Ryan's Blog on NMR Software

From FID to Structure in 30 Minutes? Investigating the CASE Limiting Step

In yesterday's post I pointed you to an article that has become the most accessed article of all time in the Journal of Cheminformatics, co-authored by representatives of ACD/Labs.

This article is a very comprehensive outline of the different approaches, developments, and successes of the development of CASE (Computer-Assisted Structure Elucidation) systems . I hope you agree that this technology has come a very, very, very long way, to the point that there are many spectroscopists around the world using ACD/Structure Elucidator routinely to identify unknowns in thier labs whether they be natural products, impurities, degradants, metabolites, etc. 

Anna Codina from Pfizer is an example of just one of those users. She has been a long-time user of Structure Elucidator, and one of the very best in the world. She, along with her group, has really stretched the limits and applications of the software and has also been instrumental in the ongoing improvement of this software over the years. 

At SMASH 2009, Anna shared some of her most recent experiences with the software in a presentation entitled, "From FID to Structure in 30 minutes?" This presentation can be accessed here.

For this presentation, she wanted to see whether it was possible to do a full elucidation starting from the raw data, all the way to the solution in less than 30 minutes. She was able to achieve this with several of her in-house Pfizer compounds, and then, for the purposes of this presentation reproduced these findings with compounds she could share in a pubic forum.

In this presentation she goes through 3 such examples.

The most interesting piece for me was her discussion regarding the CASE limiting step in slides 9 and 10.

In an ideal world, we would be talking about completely automated structure elucidation. Of course, we are not quite there yet, but it is still a dream, as Elyashberg et. al refer to it in the J. Chem. Inf. article.

In the meantime, the process generally involves some manually handling of the data. For this process the general principle applies, "Garbage IN- Garbage OUT"

So the quality of data as well as the peak picking of said data is crucial.

The peak picking of multiple spectra is what Anna was referring to as the CASE-limiting step. We have made tremendous strides over the years to simplify this process as much as possible (Check out the demonstration movie here). But the traditional argument seems to still apply for some:

Why would I spend so much time peak picking all my 2D spectra?

By the time I finish picking and grooming the data, I have already solved the structure, so what's the point?

I will try to address these questions in a different post, but in the meantime, what's Anna's answer?

NMR Workbook, and specifically the NMRSync technology that we developed and released late last year. Note, that NMR Workbook is included with ACD/Structure Elucidator.

Anna proclaims that thanks to NMR Workbook, there is no longer a CASE-limiting step. With syncrhonized peak picking which carries through peak picking applied in one spectrum, to all others associated with the sample, the time spent to prepare the data is drastically reduced and is more consistent with the natural workflow.

For those unfamiliar with NMR Workbook and the NMRSync functionality, I introduced it on the blog about a year ago:

http://acdlabs.typepad.com/my_weblog/2008/12/if-all-of-these-spectra-are-from-the-same-compound-why-am-i-handling-them-all-separately.html

If you want to skip right to the demonstration go here:

http://www.acdlabs.com/products/spec_lab/exp_spectra/nmrworkbook/movie/NMRWorkbookFlash.htm

This product has turned out to be immensely popular and has evolved a long way in just one short year. Admittedly, it's probably been the biggest reason I have not been blogging as much over the past year, I have been touring the world showcasing this product, as well as our other solutions.

I hope over the next little while I can dive a bit more into the details of the product.

Stay Tuned.

Most Accessed Article on Journal of Cheminformatics of All Time!

An article co-authored by several ACD/Labs scientists, the Russian Academy of Scientists, and ChemZoo, Inc. has been generating a lot of interest over the past year.

In fact, this article entitled, "Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream" is the most accessed article of all time, on the Journal of Cheminformatics website.

The news gets better. This article is FREE for your reading pleasure! As per the policy of the Journal:

"The Journal of Cheminformatics offers scientists the opportunity to publish their research rapidly in an open access medium that is freely available online to researchers worldwide. All manuscripts submitted to the journal are subject to rigorous peer review. Published material may include electronic supplementary material, such as animations (e.g. graphical chemical structures) or data (e.g. spectra) that can be downloaded for a reader's use.

The Journal of Cheminformatics aims to work closely with operators of open data repositories such as PubChem. Requests for collaboration are welcome; please contact the Editorial Office."

This motivation for this article was to mark the 40 year anniversary of published developments regarding CASE (computer assisted structure elucidation systems).

It a very interesting read that draws from many meaningful publications on CASE over the last 40 years and tracks history to outline some of the approaches that have been considered, implemented, and successful.

Some of the more significant developments such as fuzzy generation, used to deal with the ambiguity of 2D NMR experiments, as well as the determination of relative stereochemistry of large and rigid molecules with many stereocenters are discussed in this article.

I could spend more time talking about this article, but as I've already mentioned, it's FREE and can be accessed here:

http://www.jcheminf.com/content/1/1/3

Enjoy and feel free to leave any comments for the authors, and I will be sure to get them. 

How Do you Report a Proof of Structure by NMR?

For several years many customers have shown me different ways in which they like to report the interpretation of an NMR dataset. While there have certainly been a variety of different approaches, the most common way I have across looks similar to this:

You’ll also find a similar reporting style in journal articles such as the Journal of Natural Products.
When I introduced NMR Workbook on this blog a while back, if you watched the movie, you will likely have found that the NMRSync functionality was the really neat piece: to simultaneously peak pick and assign all multiplets and correlations in a sample dataset.  Certainly, many spectroscopists are already commenting that this is a huge time-saver.

However, the purpose of this post is to also highlight that while saving all that time with synchronous peak picking and assignment, you are also, on the fly, creating a table just like the one above,  that is organizing and reporting all of those assignments you are making in your head and applying to spectrum within the software. We call it the Common Assignment Table, or C.A.T.

What we’ve tried to do with NMR Workbook is mimic the NMR Spectroscopists manual workflow with working with a number of different experiments associated with one sample. However, in addition to doing that, we hope to save you time in the reporting and bookkeeping process. The on-the-fly creation of a Common Assignment Table, along with the already available functionality of multiplet reporting in patent and journal formats, correlation arrows and chemical shift values on the structure, I hope that we have made this reporting process much less tedious and just another reason to embrace spectrum analysis and interpretation in an electronic medium.

How do you report your NMR and proof of structure data?

If All of these Spectra are From the Same Compound, Why am I Handling them all Separately?

Last week, we released a new, updated version of 2D NMR Manager, and have decided to call it ACD/NMR Workbook, as the functionality and possibilities within this software package have significantly changed.

Over the last few months I have been touring the world, presenting about this new product and it's new NMRSync functionality. Please see my presentation below to learn why we did it, what it is, and how it works:

Alternatively, I highly recommend you check out the link here, to watch a demonstration of the software in action.I hope you won't be disappointed in what you see.

Lots more exciting new things in Version 12, and I hope to blog about them over the next little while.

The Balancing Act of False Postives vs. False Negatives

A few months back, I referenced Derek Lowe's excellent blog, "In the Pipeline"

Some of the most interesting entries for me are:

Backtracking, Necessary, and Unnecessary

I Can Has Ugly Molecules?

Oops.

One of the take home messages for me, is when Derek says, "False Negatives and False Positives are waiting in your dataset, depend on it"

I think this is a point that is largely acknowledged in the industry. For example, I think it is pretty obvious to most organizations that there are a significant amount of incorrect structures in their registration database. Some will have a pretty good idea of how much, and others will have no idea.

I think the key point however, is to acknowledge it.

Now this brings me to the topic of the balancing act between false positives and false negatives. If I go back to the application of validation compound registrations with automated NMR verification. This application is one I have blogged about quite a bit over the last year and a half.

The key point to emphasize here, is that this application is NOT replacing the chemists analysis and QC

Chemists are still looking at their data and registering their compounds the normal way. But is an automated validation step necessary after the fact to ensure the quality of the registration database is accurate?

I asked the question from an earlier post, "what is the acceptable limit of false positives and false negatives for automated verification by software for the evaluation of  registered compounds in a library?"

I didn't get any comments on the blog, but I got a few email responses and I have discussed this with some industry people over the last few months. Not surprisingly, the results vary significantly.

Of course everyone would prefer a 0% False Positive Rate, and a 0% False Negative Rate. Yes, in a perfect world that would be great. But it's not going to happen. Not ever. So decisions need to be made about how important this this exercise is, and furthermore what is deemed acceptable?

If we acknowledge that there are incorrect structures in the registration database, then the question is how much, and furthermore, how many can be removed with the use of some automation.

I think the challenge that most organizations face today when evaluating such a system is trying to balance out to sides, false positives vs. false negatives. Why?

My understanding is that if you have a system that is false positive tolerant, well, you are sacrificing the overall quality of your organizations registration database. On the other side of the coin, if you have a system that is false negative tolerant, well, someone needs to look at the data manually to see if this is indeed the right or wrong structure. So there are two forces pulling here. One, is actually knowing that despite your efforts, you are still letting incorrect structures in your database. The other force is knowing that you need a real person's time to spend on manually evaluating a bunch of spectra.

Most spectroscopists I know, do not have a lot of time for this. So of course it would be preferable to have a system that is potentially more false positive tolerant. However, the whole point of implementing the system in the first place was to identify the false positives.

Tough decision...

But at the end of the day, I believe there are systems and applications out there that can help drastically improve the quality of your registration databases.

However, the balancing act between false positives and false negatives is an issue that you are most certainly going to have to juggle.

False Negatives and False Positives are Waiting...

Great post from Derek Lowe from In the Pipeline the other day talking about the dangers of not quality checking those fine-looking starting compounds for your project. Chemistry happens and yes, mistakes do too.

In fact, it appears that Derek has been on a kick as of late referring to personal QC.

I Can Has Ugly Molecules?

Oops.

I thought this would once again be a good opportunity to provide you with a link to a poster Sergey Golotvin presented at ENC 2008 entitled, "Validating the Quality of Large Collections of NMR Spectra Automatically".

Long story short, 15,000 1H NMR Spectra from the Aldrich collection were evaluated in complete automation and the software was able to confirm 88% of the collection as having chemical structures that were consistent with the respective spectra. In addition, 4% were flagged by the software as being inconsistent. A closer, manual look at those 4% revealed that there were indeed some truly wrong structures (or incorrect tautomers) in the collection.

This was evaluating the 1H NMR data only. Using additional 2D experiments, such as HSQC, will likely improve these results.

Just an example of a check an organization can build into their process for additional QC of their registration database for example.

Is it perfect? Absolutely not. There are perhaps a few more false positives in there that the software didn't catch, and of course the software provided some false negatives as well, annoying because presumable someone has to look over them manually only to realize that they were indeed the right structure all along. But at least this doesn't involve manually pining over 15,000 spectra!

We continue to run these datasets, and actually have a consortium consisting of several NMR experts in the industry we call ASCI (Automated Structure Confirmation Initiative) where we are testing and validating this technology in the real pharmaceutical world. Identifying the common areas where false negatives and false positives occur and trying to address them with algorithms.

Will we ever solve all the problems, especially in the world of novel chemistry? Of course not, and for that matter there are some existing problems that appear to be too hard to solve.

But that being said, what is the acceptable limit of false positives and false negatives for automated verification by software for the verification of  registered compounds in a library?

Interested in hearing your thoughts.

Looking for a Great Weekend Read?

In fact, to borrow a phrase from a colleague, this might be the defacto article on Computer Assisted Structure Elucidation (CASE) for the next decade!

This article written by Mikhail Elyashberg, Antony Williams, and Gary Martin spans across two issues of the review journal, Progress in Nuclear Magnetic Resonance Spectroscopy. 

This article entitled, entitled, "Computer-Assisted Structure Verification and Elucidation Tools in NMR-based Structure Elucidation" is available online and you can review a preview of the content at:

http://dx.doi.org/10.1016/j.pnmrs.2007.04.003

This is a very important and comprehensive review of modern expert CASE systems over many years. It includes specific examples of complex natural product structures that have been automatically elucidated using such systems.

I thank the authors of this publication for their contributions in this area, and the efforts they have now put forth to communicate this story to the scientific community.

Please obtain a copy for yourself, I can promise that it is a very informational and intriguing read for those of you who do NMR regularly.

New Blog by Arvin Moser

Those of you who are current users may recognize the name Arvin Moser as he has spent many years as both a Technical Support Specialist and Application Scientist at ACD/Labs.

Arvin has decided to start a blog and share his knowledge and experience about structure elucidation. I think this blog promises to be a very interesting one as Arvin has a wealth of experience in both manual and computer assisted structure elucidation (CASE).

From Arvin's About Page:

My goal is to focus on the science of data interpretation and structure elucidation. I would like to pass on my experiences including what I have learnt from the experts. By sharing these experiences with the scientific community, I think an emerging elucidator can be better equipped with handling anything that comes their way.

Visit Arvin's Blog here.

More on Indirect Covariance

Gary Martin has added a comment to an earlier post I wrote on Indirect Covariance and was kind enough to post an updated publication list on this topic. I have simply copy and pasted his comments in this post to provide more exposure to his list:

Ryan, it has been a while since you updated the publication list on indirect covariance methods, so I thought it appropriate to do that with a post:

F. Zhang and R. Bruschweiler, J. Am. Chem. Soc., 126, 13180 (2004).

K. A. Blinov, N. I. Larin, M. P. Kvasha, A. Moser, A. J. Williams, and G. E. Martin, Magn. Reson. Chem., 43, 999 (2005).

K. A. Blinov, N. I. Larin, A. J. Williams, M. Zell, and G. E. Martin, Magn. Reson. Chem., 44, 107 (2006).

K. A. Blinov, N. I. Larin, A. J. Williams, K. A. Mills, and G. E. Martin, J. Heterocyclic Chem., 43, 163 (2006).

K. A. Blinov, A. J. Williams, B. D. Hilton, P. A. Irish, and G. E. Martin, Magn. Reson. Chem., 45 544 (2007).

W. Schoefberger, V. Smrečki, D. Vikić-Topić, and N. Müller, Magn. Reson. Chem., 45, 583 (2007).

G.E. Martin, P. A. Irish, B. D. Hilton, K. A. Blinov, and A. J. Williams, Magn. Reson. Chem., 45, 624 (2007).

G.E. Martin, B.D. Hilton, P.A. Irish, K.A. Blinov, and A.J. Williams, J. Heterocyclic Chem., 44, 1219 (2007).

G.E. Martin, B.D. Hilton, P.A. Irish, K.A. Blinov, and A.J. Williams, J. Nat. Prod., 70, 1393 (2007).

G.E. Martin, P. A. Irish, B. D. Hilton, K. A. Blinov, and A. J. Williams, Magn. Reson. Chem., 45, 883 (2007).

B. Hu, J.-P. Amourex, and J. Trebose, Solid State Nuclear Magnetic Resonance, 31, 163 (2007).

G.E. Martin, B.D. Hilton, P.A. Irish, K.A. Blinov, and A.J. Williams, J. Nat. Prod., 70, 1966 (2007).

D. A. Snyder, Y. Xu, D. Yang, and R. Bruschweiler, J. Am. Chem. Soc., 129, 14126 (2007).

G.E. Martin, B. D. Hilton, K. A. Blinov, and A. J. Williams, Magn. Reson. Chem., 46, 138 (2008).

G.E. Martin, B.D. Hilton, K. A. Blinov, and A. J. Williams, J. Heterocyclic Chem., 45, in press (2008).

This is the list I currently have. Note that this list does not contain additional papers that pertain to homonuclear covariance processing methods. I don't have that list of publications handy that I can cut and paste into this post.

Thanks Gary!

Fringe Benefits and Knowledge Management

Last week I blogged about Phil Keyes' and Anthony Macherone's applications of NMR software towards automated structure confirmation.

A few months back, I pointed you to Steve Coombes' workflow when working with ACD/Structure Elucidator.

Phil had a very nice section in his presentation about the "fringe benefits" he was able to derive outside of the main goal of the project, "Automated Structure Verification".

Specifically, Phil pointed to a couple of fringe benefits:

1) A spectral database is grown as a result of the automated structure confirmation. This database is heavily searchable and can be used as a resource within the company. Building the database is part of the workflow. No extra work needs to be done.

2) The software provides an assignment starting point. In running the verification algorithm, the software automatically attempts to assign multiplets in the 1D and 2D spectra, provides feedback of the quality of those assignments, along with the ability to easily edit them:

Anthony Macherone also mentioned automatically storing data in a searchable database as an additional benefit to conducting automated structure confirmation in his presentation.

On a different application, Steve Coombes spoke a lot about the additional benefits he receives out of ACD/Structure Elucidator.

In this presentation Steve really stresses the knowledge management angle from Structure Elucidator. Sure, the software can help elucidate the chemical structure of unknowns, but it also supports the ability to store the knowledge you gain from working on your data.

In Steve's opinion this is what separates ACD/Labs software from many other packages out there. The "ability to extract the information and knowledge for further use"

It's not just the ability to build databases with structures and spectra. The key is the ability to assign that data electronically and store it in a searchable database. That's knowledge.

And of course by retaining that knowledge through electronic assignments, you can share that knowledge with the software by training the predictions and improving elucidation and verification performance. 

I'd like to thanks these guys for teaching me a nice "marketing" lesson. It's not always about the main application of the software. Always be on the lookout for "fringe benefits"