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JournalofProteom e Research • Vol. 1, No. 3, 2002
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EDITOR-IN-CHIEF
William S. Hancock Thermo Finnigan 390 Robinwood Lane Hillsborough, CA 94010 650-348-0204; fax: 650-348-0204
[email protected] ASSOCIATE EDITORS
Joshua LaBaer Harvard Medical School
György Marko-Varga AstraZeneca and Lund University EDITORIAL ADVISORY BOARD
Ruedi H. Aebersold Institute for Systems Biology
Leigh Anderson Large Scale Biology
Ettore Appella National Cancer Institute
Ronald Beavis ProteoMetrics, Inc.
Walter Blackstock Cellzome
Brian Chait The Rockefeller University
Patrick L. Coleman 3M
Catherine Fenselau University of Maryland
Daniel Figeys MDS Proteomics
Stanley Hefta Bristol-Myers Squibb
Donald F. Hunt University of Virginia
Barry L. Karger Northeastern University
Daniel C. Liebler University of Arizona
Matthias Mann University of Southern Denmark
Stephen A. Martin Applied Biosystems
Jeremy Nicholson Imperial College of London
J. Michael Ramsey Oak Ridge National Laboratory
Pier Giorgio Righetti University of Verona
John T. Stults Genentech, Inc.
The Importance of Databases ecently the investment community has soured on the profitability of biological databases, particularly those based on the recent sequencing of the human genome. There have been several well-known companies with high stock prices that suffered greatly in the 2001 market meltdown. These companies have announced their intention to move away from database development and into drug discovery. While clearly there are significant problems with both technical and business aspects of biological databases, we can only hope that research investment in this field continues. Fulfillment of the promise of proteomics depends on it. Databases not only refer to the characterization or profiling of a large number of proteins in a given sample, but also relate this information to individual samples or biological events. These samples, of course, can be generated in several different ways. For example, research can be performed on a series of timed samples collected after a cell line has been stimulated by a change in environment. Another way is to collect samples from a set of animal models. For the development of new pharmaceuticals, however, the measurement of differences in protein expression or modification in individual patients is of primary importance. Such measurements could allow for the early detection of disease or monitor the progress of an individual during therapeutic intervention. In these latter studies, individual data is clearly of more value than pooled samples. However, looking at a series of individual samples brings the challenge of sensitivity. Meaningful research is likely to collect a large number of individual samples with very small amounts of proteins. The analysis of these materials must be made on well-preserved or fresh samples so that protein degradation is minimized. Sample handling must be minimized and well optimized so that losses and artifacts are avoided. In addition, proteomic analysis needs to be correlated with individual patient records and the corresponding genotypic information. As several leaders in the field have noted, many studies have been compromised by poor collection of samples or by inappropriate storage of material. Even the mundane challenge of preparing replicates is fraught with technical difficulties, as freezing and rethawing of samples often produces significant changes. This is very difficult research. Currently, the pharmaceutical industry is awash in potential lead compounds and drug targets, and so there is little value in a proteomics research group coming up with hundreds or even thousands of new potential targetsi.e., novel or modified proteins even if there appears to be some association of these proteins with disease processes. What the pharmaceutical industry needs is a handful of quality leads, well documented in relation to histology/pathology information, and well correlated with individual disease monitoring. A short list of well-validated protein markers would be of key significance in screening lead compounds and designing biological interventions such as antibody-based therapeutics. What is the alternative if the scientific community does not come up with quality databases? The use of animal models has value but is fraught with a number of difficulties, particularly as none of the model systems have been able to accurately predict clinical trials. The only real predictor of the success of a new therapeutic is the human patient, but there are many ethical issues behind concepts such as clinical experiments, even in the case of terminal disease. So the challenge of providing quality proteomic databases is of key importance. Let us hope that as companies redirect their efforts toward drug discovery, development of databases does not atrophy. Progress in the understanding of human health may well depend on them.
R
Peter Wagner Zyomyx
Keith Williams Proteome Systems
John R.Yates, III The Scripps Research Institute © 2002 American Chemical Society
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