Insilico methods for design of novel inhibitors of Human leukocyte elastase

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Oral contributed paper “Insilico methods for design of novel inhibitors of Human leukocyte elastase” in the International conference on Systemics, Cybernetics and Informatics-2006

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Insilico methods for design of novel inhibitors of Human leukocyte elastase

  1. 1. Insilico methods for design of novel inhibitors of Human leukocyte elastase by L. Jayashankar, M.Tech Pharma., GVK Biosciences, Hyderabad. (Contributed oral paper in ICSCI-2006)
  2. 2. The possible ways of drug design <ul><li>Structure based drug design </li></ul><ul><li>Analogue based drug design </li></ul>
  3. 3. Stages in Drug Discovery
  4. 4. Identify disease state Relevant biomolecular target Assay Development e.g. Receptor cloning and expression Compound Collections Primary Assay (high through-put, usually in vitro ) Secondary Assays (counter screens, bioavailability, toxicity, metabolism, etc.., usually in vivo ) Bioinformatics Protein Modeling Drug Discovery and Design Clinical Candidate Lead compounds and SAR Chemical Synthesis Design Mapping Fitting In Silico
  5. 6. Raw data X-ray NMR Homology Target definition via Structure determination and prediction
  6. 7. Get the diffraction pattern Phasing : MIR and molecular replacement Electron density map Refinement Fit sequence to density X-ray based Target Definition
  7. 8. Ligand design When the structure of an enzyme is known, It is possible to display in a modeling environment ( Insight II ) to select potential binding sites by inspection and to design an inhibitor that targets those sites.
  8. 9. De Novo (New) Ligand Design They analyze the properties of the active site Determine favorable-binding locations for individual atoms or small fragments. Although conceptually simple, these approaches are quite useful for successful ligand design.
  9. 10. <ul><li>Human leukocyte is a serine protease. </li></ul><ul><li>It is released upon inflammatory stimulus </li></ul><ul><li>HLE aids in the migration of neutrophils to extra vascular compartments through degradation of a number of structural proteins including elastin. </li></ul><ul><li>Normally kept in check by the natural inhibitor α -1-proteinase. </li></ul>Human Leukocyte Elastase
  10. 11. <ul><li>α -1-proteinase may be damaged by the benzopyrenes of cigarette smoke. </li></ul><ul><li>Produced in insufficient quantities due to genetic defect. </li></ul><ul><li>The in sufficient balance between α -1-proteinase and HLE can cause tissue damage which manifests in diseases such as emphysema ,cystic fibrosis, and adult respiratory distress syndrome. </li></ul>
  11. 12. <ul><li>Catalytic triad of serine proteinases </li></ul>
  12. 15. <ul><li>HLE is a trypsin like serine protease that contains the characteristic Asp-102/His-57/Ser-195 catalytic triad. </li></ul><ul><li>The side chain hydroxyl group of Ser-195 functions as a nucleophile which attacks the substrate amide carbonyl group. </li></ul><ul><li>His -57 acts as a general base catalyst </li></ul><ul><li>Asp -102 carboxylate anchors the His -57 in proper orientation and tautomeric state </li></ul>
  13. 16. <ul><li>The reaction intermediate hemiketal alkoxide anion is stabilized through interaction with backbone NH groups of Gly-193 and Ser-195. </li></ul><ul><li>The cavity is commonly reffered to as the oxyanion hole. </li></ul>
  14. 17. <ul><li>The crystal structure of HLE is taken from the protein database with ID 1 EAS </li></ul><ul><li>The residues of 1EAS fall about 88.3% in the most favored regions . </li></ul>
  15. 18. Ramchandran plot for 1 EAS
  16. 19. <ul><li>The inhibitors of human leukocyte elastase </li></ul><ul><li>between variously substituted benzoxazinones are designed by various Hit and trial methods. The pk i values of the molecules are experimentally performed </li></ul>
  17. 20. Site Search Aim: To find all cavities inside a protein Protein is mapped on a grid. One must visually inspect, select, adjust and define the binding site.
  18. 21. Ligand based drug designing <ul><li>QSAR(Quantitative structure activity relation ship) </li></ul><ul><li>Attempt to identify and quantify the physiochemical properties of a drug and to see whether any of these properties has an effect on the drugs biological activity </li></ul><ul><li>A range of compounds are synthesized in order to vary one physiochemical property(e.g log P) and to test how this affects the biological activity(log 1/C) </li></ul>
  19. 22. . . . . . . Log P Log 1/C Y X Draw best possible lines through the data points on the graph
  20. 23. Best line will be the one close to the data points To measure how close the data points are vertical lines are drawn from each point These verticals are measured and then scored in order to eliminate the negative values Squares are then added up to give a total Best line through the points will be the line where the total is a minimum
  21. 24. The significance of the equation is know as regression coefficient(r) For a perfect fit r2=1 Good fit generally have r2 values of 0.95 or above Physiochemical properties Most commonly studied are Hydrophobic,Electrostatic and steric interaction Hydrophobic properties can easily quantified for complete molecules or for individual substituents
  22. 25. Electronic and steric properties are more difficult to quantify,and quantifications are only feasible for individual substituents QSAR studies are being carried out on compounds of the same general structure where substituents on aromatic rings or accessible functional groups are varied QSAR studies then considers how the hydrophobic,electronic,and steric properties of the substituents affect the biological activity
  23. 26. Hydrophobicity How easily it crosses the cell membranes and may well also be important in receptor interactions Changing substituents on a drug may well have significant effects on its hydrophobic character and hence its biological activity P= Concentration of the drug in octonol Concentration of drug in aqueous solution
  24. 27. Hydrophobic compounds - P-values hydrophilic compounds - low P values Biological activity = 1/C C=Concentration of the drug required to achieve a defined level of biological activity If Log P values is resticted to a small range (1-4) a straight line graph is obtained showing that there is a relation ship between hydrophobicity and biological activity Log(1/C)=K1 log P+k2
  25. 28. Increasing the hydrophobicity of a lead compound results in a increase in biological activity Compounds having a log P value close to 2 should be capable of entering the central nervous system effectively Drugs which are designed to act elsewhere in the body should have lop values significantly different from 2 in order to avoid possible central nervous system
  26. 29. Substituent Hydrophobicity constant Measure of how hydrophobic a substituent is relative to hydrogen πx = log Px - log PH PH-partition coefficient of a standard compound Px-partition coefficient of a standard compound with substituent +value –Substituent is more hydrophobic -value - Substituent is less hydrophobic
  27. 30. The electronic effects of various substituents will clearly have an effect on drugs ionisation or polarity Measured in terms of Hammet substituent constant σ σ-measure of electronic with drawing or electron donating ability of a substituent Determined by measuring the ability of a series of substituted benzoic acids compared to the dissociation of benzoic acid itself Cl, CN, CF3 –σ values positive (Electron withdrawing) Me ethyl and butyl – σ –values (electron donating) Values also depend whether the subsituent is meta or or para
  28. 31. σ values cant be measured for ortho substituents since such substituents have an important steric as well as electronic effects Electron withdrawing groups increase the rate of hydrolysis and have positive values Steric properties Bulk ,size,and shape of the drug may have influence on this process Tafts steric factor Molar refractivity-measure of volume occupied by an atom or group of atoms
  29. 32. <ul><li>QSAR is a analogue based drug design. </li></ul><ul><li>In QSAR active molecules are minimized and conformers for the respective molecules are generated. </li></ul><ul><li>The set of molecules are divided into two sets i.e.. Training set , test set. </li></ul>QSAR
  30. 33. <ul><li>MFA (molecular field analysis) </li></ul><ul><li>In this method all the molecules are aligned one upon the other projecting there diversified functional groups with the common scaffold. </li></ul><ul><li>The interactive groups of the molecules are known by the grid search method where in the positions are determined by the probe search analysis method. </li></ul>
  31. 35. Grid search
  32. 36. <ul><li>After aligning the molecules the molecules are loaded into the study table of the QSAR analysis. </li></ul><ul><li>The various descriptors of the molecules are present in the data base of Accelerys software. </li></ul><ul><li>The properties of the molecule are described by the descriptors. </li></ul>
  33. 37. <ul><li>Example of descriptor. </li></ul><ul><li>Structural descriptors </li></ul><ul><li>The following table lists the structural descriptors available in QSAR </li></ul><ul><li>Symbol Description </li></ul><ul><li>Mw molecular weight </li></ul><ul><li>Rotlbonds number of rotatable bonds </li></ul><ul><li>Hbond acceptors number of hydrogen bond acceptors </li></ul><ul><li>Hbond donors number of hydrogen bond donors </li></ul>
  34. 38. <ul><li>The properties described by the descriptors are set to independent variables) and the biological value of the molecules is given by the dependent variable). </li></ul><ul><li>Y= mx + c where c = constant </li></ul><ul><li>Y=dependent variable </li></ul><ul><li>X=independent variable </li></ul>
  35. 39. Typical QSAR study table
  36. 40. <ul><li>Depending upon the x, and y variables the statistical analysis for the molecules is done by the G/PLS ( a combinational method of both genetic and partial least sum of squares method) with 50,000 cross overs are generated. </li></ul><ul><li>After performing the G/PLS method an equation is generated basing upon the y, and x cmponent analysis. </li></ul>
  37. 41. <ul><li>Equation generated by the G/PLS method </li></ul><ul><li>Activity - 0.046748 * &quot;CH3/334&quot; + 0.03696 * &quot;H+/467&quot; + 0.04704 * &quot;CH3/543&quot; - 0.027816 * &quot;H+/600&quot; + 0.042922 * &quot;CH3/193&quot; + 0.064957 * &quot;CH3/187&quot; - 0.025432 * &quot;CH3/606&quot; . </li></ul>
  38. 42. <ul><li>The graphical representation of predicted to biological value is given by the correlation coefficient </li></ul>
  39. 43. <ul><li>With the equation obtained from the trainnig set molecules the predicted values of the test se t molecules are determined. The efficiency of the prediction is determined from the correlation coefficient of the test molecules. </li></ul><ul><li>For the newly designed molecules with unknown biological value are determined by the equation generated by the QSAR analysis. </li></ul>
  40. 44. <ul><li>Advantages </li></ul><ul><li>The generated equation can be used to predict the unknown biological activity of the randomly predicted molecules </li></ul><ul><li>The scalability and efficient molecules in minimized time with maximum inhibition can be achieved. </li></ul><ul><li>QSAR is very much useful when the structure of the protein molecule is not known. </li></ul><ul><li>Serves as a database for the prediction of biological activity. </li></ul>
  41. 45. <ul><li>In the similar way adding different descriptors the molecular surface analysis ,and 2D QSAR are done (MSA,2D QSAR) </li></ul>
  42. 46. Comparision of different statistical analysis r^2=correlation coefficient .856 .739 2 .798 .013 9.26 .910 .839 2 .795 .0168 6.26 .839 .793 2 .845 .002 10.56 R^2 XVR^2 Outliers BSR^2 BSR^2ERROR PRESS 2D QSAR RSA MFA Statistical parameters
  43. 47. <ul><li>Rigid body docking </li></ul><ul><li>Protein as well as ligand are held fixed in conformational space </li></ul><ul><li>Reduces the problem to the search for the relative orientation of the two molecules with lowest energy </li></ul><ul><li>Clique search based approach </li></ul><ul><li>Depends on compatibility </li></ul><ul><li>Superimposes all ligand features to the matched protein features </li></ul><ul><li>e.g. dock software: set of spheres are created inside the active site which represent the volume which can be occupied by the ligand molecule </li></ul>
  44. 48. Flexible docking based on fragmentation <ul><li>Ligand is divided into several fragments </li></ul><ul><li>Each fragment is either rigid or has only a small no of conformations which can be handled by a conformation ensemble </li></ul><ul><li>Incremental construction algorithm </li></ul><ul><li>Starts with placing one fragment (called base or anchor) into the active site of the protein </li></ul><ul><li>Add the remaining parts of the ligand to the already placed fragments interactively eg Flex X </li></ul>
  45. 49. Docking by simulation <ul><li>Begin their calculation with a starting configuration and locally move to configurations with lower energy </li></ul><ul><li>Monte carlo simulations </li></ul><ul><li>Local moves of the atoms are performed randomly </li></ul><ul><li>Description of the degrees of freedom and the energy evaluation </li></ul><ul><li>High energy states are avoided </li></ul><ul><li>Energy of Bond length>bond angle>torsion Angle </li></ul>
  46. 50. <ul><li>The performance of the designed molecules is known by the docking analysis. </li></ul><ul><li>The various docking softwares are </li></ul><ul><li>Autodock,ligand fit, affinity the docking scores of the molecules in terms of energy is stated after minimizing the molecule in the active site . The flexibility and conformations in the active site is allowed by giving flexibility to ligand and protein. </li></ul>
  47. 51. Pretein scffold with ligand docked at active site
  48. 52. The docked molecule in space filled model Ligand
  49. 53. Docking scores of the ligand in the active site of human leukocyte elastase
  50. 54. <ul><li>The designed molecules are docked in to the proteins active site and the interaction of ligand molecule with the proteins amino acid residues is proved from affinity background files. </li></ul><ul><li>@list subset P_1EAU$SITECAT </li></ul><ul><li>P_1EAU:HIS_57:N HN CA HA C O CB HB1 HB2 CG ND1 CD2 HD2 CE1 HE1 NE2 HE2 </li></ul><ul><li>ASP_102:N HN CA HA C O CB HB1 HB2 CG OD1 OD2 HD2 </li></ul><ul><li>SER_195:N HN CA HA C O CB HB1 HB2 OG HG </li></ul><ul><li>SER_214:N HN CA HA C O CB HB1 HB2 OG HG </li></ul>
  51. 55. LIGAND INTERACTING WITH THE STATED AMINOACIDS IN THE ACTIVE SITE
  52. 56. <ul><li>The energy conformations of the Active molecules in the active site of human leukocyte elastase </li></ul><ul><li>The least energy conformer is used for clinical phase 3 </li></ul>Affinity
  53. 57. Results and discussion <ul><li>Novel approach for the design of new ligands </li></ul><ul><li>Reduces the time phase in synthesis of molecules </li></ul><ul><li>Interpolative molecules which are about to synthesize are loaded into the study table for the prediction of biological value. </li></ul>

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