<div><div>Dear Dr Williams;<br><br>Thank you for your expert input; I must
confess
to only looking at a few CASE examples from google scholar. We
do<br> however reference your recent work in Journal of
Cheminformatics, in our paper on information extraction
from<br>documents.<br><br>There was an excellent presentation given by Jiawei
Han at PSU last Friday, I
foresee great application of his algorithms <br>to CASE. Your expert advice
would also be
greatly valued, I will indeed be in touch and cc Peter et al,
there<br> are a
number of folks here at PSU who will no doubt be interested as well.
<br><br>many thanks again;<br><br>-bill brouwer<br>(PSU
Chemistry)<br><br><br><br>On Mon, Jun 15, 2009 08:25 AM, <b>Antony Williams
<WilliamsA@rsc.org></b> wrote:<br><blockquote id="quoted_response"
style="border-left: 1px solid rgb(0, 0, 0); padding-left: 3px; padding-right:
0px; margin-left: 3px; margin-right: 0px;">
<pre>
Dr Brouwer,
Things have come a long way since the 1996 article you reference. For a modern
review regarding automated structure elucidation I refer you to:
M. E. Elyashberg, A. J. Williams, and G. E. Martin. Computer-Assisted
Structure Verification and Elucidation Tools In NMR-Based Structure
Elucidation. Review article. Progress in NMR Spectroscopy (2007)
10.1016/j.pnmrs.2007.04.003
As one of the authors of this work feel free to contact me at the email address
below and I can provide some guidance regarding where automated structure
elucidation is today. There are commercial products on the market today and
Christoph Steinbeck from EBI has his own work going on in this area. Peter
knows him well I believe. Chris also has Open SOurce NMR prediction tools
online at NMRSHiftDB that you might be interested in using.
As the product manager for a CASE system (Computer Assisted Structure
Elucidation) for many years I can say that the challenge is not easy but
that there has been a lot of progress made over the years. SOme other papers
that might interest you (excuse the numbers...snipped out of my CV).
On ChemSpider we will be integrating Chris Steinbeck's NMR shift prediction
technology in the near future we hope. Best wishes.
44. G.E. Martin, C.E. Hadden, D.J. Russell, B.D. Kaluzny, J.E. Guido, W.K.
Duholke, B.A. Stiemsma, T.J. Thamann, R.C. Crouch, K.A. Blinov, M.E.
Elyashberg, E.R. Martirosian, S.G. Molodtsov, A.J. Williams, P.L. Schiff, Jr.,
Identification of Degradants of a Complex Alkaloid Using NMR Cryoprobe
Technology and ACD/Structure Elucidator, J. Heterocyclic Chem. 39, 1241
(2002)
45. M.E. Elyashberg, K.A. Blinov, A.J. Williams, E.R. Martirosian, S.G.
Molodtsov, Application of a New Expert System for the Structure Elucidation of
Natural Products from the 1D and 2D NMR Data, J. Nat. Prod., 65, 693
(2002)
50. K. A. Blinov, D. Carlson, M. E. Elyashberg, G. E. Martin, E. R.
Martirosian, S. Molodtsov, and A. J. Williams, Computer-Assisted Structure
Elucidation of Natural Products with Limited 2D NMR Data: Applications of the
StrucEluc System, Magn. Reson. Chem., 41, 359-372 (2003).
51. G. E. Martin, D. J. Russell, K. A. Blinov, M. E. Elyashberg and A. J.
Williams, Applications and Advances in Cryogenic NMR Probes &
Computer-Assisted Structure Elucidation. Ann. Magn. Reson., 2, 1-31
(2003)
52. A.J. Williams. Recent Advances in NMR Prediction and Automated Structure
Elucidation Software. Current Opinion in Drug Discovery & Development, 3,
298 (2003)
53. K. Blinov, M. Elyashberg, E. R. Martirosian, S. G. Molodtsov, A. J.
Williams, M. H. M. Sharaf, P. L. Schiff, Jr., R. C. Crouch, G. E. Martin, C. E.
Hadden, and J. E. Guido, “Quindolinocryptotackieine: The Elucidation of a
Novel Indoloquinoline Alkaloid Structure through the Use of Computer-Assisted
Structure Elucidation and 2D-NMR,” Magn. Reson. Chem., 41, 577-584
(2003).
54. M. E. Elyashberg, K. A. Blinov, E. R. Martirosian, S. G. Molodtsov, A. J.
Williams, and G. E. Martin, Automated Structure Elucidation – The Benefits of
a Symbiotic Relationship between the Spectroscopist and the Expert System, J.
Heterocyclic Chem., 40, 1017-1029 (2003).
2004
55. M. E. Elyashberg, K. A. Blinov, A. J. Williams, S. G. Molodtsov, G. E.
Martin, and E. R. Martirosian, Structure Elucidator: A Versatile Expert System
for Molecular Structure Elucidation from 1D and 2D NMR Data and Molecular
Fragments, J. Chem. Inf. Comput. Sci. 44, 771-792 (2004).
57. S. G. Molodtsov, M. E. Elyashberg, K. A. Blinov, A. J. Williams, E. E.
Martirosian, G. E. Martin, and B. Lefebvre. Structure Elucidation from 2D NMR
Spectra Using the StrucEluc Expert System: Detection and Removal of
Contradictions in the Data. J. Chem. Inf. Comp. Sci., 44, 1737-1751
(2004)
58. G. J. Sharman, I. C. Jones, M. P. Parnell, M. C. Willis, M. F. Mahon, D. V.
Carlson, A. J. Williams, M. E. Elyashberg, K. A. Blinov, S. G. Molodtsov.
Automated structure elucidation of two products in a reaction of an
-unsaturated pyruvate. Magn. Reson. Chem. 42, 567 (2004)
2005
60. Y. D. Smurnyy, M. E. Elyashberg, K. A. Blinov, B. A. Lefebvre, G. E.
Martin, and A. J. Williams, Computer-Aided Determination of Relative
Stereochemistry and 3D Models of Complex Organic Molecules from 2D NMR Spectra,
Tetrahedron, 61, 9980-9989 (2005).
63. S. S. Golotvin, E. Vodopianov, B. A. Lefebvre, A. J. Williams, and T. D.
Spitzer. Automated structure verification based on 1H NMR prediction. Magn.
Reson. Chem., 44, 524 (2006)
66. M. E. Elyashberg, K. A. Blinov, A. J. Williams, S. G. Molodtsov, and G. E.
Martin, Are Deterministic Expert Systems for Computer-Assisted Structure
Elucidation Obsolete? J. Chem. Inf. Model. 46, 1643-1656 (2006).
70. M. E. Elyashberg, K. A. Blinov, S. G. Molodtsov, A. J. Williams, and G. E.
Martin, Fuzzy Structure Generation: An Efficient New Tool for Computer-Aided
Structure Elucidation (CASE), J. Chem. Inf. Model., 47, 1053-1066
(2007). 10.1021/ci600528g
76. S. S. Golotvin, E. Vodopianov, R. Pol, B. A. Lefebvre, A. J. Williams, R.
D. Rutkowske and T. D. Spitzer, Automated structure verification based on a
combination of 1D 1H NMR and 2D 1H–13C HSQC spectra, Magn. Reson. Chem. 2007,
45, 803–813
90. M. E. Elyashberg, A. J. Williams, D. C. Lankin, G. E. Martin, J. Porco, W.
F. Reynolds, and C. Singleton, Applying Computer-Assisted Structure Elucidation
Algorithms for the Purpose of Structure Validation – Revising the NMR
Assignments of Hexacyclinol, J. Nat. Prod., 71, 581-588 (2008).
Antony Williams, VP Strategic Development
ChemSpider, Royal Society of Chemistry
US Office: 904 Tamaras Circle, Wake Forest, NC-27587
Phone: +1 (919) 201-1516
Fax: +1 (919) 300-5321
Email: antony.williams@chemspider.com
URL: www.chemspider.com
Blog: http://www.chemspider.com/blog
Twitter: http://twitter.com/ChemSpiderman
Skype: tony27587
LinkedIn: http://www.linkedin.com/in/antonywilliams
________________________________
From: orechem-bounces@openarchives.org [orechem-bounces@openarchives.org] On
Behalf Of WILLIAM J BROUWER [wjb19@psu.edu]
Sent: Friday, June 12, 2009 2:40 PM
To: Peter Murray-Rust
Cc: orechem@openarchives.org; Geoffrey Fox; Nick Day
Subject: [Orechem] Re: High-throughput semantic computation in OREChem
no worries Peter, understood. If anybody needs anything from me beyond what's
in our paper & at the wiki already ->
http://services.nsdl.org/trac/oreChem/wiki/ChemistryDataExtraction, do let me
know...
I'm going to start taking a look at the AI/search possibilities of our fitted
spectra database then -> http://pubs.acs.org/doi/abs/10.1021/ci950092p
cheers,
bill
On Fri, Jun 12, 2009 11:14 AM, Peter Murray-Rust <pm286@cam.ac.uk> wrote:
Great - that's exciting Bill and I am sure that it will be invaluable for
assignment. However I am focusssing on what we can integrate today. The
integration problems are not trivial and the more that the components - or the
sites - are modularised the faster progress we shall
It's important to be pragmatic at this stage - there are things we can do now
and things that are research. We should do both but we must make sure that the
infrastructure continues in a straight line. I detailed what we could do at
present (some as rough proof of concept) that could fit into a linear
workflow. We must make sure that the research efforts in the pipeline I
indicated are small as the integration of itself will still be challenging.
So I am propopsing that we should ask:
* what can we do by Friday 19?
* what can we do by the start of August?
* what can we do in the rest of the project.
Each part depends on the previous one:
* Mark needs a few papers from Lee/Prasenjit which have good PDF chemistry
* PMR needs a few molecules and spectra in SVG
* Marlon needs a few CML molecules and the NMREye workflow.
I agree that Mark's work on general PDF parsing is exciting but we need a
stream of molecules for the later stages.
I am also going to suggest that we try to arrange weekly telcons to review
progress. The problem of a pipeline/workflow is that all bits have to be
delivering.
P.
On Fri, Jun 12, 2009 at 3:47 PM, WILLIAM J BROUWER <wjb19@psu.edu> wrote:
cool peter...
I would also add that there's some mileage in substructure & similarity
search on spectra. Han gave a great talk this morning, there is strong
application of his graph mining work to building up complicated spectra on the
basis of simpler (sub)spectra...
-bill
On Fri, Jun 12, 2009 10:31 AM, Peter Murray-Rust <pm286@cam.ac.uk> wrote:
This is to review the subprojects that the computational geeks in OREChem have
put together over the last few days. (a) is long term, (b)
is immediate
(a) The general goal is to compute NMR spectra for all new published
compounds and compare them with spectra. This is a new approach "robot
refereeing of chemistry publications" and any differences suggest errors
or new chemistry. This is long term (months) and consists of the
following (as we have put on the wiki):
* PSU-Lee/Prasenjit retrieve chemistry-rich docs from publisher sites (ask
for forgiveness policy) and segment the papers into text+non-text
(tables, diagrams). This passes to:
* Mark - Soton extracts molecules and spectra out of this and converts them to
SVG. The short-term goal is to get this working by the end of next week in a
pragmatic form. (we do not mind if recall is poor as long as we get a few
SVGs as we need to develop the machine-learning and/or heuristics and find out
what unknown horrors we have to deal with.
Bitmaps are rejected at this stage
* PMR- cambridge develops heuristics to interpret (i) molecules
(ii) spectra (C13 and H1). These might later be
crowdsourced. The output is CML molecules and spectra. It is unlikely we have
assignments
* PSU - Bill+Karl. Analyse spectra with peak-fitting.
* IU - Marlon. (independently) molecules are passed to IU in CML and
put into the NMREye workflow for computing peaks (below). IU run this
automatically and return results in CML
(b) To get IU up to speed we shall start immediately on simple
molecules from Pubchem. This involves just Cambridge and IU.
* The NMREye workflow has been developed and tested and should work on simple
organic compounds. It consists of the following:
- convert PubchemXML2CML (already available in JUMBO)
- convert CML to Gaussian input. We have an XSLT script, but could convert
this to Java in an hour.
- in parallel - create RDF metadata for provenance to this point (as
this does not survive the Gaussian run)
... submit and run job ... (IU) ... and collect results
- convert LOG file to CML (JUMBOMarker, effectively done)
- convert CML to RDF (JUMBO). Add GaussianOWL dictionary in RDF
upload RDFs into reopository/tripleStore
In (b) we would expect to get 10,000 - 100,000 small molecules from
Pubchem of up to, say , 15 first row atoms. These already have 3D coordinates
(I am ignoring conformers at this stage). The process should be
automatic. Jobs take from 0.1 seconds to 1 day (probably) as they
scale with N^4.
P.
I will try to send this to the Wiki
--
Peter Murray-Rust
Reader in Molecular Informatics
Unilever Centre, Dep. Of Chemistry
University of Cambridge
CB2 1EW, UK
+44-1223-763069
--
Peter Murray-Rust
Reader in Molecular Informatics
Unilever Centre, Dep. Of Chemistry
University of Cambridge
CB2 1EW, UK
+44-1223-763069
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</blockquote>
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