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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)
The possible ways of drug design ,[object Object],[object Object]
Stages in Drug Discovery
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
 
Raw data X-ray NMR Homology Target definition via Structure determination and prediction
Get the diffraction pattern Phasing : MIR and molecular replacement Electron density map Refinement Fit sequence to density X-ray based Target Definition
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.
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.
[object Object],[object Object],[object Object],[object Object],Human Leukocyte Elastase
[object Object],[object Object],[object Object]
[object Object]
 
 
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object]
Ramchandran plot for 1 EAS
[object Object],[object Object]
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.
Ligand based drug designing ,[object Object],[object Object],[object Object]
. . . . . . Log P Log 1/C Y X Draw best possible lines through the data points on the graph
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
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
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
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
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
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
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
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
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
[object Object],[object Object],[object Object],QSAR
[object Object],[object Object],[object Object]
 
Grid search
[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
Typical QSAR study table
[object Object],[object Object]
[object Object],[object Object]
[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object]
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
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Flexible docking based on fragmentation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Docking by simulation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object]
Pretein scffold with ligand docked at active site
The docked molecule in space filled model Ligand
Docking scores of the ligand in the active site of human leukocyte elastase
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
LIGAND  INTERACTING WITH THE STATED AMINOACIDS IN THE ACTIVE SITE
[object Object],[object Object],Affinity
Results and discussion ,[object Object],[object Object],[object Object]

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Insilico methods for design of novel inhibitors of Human leukocyte elastase

  • 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.
  • 3. Stages in Drug Discovery
  • 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
  • 7. Get the diffraction pattern Phasing : MIR and molecular replacement Electron density map Refinement Fit sequence to density X-ray based Target Definition
  • 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.
  • 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.
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  • 19.
  • 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.
  • 21.
  • 22. . . . . . . Log P Log 1/C Y X Draw best possible lines through the data points on the graph
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
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  • 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
  • 47.
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  • 51. Pretein scffold with ligand docked at active site
  • 52. The docked molecule in space filled model Ligand
  • 53. Docking scores of the ligand in the active site of human leukocyte elastase
  • 54.
  • 55. LIGAND INTERACTING WITH THE STATED AMINOACIDS IN THE ACTIVE SITE
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  • 57.