# Modern open-source tools for simulation of NMR spectra

I am interested in predicting the NMR spectrum of small organic compounds. It doesn't matter to me if the prediction is very accurate. I'll eventually be comparing the prediction to experimental results.

It looks as if several free online tools offer the ability to do such predictions:

1. NMR DB is a free website that offers a prediction of 1H, 13C, and supposedly even 2D NMR experiments. Structures are entered via a GUI editor.

2. VeSPA and PyGamma are Python packages (or Python wrappers around C libraries) that supposedly simulate NMR spectra of molecules. However, both packages are very old and have not been substantially updated in some time.

My question is, what is the best available (free) computational tool for predicting NMR spectra? As I mentioned, I understand that predictions are imperfect. What software, if any, are widely used by practicing chemists for NMR simulation? What is the best reference to read about such software, including the heuristics and algorithms it uses to simulate spectra? Is Vespa and/or PyGamma state of the art? The NMR DB site is nice, but I'd very much prefer an interface that is amenable to scripting, and where structures could be supplied computationally rather than via a GUI interface.

(I'm a mass spectrometrist and biochemical engineer with little training in NMR methods.)

• I know that Orca can perform such calculations. I never used Orca for that. It is not open source. I would look for Nwchem as an open source alternative . – user1420303 Dec 21 '16 at 0:17
• I'm not sure about their ability for computing coupling constants. – user1420303 Dec 21 '16 at 0:20
• Yes, Nwchem and Orca rely on electronic structure calculations. NMR DB is very different. I do not know exactly what VeSPA/PyGamma do, but I bet they are different too. Yes, there are a lot chemist doing this kind of calculations. They are useful mostly to predict spectra or chemical shifts. Take in mind that electronic structure calculations of NMR spectra can be very time consuming as their requires the computation of the expected values of many hamiltonian's derivatives. – user1420303 Dec 21 '16 at 0:41
• Everybody uses the empiric prediction routines integrated in Chemoffice, Mnova, etc., which are based on chemical shift increments, afaik. Very, very few people have a need for accurately simulated spectra. You need to know not only the correct structure but also the dynamics in the system. – Karl Dec 21 '16 at 1:35
• I use GAMESS (US) for this process msg.ameslab.gov/GAMESS where I have used it as the basis of Goodman's DP4 algorithm. – user1945827 Dec 21 '16 at 11:55

In Org Biomol Chem 2016, 14, 3943, Goodman reports the replacement of some "tradition" (expensive) programs with free/open-source ones, as applied to their dp4 method.

Specifically:

• Molecular mechanics with tinker (I believe as a replacement for MacroModel), you may or may not want this step depending on what you're doing. The paper is looking at molecules with stereocentres and as such, they appear to have wanted to ensure the NMR values calculated matched the most likely conformation of the molecule experimentally studied.
• NMR prediction using NWChem (replacing Jaguar as the gold standard) to do the DFT calculations. There is some mention that this was slower, but again, it would depend on what you're interested in studying.

I think that fulfils your requirement for being able to do the prediction using open-source programs.

As for scripting, there is a mention in the paper of wrapping the whole thing up in a python script (and to my knowledge, there isn't actually a GUI for either piece of the aforementioned programs), so it should be amenable to this.

One thing that it doesn't appear to do, is to graphically plot the resulting data generated (I believe they just compare a list of values to a list of experimental values), but you should be able to plot this in something like MatLab, or, if you play enough, it should be importable into TopSpin via something to turn it into a set of suitably written values.

You can submit the structure to the NMR database website using this link.

Concerning the algorithms, there are references on the nmrdb.org website. For $\ce{^1H}$ prediction we are using Spinus (based on the neural network). For $\ce{^13C}$ we are using NMR shift DB that is based on hose code.

To get an overview of the prediction algorithms you may be interested in our last publication.