Squares Regression Based Approaches 10.1021/ci700256n
The efficacy of neural network (NN) and partial least-squares (PLS) methods is compared for the prediction of NMR chemical shifts for both 1H and 13C nuclei using very large databases containing millions of chemical shifts. The chemical structure description scheme used in this work is based on individual atoms rather than functional groups. The performances of each of the methods were optimized in a systematic manner described in this work. Both of the methods, least-squares and neural network analyses, produce results of a very similar quality, but the least-squares algorithm is approximately 2-3 times faster.
Stumble it!
Entries (RSS)
December 7th, 2007 at 12:33 pm
Comparing NMR Prediction Approaches
A new article is now available on JCIM ASAP entitled, Toward More Reliable 13C and 1H Chemical Shift Prediction: A Systematic Comparison of Neural-Network and Least-Squares Regression Based Approaches 10.1021/ci700256n A very interesting read for those…
December 7th, 2007 at 10:32 pm
I posted this on Peter’s recent comment to respond to me:
http://wwmm.ch.cam.ac.uk/blogs/murrayrust/?p=854
Peter…you comment
“PMR: This is a scientific experiement to see if Quantum mechanical methods can predict NMR shifts. The emphasis is on Quantum Mechanics. Does Quantum Mechanics agree with experimental data?”
That’s known I thought. There are tens of papers out there already where this has been shown. You’ve commented on this re. Hexacylinol yourself, a famous example of GIAO application. So, it’s at best a repeat experiment, one conducted many times.
The inclusion of spin-orbit coupling into GIAO NMR predictions has been discussed previously a decade ago:
http://www3.interscience.wiley.com/cgi-bin/abstract/5008678/ABSTRACT?CRETRY=1&SRETRY=0
Note the abstract re. normal halogen dependence
“Spin-orbit coupling is responsible for many heavy-atom effects on NMR chemical shifts, for example, normal halogen dependence. A simple but general model for spin-orbit-induced substituent effects has now been developed by analogy to the Fermi contact spin-spin coupling mechanism (see below). DFT calculations on some simple iodo compounds illustrate the scope and validity of the model.”
The upfield shifts you talked about here http://wwmm.ch.cam.ac.uk/blogs/murrayrust/?p=732 regarding the halogens are well-known effects. You commented “the effects can be calculated, and are somewhat basis set dependent. For our basis, Br should be corrected by -12 ppm (and approx -24 for two) and Cl by -3 ppm. S is probably -2ppm, and Iodine -28 ppm. That should probably suffice for the halogens.”
I’ve done a lot of heavy metal NMR over the years. One Chapter of my PhD focused on pressure and temperature dependent shifts of Co-59 (http://www3.interscience.wiley.com/cgi-bin/abstract/88511686/ABSTRACT). During that work I read a lot about the theory of chemical shifts and specifically the work of Cynthia Jameson. At the same time I was examining the temperature dependence of C-13 shifts in octyl halides …the temperature-based shift dependence of the Carbon alpha to the halogen was significant for all halogens increasing from F through to I. I recalled reading about the normal halogen dependence and it’s connection to spin-orbit coupling at that time.
A quick search on google on “spin orbit normal halogen dependence” gives as a top hit:
http://pubs.acs.org/hotartcl/cenear/980928/nmr.html
This contains the following nugget:
“…carbon-13 in iodomethanes, were shifted far upfield, way out of character for what was expected. This is called the normal halogen dependence.
Eventually, in 1969, Japanese theorists determined the effect was due to spin-orbit coupling… ”
Looks like the effect you’ve noticed was first explained about 40 years ago.
Ain’t the web great?
In regards to GIAO vs HOSE, Neural Net and Increment based methods we were hoping to get a good data set for comparison out of your work. What we’ve done in the meantime until the entire dataset is online for us to compare is to look in the literature for GIAO NMR calculations. We’ve got over 30 publications out of the literature to data and have done the comparable predictions. I’ll blog about it soon…it’s consistent with expectations.