The ChemConnector Blog by Antony Williams

I am a week behind on submitting a Chapter for publication in the Second Edition of the Encyclopedia of Spectroscopy. Too much work…not enough time. In the meantime I’ve co-authored a couple of publications with friends from ACD/Labs…one of these addresses an issue discussed on the ChemSpider Blog…a longstanding wish to compare empirical and quantum-mechanical NMR prediction approaches.

A Systematic Approach for the Generation and Verification of Structural Hypotheses.

During the process of molecular structure elucidation, selection of the most probable structural hypothesis may be based on chemical shift prediction. The prediction is carried out either by empirical or quantum-mechanical (QM) methods. When QM methods are used NMR prediction commonly utilizes the GIAO option of the DFT approximation. In this approach the structural hypotheses are expected to be investigated by the scientist. In this article we hope to show that the most rational manner by which to create structural hypotheses is actually by the application of an expert system capable of deducing all potential structures consistent with the experimental spectral data and specifically using 2D NMR data. When an expert system is used the best structure(s) can be distinguished using chemical shift prediction using either incremental or neural net algorithm. The time-consuming quantum-mechanical calculations can then be applied, if necessary, to one or more of the “best” structures to confirm the suggested solution.

The Application of Empirical Methods of NMR Chemical Shift Prediction to Determine Relative Stereochemistry.

The reliable determination of stereostructures contained within chemical structures usually requires utilization of NMR data, chemical derivatization, molecular modeling, quantum-mechanical calculations and, if available, X-ray analysis. In this article we show that the number of stereoisomers which need to be thoroughly verified can be significantly reduced by the application of NMR chemical shift calculation to the full stereoisomer set of possibilities using a fragmental approach based on HOSE codes. The usefulness of suggested method is illustrated using experimental data published for artarborol.

Following on from my presentation regarding text-mining and document mark-up at the ACS meeting in Philly it was interesting to see the announcement about the Chem4Word project from Microsoft. In collaboration with the Unilever School of Informatics at Cambridge university, and specifically working with Peter Murray-Rust and some of his team. From the website announcement it states:  “Microsoft Research is investigating the introduction of chemistry-related features in Microsoft Office Word, including authoring and semantic annotations. Our approach to chemistry authoring will be modeled after the mathematic equation authoring in Word 2007 and will leverage many of the user-interface and XML extensibility options that are provided by Office 2007.

The goal of the Chem4Word project is to enable similar authoring, display, and mining scenarios for chemistry-related information within Office Word. Specifically, we aim to:

• Provide easy authoring of chemical information within Microsoft Office Word 2007 documents
• Allow end-user denotation of inline “chemical zones”
• Render high-quality, print-ready visual depictions of chemical structures
• Store and expose chemical information in a semantically rich manner to support publishing and mining scenarios, for authors, readers, publishers, and other vendors across the broad chemical information community”

This will be very useful in terms of supporting our efforts to enable the publication process for chemists and we will be watching this project with interest and hope to be engaged in early testing if we are invited.

I had the pleasure of representing ARChem Route Designer, a retrosynthetic analysis tool from SimBioSys at the American Chemical Society meeting in Philadelphia last week. While I am not an organic synthetic chemist I have done my fair share of syntheses during my BSc and PhD and actually had a bit of a green thumb when it came to purity and yield. When given the opportunity I ran instead at exciting nuclear spins in large magnets (and enjoyed my choice for many years).

Since I was in the commercial sector for over a decade managing the development of chemistry software I have always had an interest in the development of a retrosynthetic analysis tool. It’s a lot of work and requires a deep understanding of organic chemistry. ARChem results from combining the deep understanding of Peter Johnson with the software development skills of SimBioSys. Peter was not able to make it to the ACS meeting in Philadelphia and, since I have had some experience of ARChem as a result of working with SimBioSys over the past few months, I was asked to step in and present on the product.

A link to the presentation is given here. A paper on ARChem has also been submitted if anyone is interested.