Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome

Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer''s disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover “behind-the-scenes” aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm.     

Mechanistic basis of enzyme-targeted drugs

Enzymes offer unique opportunities for drug design that are not available to cell surface receptors, nuclear hormone receptors, ion channels, transporters, and DNA. Here, we review the variety of inhibition mechanisms for enzyme-targeted drugs, and establish an enzyme target database for drugs currently marketed in the United States. From an analysis of the FDA Orange Book, there are 317 marketed drugs that work by inhibiting an enzyme. These drugs inhibit 71 enzymes, including 48 human, 13 bacterial, five viral, four fungal, and one protozoal enzyme. Among the 317 drugs, 65% either undergo reactive chemistry in the active site of the target enzyme or contain a structural motif related to the substrate. Among the 71 enzyme targets, 25 are irreversibly inhibited by drugs, and 19 of the 25 irreversibly inhibited enzymes are covalently modified by the drug. In two additional cases, the drug forms a covalent complex with the substrate, and in three more cases, the drug traps a covalent enzyme-substrate intermediate. Four of the 71 enzymes are inhibited by transition-state analogues. Moreover, advanced methods for determining transition-state structure now offer the opportunity for direct drug design without resorting to expensive random testing campaigns. A full appreciation of enzyme mechanisms sets enzymes apart as a specialized class of targets for highly directed drug design.     

Drugging the undruggables: exploring the ubiquitin system for drug development

Dynamic modulation of protein levels is tightly controlled in response to physiological cues. In mammalian cells, much of the protein degradation is carried out by the ubiquitin-proteasome system (UPS). Similar to kinases, components of the ubiquitin system are often dysregulated, leading to a variety of diseases, including cancer and neurodegeneration, making them attractive drug targets. However, so far there are only a handful of drugs targeting the ubiquitin system that have been approved by the FDA. Here, we review possible therapeutic intervention nodes in the ubiquitin system, analyze the challenges, and highlight the most promising strategies to target the UPS.     

Study of drug function based on similarity of pathway fingerprint

Drugs sharing similar therapeutic function may not bind to the same group of targets. However, their targets may be involved in similar pathway profiles which are associated with certain pathological process. In this study, pathway fingerprint was introduced to indicate the profile of significant pathways being influenced by the targets of drugs. Then drug-drug network was further constructed based on significant similarity of pathway fingerprints. In this way, the functions of a drug may be hinted by the enriched therapeutic functions of its neighboring drugs. In the test of 911 FDA approved drugs with more than one known target, 471 drugs could be connected into networks. 760 significant associations of drug-therapeutic function were generated, among which around 60% of them were supported by scientific literatures or ATC codes of drug functional classification. Therefore, pathway fingerprints may be useful to further study on the potential function of known drugs, or the unknown function of new drugs.     

Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets

Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state “signature”. These modules were significantly enriched for genes that are known to be drug targets. Interestingly, drugs known to target these genes/proteins are already known to treat significantly more diseases than drugs targeting other genes/proteins, highlighting the importance of these core modules as prime therapeutic opportunities.     

Can medical genetics and evolutionary biology inspire drug target identification?

New strategies for target identification are urgently needed to tackle the current productivity challenges in drug discovery. By examining successful human drug targets, it can be seen that approximately 50% are associated with genetic disorders. Further analysis shows that these successfully targeted genes share some common evolutionary features, which strongly suggests that evolutionary information can help identify drug targets with the greatest potential for therapeutic development.     

Antibodies directed against receptor tyrosine kinases

Approximately 30 therapeutic monoclonal antibodies have already been approved for cancers and inflammatory diseases, and monoclonal antibodies continue to be one of the fastest growing classes of therapeutic molecules. Because aberrant signaling by receptor tyrosine kinases (RTKs) is a commonly observed factor in cancer, most of the subclasses of RTKs are being extensively studied as potential targets for treating malignancies. The first two RTKs that have been targeted by antibody therapy, with five currently marketed antibodies, are the growth factor receptors EGFR and HER2. However, due to systemic side effects, refractory patients and the development of drug resistance, these treatments are being challenged by emerging therapeutics. This review examines current monoclonal antibody therapies against RTKs. After an analysis of agents that have already been approved, we present an analysis of antibodies in clinical development that target RTKs. Finally, we highlight promising RTKs that are emerging as new oncological targets for antibody-based therapy.     

Exploration of Target Spaces in the Human Genome for Protein and Peptide Drugs

After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However,owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target s...     

Metabolic targeted therapy of cancer: current tracer technologies and future drug design strategies in the old metabolic network

Targeted drugs tailored against genes and signaling proteins have formed the new era termed Targeted Therapies. Although the field is relatively young, since only about 5 years ago clinical trials started showing promise, there have are already been significant setbacks due to drug resistance caused by point mutations, alterations in gene expression or complete loss of target proteins with disease progression. Although new drugs are continuously designed and tried, it seems inevitable that genetic and signal protein targets pose too broad flexibility and variability, often changing target characteristics and thus escape treatments turning “magic bullets” into rather “wondering bullets”. This is especially true in cancer, where old and new targeted therapies continue to fail and the most recent ones do not offer much improvement on clinical outcome parameters. Metabolic targeted therapies are aimed at control points of the metabolic network by targeting particular enzymes of major macromolecule synthesis pathways in cancer. This review summarizes the potential benefits of targeted therapies in the metabolic network as applied with genetic and proteomic approaches. The metabolic target approach is most efficient if and when pathway flux information is available for drug target development using the stable isotope based dynamic metabolic profile (SIDMAP) of tumor cells, in vitro or in vivo.This revised version was published online in June 2005. The previous version did not contain colour images.     

Prediction of off-target effects on angiotensin-converting enzyme 2

The authors describe a structure-based strategy to identify therapeutically beneficial off-target effects by screening a chemical library of Food and Drug Administration (FDA)-approved small-molecule drugs matching pharmacophores defined for specific target proteins. They applied this strategy to angiotensin-converting enzyme 2 (ACE2), an enzyme that generates vasodilatory peptides and promotes protection from hypertension-associated cardiovascular disease. The conformation-based structural selection method by molecular docking using DOCK allowed them to identify a series of FDA-approved drugs that enhance catalytic efficiency of ACE2 in vitro. These data demonstrate that libraries of approved drugs can be rapidly screened to identify potential side effects due to interactions with specific proteins other than the intended targets.     

Current perspectives on therapeutic antibodies

Since the first monoclonal antibody, muromonab-CD3, was approved for therapeutic use in 1986, numerous molecules have been targeted using therapeutic antibody technology, resulting in 26 therapeutic antibodies being approved by the US FDA as of November, 2009. Initial concerns regarding antibody drugs focused on immunogenicity, short serum half-life, and weak efficacy. As the types of antibodies progressed from murine to chimeric, humanized, and fully human antibodies, great progress has been made in immunogenicity and in vivo instability issues. For example, humanized antibodies, such as bevacizumab, exhibit less than 0.2% immunogenicity and a 20 day serum half-life, which is comparable to native immunoglobulin. Some recently developed antibodies are exceedingly efficacious and have become first-line therapy for their target diseases. Here, we address and analyze all clinically approved therapeutic antibodies to date by discussing immunogenicity, half-life, and efficacy.     

The Human Kinome Targeted by FDA Approved Multi-Target Drugs and Combination Products: A Comparative Study from the Drug-Target Interaction Network Perspective

The human kinome is one of the most productive classes of drug target, and there is emerging necessity for treating complex diseases by means of polypharmacology (multi-target drugs and combination products). However, the advantages of the multi-target drugs and the combination products are still under debate. A comparative analysis between FDA approved multi-target drugs and combination products, targeting the human kinome, was conducted by mapping targets onto the phylogenetic tree of the human kinome. The approach of network medicine illustrating the drug-target interactions was applied to identify popular targets of multi-target drugs and combination products. As identified, the multi-target drugs tended to inhibit target pairs in the human kinome, especially the receptor tyrosine kinase family, while the combination products were able to against targets of distant homology relationship. This finding asked for choosing the combination products as a better solution for designing drugs aiming at targets of distant homology relationship. Moreover, sub-networks of drug-target interactions in specific disease were generated, and mechanisms shared by multi-target drugs and combination products were identified. In conclusion, this study performed an analysis between approved multi-target drugs and combination products against the human kinome, which could assist the discovery of next generation polypharmacology.     

Drug Repositioning for Diabetes Based on 'Omics' Data Mining

Drug repositioning has shorter developmental time, lower cost and less safety risk than traditional drug development process. The current study aims to repurpose marketed drugs and clinical candidates for new indications in diabetes treatment by mining clinical ‘omics’ data. We analyzed data from genome wide association studies (GWAS), proteomics and metabolomics studies and revealed a total of 992 proteins as potential anti-diabetic targets in human. Information on the drugs that target these 992 proteins was retrieved from the Therapeutic Target Database (TTD) and 108 of these proteins are drug targets with drug projects information. Research and preclinical drug targets were excluded and 35 of the 108 proteins were selected as druggable proteins. Among them, five proteins were known targets for treating diabetes. Based on the pathogenesis knowledge gathered from the OMIM and PubMed databases, 12 protein targets of 58 drugs were found to have a new indication for treating diabetes. CMap (connectivity map) was used to compare the gene expression patterns of cells treated by these 58 drugs and that of cells treated by known anti-diabetic drugs or diabetes risk causing compounds. As a result, 9 drugs were found to have the potential to treat diabetes. Among the 9 drugs, 4 drugs (diflunisal, nabumetone, niflumic acid and valdecoxib) targeting COX2 (prostaglandin G/H synthase 2) were repurposed for treating type 1 diabetes, and 2 drugs (phenoxybenzamine and idazoxan) targeting ADRA2A (Alpha-2A adrenergic receptor) had a new indication for treating type 2 diabetes. These findings indicated that ‘omics’ data mining based drug repositioning is a potentially powerful tool to discover novel anti-diabetic indications from marketed drugs and clinical candidates. Furthermore, the results of our study could be related to other disorders, such as Alzheimer’s disease.     

Current status of targets and assays for anti-HIV drug screening

HIV/AIDS is one of the most serious public health challenges globally. Despite the great efforts that are being devoted to prevent, treat and to better understand the disease, it is one of the main causes of morbidity and mortality worldwide. Currently, there are 30 drugs or combinations of drugs approved by FDA. Because of the side-effects, price and drug resistance, it is essential to discover new targets, to develop new technology and to find new anti-HIV drugs. This review summarizes the major targets and assays currently used in anti-HIV drug screening.      

Current Status of Targets and Assays for Anti-HIV Drug Screening

HIV/AIDS is one of the most serious public health challenges globally. Despite the great efforts that are being devoted to prevent,treat and to better understand the disease,it is one of the main causes of morbidity and mortality worldwide. Currently,there are 30 drugs or combinations of drugs approved by FDA. Because of the side-effects,price and drug resistance,it is essential to discover new targets,to develop new technology and to find new anti-HIV drugs. This review summarizes the major targets and assays currently used in anti-HIV drug screening.     

Drug-target network

The global set of relationships between protein targets of all drugs and all disease-gene products in the human protein-protein interaction or 'interactome' network remains uncharacterized. We built a bipartite graph composed of US Food and Drug Administration-approved drugs and proteins linked by drug-target binary associations. The resulting network connects most drugs into a highly interlinked giant component, with strong local clustering of drugs of similar types according to Anatomical Therapeutic Chemical classification. Topological analyses of this network quantitatively showed an overabundance of 'follow-on' drugs, that is, drugs that target already targeted proteins. By including drugs currently under investigation, we identified a trend toward more functionally diverse targets improving polypharmacology. To analyze the relationships between drug targets and disease-gene products, we measured the shortest distance between both sets of proteins in current models of the human interactome network. Significant differences in distance were found between etiological and palliative drugs. A recent trend toward more rational drug design was observed.