a The History of the NIST/EPAAIIH Mass Spectral Database

Today's Chemist at WorkFebruary 1999Today's Chemist at Work, 1999, 8(2), 45-46, 49-50.Copyright O 1999 by the American Chemical Society.

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system has become theidentification methods.

The History of the NIST/EPA/NlH MassSpectral Database

Stephen R. Heller

Developed in the 1970s, thisbackbone of today's GC/MS

Today, seemingly everyanalytical instrument comes withan attached personal computer(PC) to collect and process data.This occurrence may seem to besuch a given that some peoplethink it was always so. However,those of us who came of age inthe 1960s know it was not.Today, we think little ofextracting a wastewater orsludge environmental sample ora blood, urine, or other biologicalsample; injecting the solvent in agas chromatog raph/massspectrometer or liquidchromatograph/massspectrometer; and having anattached data system tell uswhat analytes are present in theextract and the degree to whichwe can trust the identification.Pretty printouts come withoutbidding from laboratory printers,and data can be transferred to acentral laboratory informationdata system. Computers areeverywhere in the modernlaboratory, and with regard tothe mass spectrometer -arguably the mostinformation-rich source ofanalytical data - laboratoriescould not produce the information needed for environmental andbiological analyses without computers. lt was not always this way.

Although MS has been around for nearly a century, before 1970 suchinstruments generated data of only the most rudimentary type. Mostlaboratories used mass spectrometers as one part of a complexidentification process to determine the chemical structure of naturalproducts, such as alkaloid drug candidates, or to determine whetheran organic synthesis had been carried out properly to generate a

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compound of the correct molecular weight. MS data often werecombined with NMR, lR, and UV spectroscopic data to give insightinto the overall structure of a complex molecule. There were no datasystems, and, actually, none was needed. For structural analysis, itwas necessary only to introduce the sample directly to the massspectrometer and generate a single representative spectrum to bemanually deciphered. First, one had to identify the m/z value of eachpeak by manual counting (28 for nitrogen, 32for oxygen, 149 for aphthalate ester impurity coming from plastic tubing, and so on). Afterthe m/z values for each peak had been labeled, the analyst - typically,a Ph.D. chemist - then identified the molecular ion and each daughterion. Knowledge of how the chemical bonds rearranged on ionizationhopefully allowed the original structure to be written out.

However, when a gas chromatograph was combined with a massspectrometer (Figure 1), analytical chemists were faced withexponentially increasing amounts of data. lt was cumbersome, if notimpossible, to generate a representative spectrum from eachchromatographic peak, much less manually count each m/z peak toidentify the chemical species. Fortunately, the introduction oflaboratory computers effectively coincided with the development ofGC/MS. Computerized GC/MS quickly revolutionized the field of traceorganic analysis and made very significant contributions to researchin medicine, biochemistry, flavors, fragrances, and organicgeochemistry. Thirty years later, GC/MS is still the major analyticaltool for environmental analysis. However, it is not only the automationof individual m/z mass spectral peak identification that makes thecomputer so necessary today; it is also the computer's ability toroutinely identify compounds on the basis of their mass spectrum.

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Figure 1

A 1966 advertisement fromAnalytical Chemistry showinga gas chromatograph/massspectrometer from LKBI nstruments (Rockville, MD;Stockholm, Sweden).

The main advantage of the analytical technique and the database isthat they have substantially increased the capac.ity of.staff to handlemany .e nvi ro n menta I s.amp les and to.accu ratelf identify specificorganic compounds without the need for a Ph.D.'s training in massspectral structure elucidation. Back in the 1960s, few chemists knewMS. When the demand for GC/MS analysis arose, many chemistswith other backgrounds - such as chromatography - were pressedinto service to do environmental analysis. The mass spectraldatabase, along with various search algorithms, became a crucial toolin meeting the demand for trained staff, which was much greater thanthe supply. In a sense, one could say that the mass spectral

This ability to decipher identity dependson the existence of a database massspectra from a wide range ofcompounds; the most universaldatabase is that maintained by theNational Institute of Standards andTechnology (NIST). Since thedevelopment of this database in the1970s. underthe National Institutes ofHealth (NlH) and the U.S.Environmental Protection Agency(EPA), the NIST mass spectraldatabase has become an essential toolin environmental monitoring forregulatory compliance.

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database and search system has taken the chemist out of analyticalchemistry.

A World-Class ProductIt would be nice to look back now and see how a careful study wasdone on what needed to be done and was followed bv awell-implemented plan. Certainly, the success of the database andthe many problems it has solved would support such a story.Unfortunately, the true history is not so clean and neat. However, it isa nice story about many people in different organizations who workedtogether to produce a world-class product used today in thousands ofanalytical chemistry labs around the world.

In the 1960s, Scotty Pratt, the NIH Division of Computer Researchand Technology (DCRT) director, was looking for projects to prove toNIH scientists that computers were more than calculators. He realizedearly on that for any such project to be a success, it needed acomputer group willing to provide the necessary hardware andsoftware support, an NIH lab willing to explore something new, and ascientist willing to work full-time as a computer chemist. Having tiredof synthesizing nitrogen and sulfur compounds, I was fortunate tohave the opportunity to work at DCRT as a senior staff fellow (theU.S. government title for a postdoc at that time) and to work withHenry Fales at NIH's National Heart, Lung, and Blood Institute. Faleswas (and is) an eminent organic chemist and mass spectrogcopist,and he realized the potential benefit of automating the mass spectraldata analysis process. He was willing to test any computer-basedanalysis tool developed. He asked one of his lab chemists, Bill Milne(now editor of the American Chemical Society's Journal of ChemicalInformation and Computer Sciences), to work with us in testing thesystem.

The first task was to find a database. Fales convinced Klaus Biemannat the Massachusetts Institute of Technology to let NIH use histape-based database of some 8000 spectra that he had beencollecting as part of his research during the past decade. Biemannand students (Harry Hertz, now at NIST, and Ron Hites, now atIndiana University) had been developing batch-search software as amass spec data analysis tool. The user manually input the m/zvalues, and the closely matching compounds were printed out.

ln 1970-71, with the assistance of Richard Feldmann, a very talentedDCRT programmer, we wrote a time-sharing program in theFORTRAN programming language on a Digital EquipmentCorporation PDP-10 minicomputer to search the database providedby Biemann. The first of several papers to describe the database andsearch system was published in Analytical Chemistry in 1972, butthat was only the beginning.

When Fales traveled, lectured, or welcomed chemists from all overthe world to NlH, he would take a few minutes during his lecture orlab tour to show off the software, called the NIH Mass SpectralSearch System (MSSS). One day, Fales called to tell me that a few ofhis scientific friends and colleagues (more like a few dozen) liked theMSSS. He asked whether it was possible to find a way to let themuse it from their home laboratories. Accomplishing such a task wasnot as easy then as it is now. There was no Internet, no computer

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and a microfiche device.

networks - only 1 10-baud modems connecting an ASR teletypeprinter to a single mainframe computer. Nonetheless, the MSSS wasopened to the public as an experimental project via a time-sharearrangement with the NIH computer center. Originally, I wrote asimple manual, but as users of the search system and databaseasked for more features - which eventually grew to some two dozenoptions - | wrote a formal 59-page manual that NIH printed inNovember 1972.

Graphics on MicroficheIn the early 1970s, disk space was expensive, and few computergraphics were available. Thus, among the options added to theMSSS search program was one that linked search results to acomputer-driven microfiche reader that contained the identifiedcompound's full spectrum, with all the peaks nicely plotted. Figure 2shows the author with an old teletype, a telephone 1 10-baud acousticcoupler, and a microfiche device.

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As the popularity of the systemincreased and more peopledialed into the DCRT PDP-10.NIH administrators decidedthat the DCRT could notcontinue to provide MSSScomputer support. In"stead, acollaboration was establishedwith the Mass SpectrometryData Centre (MSDC) inAldermaston, England. TheMSDC also had a massspectral database, and the twosystems were combined.Subsequently, the MSDC

transferred its system to a commercial (General Electric) time-sharingsystem that was available throughout Europe and the United States.Soon, hundreds of chemists worldwide were using the database andthe search system. The MSSS later moved to the Automatic DataProcessing (ADP)-Cyphernet system and became part of a largerNIH-EPA Chemical lnformation Systems (ClS) database.

In 1973, ljoined EPA at its headquarters in Washington, DC. Shortlybefore then, EPA had been given a congressional mandate todevelop routine monitoring methods for environmental analysis.Working primarily with EPA scientists Bill Budde in Cincinnati, OH,and John McGuire in Athens, GA, we developed the MSSS and itsattendant mass spectral database as a mainstay of EPA'senvironmental analysis program, much of which was based onGC/MS analysis.

Because EPA had a large and practical need for mass spectralsearch and analysis, considerable funds were provided to increasethe size and quality of the database. The primary EPA database andsoftware work was contracted to Fein-Marquart Associates. Theirchief technologist, Dave Martinsen, began evaluating the quality ofthe spectra, and added Chemical Abstract Service (CAS) RegistryNumbers to each chemical in the MS database.

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ln addition, Cornell University professor Fred Mclafferty, undercontract to EPA, developed a Quality Index computer program for thedatabase, thereby permitting an analyst to judge how well unknownqpectra matched those in the MSSS database. Through the work ofFein-Marquart, McLafferty, and others, by 1975 morelhan 30,000spectra were in the database. In 1978, the National Bureau ofStandards (NBS) agreed to print a five-volume collection of some25,500 different mass spectra, along with the chemical names,synonyms, and chemical structures. More than 1500 copies of thesebooks were sold.

NIST Given ResponsibilityAlthough the driving force behind the rapid expansion and use of thedatabase was EPA, the information was finding other research uses,including assisting in organic chemistry structure elucidation problemsand toxicology research. For this reason, in 1980, EPA transferredresponsibility for database maintenance to NBS (which later becameNIST). NBS had recently been authorized, through a uniquecongressional authority to copyright databases, to disseminateinformation such as that in the MSSS. Under the leadership of DaveLide and Lew Gevantman of NIST's Office of Standard ReferenceData (OSRD), the database was expanded.

By the late 1980s, EPA's Budde had turned over all furtherenvironmental database development activities to Sharon Lias andSteve Stein at NIST. Using income from the lease of the database(more than 25,000 copies have been distributed since 19BB), NISTenlarged the database and improved its quality by manuallyexamining each mass spectrum. ln addition, Stein developed aPC-based search algorithm. Contracts to obtain complete massspectra for each compound, as opposed to spectra from the scientificliterature which often contained only a few peaks because of journalspace limitations were undertaken by NIST. Many spectra of "useful"compounds, such as those commercially available and those ofmedicinal chemical interest, were added to the database. Thesecompounds came from such sources as the Toxic SubstancesControlAct (TSCA) Inventory, EPA Monitoring Methods Index(EMMI), the U.S. Pharmacopoeia/United States Adopted Names(USP/U.S.A.N.), the Chemical Rubber Company's Handbook of Dataof Organic Compounds (HODOC), and the European Index oflndustrial Chemical Substances (El N ECS).

ln the area of database searching, the original Biemann searchalgorithm using the two largest peaks in every 14 m/z interval alsohas evolved. Incos, a 1970s software company, had developed asearch system that was incorporated into the Finnigan data systemsat the beginning of that decade. The 1990s Stein/NIST system hastaken the Incos approach and expanded it. In the middle to late1970s, Cornell's Mclafferty developed the Probability BasedMatching (PBM) program, which improved on searching forcompounds in mixtures. PBM is still used today by several massspectrometer manufacturers. Mclafferty also developed theSelf-Training and Interpretation System (STIRS) program, whichattempted to elucidate chemical structures for compounds not foundin the NIST database. Today, the Stein software does substructureanalysis and is able to perform a highly evolved library searchalgorithm with sophisticated probability calculations to show that a

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The-History of the NIST/EPAA{IH Mass Spectral Database

given library identification is correct. An example of the Stein/NISTmass spectrum interpreter program is presented in Figure 3.

Figure 3 o

An example of the Stein/NIST mass spectrum interpreter program

The main effort in the database work in the 1990s has been to build alarge high-quality database. Some areas of current and future workon the database and associated search software being undertaken atNIST include acquiring additional spectra of useful compounds,adding retention index information, developing fragmentationsoftware to identify peaks that are consistent with fragmentationrules, improving chemical nomenclature, adding CAS RegistryNumbers to database entries that currently lack this information, andimproving the internal administrative evaluation and editing program.

The latest release of the database, NlST98, stands at 107,886compounds - almost 100,000 more than the original databaseprovided by Biemann almost 30 years ago. Today's NIST softwareallows a user to display and print not only a compound's massspectra but also its chemical structure. The effort to create thisdatabase took a team of mass spectrometrists about 10 years toevaluate the entire database by hand. Including additional spectra forsome compounds, there are a total of 129,136 spectra (out of amaster database of 175,510 spectra, which include some duplicatesand some low-quality spectra), all of which have been criticallyevaluated. Information about how to obtain the current version of thisdatabase is available at the NIST home page ( www.nist.gov/srd/).

An Ongoing Endeavorln summary, throughout three decades, the NIST-EPA-NlH massspectral database has been a very useful tool for problem solving,almost anywhere mass spectrometers are used, and it will becomeeven more so in the future. The Bieman database has become anongoing, not a static, endeavor. lt gives the ordinary chemist,untrained in spectral problem solving, the ability to solve today's

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questions - whether they involve environmental analysis or theanalysis of compounds from combinatorial chemistry studies.

Stephen R. Heller is past chair of the IUPAC Committee onChemical Databases and the software review editor for ACS's Journalof Chemical lnformation and Computer Sciences. He is a consultantat Pool, Heller & Milne and can be reached by e-mail atsteve@phm.com

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