Pre-ENC User Meeting Video

As you may know, we are going to hold an user meeting prior to the 50th ENC Conference.
There, Mestrelab's team and some guests are going to present some new Mnova features, algorythms and new products.

You can check the meeting program and get registered here.
Whether you are planning to attend or not I also encourage you to watch this 5 minutes video.

Double-click to switch to full screen

Pre-ENC User Video from Dani Fraga on Vimeo.

NMR and the Chemist’s Illusion

Stan has just posted a nice entry in which he uses the aromatic region of Strychnine to discourse about the different effects in the NMR spectrum (in terms of resolution and multiplicity) produced when the magnetic field frequency is changed. In particular, I like his description of the ‘Chemist’s Illusion’ and as a chemist, I would like to illustrate, just with a picture, what this illusion is all about.

In the picture below, I have synthesized the ABCD spin system corresponding to the aromatic region of Strychnine at different fields (we don’t own a 1500 MHz spectrometer and we don’t expect to get one for Mestrelab in the short- or mid-term :-) ). It can be appreciated that as we move to higher fields, the multiplets appear to be more separated (this is an illusion: their chemical shifts, in ppm, are exactly the same!) and get more resolved and more first-order like.

Below I’m showing an expansion of the right most multiplets:


Another interesting and well known example is represented by an AA’BB’ spin system (for example, o-diclhrobenzene) . Again, as we go to higher fields, the apparent multiplets separation looks larger, although the multiplet fine structure remains virtually unchanged. In other words, in these systems, second order effects will always exist regardless of the magnetic field. When the magnetic field is increased, it will be possible to get a larger chemical shift difference between the AA’ and the BB’ groups, but not between A and A’ or B and B’ (it’s always zero), so that the highest simplification one can achieve by increasing the magnetic field is to move from an AA’BB’ group to an AA’XX’ group which is a second order spin system too.

Peak Shapes in NMR Spectroscopy

Routine analysis of NMR data involves peak picking and integration to get chemical shifts (and couplings) and quantitative information (e.g. number of protons). When the peaks are not well resolved, none of these parameters can be accurately estimated and nonlinear least squares fit (curve fitting or deconvolution) is often performed to extract the desired information. However, deconvolution presents, at least two important difficulties:

Problem #1

In general, line fitting is applied to some limited number of lines in a spectrum as a deconvolution of the full spectrum is very difficult to say the least. This implies a manual intervention of the User (choice of multiplet, specification of the number of lines and of their starting parameters).

Problem #2

Curve fitting requires the definition of an analytical model for the line shape and in particular, NMR lineshaphes have typically been assumed to be either Lorentzian, Gaussian, or a combination of both (e.g. Voight Profile). The problem is that Lorentzian deconvolutions are numerically ill defined because all complete sets of Lorentzian-shaped functions are approximately linearly dependent (in other words, a Lorentzian peak can be approximated very well by several Lorentzian lines). This problem is specially important in 1H-NMR spectra where peaks are really complicated envelopes of many unresolved transitions (for example, in a generic 10 spin system there are 5120 distinct main transitions, but one typically resolves less than 100 peaks).

These problems have been the motivation of the development of a brand new peak analysis algorithm, the so-called GSD (Global Spectral Deconvolution) which has been recently presented by Stan Sykora in a talk he gave at MMCE 2009 conference. In fact, GSD is now fully operative within MestReNova .

If you are interested in GSD and planning to visit ENC, we will be pleased to show you every detail at the user meeting we will keep on Sunday 29th March and at our exhibitor and hospitality suite (you do not need to be a MestReNova User to participate).

DOSY-shift reagents

A well-known procedure to separate resonances that would otherwise overlap in crowded NMR spectra is by adding to the sample some paramagnetic substance, the so-called shift-reagent. The most commonly used shift reagents are complexes of paramagnetic lanthanide ions such as europium(III) for down field shifts and praseodymium(III) for upfield shifts.

A similar approach has been recently reported to resolve mixture components via DOSY-NMR. It’s not very uncommon that in some mixture analyses, 2 or more compounds have diffusion coefficients so similar that they cannot be resolved by any mathematical procedure. For example, the figure below shows a synthetic DOSY spectrum (based on Figure 2 of the original article) of a mixture of two peptides, Trp-Gly and Leu-Met having D values nearly identical

M. E. Zielinski and K. F. Morris proposed in their article to add perdeuterated surfactant micelles to the mixture. Analogous to the chemical offsets induced by shift reagents, the molecules in the mixture under analysis interact differentially with the micelles and thus have different Diffusion values.

Using perdeuterated surfactant micelles to resolve mixture components in diffusion-ordered NMR spectroscopy
Matthew E. Zielinski, Kevin F. Morris, Magnetic Resonance in Chemistry
Volume 47 Issue 1, Pages 53 - 56

Microreview on NMR structural elucidation

A nice short review presenting practical strategies for the elucidation of small organic molecules with NMR spectroscopy has been published a few months ago. I highly recommend it as a reference for organic chemists engaged in structural elucidation tasks.

Eugene E. Kwan, Shaw G. Huang, Structural Elucidation with NMR Spectroscopy: Practical Strategies for Organic Chemists European Journal of Organic Chemistry, 2008 (16), 2671-2688

DOI: 10.1002/ejoc.200700966

Better NMR Processing and Analysis with Mnova 5.3.0

I’m pleased to announce the release of the latest version of Mnova (version 5.3.0), our software for the efficient processing, analysis and prediction of NMR spectra.
With the unveiling of version 5.3.0 come a multitude of enhancements over previous releases . Here I’d just like to highlight some key new features which I’m very proud of as I think they represent a substantial enhancement in the software’s capabilities and, in some cases, new breakthroughs in the world of NMR software:

• Bayesian DOSY Processing
• Whitening algorithm for 2D automatic Phase Correction
• Prediction of X-Nuclides spectra
• Spin Simulation module with support for scalar, dipolar and quadrupolar interactions and its unique classification of transitions feature
• Covariance NMR: Direct, Indirect and Unsymmetrical by means of the Advanced Arithmetic Module
• Multipoint (manual) Baseline Correction

We have also greatly improved some algorithms such as peak picking, automatic noise estimation, resolution booster, integration, etc.
It’s also worth mentioning that most of the new dialog boxes in the program are modeless. For example, now while phase correcting a spectrum, you can zoom in to a particular spectral region without having to quit the phase correction dialog.
There are many other new features in this new version, and many more to come shortly in forthcoming updates. I will be featuring some of them in future posts.
I would like to take this opportunity to congratulate our development team on the fantastic work they have done. Big thanks, guys!

Note. This version will be available for download from our web site Friday 19th

Quantitation of Pharmaceutical Compounds

This is probably something that you weren’t expecting, but I think it’s a fun way to end the week

Intelligent NMR Clipboard

The clipboard is for sure one of the most useful features in any modern Operating System and it is used for short-term data storage and/or data transfer between documents or applications, via copy and paste operations. Any modern application should support clipboard operations and, of course, Mnova is no exception. However, Mnova goes one step further compared to other applications as I will try to show in this post.

Following the same principles as standard Office applications, with Mnova it’s possible to copy any object (e.g. spectra, molecules, etc) into the clipboard and paste it either in Mnova (for example in a different page) or in any other application such as MS Office. The peculiar thing is that once a spectrum has been transferred to the clipboard (via Ctrl+C), it is possible to ‘paste’ it into another spectrum. Two simple examples will illustrate this new feature.

Example #1

You have processed a spectrum and integrated carefully in order to quantify some signals of interest. Next you realize that you also want to integrate a different spectrum but using exactly the same integral regions as those in the first spectrum. There are several ways to do that in Mnova, but a very simple one involves copying the first spectrum into the clipboard and then selecting ‘Paste Integrals’ from the Edit menu. You can paste these integrals either to a single spectrum or to a bunch of selected spectra (or pages).

Example #2

You have customized the graphical properties of a spectrum (e.g. fonts, colors, grid, etc) and you find that you want to rapidly apply the same graphical settings to another spectrum. Once more, this is very easy with the clipboard: copy the first spectrum (Ctrl+C) and then select the target spectrum and issue command ‘Paste NMR Properties’.

NMR Arithmetics

2D NMR spectra are simply 2D matrices (Note: these matrices can be real, complex or hypercomplex, but for the sake of simplicity, we will consider real matrices only) which can be subject to standard matrix algebra operations. I have presented in previous posts how Indirect and Direct Covariance NMR can be applied by proper matrix algebra. These methods are incorporated in Mnova as a dedicated module which also makes the filtering of spurious resonances possible . In order to show you that Covariance NMR actually involves these matrix operations, you can use Mnova’s powerful Arithmetic module which we have recently completed. This module has been designed in such a way that it operates as a simple spectral calculator. You enter the equation which the program parses and produces the expected result. For example, if we have a HSQC-TOCSY spectrum (A), we can enter the Indirect Covariance formula like this:

Where A corresponds to the real part of the original spectrum and TRANS indicates the transpose operation. This operation will produce the (unnormalized) Covariance NMR spectrum, in this case the 13C-13C correlation spectrum. Of course, in order to better approximate the covariance spectrum to the corresponding standard 2D FT counterpart, it’s necessary to calculate the square-root using, once more, matrix algebra. This is again very simple with our arithmetic module by just adding the square root operation (SQRT) into the equation:




This arithmetic module is not restricted to matrix operations within a single spectrum. We can freely combine as many spectra as we want. For instance, if we have, in the one hand a COSY spectrum and in the other a HSQC spectrum, we can combine both in an analogous way so that the indirect covariance NMR spectrum yields a HSQC-COSY 2D spectrum. More about this in a future post …

Removal of artifacts in direct Covariance NMR

I have previously blogged about direct Covariance NMR as a technique to increase the digital resolution of the indirect dimension in 2D homonuclear experiments. As is always the case, there is some price to pay: Covariance NMR introduces some unexpected resonances, in special when the number of t1 increments is small making the covariance exhibit poor statistics (JACS, 2006, 128, 15564–15565). Some of these extra resonances are true spurious peaks whilst others correspond to multistep or RCOSY-type correlations (see MRC, 2008, 46, 997-1002)

The picture below shows the regular 2D FFT spectrum of Strychnine:

And this is its standard direct Covariance counterpart where I have highlighted some of the extra resonances.

While some of these additional resonances can be beneficial because they provide kind of TOCSY correlations, others are just pure artifacts which make the analysis of these experiments unreliable (it’s difficult to know in advance whether a peak is a real correlation or just an artifact).

We have recently incorporated into Mnova a new filter which eliminates these artifacts very efficiently. For example, this is the result obtained after automatic filtering of the Covariance NMR spectrum:

It can be observed that extra peaks have been eliminated without giving up the resolution advantage.

All these new processing capabilities will be available in the next version of Mnova (5.3.0, to be released in a few days), although we have a pre-release candidate available to anyone interested. Just contact me and I’ll be happy to send it out.