Target Identification b)-Bioinformatics Associate Prof. Dr.rer.nat. Osama Abd
Target Identification b)-Bioinformatics Associate Prof. Dr.rer.nat. Osama Abd Elrahman Target Identification a)-Genomics 2
DNA sequence (split into genes) What is? codes for
Amino Acid Sequence folds into Protein has
3D Structure dictates Protein Function determines
Cell Activity Gene Expression: The process by which the information encoded in a gene is converted into an
observable phenotype (most commonly production of a protein). The degree to which a gene is active in a certain tissue of the body, measured by the amount of mRNA in the tissue. Microarrays: Tools used to measure the presence and abundance of gene expression in tissue.
microarray technologies provide a powerful tool by which the expression patterns of thousands of genes can be monitored simultaneously Background Gene Expression Cells are different because of differential gene expression.
About 40% of human genes are expressed at one time. Gene is expressed by transcribing DNA into single-stranded mRNA
mRNA is later translated into a protein Microarrays measure the level of mRNA expression
A Dynamic View Gene expression depends on environment! Interactions Environment Metabolites
DNA RNA Protein Growth rate Expression
Microarray Technology Microarrays, a recent development, provide a revolutionary platform to analyse thousands of genes at once. They have enormous potential in the study of biological processes in health and disease. Microarrays have become crucial tools in diagnostic applications and drug discovery. 6
normal Biomarkers and gene expression malignant Microarray based studies have provided the essential impetus for biomedical experiments, such as identification of disease-causing genes in malignancies and regulatory genes in the
cell cycle mechanism. Microarrays can identify genes for new and unique potential drug targets, predict drug responsiveness for individual patients and, finally, initiate gene therapy and prevention strategies. Perou et al. Molecular Portraits of Breast Cancer, Nature, May 2000 7 GREEN represents Control DNA, where either DNA or cDNA derived from normal tissue
is hybridized to the target DNA. RED represents Sample DNA, where either DNA or cDNA is derived from diseased tissue hybridized to the target DNA. YELLOW represents a combination of Control and Sample DNA, where both hybridized equally to the target DNA. BLACK represents areas where neither the Control nor Sample DNA hybridized to the target DNA. Each spot on an array is associated with a particular gene. Each color in an array
represents either healthy (control) or diseased (sample) tissue. The location and intensity of a color will tell us whether the gene, or mutation, is present in either the control and/or sample DNA. It will also provide an estimate of the expression level of the gene(s) in the sample and control DNA. 8 Functional Genomics: Microarrays of
Gene Expression normal Normal tissue Diseased
cDNA Diseased associated Microarray Technology Quantitative Measurement of Gene Expression
Also known as DNA microarrays, DNA arrays, DNA chips, gene chips, Whatever the name, their use is effectively transforming a living from a black box into a transparent box. Background DNA/RNA Hybridization
DNA molecules: DNA molecules are long double-stranded chains; 4 types of bases are attached to the
backbone: adenine (A), guanine (G), cytosine (C), and thymine (T). A pairs with T, C with G. DNA-RNA hybridization: When a mixture of DNA and RNA is heated to denaturation temperatures to form single strands and then cooled, RNA can hybridize (form a
double helix) with DNA that has a complementary nucleotide sequence. Microarrays Basic Idea A Microarray is a device that detects the presence and abundance of
labelled nucleic acids in a biological sample. In the majority of experiments, the labelled nucleic acids are derived from the mRNA of a sample or tissue.
The Microarray consists of a solid surface onto which known DNA molecules have been chemically bonded at special locations. Each array location is typically known as a probe and contains many replicates of the same molecule. The molecules in each array location are carefully chosen so as to hybridise only with mRNA molecules corresponding to a single gene.
Chemistry Basics: The Process Surface Chemistry is used to attach the probe molecules to the glass substrate. Chemical reactions are used to attach the florescent dyes to the target molecules
Probe and Target hybridise to form a double helix Labelled targets in solution Probes on array Heteroduplexes
Hybridisation Basic Idea A Microarray works by exploiting the ability of a given mRNA molecule to bind specifically to, or hybridize to, the DNA template from which it originated.
By using an array containing many DNA samples, scientists can determine, in a single experiment, the expression levels of hundreds or thousands of genes within a cell by measuring the amount of mRNA bound to each site on the array.
With the aid of a computer, the amount of mRNA bound to the spots on the Microarray is precisely measured, generating a profile of gene expression in the cell. Applying a Labelled Sample
The molecules in the target biological sample are labelled using a fluorescent dye before sample is applied to array If a gene is expressed in the sample, the corresponding mRNA hybridises with the molecules on a given probe (array location). If a gene is not expressed, no hybridisation occurs on the corresponding
probe. Reading the array output After the sample is applied, a laser light source is applied to the array. The fluorescent label enables the detection of which probes have hybridised (presence) via the light emitted from the probe.
If gene is highly expressed, more mRNA exists and thus more mRNA hybridises to the probe molecules (abundance) via the intensity of the light emitted. The array Steps of a Microarray Experiment 1.
Prepare DNA chip(s) by choosing probes and attaching them to glass substrate. Note location and properties of each probe. 2. Generate a hybridization solution containing a mixture of fluorescently labelled targets.
Scan the arrays and store output as images Quantify each spot Subtract background Normalize Export a table of fluorescent intensities for each gene in the array Analyze data using computational methods.
Target Identification b)-Bioinformatics Bioinformatics the in silico identification of novel drug targets is now feasible by systematically searching for paralogs (related proteins within an organism) of known drug targets (eg. may be able to modify an existing drug to bind to the paralog).
Can compare the entire genome of pathogenic and nonpathogenic strains of a microbe and identify genes/proteins associated with pathogenism. Current Opin. Microbiol 1:572-579 1998 Using gene expression microarrays and gene chip technologies, a single
device can be used to evaluate and compare the expression of up to 20000 genes of healthy and diseased individuals at once. Trends Biotechnol 19:412-415 2001 18 What is Bioinformatics? Conceptualizing biology in terms of molecules
and then applying informatics techniques from math, computer science, and statistics to understand and organize the information associated with these molecules on a large scale 19 What is Bioinformatics?
20 Bioinformatics Hub 21 How do we use Bioinformatics? Store/retrieve biological information (databases)
Retrieve/compare gene sequences Predict function of unknown genes/proteins Search for previously known functions of a gene Compare data with other researchers Compile/distribute data for other researchers 22
Bioinformatics Tools The processes of designing a new drug using bioinformatics tools have open a new area of research. However, computational techniques assist one in searching drug target and in designing drug in silco, but it takes long time and money. In order to design a new drug one need to follow the following path. 1.
2. 3. 4. 5. 6. 7. 8.
Identify target disease Study Interesting Compounds Detection the Molecular Bases for Disease Rational Drug Design Techniques Refinement of Compounds Quantitative Structure Activity Relationships (QSAR) Solubility of Molecule Drug Testing
23 QSAR Quantitative Structure Activity Relationships (QSAR) We have already seen that by changing groups in a drug may increase or decrease the activity, especially in terms of receptor binding interactions. Structural changes may also effect drug absorption ,distribution,
metabolism, Toxicity, decreased side effects, increased water solubility or lipophilicity (LADMET). QSAR provides a method to quantify a linear relationship between a physicochemical property of a drug and its biological activity. we will gain an understanding of QSAR regarding electronic and steric effects as well as lipophilicity.
Hammett Equation (Electronic Effects) Linear Free Energy Relationships allow a correlation of substituents with a reaction rate, biological activity, pKa, etc. To help us understand the magnitude of the sensitivity of reaction to changing substituents, we need a reference reaction. This is precisely what Hammett set out to accomplish. Hammett Equation (Electronic Effects) relates reaction rates with
acid dissociation constants. Consider the following dissociation of a substituted benzoic acid. Ka = dissociation constant Ka0 = dissociation constant when X = H Hammett Equation (Electronic Effects) Lets consider a few different types of X-groups compared to H.
If X = EWG, the carboxylate ion is stabilized more than when X = H As a result, Ka increases (compared to when X = H) If X = EDG, the carboxylate ion is less stabilized than when X = H. As a result, Ka decreases (compared to when X = H) Thus, we can make measurements of Ka for many different substituents and then make the following definition. log Ka/Ka0 = (sigma) When X = H, Ka = Ka0 and log Ka/Ka0 = = 0.
When X = EWG, Ka > Ka0 and > 0 (+ value) When X = EDG, Ka < Ka0 and < 0 (- value) Hammett Equation (Electronic Effects) Therefore, depends upon electronic properties of the substituent and its position. is also known as substituent constant. When the substituent X is in the meta position on the aromatic ring, the effect is mostly inductive. However, when the substituent X is in the para position, both inductive and
resonance effects are contributing. Therefore, meta and para are generally not the same for the same substituent. ortho are more difficult to measure and simply quantify due to steric effects on the reactive portion of the molecule. Hammett Equation (Electronic Effects)
Calculating a few values should provide a further appreciation. Ka X = meta-NO2 3.45x10-4 = log (3.45x10-4 / 6.46x10-5) = 0.73 X=H 6.46x10-5 X = para-CH3O 3.38x10-5
= log (3.38x10-5 / 6.46x10-5) = -0.28 Hammett Equation (Electronic Effects) For example, a nitro group in the meta position increases the dissociation constant, because the nitro group is electron-withdrawing , thereby stabilizing the negative charge that develops.
Consider now the effect of a nitro group in the para position. The equilibrium constant is even larger than for the nitro group in the meta position, indicating even greater electron-withdrawal. Now that weve identified our reference reaction (i.e., dissociation of substituted benzoic acids) lets compare it to a different systems. Remember that Ka0 is for when X = H.
If we plot log (Ka/Ka0) for these dissociation reactions vs. the values obtained from our reference reaction, we should see similar trends but perhaps to a different extent as the X-group is now further away from the business portion of the molecule
Hammett Equation (Electronic Effects) From these plots we also get more information. We now can compare the slopes for different reactions and draw more conclusions. First we must define the slope = (rho) For our reference reaction, (dissociation of benzoic acids) = 1. This is because we would be plotting log (Ka/Ka0) for substituted benzoic acids vs. values. But remember, = log (Ka/Ka0) for
substituted benzoic acids! then becomes a measure of a reactions sensitivity to electronic effects. The further away the substituent is from the reaction center, the weaker the effect and thus <1 but still greater than 0 as long as EWG increase the extent (or rate) of reaction and EDG decrease the extent (or rate) of the reaction if the effect of substituents is proportionally greater than on the benzoic acid
equilibrium, then > 1; if the effect is less than on the benzoic acid equilibrium, < 1. By definition, for benzoic acid is equal to 1. (rho),the slope of the line, is a proportionality constant pertaining to a given equilibrium. It relates the effect of substituents on that equilibrium to the effect of those substituents on the benzoic acid equilibrium. In the aniline and phenol equilibria, the hydrogen ion that is dissociating is one
atom removed from the phenyl ring, whereas in the benzoic acid equilibrium it is two atoms removed. Thus, substituents are able to exert a greater effect on the dissociation in aniline and phenol than in benzoic acid and the value of > 1. In phenylacetic and phenylpropionic acids, the hydrogen ion dissociating is three and four atoms removed, respectively, from the phenyl ring. Substituents are able to exert a lesser effect on the equilibrium than on the benzoic acid equilibrium and < 1.
Hammett Equation (Electronic Effects) So how does this effect activity of our drugs? Consider that an amine may be protonated in a receptor (Target) and must be so to form ionic interactions with the receptor. Thus if you want to maximize the interactions of your drug with the receptor, you can now logically select which X-groups would be beneficial. Should one select a substituent with a that is + or in this case? Would the sign of be + or ?
Hammett Equation (Electronic Effects) Hammett also considered reaction rates as well as dissociation constants. Specifically, he examined the alkaline hydrolysis of substituted ethyl benzoates. k is the rate constant for X k0 is for when X = H Again, EWG (+ values) will increase
the rate of reaction as the carboxylate ion is stabilized by such groups. EDG will slow the reaction down. Therefore, the slope (or the value should remain positive). Hammett Equation (Electronic Effects) doesnt need to be positive. We could imagine a reaction where EWG
would decrease the rate or extent of reaction. Consider the acid hydrolysis of an amide (perhaps in the stomach?). If the rate limiting step is the protonation of the carbonyl oxygen, how do substituents effect this step? We would expect that EDGs would favor this step. As a result, the value should be negative! In fact = -0.483 for this reaction. So how would you use this information if you wanted to increase the stability of your drug in the stomach??
Hammett Equation (Electronic Effects) QSAR In conclusion provides a measure of the sensitivity to electron donation or withdrawal may be (+) or (-). If = (+); the reaction rate is increased by EWG If = (-); the reaction rate is increased by EDG
The magnitude of is dependent upon the distance of the substituent from the reaction center (or the sensitivity to substituent effects). What about steric effects on reactions? The Taft Equation (Es) The Taft Equation (Es) In the 1950s, Taft proposed that Linear Free Energy Relationships could be
extended to include steric factors. The reference reaction that he utilized was the acid-catalyzed hydrolysis of substituted methyl acetates. The Steric Contribution Es was defined by the following equation which should seem similar to that for sigma values for electronic effects discussed previously. Es = log (kX-COOMe / kMe-COOMe) The reference substituent was chosen to be X = CH3. In this case any group larger than CH3 should give a ()
A group smaller (i.e., X = H) gives a (+) value Hydrophobicity Constant ()) Sometimes it may be useful to be able to predict the lipophilicity (or hydrophobicity) of a compound similar to steric and electronic effects. Hansch derived substituent constants for the contribution of atoms or groups on
lipophilicity or more specifically, partition coefficient (P) Why is the partition coefficient important? Hydrophobicity may effect a drugs ability to cross cell membranes or receptor binding interactions. P is defined by the following equation. P = [compound]octanol / [compound]water Hydrophobic compounds (nonpolar) favor solution in octanol
Hydrophilic (polar) compounds favor solution in water. Hydrophobic compounds will have a LARGE P and Hydrophilic compounds will have a small P. Hydrophobicity Constant ()) How is P related to biological activity? If we let C = concentration of drug needed to achieve a desired pharmacological effect, we can express biological activity as 1/C. As a result, a low C would have a GREATER effect.
In general, we find that increased hydrophobicity causes an increase in biological activity. This most probably due to the fact that drugs need to pass across membrane barriers to reach the target site. Thus, we should expect a linear correlation of biological relationship vs. hydrophobicity. On the contrary, we observe a parabolic relationship. Hydrophobicity Constant ()) Why do we see such a relationship? There are 3 major reasons to account for this.
Drugs that are too hydrophobic are not soluble in the aqueous phase Drug trapped in fat deposits and never reach site of action Hydrophobic drugs may be more susceptible to degradative metabolism So, back to Hanschs hydrophobicity constant (). How could it be useful? Well). How could it be useful? Well first we need to define this constant. Hansch defined the hydophobicity constant (). How could it be useful? Well) by the following equation. log (PX / PH) =
PX is the partition coefficient of a compound containing substituent X PH is the partition coefficient for the parent (or unsubstituted) drug. Substituents that increases the hydrophobicity (or lipophilicity) of a compound will have (+) ) values Substituent that decrease the hydrophobicity (or lipophilicity) of compound will have (-) ) values The Craig Plot
Weve discussed electronic, steric, and hydrophobic effects and perhaps it would be useful to combine and display this information. Such a presentation is called a Craig Plot. Often you will see values for ). How could it be useful? Well and plotted together as in the following graph. The Craig Plot The advantage to such a plot is that one may quickly identify substituents with
similar electronic effects but vary in hydrophobic ). How could it be useful? Well effects. Conversely, substituents with similar ). How could it be useful? Well values with differing values can be just as easily identified. Thus, if one is looking for a substituent to cause a specific change in a property of a drug, a logical choice can be made. It should be noted that other Craig Plots may be generated for P, Es,
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