PROTEIN MARKERS FOR PHARMACEUTICALS AND RELATED TOXICITY

Abstract: Protein markers of toxicity and efficacy for drugs are determined. For example, methods and reagents are disclosed for determining whether a patient receiving an antilipemic drug, especially a statin or HMGCoA reductase inhibiting drug, is experiencing drug efficacy and/or toxicity. Individual susceptibility is also determined prior to treatment. Also, drug discovery of similar acting candidates and their likelihood of being toxic or effective is determined by analysis of all proteins in a sample simultaneously by 2-dimensional gel elecrotphoresis.

Description: PROTEIN MARKERS FOR PHARMACEUTICALS AND RELATED TOXICITY FIELD OF THE INVENTION The present invention relates to the discovery of lipid regulating drugs, and to determination of efficacy and toxicity. BACKGROUND OF THE INVENTION A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but all other copyright rights whatsoever are otherwise reserved. High levels of low-density lipoprotein (LDL) cholesterol and low levels of high-density lipoprotein (HDL) cholesterol are both considered risk factors for coronary heart disease. In addition LDL cholesterol is involved in atherogenesis. Cholesterol is synthesized predominantly in the liver and transported to various body tissues by lipoproteins in blood plasma. Therapeutic interventions to normalize elevated plasma LDL cholesterol levels in hypercholesterolemic individuals are in widespread use. A number of proteins are involved in lipoprotein cholesterol regulation. Considerable variation between individuals regarding such metabolism exists. For example, Tangier disease results from a mutation in the gene ABC1 and causes marked low HDL-cholesterol levels. A number of polymorphisms of that gene have been noted in control subjects. HDL apolipoproteins appear to be actively transported by a pathway controlled by ABC1. ABC1 is induced by cAMP and is a mediator in the conversion of apoAI and HDL-precursor to mature HDL. Likewise, secreted phospholipases, e.g. secretory PLA2 and endothelial lipase, hydrolyze HDL phospholipids, thereby influencing HDL metabolism and function. SR-BI (Cla-1) mediates cellular uptake of cholesteryl ester from HDL. ApoAI and apoE can remove cholesterol and phospholipid as well. Cholesteryl ester transfer protein (CETP) activity and lipoprotein lipase also affect HDL by reverse cholesterol transport. CETP exchanges cholesteryl ester and triglycerides between HDL and apoB, leading to a decrease in HDL-C. Thus, an individual's distribution of proteins affects cholesterol regulation. HMG-CoA reductase inhibitors (the best known class of which are called "statins") have been available since 1987 and have become one of the most widely prescribed families of drugs. Statins lower LDL-C, apo B and triglycerides and raise HDL-C and apoAI. HMG-CoA reductase is an essential regulatory enzyme in the biosynthetic pathway for cholesterol and catalyzes the conversion of HMG-CoA to mevalonate. The inhibition of this enzyme results in both the down-regulation of cholesterol synthesis and the up-regulation of hepatic high affinity receptors for low density lipoproteins (LDL) followed by increased catabolism of LDL cholesterol. Otherwise, HMG-CoA reductase inhibitors do not affect to a significant extent the levels and/or composition of the other major lipoprotein fractions. Sirtori, Pharmacological Research. 22:555-563 (1990). Current commercially sold statin-class drugs include: lovastatin (Mevacor®), cerivastatin (Baycol ® ), fluvastatin (Lescol ® ), pravastatin sodium (Pravacol ® ), atorvastatin (Lipitor ) and simvastatin (Zocor"). Lovastatin and others are administered as prodrugs in their lactone forms and undergo first-pass metabolism, hepatic sequestration and hydrolysis to the beta-hydroxy acid active form. Slater et al., Drugs, 36:72-82 (1988). Thus, the drugs appear in much higher concentrations in the liver than in non-target organs and the liver is the primary site of both action and side effects. Long term use of the drugs results in marked increases in serum transaminases and biochemical abnormalities of liver function in a small (-1.9%) subset of patients who received HMG-CoA reductase inhibitors and other lipid-lowering agents. See the Physician's Desk Reference. Toxicity testing in early drug development has changed little in decades. Toxicity is predominantly evaluated in laboratory animals using hematological, clinical chemical and histological parameters as indicators of organ or tissue damage. Statin drugs are known to alter the protein pattern of various cells as detectable by 2-dimensional gel electrophoresis (2DGE). Anderson et al., Electrophoresis, 12:907-930 (1991), Gromov et al., Electrophoresis, 17(11):1728-1733 (1996), Maltese et al., Journal of Biological Chemistry 265(29):17883-17890 (1990) and Patterson et al, Journal of Biological Chemistry 270(16): 9429-9436 (1995). Other drugs are known for antilipemic effects. Niacin and fibric acid derivatives raise HDL, with niacin particularly raising HDL-C while reducing LDL-C. Other cholesterol-lowering drugs include: probucol (Lorelco ® ), gemfibrozil (Lopid ® ), niacin/nicotinic acid (Nicolar ® ), clofibrate (Atromid-S ® ), fenofibrate (Tricor ® ), colestipol (Colestid ® ) and cholestyramine (Questran ® ). In addition, a change in diet, particularly intake of cholesterol and fats, has an effect on the blood lipid concentration. Most cellular proteins are post-translationally modified under normal physiological conditions. Over 200 amino acid modifications are known to occur in vivo. Krishna et al., Protein Structure - A Practical Approach, 2 nd ed. Creighton, ed. Oxford Univ. Press, 91-116 (1997). Given such variation, it is understandable that functional genomics has significant limitations in determining physiological changes. Tissue proteome analysis has previously been applied to investigate the molecular effects of drugs and to obtain information on action. Arce et al, Life Sci., 63: 2243-50 (1998), Anderson et al., Toxicol. Pathol. 1996, 24, 72-6, Anderson et al, Toxicol. Appl. Pharmacol. 1996, 137, 75-89, Steiner et al., Biochem. Biophys. Res. Commun. 1996, 218, 777-82, Aicher et al, Electrophoresis 1998, 19, 1998-2003, Myers et al., Chem. Res. Toxicol. 1995, 8, 403-13, Cunningham et al., Toxicol. Appl. Pharmacol. 1995, 131, 216-23 and Steiner et al, Biochem. Pharmacol. 51(3):253-258 (1996). Long term application of various anti-lipemic drugs is associated with hepatotoxicity in rodent studies. Proteomics typically uses two-dimensional gel electrophoresis as a separation technique and mass spectrometry as a protein identification technique though other advanced separation and detection systems may be used. The use of radioactive substrates to trace metabolites acted on by various enzymes is a well-known traditional biochemical technique. Such has been used to determine enzyme activity and to follow the molecule throughout metabolism and distribution in an animal. SUMMARY OF THE INVENTION The object of the present invention is to determine the degree of efficacy and potential toxicity resulting from administration of a drug by detection and/or quantification of at least one protein marker indicative of drug toxicity or efficacy in a biological sample. It is a further object of the present invention to determine protein markers and other proteins that are potential targets for drugs and to enable screening of compounds against such proteins. Proteins strongly regulated by a drug may serve as alternative drug targets. It is another object of the present invention to determine other components in the metabolic pathway than the one targeted by the effective agent, toxic or therapeutic intervention by detection of at least one protein marker. It is yet another object of the present invention to determine efficacy and toxicity protein markers for drugs and establish as protein markers themselves, both known proteins and newly discovered proteins. It is still another object of the present invention to screen for new classes of agents having similar biological effects by detecting the effects on at least one protein marker, particularly the effects on IPP isomerase. It is another further object of the present invention to screen for new agents that will ameliorate the effects of toxicity by detecting the effects on at least one protein marker of toxicity. It is yet another further object of the present invention to compare protein markers of candidate drugs to protein markers for known drugs to determine comparative efficacy, toxicity and whether similar mechanisms of action are involved. It is a still another object of the present invention to determine whether a subject will be susceptible to either the toxic and/or effective properties of a particular drug by measurement of susceptibility markers. Other aspects of the invention include the protein markers themselves, proteomic displays containing abnormal abundance of the protein markers, and their many uses for research and monitoring patients. Also combinations of plural proteins constituting a combination marker may be used as other protein markers. The present invention accomplishes this goal by determining which proteins are present in abnormal abundance in patients undergoing drug therapy and deducing the mechanism of action from the perturbed metabolic pathway. Initially, all readily detectable proteins are measured; but after the markers are determined, an assay for the markers alone is sufficient. Both efficacy and toxicity determination assays may be made. In addition, monitoring of either patients on the drug or laboratory animals in drug discovery or pre-clinical testing protocols may utilize such an assay. Sets of perturbed protein markers provide a proteomic pattern or "signature" indicating relative toxicity and/or efficacy. DESCRIPTION OF THE PREFERRED EMBODIMENTS The term "drugs" refer to chemicals that lower blood lipids, particularly LDL or cholesterol. The agents are useful as pharmaceuticals and include the "statin" family, HMGCoA reductase inhibitors, fibric acid derivatives, bile acid sequestrants, niacin etc. While these drugs act by a variety of different mechanisms, the beneficial effects of drugs using these agents is well documented. These agents may be in purified form, as a natural product or extract. The term "isolated", when referring to a protein, means a chemical composition that is essentially free of other cellular components, particularly most other proteins. The term "purified" refers to a state where the relative concentration of a protein is significantly higher than a composition where the protein is not purified. Purity and homogeneity are typically determined using analytical techniques such as polyacrylamide gel electrophoresis or high performance liquid chromatography. Generally, a purified or isolated protein will comprise more than 80% of all macromolecular species present in the preparation. Preferably, the protein is purified to greater than 90% of all macromolecular species present. More preferably, the protein is purified to greater than 95% and most preferably the protein is purified to essential homogeneity or wherein other macromolecular species are not significantly detected by conventional techniques. The term "protein" is intended to also encompass derivatized molecules such as glycoproteins and lipoproteins as well as lower molecular weight polypeptides. The term "protein marker" is a detectable "protein" which has its concentration, abundance, derivatization status, activity or other level altered in a statistically significant way when a host producing the protein marker has been exposed to an agent. Many protein markers are agent specific. The term "agent" includes any chemical, physical, biological, electrical or radiation treatment or condition which is capable of modifying the abundance of a protein marker. Disease states and infection also may be considered an agent. Agents also may be inert or substances believed to be inert with the invention establishing the inertness such as proving pharmaceutically acceptable carriers are truly acceptable. A "level" refers to detectable abundance, derivatization status, protein variant presence, concentration, chemical or biological activity. An "altered level" refers to a change in the "level" when compared to a different sample or state. The "level" may be an actual measured amount of a protein but generally is a relative "level" of a protein compared to the "level" of other proteins or standards, which may be run in the same batch. "Small molecules" are low molecular weight, preferably organic molecules, which are recognizable by receptors. Typically, small molecules are specific binding components for proteins. The terms "binding component", "ligand" or "receptor" may be any of a large number of different molecules, and the terms can be used interchangeably. The term "ligands" refers to chemical components in a sample that will specifically bind to receptors. A ligand is typically a protein or peptide but may include small molecules, particularly those acting as a hapten. For example, when detecting proteins in a sample by immunoassay, the proteins are the ligands. The term "receptors" refers to chemical components in a reagent, which have an affinity for and are capable of binding to ligands. A receptor is typically a protein or peptide but may include small molecules. For example, an antibody molecule acts as a receptor. The term "bind" includes any physical attachment or close association, which may be permanent or temporary. Generally, an interaction of hydrogen bonding, hydrophobic forces, van der Waals forces etc., facilitates physical attachment between the ligand molecule of interest and the receptor. The "binding" interaction may be brief as in the situation where binding causes a chemical reaction to occur. This is typical when the binding component is an enzyme and the analyte is a substrate for the enzyme. Reactions resulting from contact between the binding component and the analyte are within the definition of binding for the purposes of the present invention. Binding is preferably specific. The binding may be reversible, particularly under different conditions. The term "bound to" or "associated with" refers to a tight coupling of the two components mentioned. The nature of the binding may be a chemical coupling through a linker moiety or a physical binding or packaging such as in a macromolecular complex. Likewise all of the components of a cell are "associated with" or "bound to" the cell. "Labels" include a large number of directly or indirectly detectable substances bound to another compound and are known per se in the immunoassay and hybridization assay fields. Examples include radioactive, fluorescent, enzyme, chemiluminescent, hapten, spin labels, a solid phase, particles etc. Labels include indirect labels, which are detectable in the presence of another added reagent, such as a receptor bound to a biotin label and added avidin or streptavidin, labeled or subsequently labeled with labeled biotin simultaneously or later. In situations where a chemical label is not used in an assay, alternative methods may be used such as agglutination or precipitation of the ligand/receptor complex, detecting molecular weight changes between complexed and uncomplexed ligands and receptors, optical changes to a surface (e.g., in the Biacore ® device) and other changes in properties between bound and unbound ligands or receptors. An "array" or "microarray" (depending on size) generally is a solid phase containing a plurality of different ligands or receptors immobilized thereto at predetermined locations. By contacting ligands under binding conditions to the microarray, one can determine ligand or receptor identity or at least part of the ligand structure based on location on the microarray. While not a single solid phase, a series of many different solid phases (or other labeling structure) each with a unique receptor immobilized thereon is considered a microarray. Each solid phase has unique detectable differences allowing one to determine the ligand or receptor immobilized thereon. An array may contain different receptors in physically separate locations even when not bound to a solid phase, for example a multiwelled plate. The term "disease-related marker or portions thereof as used herein refers to particular compounds or complexes that are found in abnormal abundance in a disease. The term "biological sample" includes tissues, fluids, solids (preferably suspensable), extracts and fractions that contain proteins. These protein samples are from cells or fluids originating from an organism. The biological sample may be taken directly from the organism or tissue being affected or indirectly from the organism such as from serum or urine. In the present invention, the host generally is a plant or animal, preferably a mammal. The term "proteome" is a large number of proteins expressed in a biological sample, representing the total, relevant portion or preferably all detectable proteins by a particular teclmique or combination of techniques. "Proteome analysis" generally is the simultaneous measurement of at least 100 proteins, generally at least a few hundred proteins, preferably over 1000 and most preferably plural thousands of detectable proteins from a sample when separated by various techniques. In the present invention, the proteome analysis involves two-dimensional gel electrophoresis. While that is the generally accepted technique for analyzing proteomes, other techniques are acceptable and may be used for the present invention if large numbers of quantitatively detectable proteins are generated. Another example is discussed in PCT Ser. No. US00/31516. The term "target" refers to any protein perturbed by a disease, developmental stage or after drug treatment. Frequently, a target refers to a drug development target that is capable of binding or being altered by, an agent. Such drug development targets are suitable for screening candidate compounds either using direct binding assays or by observing a perturbed level, thereby indicating the candidate compound is appropriate for the next level of drug screening. The terms "host", "subject", "individual", and "tissue of interest" include both simple (viruses and unicellular organisms) and complex organisms (plants and animals) and tissues, whether normal or abnormal, and various fractions (including subcellular fractions) of each of those. The instant invention provides for the first time, a means to determine the relationship between a drug and tissue (or cell) proteins of an organism. By comparing the proteomes of samples before and after exposure to a compound, such as a drug or candidate drug, as well as comparing the proteomes among members of a population, the instant invention reveals those proteins and polypeptides that vary and thus are influenced by the presence of the compound. Those markers can identify the particular target of the compound, identify a diagnostic marker, reveal relationships between and among proteins, identify target protein(s) associated with the altered or pathologic state and so on. The instant invention can be applied to the use of any known compound, such as a drug and to candidate drugs, particularly when proteins diagnostic of a particular malady are known, and so on. Thus, if one or more proteins are diagnostic of a disease, candidate drugs can be screened by monitoring the reaction of those diagnostic protein(s) on exposure to the candidate drugs. The instant invention can be used as a screening assay to ascertain the response of an individual to a range of drugs. For example, if a physician has a range of drugs available for treating a condition, the effect of the various drugs on the proteome can be assessed. Should certain proteins be associated with an undesirable side effect, drugs that do not enhance or minimize presence of those undesirable proteins can be selected. That exercise may result in a patient experiencing fewer side effects. Identifying markers associated with certain side effects can yield a library of diagnostic markers associated with one or more side effects. That library can be used to compare various drugs. Such a library of proteins provides a baseline of what are acceptable side effects. The invention can be used to determine changes in a proteome on exposure to undesirable chemicals, such as toxins, mutagens, carcinogens, noxious compounds, poisons and so on. The diagnostic proteins can provide a baseline of tolerable side effects, identify targets of those undesirable chemicals and so on. Because the instant invention provides for an automated and computerized method for storing the data, a number of defining groupings and comparisons can be made by the appropriate data manipulation. Thus, for example, similar compounds that comprise a class can be compared. The data manipulation can include isolating particular side effects and protein(s) associated therewith for screening any drugs or candidate drugs for any correlation with that particular side effect. Similarly, a particular protein or subset of proteins may be associated with a desirable trait or result from exposure to one or more drugs targeted for a particular indication. A wholly unrelated drug designated for a different indication may be found to effect one or more proteins associated with those beneficial traits or results. That could yield a new use of that wholly unrelated known compound. For example, statins have been found to have associations with proteins diagnostic of exposure to cyclosporin A, a known immunosuppressant used to combat graft rejection. Thus, statins are effective in preventing organ rejection following transplantation. Accordingly, the materials and methods of the invention provide a method of screening candidate drugs for desirable and undesirable effects. A rate-limiting enzyme in the cholesterol synthesis pathway is HMG-CoA reductase that is competitively inhibited by the statin class of drugs. While such drugs are effective, liver cells alter metabolism in an attempt to compensate for that disruption. Such secondary drug effects may contribute to the pharmacological action, e.g. the up-regulation of LDL receptors to remove LDL from the blood, but often are related to adverse reactions. By elucidating the biochemical pathways and networks affected upstream and particularly downstream from the blockade of HMG-CoA reductase, methods for better drug design and/or ways for compensating for toxic reactions may be found. Other drugs may function by different mechanisms of action and toxicity may be entirely different due to different chemical natures. However, because the therapeutic effects themselves can cause certain secondary drug effects, similarities can occur although the mechanism of action and chemical structure differ dramatically. While applicants do not wish to be bound by any particular theory or mechanism of action, the following metabolism is believed to account for many of the effects of certain lipid lowering drugs and to provide a logical basis for the present invention. For easy understanding of the present invention, certain theories of action have been presented. While the expected reactions are suggested, applicants do not wish to be bound by any implication that these are the only possible markers or that a marker may be indicative of multiple events. It is likely that many proteins have plural functions and that the initial function found, for which the protein is usually named, may not be the true function of the protein in nature. Conversely, many genes produce multiple protein variants, differing by glycosylation, splicing, post-translational cleavage etc. Each "protein variant" may have plural uses as well. That is demonstrated clearly by the data below where one version of a protein serves as a protein marker whereas a different version of the protein does not serve as a protein marker. The proteins may be of the same origin or encoded by different genes. An example of such is in HMG CoA synthetase or a cleavage or breakdown product thereof. As such, changes in the mRNA abundance would not necessarily reflect the marker utility of the protein. Thus, actual measurement of the protein abundance per se is needed. Proteomics is uniquely useful in detecting and quantifying post-translational modifications. Not only does functional genomics (typically the measurement of different levels of mRNA) provide little information on RNA splicing, but also it is devoid of post-translational modification to produce protein variants. Measuring mRNA merely suggests a possible rate of synthesis, not a rate or level of protein maturation and not a level of the protein per se present. Proteomics permits detection of very small chemical changes that change the peptide isoelectric point or mass, and hence the spot location on a 2-dimensional gel due to charge and mass differences. Given the large number of different post-translational modifications and their known changes as a consequence of disease or chemical/pharmacological exposure, the present invention considers changes in abundance of different protein "variants" to be equally important as overall amounts of the protein (all variants). Various chromatographic, sedimentation, electrophoretic and other methods can fractionate protein mixtures and have been used to separate thousands of proteins. However, most proteins in a typical biological sample have not been isolated or identified, as such techniques are labor intensive, time consuming and most proteins are considered simply not to be of interest. The techniques separate the protein mixtures according to only one property and thus the separation may not be complete. To enhance purification and separation, multiple different separation techniques are used in series. However, in order to do so, each fraction from the first separation technique must be fractionated separately by a second technique. To avoid problems with handling so many fractions, applicants used two-dimensional gel electrophoresis (2DGE) that seamlessly merges two different techniques. The process involves subjecting the sample proteins to isoelectric focusing in a pH gradient, preferably in an elongated gel to hold the proteins in a separated state. The elongated gel then is placed on a gel sheet and subjected to denaturing SDS gel electrophoresis across the elongated gel through the gel sheet. Isoelectric focusing separates the proteins based on charge. Denaturing gel electrophoresis separates protein molecules based on the rate of passage through the gel, a measurement that corresponds to molecule size and is an indication of molecular weight. The two-dimensional gels are prepared according to the methods in the examples. Other suitable protocols are known per se and found in several publications by the inventors and others. If so desired, the proteins can be deglycosylated prior to 2DGE separation. That generally reduces the number of protein spots on the gel as some gene expression products have multiple glycosylations with each version of the product. In certain applications, that may be desirable. Patients with high serum cholesterol, particularly those with high LDL levels compared to HDL levels may be evaluated based on levels and patterns of proteins from a biological sample. The likelihood of success and the absence of toxicity in treating the condition with a drug also may be determined by proteome analysis of a biological sample from the patient after a short period of time on therapy, before toxicity becomes evident by gross symptoms or by increased serum transaminases and perhaps even before efficacy is confirmed by repeated blood cholesterol assays. Therapy also may be tailored to the individual before beginning therapy by performing proteome analysis on a patient sample and comparing the protein pattern to protein patterns from a standardized normal and/or standardized patients known to respond to various antilipemic drugs and/or standardized patients who experience toxicity from statin or HMGCoA reductase inhibiting drugs. Once a protein marker of interest has been identified, it may be produced by a number of different methods, many of which are unrelated to the manner by which the protein was identified. Likewise, once protein markers are determined by proteome analysis, different assays for routine use in test animals or humans are preferred. Immunoassays and other binding assays are preferred particularly for protein marker quantification but when the marker is an enzyme, enzyme activity may be measured alone or in addition to binding assays. The level of expression of a protein may be determined using well-known techniques such as immunofluorescence, ELIS A, Western blot analysis and similar techniques. Two-dimensional electrophoretic gels need not be used as long as the technique measures a predetermined set of proteins of interest. An extract for analysis of protein by any well-known technique is made by conventional methods from the tissue, fluid sample or fractions thereof. An antibody that specifically detects the selected protein, and which is conjugated to a known label, is prepared by methods known to those of skill in the art. Any agent that produces similar changes in protein markers as demonstrated by the test drugs has potential use as a pharmaceutical. The dosages, formulations and routes of administration are determinable readily by those skilled in the art depending on the chemical structure of the agent. For example, the dosage employed would be sufficient to alter protein marker abundance to approximately the same extent as the alteration to the same marker caused by one or more known antilipemic pharmaceuticals such as those listed in the examples below. Conventionally, to determine the effect of a compound on a cell or biological system, the compound is added and a single or few end products are measured. While such an approach is acceptable to optimize production of a single product from the system (e.g. penicillin production from culture), that approach will not determine how a toxin affects the entire metabolism of a cell. The present invention permits one to determine global effects of a compound on the cell by measuring a protein involved in or using a reagent containing receptors for, many or all enzymes in a metabolic pathway. One also may decipher the metabolic pathway by using plural agents to ease the process. One need not determine an entire metabolic pathway to hypothesize at the remaining components. Furthermore, for drug development, the entire metabolic pathway need not be determined. For many uses, it is sufficient to know that metabolic pathway performance is reflected by the measurement of a single or relative small number of proteins in an otherwise large number of actual proteins in the metabolic pathway. Because some metabolic pathways cross other metabolic pathways, a single metabolite may be degraded or synthesized into multiple products. Therefore, it is desirable to know as much of the cellular metabolism as possible to determine global changes. To elucidate further the metabolic pathway and effects of a drug on metabolism, the present invention also prepares an antisense compound to a previously determined protein marker for administration to cells. When the gene is known, the antisense compound to the gene or the mRNA may be prepared by any of the conventional techniques for preparing antisense compounds such as those of Vander Krol et al., Biotechniques 6:958 (1988), U.S. Patent Nos. 6,066,625, 6,063,626, 5,925,346, 5,910,444 and 5,859,342. Also, the antisense compound-treated cells may be exposed to the drug or used as unexposed controls. By measuring the various proteins of the proteome, one can determine the effects of a particular drug on metabolism that has been altered by having a particular protein removed. In the situation of lipid lowering drugs, one can measure the effects on serum cholesterol of the antisense compound alone to confirm that the protein marker is a good drug target. By comparing the effects on serum cholesterol of the antisense compound and a particular drug, one can determine whether combination therapy is appropriate. Instead of measuring serum cholesterol, one may measure the levels of other proteins, particular the other protein markers, in the proteome. Determination of differential abundance between two samples is also helpful in identifying disease specific markers, in plant and animal breeding, and in a large number of analytical and diagnostic determinations; While the emphasis of the experiments below is on finding and evaluating drugs for human use, the present invention is also useful for agricultural, horticultural, companion animals, and wild plants and animals. In the present invention, high cholesterol diet is a proxy for a disease state as it is difficult to obtain both high and low serum cholesterol in the same population of inbred rats. Protein markers that are elevated in either the high cholesterol group or the drug treatment group but depressed in the other are particularly confirmed markers for the disorder. The same is true for other physiological conditions, particularly disease. In such a situation, protein markers from diseased and treated individuals are appropriate comparisons. More preferred are biological samples from diseased individuals taken before pharmaceutical treatment and matched samples from the same individuals after pharmaceutical treatment. Such a method is also more preferred for non-inbred populations such as those of humans. The examples in the present invention used inbred rats of the same age to reduce genetic variability so that what is seen is the result from the agent. For some purposes, it is ideal to use the same subject to reduce further biological variability. For tests in humans, twins especially are preferred for the same reasons. Other test organisms are useful as well, as the present invention is equally applicable to plants, microorganisms, livestock and wildlife (zoos and in nature). By knowing how an organism responds to a compound, for example, better pesticides can be developed. The metabolism of an organism can be engineered to obtain desirable traits, such as animals producing lower amounts of cholesterol in milk, meat and eggs. Alternatively, the organism may be altered genetically to respond to various chemicals for the same or different purposes. The present invention can be used to alter the metabolism of an organism to respond with greater efficacy or less toxicity to a given compound. That is particularly useful for treating common diseases with chemicals that are otherwise not effective or overly toxic. The present invention may be used as a proxy for traditional toxicity testing of new compounds for non-drug use such as cosmetics, pesticides (herbicides, fungicides, insecticides, rodenticides, antimicrobials etc.), food and feed additives, fertilizers, agricultural and consumer products (for contact with an organism), waste effluent from industrial processes etc. Protein abundance and gene expression regulation following exposure to various biologically active agents are complementary to the information typically obtained by conventional tissue slide-based toxicity scoring. By comparing proteins expressed following treatment with a given agent to untreated controls, one can identify changes in the biochemical pathways via observed alterations in a protein marker or sets of markers that may be related to the efficacy or toxicity of an agent. The assumption is that changes in protein abundance precede morphological changes and that the proteins are efficacy and toxicity markers that may be used alone in high throughput screening assays to test large numbers of agents. The present invention is particularly useful in drug development in preclinical testing, proof-of-concept studies, phase I, II and III clinical testing. Even drug candidates, which have previously failed testing, may be "rescued" by proteomic analysis to stratify the patient population or to provide an indication that analogs of the drug candidate may overcome the reason for trial failure. Furthermore, enormous time and effort may be saved by avoiding animal and human testing of candidates that proteomic analysis can indicate is doomed to failure. A method for quantifying the level of the proteins of the present invention is the abundance or ratio compared to a normal or untreated control, although other comparable methods are within the scope of the invention. The level of protein also may be determined absolutely or as a ratio compared to various components in the biological sample being tested. While the examples in the present invention use a liver sample as the source of proteins, other tissues and body fluids may be used. Sources of proteins may be distant from the actual organ tissues being affected, such as measuring protein markers in serum even when the tissue being affected is the lung. Representative fluids include blood, serum, urine, saliva, feces, sputum, CSF etc. Depending on the protein sample source, different protein markers may be developed and used. Likewise, the baseline abundance of various protein markers may differ between rat or other animal, and human sources of proteins. Homologous proteins from different species are preferred protein markers for both efficacy and toxicity. While it is very useful to know the quantities of various protein ligands in a sample, in some situations, it may be useful to compare the sample to a standard or to measure differences in concentrations of various ligands from another sample. For example, disease-specific markers may be deduced by determining which proteins are in higher or lower concentrations in a sample from diseased tissue as compared to normal tissue. The differential may be determined by using the present invention to determine the quantities in a normal and a diseased sample. The results from each experiment are compared to generate the differential results. A particular protein level may be compared to total protein levels in the sample if a concentration control is desired. That will generate a coefficient to compare to standards so that a control need not be run side by side every time. Total protein may be determined by measuring total protein being loaded on the gel, but preferably, compared to all other spots in the 2DE gel. Alternatively, a particular protein may be compared to a standard protein in the sample (natural internal control) or added to the sample (added internal control). Proteomic techniques were used to study proteome changes in biological samples from antilipemic drug-treated rats. The drugs were found to induce a complex pattern or "signature" of alterations in rat liver proteins, some of which were related to cholesterol synthesis but many were affecting other pathways and endpoints. The pattern then is usable for studying the biological effects of an agent or for high throughput screening of other agents for the degree of efficacy or toxicity. Numerous changes in the proteome of liver cells exposed to drugs such as statin or other HMG-CoA-inhibiting drugs were detected by the present invention. Several represent protein markers for efficacy and/or toxicity. Protein markers are also potential targets for other agents aimed at producing similar biological effects as well as targets for agents ameliorating the efficacy and/or toxicity action. Also changes in metabolism and further understanding of metabolic pathways are noted. For example, in lovastatin treatment, the markers for metabolic change include those in: I) cholesterol metabolism, 2) carbohydrate metabolism, 3) membrane trafficking, 4) cytoskeletal structure, 5) calcium homeostasis, 6) nucleotide metabolism, 7) amino acid metabolism, 8) protease inliibitors, 9) cell signaling, 10) apoptosis, I I) biotransformation and 12) pheromone binding protein. Specific markers in each are described below. Some also may serve as new drug targets for biological effects relating to decreasing cholesterol synthesis or removal from blood. Additionally, the markers may be drug targets for ameliorating toxicity from the drug or other antilipemic drugs and potentially from any other compound producing toxicity by the same pathway. The protein spots affected by the treatment were identified and grouped based on cellular function and participation in biochemical and signaling pathways. Several interesting observations were made. 1) Inhibition of the enzyme, HMG-CoA reductase, by inhibitors such as statins provoked a regulatory response associated with the strong induction of the enzymes cytosolic HMG-CoA synthase and IPP-isomerase. The fact that one enzyme is located down-stream and one is up-stream of the blockage demonstrates attempts to maintain normal cholesterol synthesis rates. 2) The liver response was not restricted to the previous therapeutically targeted pathway but involved other key enzymes regulating energy metabolism such as fructose- 1,6-bisphosphatase and glucose-6-phosphate 1-dehydrogenase. 3) Several protein changes (e.g. senescence marker protein-30, serine protease inhibitor 2, protein kinase C inhibitor) indicated that high doses of statins were associated with cellular perturbations and an increase in cytosolic calcium, effects that are considered early indicators of toxicity. Many other interesting observations may be made particularly with different drug treated samples. Some of the changes may seem at least, in part, related to the decrease in weight gain in animals treated with high doses of lovastatin. The markers provide insights into the pathway regulation induced in response to or secondary to the therapeutic action of the drug and suggest other protein targets for drug development. Cholesterol Metabolism: Statin treatment increased the abundance of both cytosolic and mitochondrial HMG-CoA synthases, two enzymes with similar functions but encoded by different genes. Also note Ayte et al., Proc. Natl. Acad. Sci. U.S.A., 87:3874-3878 (1990). HMG-CoA synthase drives the condensation of acetyl-CoA with acetoacetyl-CoA to form HMG-CoA, which is the substrate for HMG-CoA reductase. HMG-CoA reductase is a rate-limiting enzyme of the cholesterol synthesis pathway and converts HMG-CoA to mevalonate. While cytosolic HMG-CoA synthase is not thought to be the target of the statins, the enzyme is involved in the cholesterol biosynthesis pathway, and mitochondrial HMG-CoA synthase is part of the ketone body synthesis pathway. For example, mitochondrial HMG-CoA synthase mRNA was found to be increased greatly by starvation, fat feeding and diabetes, Casals et al., Biochem. J., 283: 261-264 (1992). The strong induction of cytosolic HMG-CoA synthase following exposure to statins may represent a feedback reaction and attempt of the liver to compensate for the impaired cholesterol biosynthesis performance. The degree of induction thus may reflect the pharmacological potency of an HMG-CoA reductase inhibitor to inhibit HMG-CoA reductase and hence serves as a marker to compare efficacy among members of the statin family of compounds and between families of chemically unrelated agents with a similar mode of action. Unequivocally, greater concentrations of statins result in a greater alteration in the abundance of many of the protein markers. Isopentenyl-diphosphate delta-isomerase (IPP-isomerase) showed the most prominent effect following treatment with low and high doses of statins, levels were induced about 2-fold and 24-fold, respectively. The enzyme is part of the cholesterol biosynthesis pathway, down-stream of HMG-CoA reductase, and participates in the steps resulting in the conversion of mevalonate to farnesyl diphosphate. The strong induction of the enzyme following treatment with HMG-CoA reductase inhibitors is likely an additional approach to maintain cholesterol synthesis rate during blockade of HMG-CoA reductase. Therefore, IPP isomerase represents a good target for drugs antagonizing the activity of the enzyme. The enzyme previously is not known to be a drug target for cholesterol synthesis inhibition and therefore represents a new heretofore unknown drug target. Compounds inhibiting IPP-isomerase used in conjunction with HMG-CoA inhibitors are also suitable combinations for pharmacological use. Precursor apolipoprotein A-I is increased strongly with statins. As with most of the apolipoproteins, apolipoprotein A-I is synthesized in the liver and then secreted into the blood. ApoAI is involved in the reverse transport of cholesterol from tissues to the liver, the site where cholesterol is metabolized and secreted. Thus, the increased synthesis of precursor apolipoprotein A-I is a likely part of the therapeutic effect of statins contributing to the net effect to decrease the amount of plasma cholesterol. Carbohydrate Metabolism: Fructose- 1 ,6-bisphosphatase, a key regulatory enzyme of gluconeogenesis that catalyzes the hydrolysis of fructose- 1 ,6-bisphosphate to generate fructose-6-phosphate and inorganic phosphate, is decreased on statin treatment. Deficiency of fructose- 1,6-bisphosphatase is associated with fasting hypoglycemia and metabolic acidosis because of impaired gluconeogenesis, el-Maghrabi et al., Genomics 27:520-5 (1995). Glucose-6-phosphate 1 -dehydrogenase, the first enzyme in the pentose phosphate pathway, is elevated by statins suggesting up-regulation of the pentose phosphate pathway. Although the primary target of statins is cholesterol metabolism, in parallel it has major impacts on glucose metabolism, demonstrating the power of the regulatory network when central functions, such as energy metabolism, are affected. The effect also may be related to the treatment-related decrease in weight gain in the high dose group. Membrane Trafficking: Lovastatin induced a dose-dependent increase in annexin IV. The annexins are a group of homologous proteins that bind membranes and aggregate vesicles in a calcium-dependent fashion and contain a binding site for calcium and phospholipid. Annexins provide a major pathway for communication between cellular membranes and the cytoplasmic environment of the annexins and are implicated in membrane-related events along exocytotic and endocytotic pathways. The induction of annexin IV likely is related to the up-regulation of LDL receptor (as part of the pharmacological action of statins) and the subsequent up-regulation of the endocytosis-mediated transport of cholesterol-carrying lipoprotein into liver cells. As such, the protein is also a drug target of compounds that up-regulate the LDL receptor and/or annexins as well as compounds that down-regulate cholesterol synthesis. Cytoskeletal Structure: The abundance of type I cytoskeletal cytokeratin 18 and of major vault protein increased on treatment with high doses of a statin. Cytokeratin 18 is a subunit of cytokeratin filaments that are important components of the cytoskeletal structure. Major vault protein is required for normal vault structures, large ribonucleoprotein particles that may be involved in nucleo-cytoplasmic transport. The statin-mediated increase of proteins involved in cytoskeletal structure and membrane trafficking may be related to cellular stress induced by high doses. Thus, the protein primarily represents a marker for toxicity. Calcium Homeostasis: Senescence marker protein-30 (SMP-30) is decreased in response to statin treatment. SMP-30, a cytosolic protein with decreased expression during senescent stages, recently was reported to be identical to a calcium binding protein called regucaltin, Fujita et al, Mech. Ageing Dev. 10:7271-7280 (1999). SMP-30 is suggested to regulate calcium homeostasis by enhancing plasma membrane calcium-pumping activity. Down-regulation of the protein in livers of rats treated with high doses of statins lead to the disregulation of calcium signaling and causes cellular stress. Thus, the protein primarily represents a marker for toxicity. Nucleotide Metabolism: Adenosine is an endogenous modulator of intercellular signaling that provides homeostatic reductions in cell excitability during tissue stress and trauma. The inhibitory actions of adenosine are mediated by interactions with specific cell-surface G protein-coupled receptors regulating membrane cation flux, polarization and the release of excitatory neurotransmitters. Adenosine kinase is the key intracellular enzyme regulating intracellular and extracellular adenosine concentrations. Inhibition of adenosine kinase produces marked increases in extracellular adenosine levels that are localized to cells and tissues undergoing accelerated adenosine release, Kowaluk et al., Curr. Pharm. Des., 4:403-16 (1998). Thus the down-regulation of adenosine kinase following treatment with a statin may represent a mechanism of the liver to enhance selectively the protective actions of adenosine during stress. As such it would function primarily as a marker for toxicity. Amino Acid Metabolism: 3-Hydroxyanthranilate 3,4-dioxygenase, an enzyme of tryptophan metabolism that catalyzes the synthesis of excitotoxin quinolinic acid (QUIN) from 3-hydroxyanthranilic acid, is decreased in livers of statin-treated rats. A similar decrease is found in phenylalanine hydroxylase, a key enzyme in phenylalanine metabolism. Deficiency of that enzyme results in hyperphenylalaninemia, leading to severe mental retardation in the classical form of the disease, phenylketonuria, Lichter-Konecki et al., Mol. Genet. Metab. 67:308-16 (1999). It remains unclear why statin treatment down-regulates the two enzymes in liver but may be related to and may be a marker for indirect toxicity and/or indirect efficacy of a statin. Protease Inhibitors: The serine protease inhibitors (serpins) are a family of proteins that function to control the action of serine proteases in many diverse physiological processes. The expression of serine protease inhibitor 2 (SPI-2) was reduced in inflammation. Treatments with high doses of lovastatin are likely to induce inflammatory processes in liver that may explain the observed decrease in SPI-2. As such, the serpins are primarily suitable markers for toxicity. Cell Signaling: Lovastatin increased the abundance of protein kinase C inhibitor, a protein that acts as a regulator of the cell signaling process. Protein kinase C inhibitor activates tyrosine and tryptophan hydroxylases in the presence of calcium/calmodulin-dependent protein kinase II, and strongly activates protein kinase C. 23kD Morphine binding protein, a member of the phosphatidylethanolamine-binding protein (PEBP) family, is increased on treatment with lovastatin. A variety of biological roles have been described for members of the family, including lipid binding, membrane signal transduction, roles as odorant effector molecules or opioids and interaction with the cell-signaling machinery. Banfield et al., Structure, 6: 1245-54 (1998). The alterations in the proteins indicate that a statin affects cell signaling and are suitable targets for drug discovery and markers of efficacy and toxicity. Apoptosis: The protein product of a gene with the name "induced in androgen-independent prostate cells by effectors of apoptosis" was induced in the liver of statin-treated animals. The induction of the gene has been shown to be apoptosis specific, Sells et al., Cell Growth Differ., 5:457-66 (1994), suggesting that toxic doses of lovastatin trigger apoptosis in liver cells of treated rats. Similar observations have been reported from in vitro experiments with lovastatin, Wang et al., Can. J. Neurol. Sci., 26:305-10 (1999). As elevation of intracellular calcium is central to apoptosis, the event is likely the consequence of the treatment-related disturbance of calcium homeostasis as reflected by the decrease in SMP-30 levels. Thus, the protein is primarily a good marker for toxicity of not only a statin but also any apoptosis-related response to an agent or condition. Biotransformation: N-hydroxyarylamine sulfotransferase, a liver-specific enzyme involved in the biotransformation of endogenous and foreign substrates, is decreased by a statin. 3-Mercaptopyruvate sulfotransferase, an enzyme involved in thiosulfate synthesis, is increased strongly by high doses of a statin. As such, the protein may serve as a marker for either toxicity or efficacy. Pheromone binding protein: Alpha-2u globulin is synthesized in the liver of male but not female rats, secreted into the bloodstream and excreted in the urine, Roy et al., Proc. Soc. Exp. Biol. Med., 121:894-899 (1966). The protein binds pheromones that are released from drying urine and affects the sexual behavior of females. There are a number of chemicals that induce a toxic syndrome in male rats referred to as alpha-2u globulin nephropathy. The organ-specific toxicity is characterized by an accumulation of protein droplets in the proximal tubules. The droplets might be formed by the association between the chemical and the alpha-2u protein, Borghoff et al, Ann. Rev Pharmacol. Toxicol, 30:349-367 (1990). High doses of a statin strongly decrease the abundance of alpha-2u globulin in liver suggesting a down-regulation of synthesis or increased secretion. It is likely that either that protein has an additional function or that the effect is incidental. In either situation, the protein may still serve a function as a marker for efficacy or toxicity or as a drug discovery target. Even if the effect is incidental, the protein remains of use as a toxicity or efficacy marker. Peroxisome Proliferation: Proteins previously were reported to be induced strongly in the liver of rodents following treatment with peroxisome proliferators (Anderson et al., Toxicol. Appl. Pharmacol., 137:75-89 (1996)) or lovastatin (Anderson et al, Electrophoresis 12:907-930 (1991)). While developing the present invention, the previous proteins were identified as being a similar or perhaps even the homologous protein to peroxisomal enoyl hydratase-like protein. In the present examples, only a mild induction of that protein marker was observed. It may be used primarily as a marker for toxicity. In the present invention, proteome analysis revealed quantitative alterations in a large number of hepatic proteins following treatment with lipid lowering pharmaceuticals such as lovastatin (Mevacor ® ). Lovastatin treatment significantly altered the abundance of 32 hepatic proteins (p<0.001). Those and other marker proteins (p<0.005) are listed below. Other drugs produced similar results. That data is summarized in Table 1. TABLE 1 Summary of All Proteins That Change at p<0.005 x p < 0.001 o p < 0.005 MSN Lorelco ® Lopid ® Mevacor ® Zocor ® Lescol ® Nicolar ® Pravachol ® Protein Identification 18 o 75kD glucose related protein 24 oo Calreticulin 29 xX oo oo Keratin type I cytoskeletal 18 34 XX XX XX Unknown 41 XX XX Keratin type π cytoskeletal 8 42 55 XX o XX Senescence marker protein-30 59 o 66 X 68 o Actin gamma 69 x 73 o o x 76 o o 79 o x x x Fructose-l,6-bisphosphatase 83 o 89 x Fumarylacetoacetate hydrolase MSN Lorelco Lopid Mevacor ® Zocor" Lescol ® Nicolar" Pravachol Protein Identification 91 o X Isovaleryl-CoA dehydrogenase 97 X X Keratin type II cytoskeletal 8 99 X X Catechol O-methyl transferase 101 o o o o Methionine adenosyltransferase 103 o X Senescence marker protein-30 104 23kD morphine binding protein 106 o Catalase 113 X o xX Adenosine kinase 117 o o o o 125 o xX xX xX N-hydroxyarylamine sulfotransferase 126 Xx Xx X 3 -Hydroxyanthramlate 3,4-dioxygenase 127 X o 128 X 138 o 4-Hydroxyphenylpyruvate dioxygenase 139 x x 143 o o 142 xX xX oo Ketohexokinase 148 xX 154 o oo 155 o 162 x oo Xx oo o D-dopachrome tautomerase MSN Lorelco ® Lopid ® Mevacor ® Zocor ® Lescor Nicolar ® Pravachol ® Protein Identification 168 X o Antiquitin 172 o o Tropomysin 178 X X X Aminoacylase 182 X X X X Fructose- 1 ,6-bisphosphatase 191 o Adenosylhomocysteinase 197 200 Annexin VI 203 o 218 o 227 X o Fatty acid binding protein, liver 229 o 232 237 o 238 o 252 XX XX Serine protease inhibitor 2 267 o 268 o 270 X 282 oo Xx Pyravate kinase, isozymes 286 o 289 x MSN Lorelco ® Lopid ® Mevacor ® Zocor ® Lescol ® Nicolar ® Pravachol ® Protein Identification 292 o 297 X Unknown 305 X XX Phenylalanine hydroxylase 307 XX Heme oxygenase-1 310 X 311 o 315 XX XX Pyravate kinase L 318 o X 321 X XX Glutathione synthetase 339 o ~4 347 x o 350 o 358 X 361 X XX HMG-CoA synthase, mitochondrial fragment 362 X o X 367 X XX Peroxisomal enoyl hydratase-like protein 371 o o 372 X o o 379 384 MSN Lorelco Lopid Mevacor Zocor® Lescol W Nicolar Pravachol Protein Identification 399 o 413 x X X X HMG-CoA synthase, cytosolic 416 o 420 X X 427 o 434 o 435 o 438 o 457 o Annexin VI 463 X X o Apolipoprotein A-I oe 469 o 490 X X X Alpha 2u-globulin 492 o 497 o o 501 X X 2-oxoisovalerate dehydrogenase alpha subunit, mitochondrial 506 510 522 o 532 X Protein kinase C inhibitor 534 x ER60 protease; 58kD microsomal protein MSN Lorelco 1 Lopid'" Mevacor 7 ® Zocor" LescoF Nicolar" Pravachol ® Protein Identification 546 x 557 o 565 o 569 x 590 X Glucose-6-phosphate 1 -dehydrogenase 571 o 574 o Nucleolar phosphoprotein b23 577 Fructose-1,6- bisphophatase 605 o 610 X X 3-Mercaptopyravate sulfotransferase 613 618 637 X 644 653 664 X X Major vault protein 665 o o 666 o 669 x 671 o Nucleolar phosphoprotein b23 681 x MSN Lorelco ® Lopid ® Mevacor ® Zocor ® Lescol ® Nicolar ® Pravachol ® Protein Identification 689 o 698 x o Cytokeratin ends A 716 x Heterogeneous nuclear ribonucleoprotein K 718 719 721 734 o Lamin b 777 o o 779 X 787 x o o 802 806 810 X 839 o 876 o 879 887 o 888 900 905 932 x o Annexin IV MSN Lorelco ® Lopid ® Mevacor ® Zocor ® Lescol ® Nicolar ® Pravachol ® Protein Identification 933 x o HMG-CoA synthase, cytosolic 934 o o Ras-GTPase- activating protein SH3 -domain binding protein 966 o 993 X Induced in androgen- independent cells by effects of apoptosis 1081 X 1053 x 1119 X X X Isopentyl-diphosphate delta-isomerase 1250 o X o X HMG Co-A synthase The supporting data is presented in detail in Table 2 below. ""» , iq "i! In the present invention, a probability value of p<0.001 in a Student's t-test generally is accepted as indicating high statistical significance. While higher p values of <0.01 may be considered statistically acceptable to some, other experiments have shown that level is not acceptable for 2-dimensional gel electrophoresis with the number of samples (n=5) analyzed per group, considering the variation even between inbred animals. Such levels of significance are not certain at all and produce results with a high rate of false positives. By raising the p value from O.001 to O.005, many other markers are selected. In that way, significant information regarding the metabolic and toxic pathways and other potential drug targets may be gleaned. By discovering consistency of protein markers between similar agents, the statistical significance of the marker for the class of agents increases greatly. For example lovastatin, simvastatin and fluvastatin are chemically and pharmacologically similar and with respect to keratin type I cytoskeletal 18 in the high dose, the p values are 0.0010, 0.00131, and 0.00282, respectively. Given that correlation and considering that the protein is a marker for lovastatin, the protein is considered to be a marker for simvastatin and fluvastatin even though the p value for each may not be considered highly significant by being above the most stringent, selected cut-off value. Likewise, with respect to protein MSN 73, the p value for lovastatin high dose is <0.00412 and for simvastatin high dose is <0.00025. Indeed, chemically different but also a drug, probucol, at a high dose has a p value of 0.00144 with respect to MSN 73. Likewise, fatty acid binding protein of liver has p values for pravastatin sodium of 0.00260 and gemfibrozil of 0.00013, even though the compounds are chemically quite different and believed to have very different modes of action. Numerous other examples are present and may be so determined. Thus, cut-off values are arbitrary and may not reflect accurately true pharmacological and toxicological actions. The markers for various drugs are given in the Tables. In another study using an intermediate dosage and different aged rats, lovastatin, cholestyramine, high cholesterol diet and a combination of lovastatin and cholestyramine were used. The results are summarized in Table 3 below. The altered abundance of proteins compared to a control with given p values and other statistical data are given in Table 4 below. Because the experimental conditions were slightly different from the above experiment, some differences were noted; however, many markers of particular interest are the same. It can be seen that such studies enable identifying markers with positive and negative phenotypes in the cells and hosts from which the cells are obtained. By positive phenotype is meant a desired result, such as amelioration of a pathologic state or symptom. By negative phenotype is meant an undesirable result, such as an undesirable side effect, a detrimental state or symptom and so on. Thus, a drug side effect or an untoward response to a mutagen, toxin, noxious agent and so on are non-limiting examples of a negative phenotype. The sublibrary of markers of interest are those proteins and polypeptides that are correlated with a positive or negative phenotype. The methods taught herein reveal those proteins or polypeptides that have altered expression before and after exposure of a cell, tissue or host to a compound. A compound can be a drug, candidate drug, herbicide, pesticide, toxin and so on. The altered expression can be manifest as increased levels, decreased levels, different properties and so on. The proteins and polypeptides are identified by parameters that define and distinguish the various proteins and polypeptides. Suitable parameters include molecular weight, isoelectric point, peptide fragment pattern, partial and total amino acid sequence, secondary structure, tertiary structure, quaternary structure, post-translational modifications and so on. TABLE 3 Summary of All Proteins Changed x pθ.001 All Proteins that change at p<0.005 o p<0.005 MSN High Cholesterol Cholestyramine Lovastatin Cholestyramine Protein Identification +Lovastatin o Unknown 97 x Keratin type II cytoskeletal 8 99 x Catechol O-methyl transferase 104 X 23kD morphine binding protein u, 111155 oo Apolipoprotein E precursor 122 o 142 o Ketohexokinase 147 o HumorF06 178 o o Antiquitin 182 o Fructose- 1 ,6-bisphosphatase 191 o Adenosylhomocysteinase 204 x Alanine aminotransferase 232 o o 275 o 279 322 o MSN High Cholesterol Cholestyramine Lovastatin Cholestyramine Protein Identification +Lovastatin 361 o HMG-CoA synthase, mitochondrial 365 X 367 X X Peroxisomal enoyl hydratase-like protein 395 o 413 X o HMG-CoA synthase, cytosolic 423 o 461 X 475 o N-G 5 N-G-dimethylarginine dimethylaminohydrol 479 490 o Alpha 2u-globulin 502 556 o 578 590 o Glucose-6- phosphate 1 -dehydrogenase 602 o 610 3 -Mercaptopyruvate sulfotransferase 625 o 633 X 646 X 664 o Major vault protein MSN High Cholesterol Cholestyramine Lovastatin Cholestyramine Protein Identification ÷Lovastatin 984 x 998 o Epoxide hydrolase, soluble 1001 o 1065 o 1081 o 1172 o 1195 o 1215 90 KD heat shock protein TABLE 4 Report Data for All Significant Proteins All Groups with protein significant PO.005 in at least one group Protein significant p<0.005 in at least one group oe O © Confidence levels represent a somewhat arbitrary threshold. By comparing related agents, which may be related by chemical structure or mechanism of action, proteins with altered abundance with respect to the controls can be observed. Even though not statistically significant alone, if such a protein were found to be altered in biological samples from animals treated with slightly different but similarly acting agents, the result can be statistically significant. When determining what is to be considered a protein marker, a protein may constitute a marker of efficacy or toxicity for an agent even when not statistically significant in a single experiment with one agent alone. Identification of a protein marker may be performed by detecting proteins with altered abundance for multiple similar agents. The similarities may be chemical structure, function or physiological or toxic effect. Testing with agents having common mechanisms of action particularly is preferred for markers comparing related agents. An ideal example is screening new compounds and comparing marker changes to those of a standard pharmaceutical having the same general usage. For example, methionine adenosyltransferase has a p value above 0.001 for all of the agents tested. If one required such a stringent confidence level, that marker would be ignored. However for fluvastatin, it is 0.00234, for probucol, it is 0.00139, for pravastatin sodium, it is 0.00425 and for lovastatin, it is 0.00307. Thus, that protein is an acceptable protein marker due to altered levels in biological samples from animals treated with multiple related drugs without a need to raise the p value. Such a situation is not unique and may be found in many other markers. Representative examples are listed in Table 5. TABLE 5 Annexin VI pravastatin 0.00202 lovastatin 0.00143 MSN 76 fluvastatin 0.00161 lovastatin 0.00150 MSN 143 fluvastatin 0.00188 lovastatin 0.00353 MSN 154 probucol 0.00365 simvastatin 0.00408 MSN 172 simvastatin 0.00468 fluvastatin 0.00299 MSN 229 simvastatin 0.00182 pravastatin 0.00176 MSN 371 fluvastatin 0.00394 simvastatin 0.00188 Other examples include MSN 117, 339, 497, 506, 665, 777, 934 and others. When determining what is to be considered a protein marker, combinations of proteins may constitute a combination marker of efficacy or toxicity for an agent. Even when two or more proteins are not sufficiently statistically significant to be considered markers, when considered in combination, the combination may be statistically significant. That is done by determining proteins that are at altered abundance in biological samples from animals treated with an agent of interest and control biological samples from animals not treated with an agent of interest. Selecting two proteins that are less than statistically significant markers by themselves, one may combine the values for two or more of the proteins and determine whether the combination of values is altered in a statistically significant manner. Combination markers result when statistically significant differences between biological samples from treated animals and biological samples from untreated animals are determined. Suitable data-mining reveals a number of combination markers. Testing with agents having different mechanisms of action particularly is preferred when searching for new agents of potentially new mechanism of action. That exercise is searching by purely secondary pharmaceutical function. By comparing protein markers across different agents, less than statistically significantly changed proteins may become protein markers. Both processes were used with the exemplified antilipemic agents in the present invention. Through suitable data mining techniques, combination markers across a spectrum of different agents are identifiable such that markers that are not statistically significant alone, are significant considering determination in multiple related agents. An index marker is similar to a combination marker except that each protein in the index itself is already statistically significant as a protein marker alone. An index marker is an aggregate of plural significant protein markers, taken together and compared to the same index marker of a different sample. The index marker then is an extremely significant combination. For example, using a combination of markers, each with p<0.001, may yield an index marker of p<0.00001 or lower. Protein markers found across drugs in different categories or modes of actions producing the same markers are perhaps the best markers for screening new drugs for a given indication because the markers are not mechanism of action-specific. Those are believed to reveal elements common to the mechanism of action of the different pharmacological classes. Such a marker is good for screening for drugs having completely unknown modes of action but directed to a similar disease treatment objective. By using a different method for measuring the proteins on a two-dimensional electrophoretic gel, different markers also may be uncovered. Furthermore, by comparing how one protein changes in abundance with respect to others, still other protein markers may be found. For example, protein MSN 261 also was changed together with (i.e., abundance in a drug treatment experiment is correlated with) HMGCoA synthase (cytosolic), HMGCoA synthase (mitochondrial), HMGCoA synthase (cytosolic) (other form) and IPP-isomerase. Although MSN 261 has a p value of >0.005 for all drugs tested, MSN 261 is considered a marker because of a strong correlation with other markers. In view of the data, protein MSN 261 is at least a protein marker, and likely to be a protein in the biosynthetic pathway for cholesterol. That method is performed by comparing all proteins that change in abundance in the same or opposite direction as known protein markers. Even if the change in abundance of the proposed protein marker is not significant, the fact that the abundance changes along with established protein markers indicates a candidate protein may be an acceptable marker. Another method for finding a marker even when the data is not statistically significant is to determine whether a protein is altered in tandem with known protein markers. Proteins that are not altered sufficiently to be considered protein markers alone are called protein "submarkers" because of altered levels in a tandem direction and magnitude when consistent among a group of samples. Essentially the same experimental methodology is performed as above for finding a protein marker for efficacy or toxicity for an agent. The direction and amount of alteration between the control and agent treated samples is noted. That is compared across multiple individuals and compared to established protein markers. Tandem moving protein submarkers that are altered both in direction and in amount between individuals and paralleling known protein markers then may be considered to be "protein markers." Such then may be assayed for the multitude of purposes as any other marker. Another method for measuring the proteins in a two-dimensional electrophoretic gel is by determining qualitatively whether a protein is present or absent. For example, a protein found in a biological sample from a control but not in a comparable sample from an agent-exposed tissue would be of particular interest as that situation represents that the agent eliminated the protein completely. Likewise, the reverse where a protein is induced only in treated but not controls is also of particular interest. A p value is not even calculable as the comparison is relative to zero. Protein spot MSN 204, alanine aminotransferase, is present in controls but is eliminated in samples treated with drugs. A decrease may be seen in low dose treatments for some individuals. Protein spot MSN 1255 has the reverse behavior by usually being absent in controls and sometimes even in samples from low dose of drug treatment. However, in high dosages, the protein is consistently present. Another qualitative or quantitative change in protein marker levels is in the presence of or amount of protein variants. Some drugs are known to alter glycosylation and the agent being tested may induce a different abundance of protein variants. Likewise, cleavage fragments (or the lack thereof) may be in altered abundance. Still further, enzymes may be in the same concentration but have dramatically different activity due to the agent. In all of those situations, the altered level or change in abundance of a protein or its variant(s) may be used to serve as a suitable marker for efficacy or toxicity. That may be observed as a shift in spot location or new spot formation. Not only can the present invention determine response to an agent after treatment has begun, but also susceptibility to toxicity with an agent or effective response to treatment with the agent may be determined. Furthermore, some indication as to the appropriate dosage may be given. That is done by measuring toxicity or efficacy susceptibility markers in a biological sample from a test tissue of interest before treatment begins. The proteins in the biological sample from an agent-treated organism or tissue may be tested against a number of other groups depending on the data desired. The simplest comparison is to untreated controls. However, comparisons to positive-treated and negative-treated controls also may be performed. In that situation, the positive controls include samples from treatments with an agent having the same mechanism of action and agents having a different mechanism but the same general effect. Negative-treated controls may be from samples treated with an agent with the same mechanism of action but having an opposite effect or samples treated with agents having an mirelated mechanism. To best determine which agents have an unrelated mechanism, it is desirable to compare to a composite effect of many drugs and other agents, preferably from a large pharmaceutical proteomics database. The comparison to the positive control, same mechanism of action and the negative control, same mechanism of action may be seen as agonist/antagonist effects and correlations between the two control groups provides a further source for protein markers. Furthermore, the toxicity controls may be subdivided further into toxicity controls having been treated with an agent having the same mechanism of action, with an opposite mechanism of action and by an unrelated mechanism of action. As before, the unrelated mechanism of action control is best determined from a large database of many different and unrelated agents such as a large pharmaceutical proteomics database. Also as before, the controls with opposite mechanisms of action may be correlated to each other for providing a further source of protein markers. Still furthermore, plural (or all possible) comparisons between the test sample and plural controls are preferable. Total protein markers identified are listed below. New protein markers listed below are those that are provably unknown proteins or ones for which evidence to date does not suggest that the proteins are known. Some of the markers gave insufficient or conflicting information and are considered unknown for the purposes of the present invention. As will be shown in the examples, protein identity was determined by molecular weight, pi, molecular mass of digested peptides and fragment ions, partial or complete sequence of the peptides or entire protein etc. In some situations, the molecular mass determined by MALDI conflicted with the determination achieved by electrospray MS. That may be due to a number of factors including poorly resolved spots on the gel, experimental conditions etc. Conflicting data are not considered an identification and thus considered to be "unknown". Examples of MALDI and electrospray data are given in Table 6. "Unknown" is defined as not being listed in the public NCBI non-redundant gene sequence database or the SwissProt database. TABLE 6 Peptide Molecular Mass For MALDI MSN 372 297 806 34 Sample 47 56 18 4 Peaks 915.0180 855.9430 1013.0280 1488 Single 1105.0729 956.9130 1181 1491.2190 Charged 1123.0769 1197.0979 1390.0409 1505.6179 Ions 1559.1079 1327.0189 1634.1120 1521.5910 1778.1580 1664.9900 2029.0600 1629.7110 1949.1869 1723.1559 2316.4288 1965.0979 1844.0900 2380.1 1981.0690 1972.1060 2193.1 2398.2269 2547.0929 2366.1 2576.1268 1951.1 2681.0890 2593.2 2695.1 2723.2 872.1 Peptide Molecular Mass For Electrospray Examples of MALDI and electrospray MS data for selected proteins are given in Table 7. TABLE 7 MALDI And Electrospray Data for Selected Spots oe Even though the protein heretofore may not be isolated or characterized, the present invention effectively isolates and characterizes the proteins. From the MSN number given below, a unique isolated protein from a spot on a 2-dimensional electrophoretic gel is obtained. The relative molecular weight and relative pi for each spot are determinable by, reference to established landmark proteins that are characterized fully by sequencing and a theoretical molecular weight and pi calculated. By plotting the theoretical values on a graph and comparing the location of the previously unknown spot, the identifying features are determined. See Anderson et al, Electrophoresis 16:1977-1981 (1995) for more details, the contents of which specifically are incorporated by reference. That provides a reproducible method for isolating the protein markers of the present invention. The protein markers that are perturbed by drugs are as follows. When different variants of the proteins are present and used as markers, references to the different MSN numbers are given. Table 8: Total Protein Markers Actin gamma Adenosine kinase (EC 2.7.1.20) Adensylhomocysteinase Alanine aminotransferase Alpha 2u-globulin Annexin IV Annexin VI Antiquitin Apolipoprotein A-I Apolipoprotein E precursor Catechol O-methyl transferase Calreticulin Catalase Cytokeratin ends A N-G, N-G-dimethylarginine dimethylaminohydrolase D-dopachrome tautomerase Epoxide hydrolase, soluble ER60 protease; 58kD microsomal protein Fatty acid binding protein, liver Fructose- 1,6-bisphosphatase (EC 3.1.3.11) (MSN 79) Fructose- 1,6-bisphosphatase (EC 3.1.3.11) (MSN 182) Fructose- 1,6-bisphosphatase (EC 3.1.3.11) (MSN 577) Fumarylacetoacetate hydrolase 75kD glucose related protein Glucose-6-phosphate 1 -dehydrogenase (EC 1.1.1.49) Glutathione synthetase 90kD heat shock protein Heme oxygenase-1 Heterogeneous nuclear ribonucleoprotein K HMG-CoA synthase, mitochondrial frag. (EC 4.1.3.5) HMG-CoA synthase, cytosolic (EC 4.1.3.5) (MSN 413) HMG-CoA synthase, cytosolic (EC 4.1.3.5) (MSN 933) HMG-CoA synthase, (MSN 1250) HumorFOό N-hydroxyarylamine sulfotransferase (EC 2.8.2.-) 3-Hydroxyanthranilate 3,4-dioxygenase (EC 1.13.11.6) 4-Hydroxyphenylpyruvate dioxygenase Induced in androgen-indep. prostate cells by eff. of apopt. Isopentenyl-diphosphate delta-isomerase (EC 5.3.3.2) Isovaleryl-CoA dehydrogenase Keratin type II cytoskeletal 8 (MSN 97) Keratin type I cytoskeletal 18 Keratin type II cytoskeletal 8 (MSN 41) Ketohexokinase (EC 2.7.1.3) Lamin b Major vault protein Methionine adenosyltransferase 3-Mercaptopyruvate sulfotransferase (EC 2.8.1.2) 23kD Mo hine-binding protein Nucleolar phosphoprotein B23 (MSN 574) Nucleolar phosphoprotein B23 (MSN 671) 2-oxoisovalerate dehydrogenase alpha subunit, mitochondrial Peroxisomal enoyl hydratase-like protein Phenylalanine hydroxylase (EC 1.14.16.1) Protein kinase C inhibitor Pyruvate kinase, isoenzymes (MSN 282) Pyruvate kinase L Ras-GTPase-activating protein SH3 -domain binding protein Senescence marker protein-30 (MSN 55) Senescence marker protein-30 (MSN 103) Serine protease inhibitor 2 Tropomysin MSN 34 MSN 42 MSN 59 MSN 66 MSN 69 MSN 73 MSN 76 MSN 83 MSN 117 MSN 122 MSN 127 MSN 128 MSN 139 MSN 143 MSN 148 MSN 154 MSN 155 MSN 197 MSN 203 MSN 204 MSN 218 MSN 229 MSN 232 MSN 237 MSN 238 MSN 261 MSN 267 MSN 268 MSN 275 MSN 279 MSN 286 MSN 270 MSN 289 MSN 292 MSN 297 MSN 310 MSN 311 MSN 318 MSN 322 MSN 339 MSN 347 MSN 350 MSN 358 MSN 362 MSN 365 MSN 371 MSN 372 MSN 379 MSN 384 MSN 395 MSN 399 MSN 416 MSN 420 MSN 423 MSN 427 MSN 434 MSN 435 MSN 438 MSN 461 MSN 469 MSN 479 MSN 492 MSN 497 MSN 502 MSN 506 MSN 510 MSN 522 MSN 546 MSN 556 MSN 557 MSN 565 MSN 569 MSN 571 MSN 578 MSN 602 MSN 605 MSN 613 MSN 618 MSN 625 MSN 633 MSN 637 MSN 644 MSN 646 MSN 653 MSN 665 MSN 666 MSN 669 MSN 681 MSN 689 MSN 718 MSN 719 MSN 721 MSN 777 MSN 779 MSN 787 MSN 802 MSN 806 MSN 810 MSN 839 MSN 876 MSN 879 MSN 887 MSN 888 MSN 900 MSN 905 MSN 966 MSN 984 MSN 1001 MSN 1065 MSN 1081 MSN 1053 MSN 1172 MSN 1195 MSN 1215 and MSN 1255. Table 9: New Protein Markers MSN 34 MSN 42 MSN 59 MSN 66 MSN 69 MSN 73 MSN 76 MSN 83 MSN 117 MSN 122 MSN 127 MSN 128 MSN 139 MSN 143 MSN 148 MSN 154 MSN 155 MSN 197 MSN 203 MSN 204 MSN 218 MSN 229 MSN 232 MSN 237 MSN 238 MSN 261 MSN 267 MSN 268 MSN 275 MSN 279 MSN 286 MSN 270 MSN 289 MSN 292 MSN 297 MSN 310 MSN 311 MSN 318 MSN 322 MSN 339 MSN 347 MSN 350 MSN 358 MSN 362 MSN 365 MSN 371 MSN 372 MSN 379 MSN 384 MSN 395 MSN 399 MSN 416 MSN 420 MSN 423 MSN 427 MSN 434 MSN 435 MSN 438 MSN 461 MSN 469 MSN 479 MSN 492 MSN 497 MSN 502 MSN 506 MSN 510 MSN 522 MSN 546 MSN 556 MSN 557 MSN 565 MSN 569 MSN 571 MSN 578 MSN 602 MSN 605 MSN 613 MSN 618 MSN 625 MSN 633 MSN 637 MSN 644 MSN 646 MSN 653 MSN 665 MSN 666 MSN 669 MSN 681 MSN 689 MSN 718 MSN 719 MSN 721 MSN 777 MSN 779 MSN 787 MSN 802 MSN 806 MSN 810 MSN 839 MSN 876 MSN 879 MSN 887 MSN 888 MSN 900 MSN 905 MSN 966 MSN 984 MSN 1001 MSN 1065 MSN 1081 MSN 1053 MSN 1172MSN 1195 MSN 1215 and MSN 1255. When combinations of lipid-lowering drugs are used, some have little effect, some an additive effect and some a synergistic effect. In the present examples, the combination of cholestyramine and lovastatin gave the largest effect on major protein markers that are indicative of or . result from the treatment. While considerable interanimal variability was observed leading to a high CV and thus higher p value, the absolute change was greatest. A quick method for reading that is to compare the ratios to the controls. This is believed to be due to different modes of action of the two drugs. Combinations of pharmaceutical compounds in a composition may be prepared using known effective dosages of the known pharmaceuticals in conventional dosages. Susceptibility markers include the detection of genetic polymorphism(s) resulting in an amino acid sequence variant in all or some of the protein. The agent will interact differently depending on the polymorphism(s) present. In addition, polymorphism(s) inside or outside the coding region of a gene may result in different levels of expression. The protein markers may be involved in the metabolic pathway or may be associated with non-specific drug metabolism or repair mechanisms. For example, having a protein variant in a component of the cytochrome P-450 isoenzyme system is well lαiown to alter response to certain drugs by altering the metabolism rate (% of compound used by enzyme and/or turnover rate) and thus bioavailability. Superoxide dismutase and catalase variants appear to affect the ability of one to repair damage from free oxygen radicals and hydrogen peroxide respectively, generated by or directly from certain agents. Absolute determination of an acceptable response by measuring susceptibility marker(s) may be due to non-genetic factors as well. Normal physiological changes due to time of day, recent foods consumed, exposure to other environmental agents or other drugs etc. also cause physiological changes that alter marker protein abundance. Susceptibility markers are determined by comparing the proteins in a proteome from individuals known to respond well to the drug and individuals known to experience toxicity from the drug. That may be done in the same manner as other marker determination studies and likewise used in the same manner. Proteins that are increased or decreased above a statistically significant amount are deduced to be toxicity or efficacy susceptibility markers. While many of the differences may be too small to have any significant effect, adequate comparison reveals certain markers of susceptibility. Measuring such markers permits one to predetermine whether an agent is likely to be acceptable for the individual, species, breed or variety before treatment begins. The diagnostic kits of the present invention are typically used in an "sandwich" format to detect the presence or quantity of proteins in a biological sample. A description of various immunoassay techniques is found in BASIC AND CLINICAL IMMUNOLOGY (4th ed. 1982 and more recent editions) by D. P. Sites at al, published by Lange Medical Publications of Los Altos, Calif., and in a large number of U.S. patents including Nos. 3,654,090, 3,850,752 and 4,016,043, the respective contents of which herein are incorporated by reference. In a preferred embodiment, the kit further includes, in a separate package, an amplifying reagent such as complement, like guinea pig complement, anti-immunoglobulin antibodies or S. aureus Cowan strain protein A that reacts with the antigen or antibodies being detected. In those embodiments, the label-specific binding agent is capable of specifically binding the amplifying means when the amplifying means is bound to the protein or antibody. Important to the labeling and detection systems is the ability to determine quantity of label present to quantify the ligands present in the original sample. Since the signal and intensity of the signal are measures of the number of molecules bound from the sample and hence of the number of receptors bound, the number of ligand molecules in the original sample may be determined. Optical and electrical signals are readily quantifiable. Radioactive signals also may be quantifiable directly but preferably are determined optically by use of a standard scintillation cocktail. While the receptors most commonly utilized are antibody molecules or a portion thereof, one equally may use other specific binding receptors such as hormone receptors, certain cell surface proteins (also called RECEPTORS in the scientific literature), an assortment of enzymes, signal transduction and binding proteins found in biological systems. Likewise, ligands exemplified as proteins below also may be small organic molecules such as metabolic products in a cell. By simultaneously detecting many or all metabolites in a sample, one can determine the global effects of an effector on the cell. Effectors may be drugs, toxins, infectious agents, physiological stress, environmental changes etc. As the number of markers found is large, a simultaneous multiple assaying system such as a microarray of binding agents for each desired protein marker is preferred. In such a microarray, a specific binding receptor for each protein marker ligand, e.g. an antibody, is immobilized at a different address and contained in a distinct region of the microarray or bound to a distinct particle or label. The protein marker ligand sample then is contacted to the microarray and allowed to bind. Binding then may be detected by a number of techniques, known per se, particularly preferred being binding a labeled receptor to one or more components of a ligand/receptor complex and detecting the label. Microarrays containing multiple receptors are known per se. An earlier discovery of a test strip with multiple receptors has been used commercially for decades. A number of designs for multiple simultaneous binding assays are known per se in the analytic testing field. The array may utilize antibody or other receptor display phage as a binding agent or an immobilizing agent for the protein marker ligand. Either the receptor alone or the whole display phage may be used. When used as an immobilizing agent, different cells of the microarray contain a different phage. When used as a labeled binding agent, the phage may be labeled (before or after binding to the ligand) by a number of techniques (such as direct fluorescent dyes, e.g. TOTO-1, labeled protein A or G, labeled anti-Ig etc.) and utilized without prior identification of which display phage contains a particular antibody as an initial immobilized capture receptor performs the discrimination. The techniques described in PCT Ser. No. US00/31516 may be employed to measure a very large number of proteins simultaneously, including any or all of those in a pathway relating to efficacy or toxicity. Such a technique may be applied to detecting any or all of the protein markers of the present invention. For microarrays that are not a unitary solid phase, multiple different beads, each with a different label or having a different combination of labels may be used. For example, a bead having different shades of a chiOmagen or different proportions of different chromagens or other detectable features can be used. Each bead or set of beads with the same identifying label(s) is to have an immobilized ligand or receptor. Individual sets of beads may be identified in a mixture by spreading on a flat surface and scanning or by moving the beads past a detector. The combination of the labels and the bead label(s) provides identification of the ligand of interest in the sample. The numerical ratio of beads having labels to beads without labels or with different labels provides a quantitative measurement. Just as the sample may be deduced from which addresses contained labels in a traditional microarray, with plural unique beads, the address may be deduced by determining which bead contains the corresponding label(s). Pharmaceutical compositions may be prepared for use in humans or animals via the oral, parenteral or rectal route, in the form of wafers, capsules, tablets, gelatin capsules, drinkable solutions, injectable solutions, including delayed forms and sustained-release dressings for transdermal administration of the active principle, nasal sprays or topical formulations (cream, emulsion etc.), comprising a derivative of a general formula according to the invention and at least one pharmaceutically acceptable carrier. The pharmaceutical compositions according to the invention advantageously are dosed to deliver the active principle in a single unit dose. For oral administration, the effective unit doses are between 0.1 μg and 500 mg. For intravenous administration, the effective unit doses are between 0.1 μg and 100 mg. According to the invention, the pharmaceuticals preferably are administered orally, for example, in the form of tablets, dragees, capsules or solutions, or intraperitoneally, intramuscularly, subcutaneously, intraarticularly or intravenously, for example, by means of injection or infusion. It is especially preferred that the application according to the invention occurs in such a manner that the active agent is released with delay, that is, as a depot. Unit doses can be administered, for example, 1 to 4 times daily. The exact dose depends on the method of administration and the condition to be treated. Naturally, it can be necessary to vary the dose routinely depending on the age and the weight of the patient and the severity of the condition to be treated. EXAMPLE 1 : PREPARATION OF 2-DIMENSIONAL ELECTROPHORESIS GELS Male F344 rats (Charles River, Raleigh, NC), 8 weeks of age and weighing 167-182 g were housed individually in rat gang cages in an environmentally controlled room and were fed with Rodent Chow (Research Diets Inc., New Brunswick, NJ) and tap water ad libitum. Three groups of five rats each received control feed, rodent chow milled with 16 ppm (approximately 1.6 mg/kg/day) lovastatin and rodent chow milled with 1500 ppm (approximately 150 mg/kg/day) lovastatin respectively for 7 days. The animals were guillotined after CO 2 asphyxiation on the day following the last treatment. Liver samples (150 mg of the left apical lobe) were removed and flash-frozen in liquid nitrogen and kept at -80°C until analysis. The samples were homogenized in eight volumes of 9M urea, 2% CHAPS, 0.5% dithiothreitol (DTT) and 2% carrier ampholytes pH 8-10.5. The homogenates were centrifuged at 420,000 x g at 22°C for 30 min. (TLl 00 ultracentrifuge, TLA 100.3 rotor, 100,000 rpm (Beckman Instruments, Palo Alto, CA)). The supernatant was removed, divided into four aliquots and stored at -80°C until analysis. Ultrapure reagents for polyacrylamide gel preparation were obtained from Bio-Rad (Richmond, CA). Ampholytes pH 4-8 were from BDH (Poole, UK), ampholytes pH 8-10.5 were from Pharmacia (Uppsala, Sweden) and CHAPS was obtained from Calbiochem (La Jolla, CA). Deionized water from a high purity water system (Neu-Ion, Inc., Baltimore, MD) was used. System filters are changed monthly to ensure 18 MΩ purity. HPLC grade methanol and glacial acetic acid were furnished from Fisher Scientific (Fair Lawn, NJ). HPLC grade acetonitrile was obtained from Baker (Phillipsburg, NJ). Dithiothreitol (DTT) was obtained from Gallard-Schlesinger Industries, Inc. (Carle Place, NY). Iodoacetamide, ammonium bicarbonate, trifluoroacetic acid and α-cyano-4-hydroxycinnamic acid were obtained from Sigma Chemical Co. (St. Louis). Modified porcine trypsin was purchased from Promega (Madison, WI). All chemicals (unless specified) were reagent grade and used without further purification. Sample proteins were resolved with two-dimensional gel electrophoresis using the 20 x 25 cm ISO-DALT ® 2-D system (Anderson et al, Electrophoresis 12:907-930, 1991). Eight μl of solubilized sample were applied to each gel, and the gels were run for 25,050 volt-hours using a progressively increasing voltage with a high-voltage programmable power supply. An Angelique™ computer-controlled gradient-casting system (Large Scale Biology Corporation, Rockville, MD) was used to prepare the second-dimension SDS slab gels. The top 5% of each gel was 11%T acrylamide and the lower 95% of the gel varied linearly from 11% to 19%T. The IEF gels were loaded directly onto the slab gels using an equilibration buffer with a blue tracking dye and were held in place with a 1% agarose overlay. Second-dimensional slab gels were run overnight at 160 V in cooled DALT tanks (10°C) with buffer circulation and were taken out when the tracking dye reached the bottom of the gel. Following SDS electrophoresis, the slab gels were fixed overnight in 1.5 liters/10 gels of 50% ethanol/3% phosphoric acid and then washed three times for 30 min in 1.5 liters/ 10 gels of cold DI water. They were transferred to 1.5 liters/10 gels of 34% methanol/17% ammonium sulfate/3% phosphoric acid for one hour, and after the addition of one gram powdered Coomassie Blue G-250, the gels were stained for three days to achieve equilibrium intensity. Stained slab gels were scanned and digitized in red light at 133 micron resolution, using an Eikonix 1412 scanner and images were processed using the Kepler ® software system as described (Richardson et al., Carcinogenesis 14(2):325-329, 1994). Groupwise statistical comparisons were made to search for treatment-related protein abundance changes. EXAMPLE 2: IDENTIFICATION OF PROTEIN MARKERS Gel pieces containing the proteins of interest were excised manually from a Coomassie-stained gel and placed in a 96-well polypropylene microtiter plate. Samples were in-gel digested with trypsin according to the procedure of Shevchenko et al., Analytical Chemistry 68:850-858 (1996), with slight modifications. Briefly, the excised samples were destained by two 60 min cycles of bath sonication in 0.2 M NH 4 HCO 3 in 50% CH 3 CN with the resulting solution aspirated after each cycle. A volume of 0.2 M NH HCO 3 in 50% CH 3 CN to sufficiently cover the gel pieces was added. Reduction and alkylation were accomplished by adding 135 nmol DTT and incubating at 37°C for 20 min. After cooling, 400 nmol of iodoacetamide were added and incubated at room temperature in the dark for 20 min. The supernatant was removed and the samples were washed for 15 min in 0.2 M NH 4 HCO 3 in 50% CH 3 CN. The gel pieces were dried at 37°C for 15 min and partially rehydrated with 5 μl 0.2 M NH 4 HCO 3 . After dispensing 3 μl of trypsin (30 ng/μl), the samples were incubated at room temperature for 5 min. A sufficient volume of 0.2 M NH 4 HCO was added to ensure complete submersion of the gel pieces in the digestion buffer. Samples were incubated overnight at 37°C. All samples were acidified with 1 μl glacial acetic acid. Tryptic peptides were extracted by initially transferring the digest supernatant to a clean 96-well polypropylene microtiter plate with two subsequent extraction and transfer cycles of 60 μl of 60% CH 3 CN, 1% glacial acetic acid. The combined extraction supernatant was dried and reconstituted in 6 μl 1% glacial acetic acid for subsequent mass spectral analysis. All samples were prepared using -cyano-4-hydroxycinnamic acid as the MALDI matrix utilizing the dried droplet method, Karas et al., Analytical Chemistry 60:2299-2301. The matrix solution was saturated in 40% CH 3 CN, 0.1% trifluoroacetic acid (TFA) in water. The peptide solution (1.0 μl) was applied first to the smooth, sample plate target, then 1.0 μl of matrix solution was stirred in with a pipette tip and the sample allowed to air evaporate. MALDI experiments were performed on a PerSeptive Biosystems Voyager-DE STR time-of-flight mass spectrometer (2.0 m linear flight path) equipped with delayed ion extraction. A pulsed nitrogen laser (Model VSL-337ND, Laser Science, Inc.) at 337.1 nm (<4 ns FWHM pulse width) was used for all of the data acquisition. Data were acquired in the delayed ion extraction mode using a 20 kV bias potential, a 6 kV pulse and a 150 ns pulsed delay time. Dual microchannel plate (Model 3040MA, Galileo Electro-Optics Corp.) detection was utilized in the reflector mode with the ion signal recorded using a 2-GHz transient digitizer (Model TDS 540C, Tektronix, Inc.) at a rate of 1 GS/s. All mass spectra represent signal averaging of 128 laser pulses. The performance of the mass spectrometer produced sufficient mass resolution to produce the isotopic multiplet for each ion species below mass-to-charge (m/z) of 3000. The data was analyzed using GRAMS/386 software (Galactic Industries Corp.). All MALDI mass spectra were calibrated internally using masses from two trypsin autolysis products (monoisotopic masses 841.50 and 2210.10). Mass spectral peaks were determined based on a signal-to-noise (S/N) ratio of 3. Two software packages, Protein Prospector and Profound, were used to identify protein spots. The rat and mouse nomedundant (nr) database consisting of SwissProt, PIR, GeneBank and OWL was used in the searches. Parameters used in the searches included proteins less than 100 kDa, greater than 4 matching peptides and mass errors less than 45 ppm. For electrospray MS/MS, a home-built microelectrospray interface similar to an interface described by Gatlin et al., Analytical Biochemistry 263:93-101 (1998) was employed. Briefly, the interface utilizes a PEEK micro-tee (Upchurch Scientific, Oak Harbor, WA) into which one stem of the tee is inserted a 0.025" gold wire to supply the electrical connection. Spray voltage was 1.8 kV. A microcapillary column was prepared by packing 10 μm SelectPore particles (Vydac, Hesperia, CA) to a depth of 12 cm into a 75 x 360 μm fused silica capillary PicoTip (New Objectives, Cambridge, MA). The PicoTip has a 15 μm i.d. needle tip with an incorporated borosilicate glass frit. A 70 μl/min flow from a MAGIC 2002 HPLC solvent delivery system (Miclirom BioResources, Auburn, CA) was reduced using a splitting tee to achieve a column flow rate of 450 nl/min. Samples were loaded on-column utilizing an Alcott model 718 autosampler (Alcott Chromatography, Norcross, GA). HPLC flow was split prior to sample loop injection. Samples prepared for MALDI were diluted further 1:3 in 0.5% HO Ac, and 2 μl of each sample were injected on-column. Using contact closures, the HPLC triggered the autosampler to make an injection and after a set delay time, triggered the mass spectrometer to start data collection. A 12 min. gradient of 5-55% solvent B (A: 2% ACN/0.5% HO Ac, B: 90% ACN/0.5% HOAc) was selected for separation of trypsin digested peptides. Peptide analyses were performed on a Finnigan LCQ ion trap mass spectrometer (Finnigan MAT, San Jose, CA). The heated desolvation capillary was set at 150°C, and the electron multiplier at -900 V. Spectra were acquired in automated MS/MS mode with a relative collision energy (RCE) preset to 35%. To maximize data acquisition efficiency, the additional parameters of dynamic exclusion, isotopic exclusion and "top 3 ions" were incorporated into the auto-MS/MS procedure. For the "top 3 ions" parameter, an MS spectrum was taken followed by 3 MS/MS spectra corresponding to the 3 most abundant ions above threshold in the full scan. That cycle was repeated throughout the acquisition. The scan range for MS mode was set at m/z 375-1200. A parent ion default charge state of +2 was used to calculate the scan range for acquiring tandem MS. Automated analysis of peptide tandem mass spectra was performed using the SEQUEST computer algorithm (Finnigan MAT, San Jose, CA). The non-redundant (NR) protein database was obtained as an ASCII text file in FASTA format from the National Center for Biotechnology Information (NCBI). The 2DGE protein pattern of rat liver illustrates over 1000 Coomassie Blue-stained protein spots. Lovastatin treatment altered the abundance of 66 liver proteins, based on the application of the two-tailed Student's t-test (1 new, one lost, 8 with p<0.0001 and 32 with pO.OOl and 64 with p<0.005). All the statistically significant changes occurred in the group receiving 1500 ppm lovastatin in feed for 7 days, an amount similar to the high dose used in the 24-month carcinogenicity study in rats (PDR). Changes were evident in livers of rats treated with 16 ppm lovastatin for 7 days, an exposure comparable to the maximum recommended daily dose in humans, but were not of statistical significance. The proteins affected by the treatment are indicated with spot numbers and protein name in Table 1. Several proteins have been identified in the F344 rat liver reference 2-D pattern published previously (Anderson et al., Electrophoresis 16:1977-1981 (1995). The spots were identified previously by a variety of techniques. Many of the spots that were not yet identified and were affected strongly by lovastatin treatment were subjected to tryptic-digestion and identified by MALDI-MS and/or LC-MS/MS. The results are given in Tables 5 and 6 above. EXAMPLE 3: IDENTIFICATION OF OTHER ANTILIPEMIC PROTEIN MARKERS The methods of Example 1 and 2 were repeated with high and low doses of fluvastatin, simvastatin, pravastatin, niacin, gemfibrozil and probucol. For those experiments, only pharmaceutical grade compounds were used with the trademark identifying the source. Previous experiments indicated that so-called generic equivalents are not always equivalent. In each experiment, the low dose was equivalent to the daily human therapeutic dose. The results are given in Tables 1 and 2. The data from Example 2 is given as a separate column for comparison. Across compound data are presented in the tables where the protein markers with a significance of pO.OOl and of p<0.005 are indicated. EXAMPLE 4: INDENTIFICATION OF FURTHER PROTEIN MARKERS The methods of Example 1, 2 and 3 were repeated with, lovastatin, cholestyramine, high cholesterol diet and a combination of lovastatin and cholestyramine. In each experiment, the dose was equivalent to slightly higher than the maximal human therapeutic dose. The rats were somewhat older and slight experimental protocol differences were used and thus the data are not directly comparable to that of Examples 1-3. Across agent data is presented in Tables 3 and 4. It will be understood that various modifications may be made to the embodiments disclosed herein. Therefore, the above description should not be construed as limiting, but merely as exemplifications of preferred embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the claims appended hereto. All patents and references cited herein are explicitly incorporated by reference in their entirety.

Claims: What is claimed is: 1. A method for determining a degree of toxicity or efficacy of an agent comprising; exposing a tissue of interest in a subject to the agent such that the agent contacts said tissue of interest, obtaining a biological sample containing protein from said tissue of interest, measuring levels of protein markers of toxicity or efficacy in said sample, and comparing the levels of said markers to the levels of the same markers in a control sample or other sample exposed to known toxic or known effective agents to determine whether the tissue of interest in a subject is experiencing toxicity or an effective response or the degree of such responses. 2. The method of claim 1 wherein the protein toxicity or efficacy markers are selected from the group consisting of the markers in Table 8. 3. The method of claim 2 wherein the protein toxicity or efficacy markers are selected from the group consisting of the markers in Table 9, alanine aminotransferase (MSN 204), and MSN 1255. 4. The method of claim 1 further comprising; measuring levels of individual proteins in a proteome of said biological sample from the tissue of interest, comparing these levels with levels of the same proteins in the proteome from a sample from a tissue of interest from a control subject or a subject treated with one or more other agents known to be toxic or effective, and detecting which proteins are increased or decreased by a statistically significant amount. 5. The method of claim 4 wherein the statistically significant amount is determined as ap<0.01. 6. The method of claim 5 wherein p<0.001. 7. The method of claim 1 wherein the agent is a pharmaceutical and it is given in a pharmaceutically appropriate amount. 8. The method of claim 1 wherein the agent is a drug. 9. The method of claim 1 wherein the levels of protein markers determines the relative amount of toxicity or effectiveness. 10. The method of claim 1 wherein the levels of protein markers in the test biological sample is compared to the levels of the same protein markers in biological samples exposed to a known effective agent or known toxic agent. 11. The method of claim 4 wherein the levels of protein markers in the test biological sample is compared to the levels of the same protein markers in biological samples exposed to a known effective agent or known toxic agent. 12. The method of claim 4 wherein said proteome is prepared by two-dimensional electrophoresis. 13. The method of claim 1 wherein the comparing is to the control and the control is a biological sample contain protein from the same tissue of interest before the tissue of interest is exposed to the agent. 14. A protein toxicity or efficacy marker selected from the proteins of Table 8. 15. A protein toxicity or efficacy marker of claim 14 selected from the list in Table 9, alanine aminotransferase (MSN 204), and MSN 1255. 16. A binding reagent specific for a protein selected from the group consisting of protein toxicity or efficacy markers of claim 14 bound to a detectable label. 17. A binding reagent specific for a protein selected from the group consisting of protein toxicity or efficacy markers of claim 15. 18. A method of monitoring efficacy or toxicity in a subj ect exposed to an agent comprising; measuring the quantity or level of one or more protein toxicity or efficacy marker of claim 14. 19. A method of monitoring efficacy or toxicity in a subject exposed to an agent comprising; measuring the quantity or level of one or more protein toxicity or efficacy marker of claim 15. 20. A protein selected from the group consisting of proteins listed in Table 9, alanine aminotransferase (MSN 204), and MSN 1255. 21. A protein according to claim 20 in isolated form. 22. A binding reagent specific for the protein of claim 20. 23. The binding agent of claim 22 bound to a detectable label. 24. A method for screening candidate compounds for blood cholesterol regulating activity comprising; contacting a candidate compound with a tissue of interest, measuring the level of a protein marker of Table 8, and comparing the level of protein marker to the level of protein marker in a control tissue of interest or a tissue of interest contacted with a known anti-cholesterol synthesis agent, wherein said protein marker is not HMG-CoA synthase or HMG-CoA reductase. 25. The method according to claim 24 wherein said protein marker is isopentenyl-diphosphate delta-isomerase. 26. A pharmaceutical composition for reducing blood cholesterol levels comprising; a modifier of the level of or the activity of a protein marker of Table 8, wherein said protein marker is not HMG-CoA synthase or HMG-CoA reductase, and a pharmaceutically acceptable carrier, wherein said modifier was identified by the process of claim 24. 27. A method for reducing blood cholesterol levels comprising administering the pharmaceutical composition of claim 26 to a cell producing said protein marker. 28. The method of claim 27 wherein the cell is in an intact animal. 29. The pharmaceutical composition of claim 26 wherein said protein marker is isopentenyl-diphosphate delta-isomerase. 30. A method for screening candidate compounds for blood cholesterol regulating activity comprising; contacting a candidate compound with a protein marker of Table 8, measuring the activity of said protein marker or the binding of said compound to said protein marker, and selecting for further development those compounds which effect activity or bind, wherein said protein marker is not HMG-CoA synthase or HMG-CoA reductase. 31. The method according to claim 30 wherein said protein marker is isopentenyl-diphosphate delta-isomerase. 32. A pharmaceutical composition for reducing blood cholesterol levels comprising; a modifier of the synthesis of or the activity of a protein marker of Table 8, wherein said protein marker is not HMG-CoA synthase or HMG-CoA reductase, and a pharmaceutically acceptable carrier, wherein said modifier was identified by or produced by the process of claim 30. 33. A method of identifying biological pathways in a cell affected by the action of an agent, comprising; a) obtaining at least two biological samples, one containing protein from a subject, tissue or cells exposed to said agent, and one containing protein from a subject, tissue or cells not exposed to said agent, b) determining levels of proteins in the proteome from each biological sample, c) comparing the levels of each protein in said proteomes, d) determining which proteins have statistically significantly higher or lower levels in each sample, e) identifying a plurality of the determined proteins, and f) deducing which biological pathways are affected based on the identities of said proteins, wherein said biological pathways contain at least one protein having a statistically significantly higher or lower level in a comparison between the two samples. 34. The method of 33 wherein one sample has a combination of two or more protein markers which have statistically significantly higher or lower levels than the same combination of protein markers in the other sample. 35. The method of claim 34 wherein the method is performed on at least three samples, one exposed to a known therapeutic amount or concentration, one exposed to a known toxic amount or concentration of the agent and one unexposed. 36. A standardized two-dimensional electrophoretic distribution of proteins from a biological sample from a subject or tissue of interest exposed to a drug at a toxic amount or concentration. 37. A set of plural standardized two-dimensional electrophoretic distributions of proteins from biological samples from subjects or tissues of interest exposed to each of a plurality of pharmaceuticals wherein each pharmaceutical is indicated for the same condition. 38. A method for identifying a toxic response marker to an agent comprising: contacting a first test animal or tissue of interest with a dosage of said agent known not to cause toxicity, contacting a second test animal or tissue of interest with a dosage of said agent known to cause toxicity, obtaining a biological sample from said first, second and control test animals or tissues of interest, where the control is not contacted with said agent, measuring the level of each protein in a proteome in a biological sample from each test animal, comparing the levels between test animals to determine statistically significant differences for each protein or combination of proteins, wherein proteins with statistically significant differences between toxic and both non-toxic dosages and controls are toxicity markers. 39. A method for identifying a toxicity or efficacy marker for an agent according to claim 38 wherein the dosage of said agent known to not cause toxicity is an effective dose. 40. A protein toxicity marker identified by the method of claim 38. 41. A method of monitoring toxicity in a subj ect exposed to an agent comprising; measuring the quantity or level of one or more toxicity markers determined by the method of claim 38. 42. A binding reagent specific for a protein toxicity marker of claim 40. 43. The binding reagent of claim 42 bound to a detectable label. 44. A method for evaluating the toxicity or efficacy of a drug comprising; determining the presence or level of at least one protein marker indicative of toxicity or efficacy in a biological sample from a subject receiving said antilipemic agent, comparing the level to a standard level of said at least one marker, wherein detection of an abnormal level of the at least one marker is indicative of toxicity or efficacy. 45. The method according to claim 44 wherein the protein marker is selected from the group consisting of protein markers of Table 8. 46. The method according to claim 44 wherein the protein marker is selected from the group consisting of protein markers of Table 9, alanine aminotransferase (MSN 204), and MSN 1255. 47. The method according to claim 44 wherein the proteome of the biological sample is measured. 48. A method for determining drug toxicity or efficacy susceptibility markers comprising, obtaining biological samples from 1) individuals lαiown to respond well to the drug and 2) individuals known to experience toxicity from the drug, measuring levels of the protein markers for each biological sample, detecting which toxicity or efficacy markers are increased or decreased above a statistically significant amount thereby determining toxicity or efficacy susceptibility markers. 49. A method for determining drug toxicity or efficacy susceptibility markers according to claim 48 further comprising, measuring levels of individual proteins in the total proteome of each biological sample, comparing these levels of proteins of the total proteome from one type of biological sample to another type, wherein proteins that are increased or decreased above a statistically significant amount are thereby determined to be toxicity or efficacy susceptibility markers. 50. A method for determining whether an individual is susceptible to toxicity or effective activity from a drug comprising; obtaining a biological sample from the individual, measuring the levels of the toxicity or efficacy susceptibility markers of claim 49, and comparing the level of each marker to previously determined standards from claim 49 to determine the individual's susceptibility to toxicity of the particular drug. 51. Protein susceptibility markers produced by the process of claim 48. 52. Protein susceptibility markers produced by the process of claim 49. 53. A binding reagent specific for a protein susceptibility markers of claim 51. 54. A binding reagent specific for a protein susceptibility markers of claim 52. 55. A method for determining whether a protein is a protein marker of efficacy or toxicity for an agent when the protein is not a statistically significant marker comprising; a) determining protein markers for an agent of interest that have an altered level but with statistical significance less than an acceptable specified threshold by themselves, b) repeating step a) with at least one related agent of interest, c) comparing a list of protein markers from said agent of interest and a list from said related agent of interest, wherein protein markers in common are considered protein markers for a group of related agents. 56. The method of claim 55 wherein said agent of interest and said related agent of interest are chemically related. 57. The method of claim 55 wherein said agent of interest and said related agent of interest have at least one common mechanism of action. 58. The method of claim 55 wherein said group of related agents are drugs. 59. The method of claim 55 wherein said related agent of interest is a drug used for comparable indications but functions by a different intended mechanism of action. 60. Protein markers produced by the method of claim 55. 61. A binding reagent specific for a protein marker of claim 60. 62. A method for determining whether a combination of proteins together form a protein marker of efficacy or toxicity for an agent when the proteins individually are not markers with a desired level of statistical significance, comprising; determining proteins which are at altered levels in biological samples from an animal treated with an agent of interest and control biological samples from an animal not treated with an agent of interest, which proteins are less than the desired level for statistically significant markers by themselves, selecting two or more of said proteins, combining the values for two or more of said proteins and determining whether the combination of values is altered in a statistically significant manner, wherein said combination of proteins results in the desired level of statistically significant differences between biological samples from treated animals and biological samples from untreated animals. 63. The method of claim 62 wherein said agent of interest and said related agent of interest are chemically related. 64. The method of claim 62 wherein said agent of interest and said related agent of interest have at least one common mechanism of action. 65. The method of claim 62 wherein said group of related agents are drugs. 66. The method of claim 62 wherein said related agent of interest is a drug used for comparable indications but functions by a different intended mechanism of action. 67. A composition comprising the combination of proteins of claim 62 forming the protein marker. 68. A method for finding drug development targets for a known physiological activity comprising; exposing a tissue of interest to an agent having a known physiological activity, measuring the level of each protein in a proteome of a biological sample containing protein from said tissue of interest, comparing the level of each protein to the level in a control biological sample, determining which proteins are found in a statistically significant abnormal amount thereby indicating them to be protein markers, and determining which of the protein markers is involved in the same metabolic pathway as said agent, thereby indicating these to be drug development targets. 69. Drug development targets determined by the method of claim 68. 70. A binding reagent specific for the drug development targets of claim 69. 71. The binding reagent of claim 70 bound to a detectable label. 72. The drug development targets of claim 69 selected from those of Table 8. 73. The drug development targets of claim 72 selected from those of Table 8. 74. A method for determining whether a protein is a protein marker of efficacy or toxicity for an agent when the protein is not a statistically significant marker comprising; a) determining protein markers for an agent of interest and protein submarkers that have an altered level but are altered to less than a statistically significant amount by themselves, b) comparing the level and direction of change of protein markers with the protein submarkers, c) repeating steps a) and b) on a different biological sample from a different individual, and d) comparing the protein submarker's altered level between different individuals, wherein protein submarkers that are altered in tandem consistently with protein markers in level and direction or opposite direction are themselves considered protein markers. 75. Protein markers produced by the method of claim 74. 76. A binding reagent specific for a protein marker of claim 74. 77. A method for generating an index marker for a particular physiological state comprising; determining protein markers which differ in a statistically significant manner between biological samples from an animal treated with an agent of interest and a control biological sample from an animal not treated with an agent of interest, which proteins are statistically significant protein markers by themselves, selecting two or more of said protein markers, combining the values for two or more of said protein markers and determining whether the combination of values is altered in a manner of greater statistical significance. 78. An index marker determined by the process of claim 77. 79. An antisense compound capable of inhibiting expression of a gene listed in Table 8 but not Table 9. 80. A method for confirming protein markers or determining a metabolic pathway comprising; contacting the tissue of interest with the antisense compound of claim 79, and measuring a change in the levels of proteins in the proteome of the tissue of interest. 81. A method for determining whether plural pharmaceuticals act in an additive or synergistic manner comprising; exposing a tissue of interest to a first pharmaceutical and obtaining a protein containing sample thereof, exposing a tissue of interest to a first pharmaceutical and a second pharmaceutical and obtaining a protein containing sample thereof, measuring the levels of protein markers in each sample, comparing the changes in levels of protein markers between tissues of interest exposed to a first pharmaceutical and tissues of interest exposed to a first and second pharmaceutical and determining whether the effects of said first pharmaceutical and said second pharmaceutical is cumulative or synergistic. 82. A pharmaceutical composition comprising said first pharmaceutical and said second pharmaceutical when the effects are more than additive as determined by the method of claim 81. 83. A method for determining a reaction to an agent comprising; exposing a tissue of interest in a subject to the agent such that the agent contacts said tissue of interest, obtaining a biological sample containing protein from said tissue of interest, measuring levels of protein markers of change in said sample, and comparing the levels of said markers to the levels of said markers in biological samples from one or more of the following controls treated with an agent having the same efficacy mechanism of action, an agent having the opposite efficacy mechanism of action, an agent having an mirelated mechanism of action, an agent having the same toxicity mechanism of action, an agent having the opposite toxicity mechanism of action, and an agent having an mirelated toxicity mechanism of action. 84. The method of claim 83 wherein the data for an agent having mirelated mechanisms of action is a composite agents selected from a database of plural agents believed to have unrelated mechanisms of action. 85. A database comprising a plurality of data elements identifiable by a plurality of parameters, wherein said data elements comprise data of a polypeptide or a protein that differs in a proteome before and after exposure to a compound, wherein said parameters comprise molecular weight, isoelectric point and correlation with a positive or a negative phenotype in a host comprising said data elements. 86. The database of claim 85, wherein said compound is a drug or a candidate drug. 87. The database of claim 86, wherein said drug is an antilipemic drug. 88. The database of claim 85, wherein said positive phenotype is amelioration of a pathologic symptom in said host. 89. The database of claim 85, wherein said negative phenotype is an unwanted side effect in said host exposed to said compound.

Inventors: ANDERSON N LEIGH, STEINER SANDRA, ANDERSON, N., LEIGH, STEINER, SANDRA
Applicants: ANDERSON N LEIGH, LARGE SCALE PROTEOMICS CORP, STEINER SANDRA, ANDERSON, N., LEIGH, LARGE SCALE PROTEOMICS CORP., STEINER, SANDRA
Application year: 2001
Main classification: C12Q1
IPC codes: A61K38, A61K45, A61P3, A61P9, A61P43, C12N15, C12Q1