Chemogenomics

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Chemogenomics Staubli robot retrieves assay plates from incubators Chemical Genomics Robot.jpg
Chemogenomics Staubli robot retrieves assay plates from incubators

Chemogenomics, or chemical genomics, is the systematic screening of targeted chemical libraries of small molecules against individual drug target families (e.g., GPCRs, nuclear receptors, kinases, proteases, etc.) with the ultimate goal of identification of novel drugs and drug targets. [1] Typically some members of a target library have been well characterized where both the function has been determined and compounds that modulate the function of those targets (ligands in the case of receptors, inhibitors of enzymes, or blockers of ion channels) have been identified. Other members of the target family may have unknown function with no known ligands and hence are classified as orphan receptors. By identifying screening hits that modulate the activity of the less well characterized members of the target family, the function of these novel targets can be elucidated. Furthermore, the hits for these targets can be used as a starting point for drug discovery. The completion of the human genome project has provided an abundance of potential targets for therapeutic intervention. Chemogenomics strives to study the intersection of all possible drugs on all of these potential targets. [2]

Contents

A common method to construct a targeted chemical library is to include known ligands of at least one and preferably several members of the target family. Since a portion of ligands that were designed and synthesized to bind to one family member will also bind to additional family members, the compounds contained in a targeted chemical library should collectively bind to a high percentage of the target family. [3]

Strategy

Chemogenomics integrates target and drug discovery by using active compounds, which function as ligands, as probes to characterize proteome functions. The interaction between a small compound and a protein induces a phenotype. Once the phenotype is characterized, we could associate a protein to a molecular event. Compared with genetics, chemogenomics techniques are able to modify the function of a protein rather than the gene. Also, chemogenomics is able to observe the interaction as well as reversibility in real-time. For example, the modification of a phenotype can be observed only after addition of a specific compound and can be interrupted after its withdrawal from the medium.

Currently, there are two experimental chemogenomic approaches: forward (classical) chemogenomics and reverse chemogenomics. Forward chemogenomics attempt to identify drug targets by searching for molecules which give a certain phenotype on cells or animals, while reverse chemogenomics aim to validate phenotypes by searching for molecules that interact specifically with a given protein. [4] Both of these approaches require a suitable collection of compounds and an appropriate model system for screening the compounds and looking for the parallel identification of biological targets and biologically active compounds. The biologically active compounds that are discovered through forward or reverse chemogenomics approaches are known as modulators because they bind to and modulate specific molecular targets, thus they could be used as ‘targeted therapeutics’. [1]

Forward chemogenomics

In forward chemogenomics, which is also known as classical chemogenomics, a particular phenotype is studied and small compound interacting with this function are identified. The molecular basis of this desired phenotype is unknown. Once the modulators have been identified, they will be used as tools to look for the protein responsible for the phenotype. For example, a loss-of-function phenotype could be an arrest of tumor growth. Once compounds that lead to a target phenotype have been identified, identifying the gene and protein targets should be the next step. [5] The main challenge of forward chemogenomics strategy lies in designing phenotypic assays that lead immediately from screening to target identification.

Reverse chemogenomics

In reverse chemogenomics, small compounds that perturb the function of an enzyme in the context of an in vitro enzymatic test will be identified. Once the modulators have been identified, the phenotype induced by the molecule is analyzed in a test on cells or on whole organisms. This method will identify or confirm the role of the enzyme in the biological response. [5] Reverse chemogenomics used to be virtually identical to the target-based approaches that have been applied in drug discovery and molecular pharmacology over the past decade. This strategy is now enhanced by parallel screening and by the ability to perform lead optimization on many targets that belong to one target family.

Applications

Determining mode of action

Chemogenomics has been used to identify mode of action (MOA) for traditional Chinese medicine (TCM) and Ayurveda. Compounds contained in traditional medicines are usually more soluble than synthetic compounds, have “privileged structures” (chemical structures that are more frequently found to bind in different living organisms), and have more comprehensively known safety and tolerance factors. Therefore, this makes them especially attractive as a resource for lead structures in when developing new molecular entities. Databases containing chemical structures of compounds used in alternative medicine along with their phenotypic effects, in silico analysis may be of use to assist in determining MOA for example, by predicting ligand targets that were relevant to known phenotypes for traditional medicines. [6] In a case study for TCM, the therapeutic class of ‘toning and replenishing medicine” was evaluated. Therapeutic actions (or phenotypes) for that class include anti-inflammatory, antioxidant, neuroprotective, hypoglycemic activity, immunomodulatory, antimetastatic, and hypotensive. Sodium-glucose transport proteins and PTP1B (an insulin signaling regulator) were identified as targets which link to the hypoglycemic phenotype suggested. The case study for Ayurveda involved anti-cancer formulations. In this case, the target prediction program enriched for targets directly connected to cancer progression such as steroid-5-alpha-reductase and synergistic targets like the efflux pump P-gp. These target-phenotype links can help identify novel MOAs.

Beyond TCM and Ayurveda, chemogenomics can be applied early in drug discovery to determine a compound's mechanism of action and take advantage of genomic biomarkers of toxicity and efficacy for application to Phase I and II clinical trials. [7]

Identifying new drug targets

Chemogenomics profiling can be used to identify totally new therapeutic targets, for example new antibacterial agents. [8] The study capitalized on the availability of an existing ligand library for an enzyme called murD that is used in the peptidoglycan synthesis pathway. Relying on the chemogenomics similarity principle, the researchers mapped the murD ligand library to other members of the mur ligase family (murC, murE, murF, murA, and murG) to identify new targets for the known ligands. Ligands identified would be expected to be broad-spectrum Gram-negative inhibitors in experimental assays since peptidoglycan synthesis is exclusive to bacteria. Structural and molecular docking studies revealed candidate ligands for murC and murE ligases.

Identifying genes in biological pathway

Thirty years after the posttranslationally modified histidine derivative diphthamide was determined, chemogenomics was used to discover the enzyme responsible for the final step in its synthesis. [9] Dipthamide is a posttranslationally modified histidine residue found on the translation elongation factor 2 (eEF-2). The first two steps of the biosynthesis pathway leading to dipthine have been known, but the enzyme responsible for the amidation of dipthine to diphthamide remained a mystery. The researchers capitalized on Saccharomyces cerevisiae cofitness data. Cofitness data is data representing the similarity of growth fitness under various conditions between any two different deletion strains. Under the assumption that strains lacking the diphthamide synthetase gene should have high cofitness with strain lacking other diphthamide biosynthesis genes, they identified ylr143w as the strain with the highest cofitness to the all other strains lacking known diphthamide biosynthesis genes. Subsequent experimental assays confirmed that YLR143W was required for diphthamide synthesis and was the missing diphthamide synthetase.

See also

Related Research Articles

Allosteric regulation Regulation of enzyme activity

In biochemistry, allosteric regulation is the regulation of an enzyme by binding an effector molecule at a site other than the enzyme's active site.

Within the fields of molecular biology and pharmacology, a small molecule or micromolecule is a low molecular weight organic compound that may regulate a biological process, with a size on the order of 1 nm. Many drugs are small molecules; the terms are equivalent in the literature. Larger structures such as nucleic acids and proteins, and many polysaccharides are not small molecules, although their constituent monomers are often considered small molecules. Small molecules may be used as research tools to probe biological function as well as leads in the development of new therapeutic agents. Some can inhibit a specific function of a protein or disrupt protein–protein interactions.

Chemical specificity is the ability of binding site of a macromolecule to bind specific ligands. The fewer ligands a protein can bind, the greater its specificity.

Binding site Molecule-specific coordinate bonding area in biological systems

In biochemistry and molecular biology, a binding site is a region on a macromolecule such as a protein that binds to another molecule with specificity. The binding partner of the macromolecule is often referred to as a ligand. Ligands may include other proteins, enzyme substrates, second messengers, hormones, or allosteric modulators. The binding event is often, but not always, accompanied by a conformational change that alters the protein's function. Binding to protein binding sites is most often reversible, but can also be covalent reversible or irreversible.

Drug discovery Process by which new candidate medications are discovered

In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which new candidate medications are discovered.

Drug design Inventive process of finding new medications based on the knowledge of a biological target

Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals including peptides and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.

A biological target is anything within a living organism to which some other entity is directed and/or binds, resulting in a change in its behavior or function. Examples of common classes of biological targets are proteins and nucleic acids. The definition is context-dependent, and can refer to the biological target of a pharmacologically active drug compound, the receptor target of a hormone, or some other target of an external stimulus. Biological targets are most commonly proteins such as enzymes, ion channels, and receptors.

Docking (molecular)

In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when a ligand and a target are bound to each other to form a stable complex. Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using, for example, scoring functions.

In biology, cell signaling or cell communication is the ability of a cell to receive, process, and transmit signals with its environment and with itself. Cell signaling is a fundamental property of all cellular life in prokaryotes and eukaryotes. Signals that originate from outside a cell can be physical agents like mechanical pressure, voltage, temperature, light, or chemical signals. Chemical signals can be hydrophobic or hydrophilic. Cell signaling can occur over short or long distances, and as a result can be classified as autocrine, juxtacrine, intracrine, paracrine, or endocrine. Signaling molecules can be synthesized from various biosynthetic pathways and released through passive or active transports, or even from cell damage.

Mechanism of action Biochemical interaction through which a drug produces its pharmacological effect

In pharmacology, the term mechanism of action (MOA) refers to the specific biochemical interaction through which a drug substance produces its pharmacological effect. A mechanism of action usually includes mention of the specific molecular targets to which the drug binds, such as an enzyme or receptor. Receptor sites have specific affinities for drugs based on the chemical structure of the drug, as well as the specific action that occurs there.

Enzyme inhibitor Molecule that binds to an enzyme and decreases its activity

An enzyme inhibitor is a molecule that binds to an enzyme and blocks its activity. Enzymes are proteins that speed up chemical reactions necessary for life, in which substrate molecules are converted into products. An enzyme facilitates a specific chemical reaction by binding the substrate to its active site, a specialized area on the enzyme that accelerates the most difficult step of the reaction.

Virtual screening

Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme.

High-content screening (HCS), also known as high-content analysis (HCA) or cellomics, is a method that is used in biological research and drug discovery to identify substances such as small molecules, peptides, or RNAi that alter the phenotype of a cell in a desired manner. Hence high content screening is a type of phenotypic screen conducted in cells involving the analysis of whole cells or components of cells with simultaneous readout of several parameters. HCS is related to high-throughput screening (HTS), in which thousands of compounds are tested in parallel for their activity in one or more biological assays, but involves assays of more complex cellular phenotypes as outputs. Phenotypic changes may include increases or decreases in the production of cellular products such as proteins and/or changes in the morphology of the cell. Hence HCA typically involves automated microscopy and image analysis. Unlike high-content analysis, high-content screening implies a level of throughput which is why the term "screening" differentiates HCS from HCA, which may be high in content but low in throughput.

Fragment-based lead discovery (FBLD) also known as fragment-based drug discovery (FBDD) is a method used for finding lead compounds as part of the drug discovery process. Fragments are small organic molecules which are small in size and low in molecular weight. It is based on identifying small chemical fragments, which may bind only weakly to the biological target, and then growing them or combining them to produce a lead with a higher affinity. FBLD can be compared with high-throughput screening (HTS). In HTS, libraries with up to millions of compounds, with molecular weights of around 500 Da, are screened, and nanomolar binding affinities are sought. In contrast, in the early phase of FBLD, libraries with a few thousand compounds with molecular weights of around 200 Da may be screened, and millimolar affinities can be considered useful. FBLD is a technique being used in research for discovering novel potent inhibitors. This methodology could help to design multitarget drugs for multiple diseases. The multitarget inhibitor approach is based on designing an inhibitor for the multiple targets. This type of drug design opens up new polypharmacological avenues for discovering innovative and effective therapies. Neurodegenerative diseases like Alzheimer’s (AD) and Parkinson’s, among others, also show rather complex etiopathologies. Multitarget inhibitors are more appropriate for addressing the complexity of AD and may provide new drugs for controlling the multifactorial nature of AD, stopping its progression.

Cell surface receptor Class of ligand activated receptors localized in surface of plama cell membrane

Cell surface receptors are receptors that are embedded in the plasma membrane of cells. They act in cell signaling by receiving extracellular molecules. They are specialized integral membrane proteins that allow communication between the cell and the extracellular space. The extracellular molecules may be hormones, neurotransmitters, cytokines, growth factors, cell adhesion molecules, or nutrients; they react with the receptor to induce changes in the metabolism and activity of a cell. In the process of signal transduction, ligand binding affects a cascading chemical change through the cell membrane.

Druggability is a term used in drug discovery to describe a biological target that is known to or is predicted to bind with high affinity to a drug. Furthermore, by definition, the binding of the drug to a druggable target must alter the function of the target with a therapeutic benefit to the patient. The concept of druggability is most often restricted to small molecules but also has been extended to include biologic medical products such as therapeutic monoclonal antibodies.

Chemical genetics is the investigation of the function of proteins and signal transduction pathways in cells by the screening of chemical libraries of small molecules. Chemical genetics is analogous to classical genetic screen where random mutations are introduced in organisms, the phenotype of these mutants is observed, and finally the specific gene mutation (genotype) that produced that phenotype is identified. In chemical genetics, the phenotype is disturbed not by introduction of mutations, but by exposure to small molecule tool compounds. Phenotypic screening of chemical libraries is used to identify drug targets or to validate those targets in experimental models of disease. Recent applications of this topic have been implicated in signal transduction, which may play a role in discovering new cancer treatments. Chemical genetics can serve as a unifying study between chemistry and biology. The approach was first proposed by Tim Mitchison in 1994 in an opinion piece in the journal Chemistry & Biology entitled "Towards a pharmacological genetics".

A thermal shift assay (TSA) measures changes in the thermal denaturation temperature and hence stability of a protein under varying conditions such as variations in drug concentration, buffer pH or ionic strength, redox potential, or sequence mutation. The most common method for measuring protein thermal shifts is differential scanning fluorimetry (DSF) or thermofluor, which utilizes specialized fluorogenic dyes.

Chemoproteomics entails a broad array of techniques used to identify and interrogate protein-small molecule interactions. Chemoproteomics complements phenotypic drug discovery, a paradigm that aims to discover lead compounds on the basis of alleviating a disease phenotype, as opposed to target-based drug discovery, in which lead compounds are designed to interact with predetermined disease-driving biological targets. As phenotypic drug discovery assays do not provide confirmation of a compound's mechanism of action, chemoproteomics provides valuable follow-up strategies to narrow down potential targets and eventually validate a molecule's mechanism of action. Chemoproteomics also attempts to address the inherent challenge of drug promiscuity in small molecule drug discovery by analyzing protein-small molecule interactions on a proteome-wide scale. A major goal of chemoproteomics is to characterize the interactome of drug candidates to gain insight into mechanisms of off-target toxicity and polypharmacology.

Target 2035 is a global effort or movement to discover open science, pharmacological modulator(s) for every protein in the human proteome by the year 2035. The effort is led by the Structural Genomics Consortium with the intention that this movement evolves organically. Target 2035 has been borne out of the success that chemical probes have had in elevating or de-prioritizing the therapeutic potential of protein targets. The availability of open access pharmacological tools is a largely unmet aspect of drug discovery especially for the dark proteome.

References

  1. 1 2 Bredel M, Jacoby E (Apr 2004). "Chemogenomics: an emerging strategy for rapid target and drug discovery". Nature Reviews Genetics. 5 (4): 262–75. CiteSeerX   10.1.1.411.9671 . doi:10.1038/nrg1317. PMID   15131650. S2CID   11952369.
  2. ↑ Namchuk M (2002). "Finding the molecules to fuel chemogenomics". Targets. 1 (4): 125–129. doi:10.1016/S1477-3627(02)02206-7.
  3. ↑ Caron PR, Mullican MD, Mashal RD, Wilson KP, Su MS, Murcko MA (Aug 2001). "Chemogenomic approaches to drug discovery". Current Opinion in Chemical Biology. 5 (4): 464–70. doi:10.1016/S1367-5931(00)00229-5. PMID   11470611.
  4. ↑ Ambroise Y. "Chemogenomic techniques". Archived from the original on 23 August 2013. Retrieved 28 July 2013.
  5. 1 2 Wuster A, Madan Babu M (May 2008). "Chemogenomics and biotechnology". Trends in Biotechnology. 26 (5): 252–8. doi:10.1016/j.tibtech.2008.01.004. PMID   18346803.
  6. ↑ Mohd Fauzi F, Koutsoukas A, Lowe R, Joshi K, Fan TP, Glen RC, Bender A (Mar 2013). "Chemogenomics approaches to rationalizing the mode-of-action of traditional Chinese and Ayurvedic medicines". Journal of Chemical Information and Modeling. 53 (3): 661–73. doi:10.1021/ci3005513. PMID   23351136.
  7. ↑ Engelberg A (Sep 2004). "Iconix Pharmaceuticals, Inc.--removing barriers to efficient drug discovery through chemogenomics". Pharmacogenomics. 5 (6): 741–4. doi:10.1517/14622416.5.6.741. PMID   15335294.
  8. ↑ Bhattacharjee B, Simon RM, Gangadharaiah C, Karunakar P (Jun 2013). "Chemogenomics profiling of drug targets of peptidoglycan biosynthesis pathway in Leptospira interrogans by virtual screening approaches". Journal of Microbiology and Biotechnology. 23 (6): 779–84. doi:10.4014/jmb.1206.06050. PMID   23676922.
  9. ↑ Cheung-Ong K, Song KT, Ma Z, Shabtai D, Lee AY, Gallo D, Heisler LE, Brown GW, Bierbach U, Giaever G, Nislow C (Nov 2012). "Comparative chemogenomics to examine the mechanism of action of dna-targeted platinum-acridine anticancer agents". ACS Chemical Biology. 7 (11): 1892–901. doi:10.1021/cb300320d. PMC   3500413 . PMID   22928710.

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