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Molecular medicine and genomics technologies are inseparablefor defining new molecular targets. cDNA databases andelementary informatic tools provide instantaneous glimpses ofgene families or tissue-restricted expression patterns as ameans of new target identification. In addition, cDNAmicroarrays and two-dimensional gel electrophoresis unmaskthe expression of genes with unassigned or unexpectedfunctions. Depletion of mRNA with ribozymes or neutralizationof proteins with intracellular antibodies enable investigators toreject or embrace new molecular hypotheses about thedeterminants of disease, pharmacology or toxicology.

AddressesDivision of Molecular Pharmacology and the Department of MedicinalChemistry, The Huntsman Cancer Institute, 546 Chipeta Way,Suite 1100, Salt Lake City, Utah 84108, USA*e-mail: david.jones@hci.utah.edu†e-mail: frank.fitzpatrick@hci.utah.edu

Current Opinion in Chemical Biology 1999, 3:71–76

http://biomednet.com/elecref/1367593100300071

© Elsevier Science Ltd ISSN 1367-5931

AbbreviationsEST expressed sequence tagscFv single-chain antibodyTNF tumor necrosis factorTRAIL TNF-related apoptosis-inducing ligand

IntroductionTwo drug discovery paradigms guide most efforts todefine novel agents that selectively modify disease phe-notypes. The first, more traditional approach relies on invivo or cell-based screening models to identify com-pounds that alter a disease phenotype. This approach hasproven successful in generating many important thera-peutics and offers the strength of using a biologicalresponse to select agents with activities that are likely totranslate into in vivo efficacy. A weakness of this approachis that it often identifies lead compounds with ill-definedmolecular mechanisms of action and toxicities.

A second, more contemporary approach to drug discoveryplaces bias on a single, molecular-based target with a postu-lated rate-limiting role in disease. High-throughput,molecular screens can quickly identify compounds thatspecifically modulate this target. The molecular targetapproach allows development of potent and efficaciousinhibitors or activators through the power of structural biolo-gy and it yields compounds with defined mechanisms ofaction. Compound metabolism, bioavailability, clearance andtarget specificity often confound the promise of thisapproach, however. Furthermore, the molecular targetapproach places a premium on selection of the correct mole-cular target and understanding its role in the disease process.

Molecular target selection is benefiting from the emergingrelationships between human disease and genetics. Effortsto map, sequence and analyze the human genome areaccelerating the pace of disease gene discovery and revo-lutionizing pharmaceutical research [1]. Unfortunately, thecomplexity of the human genome makes selection ofappropriate molecular targets a daunting challenge. In thisreview, we will focus on the application of certain genomictechnologies that have accelerated molecular target discov-ery and aided in the validation of new molecular targets.

Target discovery by expressed sequence tagdatabase miningHigh-throughput DNA sequence analysis has increasedthe rate of discovery of new, biologically relevant targetmolecules. The focus of high-throughput sequencing hasbeen on identifying and tagging each expressed gene inthe human genome. These tags, in some instances, revealthe functional or disease-related importance of newly iden-tified genes. Efforts to obtain expressed sequence tags(ESTs) for each gene in the human genome are proceedingin public and private sectors and are generating massivedatabases for drug discovery purposes [2].

Database mining by homology searchesEarly efforts to extract molecular targets from EST data-bases have relied on two strategies. First, these databasesare extending existing families of target proteins. This isaccomplished by searching the new sequences for struc-tural features that are shared with known target proteins.This approach has been particularly productive in identi-fying new proteins that regulate cell death andinflammatory responses. New findings in this areainclude novel cytokines related to tumor necrosis factor(TNF), a well known inflammatory mediator, and coun-terpart receptors that bind these new TNF-like ligands.TNF-related apoptosis-inducing ligand (TRAIL) [3], aproliferation-inducing ligand (APRIL) [4] and TNF-like(TL-1) [5] are all novel cytokines with activities relatedto TNF family ligands. Database searching using thebasic local sequence alignment tool (BLAST) [6] and theamino acid sequence of TNF as the search template,identified each of these cytokines on the basis of weakstructural similarities. Follow-up studies have confirmedeach of these proteins as TNF-like and have providedpotential explanations for inconsistency regarding therole of TNF in disease. Furthermore, each new cytokineopens the possibility for new pharmacological interven-tion points that modulate immune responses or cell deathpathways in cancer, inflammation, metabolic diseases andneurologic disorders.

The identification of new, TNF-like cytokines is paral-leled by the identification of a counterpart series of

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receptors. Several new receptors in this class have beenculled from EST databases based on sequence similarity tointracellular and extracellular structural signatures of theTNF receptor family [7,8•,9,10••,11••]. For example, threenew receptors capable of binding the death-inducing lig-and TRAIL were discovered by EST database searchesusing specific domains of the TNF-family of receptors assearch queries [8•,10••,11••]. As with the ligands, thesenew receptors and their associated signaling moleculesprovide new pharmacologic targets.

Database mining by differential tissue expressionA second strategy for distilling targets from the data con-tained in large EST collections relies on differential geneexpression. As databases grow in depth and encompassdiverse tissues types, electronic surveys can define genesthat are preferentially expressed in a limited number oftissues or confined to specific diseased tissues. These tis-sue-restricted genes offer the promise of targets withgreater specificity and reduced side effects. The discov-ery of cathepsin K as an osteoclast-specific proteaseexemplifies this approach [12]. Cathepsin K was identi-fied through EST sequencing of a human osteoclastcDNA library. Although first recognized to be structural-ly related to cathepsins, further analysis revealed specificexpression of cathepsin K in osteoclasts [12]. This obser-vation stimulated identification of lead inhibitors [13],determination of the cathepsin K crystal structure [14,15]and the demonstration that mutations in the cathepsin Kgene associated with pycnodysostosis, a diseased charac-terized by the lack of bone matrix protein degradation byosteoclasts [16]. This package of information, originatingfrom taking a genomics approach, has focused drug dis-covery attention on a unique protease with a potentialrole in osteoporosis. As databases grow larger, it is certainthat we will see more examples of target selection basedon specific expression in diseased tissues.

Comprehensive molecular profiling fortarget identificationAlthough EST databases enable identification of newgene family members based on homology and differen-tial tissue expression, most of the information in thesedatabases lies dormant in anticipation of new analysismethods that reveal the function of genes with nonobvi-ous structural relatives. We expect that identification ofnew target families will result from massive, molecularprofiling of cellular components at the protein andmRNA levels. Comprehensive molecular profiles of cellsand tissues will guide our understanding of the molecu-lar basis for disease, target selection and drug mechanismof action. For example, comparison of tumor cellchemotherapeutic responsiveness with specific molecu-lar components of target cells is beginning to revealrelationships that allow new target selection and assign-ment of drug mechanism [17••]. This approach promisesto blend the strengths of cell-based screening with mol-ecular target-based drug discovery. In view of this,technologies that facilitate comprehensive examinationof cellular constituents will have a strong impact on phar-macology and toxicology research.

Comprehensive profiling by quantitative two-dimensionalgel electrophoresisOne technology that promises to advance our selection oftargets and target lead compounds is termed ‘proteomics’[18]. Similar to analyzing the genome, the aim of proteomicsis the comprehensive description of cellular proteins andhow cellular protein expression is altered in diseased states.Protein fingerprints of diseased and normal tissues are gen-erated by fractionating cellular components ontwo-dimensional gels, quantifying the resolved proteins andcomparing the two patterns qualitatively and quantitatively[18]. Specific proteins within the gels can be identified byextraction followed by mass spectroscopy [19,20]. Extension

72 Interaction, assembly and processing

Table 1

Comparison of molecular target validation approaches.

Approach Information needed Information source Selectivity Speed and adaptability Limiting features

Ribozymes Partial cDNA cDNA databases Good (≈20 Fast; adaptable to Synthesis of metabolically≈ 200 bases (e.g. Genbank) candidate many cell types stable ribozymes; half-life

ribozymes) of target protein

Antisense Partial cDNA cDNA databases Poor to good, Fast; adaptable to Synthesis of metabolically ≈ 200 bases (e.g. Genbank) depending upon many cell types stable ribozymes; half-life

sequence of target protein

Aptamers Protein/peptide Direct amino acid Good Slow to moderate; Synthesisor nucleotide sequencing or adaptable to many translation nucleotide translation cell types

Intrabodies (scFv) Protein/peptide Direct amino acid Good Moderate; Antibody engineering andsequencing or adaptable to many expressionnucleotide translation cell types

Knockout and Genomic sequence Scientific literature or Good Slow from beginning Technical proficiency and transgenic proprietary of process to creation facilities

of useful model

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of this approach to the assessment of protein expression intissues under the influence of pharmacological agents isrevealing specific relationships between protein expressionand drug mechanisms. An example of such an approach ispresented by Myer et al [21•]. In this report, the authorsemploy two-dimensional gels to profile each of 60 cellstypes used by the National Cancer Institute (FrederickMaryland, USA) to screen novel anticancer compounds.Their efforts revealed correlations between the pharmaco-logical efficacy of 3,989 compounds and specific proteinexpression profiles. These data suggest that comparison ofprotein fingerprints in responsive cells with fingerprintes innonresponsive cells will reflect drug mechanism and sug-gests potential new molecular target pathways.

Comprehensive protein profiling gains additional supportfrom more focused analyses of drug mechanisms. For exam-ple, Anderson et al. [22] recently used quantitativetwo-dimensional gel electrophoresis to examine the effectsof peroxisome proliferators on mouse liver proteins. Thisstudy compared the effects of five different peroxisome pro-liferators in mice treated for five and 35 days at variousdoses. The results demonstrated that each peroxisome pro-liferator stimulated similar changes in protein expressionpatterns. These findings further support the notion thatcomprehensive protein analyses can categorize drug mecha-nisms and provide insights into the biological responses tospecific drug classes.

Microarray expression analysisAnother technology — expression microarrays — allowscomprehensive analysis of transcriptional expression occur-ring in diseased tissues [23]. This involves quantitativehybridization of a large panel of cloned genes or syntheticoligonucleotides with the total cDNA derived from a par-ticular cell or tissue type. The target gene sequences aredeposited onto glass slides to form microscopic arrays con-sisting of one clone per spot (i.e. coordinate). The amountof DNA present in each spot exceeds the amount of anyone type of cDNA in the probe, such that the quantity ofbound probe is representative of the absolute abundance ofits corresponding message in the cell or tissue from which itwas derived. Therefore, the overall hybridization to themicroarray gives a comprehensive profile of the relativemessage levels for all genes represented in the microarray.Furthermore, a comparison of the message profiles of twodifferent cell or tissue sources (e.g. control versus drug-treated) permits identification of the genetic expressiondifferences between the experimental conditions[24–29,30•,31]. This can be done simply by hybridizing thesame microarray with two probe sets simultaneously.Because a single microarray can currently contain thou-sands of distinct genes, a large portion of the expressedgenome can be surveyed in a single experiment.

A nice example, integrating microarrays with structure-based drug design and combinatorial chemistry, wasrecently presented by Gray et al. [32••]. This study

employed microarrays to examine transcriptional profilesin yeast responding to active-site inhibitors of the cyclin-dependent kinase, Cdc28p. The experiment involvedexamination of genome-wide perturbations in response totwo active, but structurally distinct, compounds. A thirdcompound was also included, which was structurally sim-ilar to one of the active compounds but lacked potentactivity toward the Cdc28p. Array-based profiling of cellstreated with each of the active compounds revealed per-turbation of an overlapping set of genes. In contrast, theinactive compound induced few transcriptional changes.These data present two important points regarding theuse of microarrays for evaluating compounds and targets.First, they demonstrate the likelihood that drugs withcommon mechanisms can be grouped by examining theirexpression profiles. Second, they illustrate how com-pound specificity and toxicity can be linked to, ordissociated from, the intended molecular target.

Target validationStarting with a completely open mind, and using theapproaches outlined above, investigators will be able toexpand their molecular target options significantly. A pro-ject team can often use pragmatic and subjectiveconsiderations to refine the options but the number of tar-gets will remain unmanageable by current discoverystrategies. At most pharmaceutical companies, intramuralcompetition for project resources (e.g. medicinal chemistry,drug metabolism, toxicology support and funding) requirean additional demonstration of technical feasibility and bio-logical significance before advancing. Targeted genedisruption to produce ‘knockout’ or transgenic animal mod-els is the most sophisticated approach available, but it is notnecessarily well aligned with the sense of urgency in drugdiscovery enterprises. A delay of 12–18 months in order tocreate and evaluate a knockout animal would alter the com-petitive landscape unfavorably for many projects.Furthermore, knockout animals have phenotypes thatoften range from embryonically lethal to null. While infor-mative for basic biological purposes, these phenotypes arenot necessarily helpful for decisions about the fate of a drugdevelopment project. Methods that allow modulation ofgenes and proteins on a normal background, preferablyhuman, and in a timely manner, are better for these deci-sions. Among the options are the so-called anti-sensemethods which deplete the cells of mRNA that encode aprotein of interest, and the immunochemical methods thatneutralize a protein of interest. We believe these two tech-nologies will dominate functional genomics and targetvalidation for human disease.

RibozymesRibozymes are catalytically proficient RNA molecules thathybridize to and cleave mRNA. Sequences of ∼200nucleotides are sufficient to design ribozymes that depletecells of a ‘target’ mRNA [33,34]. Successful depletion ofmRNA depends on the metabolic stability of the cell, thecellular delivery and the catalytic efficiency of the ribozyme.

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All three parameters are subject to empirical improvement.Traits intrinsic to the cell and molecular target are less sub-ject to manipulation. Ultimately, success depends ondepletion of the protein transcribed by the ‘target’ mRNA.The rate of protein depletion is a function of proteinhalf-life, independent of the rate of mRNA depletion.

Ribozymes are classified by primary and secondary struc-ture. The simplest ribozymes, termed hammerheadribozymes, contain a catalytic core region with a conservedsequence of bases that cleave RNA and flanking ‘hybridiza-tion arms’ that position the ribozyme next to its RNA targetby complementary base-pairing. Optimization of hammer-head ribozymes for both hybridization and catalysis isdemanding; they must hybridize avidly to orient their cat-alytic core over a cleavage site. If they hybridize too avidly,however, they cannot release the cleavage products.Higher-order structures in mRNA can also limit access ofribozymes to cleavage sites, complicating the formulation ofrules for their design. Zhao and Lemke [35•] recently com-puted the secondary structures for over 100 RNA moleculesthat have been probed with ribozymes or antisense oligonu-cleotides. They correlated the efficacy of the ribozymeswith the predicted secondary structures to provide state-of-the-art rules for choosing hammerhead ribozyme flankingarms and RNA cleavage sites. Ribozymes seldom catalyzemore than a few turnover reactions and single turnovers arecommon on lengthy mRNA species; however, certainoligonucleotides, termed ‘facilitators’, can enhanceribozyme catalysis appreciably [36]. If facilitated turnoveron RNA substrates with >900 bases is adaptable to cellularsystems, it will be a major advance.

Depletion of the proto-oncogene HER-2/neu mRNA exem-plifies the contemporary use of ribozymes in functionalgenomics. Juhl et al. [37•] controlled expression of severalhammerhead ribozymes with a tetracycline-regulated pro-moter. Ribozyme expression diminished the cellularcontent of the HER-2/neu mRNA and protein by >90%.The regulated expression system facilitated the modulationof HER-2/neu expression on tumors in experimental ani-mals prophylactically and therapeutically, providing insightsinto the susceptibility of the tumor at different stages oftumorigenicity and validating a role for HER-2/neu as a rate-limiting component in ovarian cancer growth. Antisensestrategies can only diminish HER-2/neu expression byabout 50% and are experimentally inconclusive [38].

Antibodies and intrabodiesMonoclonal or polyclonal antibodies directed againstmacromolecular epitopes on the exterior of vertebrate cellscan reveal the functional roles of the corresponding macro-molecule. For instance, antibodies that bind to a cellsurface receptor can distort or prevent the interactionbetween that receptor and its cognate ligand. Systemicallyadministered monoclonal antibodies against certain ofthese macromolecules have therapeutic effects [39].Macromolecules in the cell interior are now accessible to

immunochemical neutralization through the use of intra-bodies (intracellular antibodies). Intrabodies aresingle-chain antibodies (scFvs) with a variable domain ofthe heavy chain linked to a variable domain of the lightchain using recombinant methods. In this way, one candeliver and modulate genes that encode and express intra-bodies with high affinity for their cognate antigen atspecific intracellular locations [40]. Cells can be transfectedwith cDNA constructs encoding scFvs. Thus, intrabodiesenable one to investigate cytoplasmic and nuclear determi-nants of disease. Direct neutralization of intracellularmolecular targets is particularly advantageous for proteinswith longer half-lives that are poor candidates for RNAdepletion approaches because of slow protein turnover.

Curiel and colleagues [41•,42,43•] have exemplified the useof intrabodies in their investigations on the determinants ofapoptosis in breast cancer cells. (ErbB-2 is a synonym forthe HER2 protein. Ligand binding to the erbB-2/HER2receptor causes activation of the Ras signaling pathway.) Agene encoding an anti-erbB-2 intracellular scFv diminishedcell surface erbB-2 levels. Induction of apoptosis (pro-grammed cell death) by intracellular expression of theanti-erbB-2 scFv in human breast and ovarian cancer celllines varied according to the cell phenotype. An adenovirusencoding anti-erbB-2 scFv was introduced into a variety ofcancer cell lines and shown to be >95% cytotoxic in theMDA-MB-361 and SK-BR-3 lines, and >60% cytotoxic inthe BT-474 line. The same intrabody had no cytotoxic orantiproliferative effect on the breast cancer cell line MCF-7, and the MDA-MB-231 cell line because anti-erbB-2scFv-mediated apoptosis correlated with the expression ofthe erbB-2 protein. Experiments using intrabodies orribozymes provide similar qualitative conclusions about theoncogenic potential of members of the erb family. The useof intrabodies has enabled investigations showing explicit-ly that the carboxy-terminal cytoplasmic domain of erbB-2is required for apoptosis, however [44].

Investigations with sFv intrabodies directed against Bcl-2,a mitochondrial proto-oncogene that antagonizes apopto-sis, exemplify the use of intrabodies to neutralize a proteinthat may function in a mitochondrial compartment.Expression of sFvs directed against Bcl-2 specificallyreduced the Bcl-2 content in cells, facilitating drug-medi-ated cytotoxicity in Bcl-2-overexpressing tumor cells. Ifone can eventually target gene delivery of intrabodies totumor cells it may provide a novel component for combi-nation therapy with conventional antineoplastic agents.

ConclusionsThe use of genomic technologies, EST databases, quanti-tative two-dimensional gel and microarrays are leading tothe rapid expansion of the list of new therapeutic targets.The expansion so far has been primarily limited to exten-sion of existing target protein families. On the nearhorizon, however, we can predict a tremendous influx oftruly novel targets that will require rapid and convincing

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validation before undertaking a drug discovery effort.Emerging technologies involving ribozymes and intrabod-ies are attractive for filtering molecular target options.

References and recommended readingPapers of particular interest, published within the annual period of review,have been highlighted as:

• of special interest••of outstanding interest

1. Dykes CW: Genes, disease and medicine. Br J Clin Pharmacol1996, 42:683-695.

2. Zweiger G, Scott RW: From expressed sequence tags to‘epigenomics’: an understanding of disease processes. Curr OpinBiotechnol 1997, 8:684-687.

3. Wiley SR, Schooley K, Smolak PJ, Din WS, Huang CP, Nicholl JK,Sutherland GR, Smith TD, Rauch C, Smith CA et al.: Identificationand characterization of a new member of the TNF family thatinduces apoptosis. Immunity 1995, 3:673-682.

4. Hahne M, Kataoka T, Schroter M, Hofmann K, Irmler M, Bodmer JL,Schneider P, Bornand T, Holler N, French LE et al.: APRIL, a newligand of the tumor necrosis factor family, stimulates tumor cellgrowth. J Exp Med 1998, 188:1185-1190.

5. Tan KB, Harrop J, Reddy M, Young P, Terrett J, Emery J, Moore G,Truneh A: Characterization of a novel TNF-like ligand and recentlydescribed TNF ligand and TNF receptor superfamily genes andtheir constitutive and inducible expression in hematopoietic andnon-hematopoietic cells. Gene 1997, 204:35-46.

6. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic localalignment search tool. J Mol Biol 1990, 215:403-410.

7. Chinnaiyan AM, O’Rourke K, Yu GL, Lyons RH, Garg M, Duan DR,Xing L, Gentz R, Ni J, Dixit VM: Signal transduction by DR3, a deathdomain-containing receptor related to TNFR-1 and CD95. Science1996, 274:990-992.

8. Pan G, O’Rourke K, Chinnaiyan AM, Gentz R, Ebner R, Ni J, Dixit VM: • The receptor for the cytotoxic ligand TRAIL. Science 1997,

276:111-113.This work identified a potential receptor for tumor necrosis factor relatedapoptosis-inducing ligand by searching expressed sequence tag databasesfor genes in the tumor necrosis factor receptor family.

9. Kwon BS, Tan KB, Ni J, Oh KO, Lee ZH, Kim KK, Kim YJ, Wang S,Gentz R, Yu GL et al.: A newly identified member of the tumornecrosis factor receptor superfamily with a wide tissuedistribution and involvement in lymphocyte activation. J Biol Chem1997, 272:14272-14276.

10. Pan G, Ni J, Wei YF, Yu G, Gentz R, Dixit VM: An antagonist decoy •• receptor and a death domain-containing receptor for TRAIL.

Science 1997, 277:815-818.This paper identified two new additional receptors for TNF-related apopto-sis-inducing ligand (TRAIL). One of these retained an active ligand bindingsite, but lacked the intracellular death domain. The authors postulated thatthis apoptosis-inactive receptor is a TRAIL antagonist.

11. Sheridan JP, Marsters SA, Pitti RM, Gurney A, Skubatch M, •• Baldwin D, Ramakrishnan L, Gray CL, Baker K, Wood WI et al.:

Control of TRAIL-induced apoptosis by a family of signaling anddecoy receptors. Science 1997, 277:818-821.

As in the counterpart paper [10••], these authors conclude that tumor necro-sis factor related apoptosis-inducing ligand induced apoptosis was regulat-ed by a receptors lacking functional intracellar signaling capabilities.

12. Drake FH, Dodds RA, James IE, Connor JR, Debouck C, Richardson S,Lee–Rykaczewski E, Coleman L, Rieman D, Barthlow R et al.:Cathepsin K, but not cathepsins B, L, or S, is abundantly expressedin human osteoclasts. J Biol Chem 1996, 271:12511-12516.

13. Votta BJ, Levy MA, Badger A, Bradbeer J, Dodds RA, James IE,Thompson S, Bossard MJ, Carr T, Connor JR et al.: Peptide aldehydeinhibitors of cathepsin K inhibit bone resorption both in vitro andin vivo. J Bone Miner Res 1997, 12:1396-406.

14. McGrath ME, Klaus JL, Barnes MG, Bromme D: Crystal structure ofhuman cathepsin K complexed with a potent inhibitor. Nat StructBiol 1997, 4:105-109.

15. Zhao B, Janson CA, Amegadzie BY, D’Alessio K, Griffin C,Hanning CR, Jones C, Kurdyla J, McQueney M, Qiu X et al.: Crystal

structure of human osteoclast cathepsin K complex with E-64.Nat Struct Biol 1997, 4:109-111.

16. Gelb BD, Shi GP, Chapman HA, Desnick RJ: Pycnodysostosis, alysosomal disease caused by cathepsin K deficiency. Science1996, 273:1236-1238.

17. Weinstein JN, Myers TG, O’Connor PM, Friend SH, Fornace AJ Jr, •• Kohn KW, Fojo T, Bates SE, Rubinstein LV, Anderson NL et al.: An

information-intensive approach to the molecular pharmacology ofcancer. Science 1997, 275:343-349.

This paper employees the strategy that molecular markers can help definechemotherapeutic mechanisms and suggest molecular target pathways. Itshows how data-rich approaches can use complete spectrums of informa-tion to impact a target disease.

18. Anderson NL, Anderson NG: Proteome and proteomics: newtechnologies, new concepts, and new words. Electrophoresis1998, 19:1853-1861.

19. Li G, Waltham M, Anderson NL, Unsworth E, Treston A, Weinstein JN:Rapid mass spectrometric identification of proteins from two-dimensional polyacrylamide gels after in gel proteolytic digestion.Electrophoresis 1997, 18:391-402.

20. Scheler C, Lamer S, Pan Z, Li XP, Salnikow J, Jungblut P: Peptidemass fingerprint sequence coverage from differently stainedproteins on two-dimensional electrophoresis patterns by matrixassisted laser desorption/ionization-mass spectrometry (MALDI-MS). Electrophoresis 1998, 19:918-927.

21. Myers TG, Anderson NL, Waltham M, Li G, Buolamwini JK,• Scudiero DA, Paull KD, Sausville EA, Weinstein JN: A protein

expression database for the molecular pharmacology of cancer.Electrophoresis 1997, 18:647-653.

The authors create a comprehesive protein expression database and illus-trate the use of comprehensive protein profiling to correlate drug action withpotential molecular targets.

22. Anderson NL, Esquer–Blasco R, Richardson F, Foxworthy P, Eacho P:The effects of peroxisome proliferators on protein abundances inmouse liver. Toxicol Appl Pharmacol 1996, 137:75-89.

23. Schena M, Heller RA, Theriault TP, Konrad K, Lachenmeier E,Davis RW: Microarrays: biotechnology’s discovery platform forfunctional genomics. Trends Biotechnol 1998, 16:301-306.

24. Schena M, Shalon D, Davis RW, Brown PO: Quantitative monitoringof gene expression patterns with a complementary DNAmicroarray. Science 1995, 270:467-470.

25. DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y,Su YA, Trent JM: Use of a cDNA microarray to analyse geneexpression patterns in human cancer. Nat Genet 1996, 14:457-460.

26. Schena M, Shalon D, Heller R, Chai A, Brown PO, Davis RW: Parallelhuman genome analysis: microarray-based expression monitoringof 1000 genes. Proc Natl Acad Sci USA 1996, 93:10614-10619.

27. Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS,Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL: Expressionmonitoring by hybridization to high-density oligonucleotidearrays. Nat Biotechnol 1996, 14: 1675-1680.

28. Shalon D, Smith SJ, Brown PO: A DNA microarray system foranalyzing complex DNA samples using two-color fluorescentprobe hybridization. Genome Res 1996, 6:639-645.

29. Wodicka L, Dong H, Mittmann M, Ho MH, Lockhart DJ: Genome-wide expression monitoring in Saccharomyces cerevisiae. NatBiotechnol 1997, 15: 1359-1367.

30. Heller RA, Schena M, Chai A, Shalon D, Bedilion T, Gilmore J, • Woolley DE, Davis RW: Discovery and analysis of inflammatory

disease-related genes using cDNA microarrays. Proc Natl AcadSci USA 1997, 94:2150-2155.

This paper describes one of the first uses of microarray profiling to identifycandidate inflammatory genes. Similar strategies are being applied in manydisease states.

31. DeRisi JL, Iyer VR, Brown PO: Exploring the metabolic and geneticcontrol of gene expression on a genomic scale. Science 1997,278:680-686.

32. Gray NS, Wodicka L, Thunnissen AM, Norman TC, Kwon S,•• Espinoza FH, Morgan DO, Barnes G, LeClerc S, Meijer L et al.:

Exploiting chemical libraries, structure, and genomics in thesearch for kinase inhibitors. Science 1998, 281:533-538.

The authors combine structure-based drug design, combinitorial chem-istry and oligonucleotide arrays in the assessment of new kinase

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inhibitors. This is a good preview of how drug discovery strategies evolveto incorporate genomics information.

33. Christoffersen RE, Marr JJ: Ribozymes as human therapeuticagents. J Med Chem 1995, 38:2023-20237.

34. Nadeau JH, Dunn PJ: Genomic strategies for defining anddissecting developmental and physiological pathways. Curr OpinGenet Dev 1998, 8:311-315.

35. Zhao JJ, Lemke G: Rules for ribozymes. Mol Cell Neurosci 1998, • 11:92-97.This paper outlines basic and advanced strategies for ribozymes generation.

36. Jankowsky E, Schwenzer B: Oligonucleotide facilitators enable ahammerhead ribozyme to cleave long RNA substrates withmultiple-turnover activity. Eur J Biochem 1998, 254:129-134.

37. Juhl H, Downing SG, Wellstein A, Czubayko F: HER-2/neu is rate-• limiting for ovarian cancer growth. Conditional depletion of HER-

2/neu by ribozyme targeting. J Biol Chem 1997, 272:29482-29486.This paper Illustrates the use of ribozymes to identify rate-limiting stepsin disease.

38. Vaugh JP, Iglehart JD, Demirdji S, Davis P, Babiss LE, Carruthers MH,Mark JR: Antisense DNA downregulation of the ERBB2 oncogenemeasured by a flow cytometric assay. Proc Natl Acad Sci USA1995, 92:8338-8342.

39. Fan Z, Mendelsohn J: Therapeutic application of anti-growth factorreceptor antibodies. Curr Opin Oncol 1998, 10:67-73.

40. Rondon IJ, Marasco WA: Intracellular antibodies (intrabodies) forgene therapy of infectious diseases. Annu Rev Microbiol 1997,51:257-283.

41. Wright M, Grim J, Deshane J, Kim M, Strong TV, Siegal GP, Curiel DT:• An intracellular anti-erbB-2 single-chain antibody is specifically

cytotoxic to human breast carcinoma cells overexpressing erbB-2.Gene Ther 1997, 4:317-322.

This paper illustrates the potential of intrabodies for validating molecular targets.

42. Grim J, Deshane J, Siegal GP, Alvarez RD, DiFiore P, Curiel DT: Thelevel of erbB2 expression predicts sensitivity to the cytotoxic effectsof an intracellular anti-erbB2 sFv. J Mol Med 1998, 76:451-458.

43. Piche A, Grim J, Rancourt C, Gomez–Navarro J, Reed JC, Curiel DT: • Modulation of Bcl-2 protein levels by an intracellular anti-Bcl-2

single-chain antibody increases drug-induced cytotoxicity in thebreast cancer cell line MCF-7. Cancer Res 1998, 58:2134-2140.

This work targeted an intracellular regulator, Bcl-2, with neutralized intra-bodies to increase drug sensitivity.

44. Grim J, Deshane J, Siegal GP, Alvarez RD, Di Fiore P, Curiel DT:The level of erbB2 expression predicts sensitivity to the cytotoxiceffects of an intracellular anti-erbB2 sFv. J Mol Med 1998,76:451-458.

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