SlideShare a Scribd company logo
1 of 28
Important Points in Drug Design based
on Bioinformatics Tools
History of Drug/Vaccine development
– Plants or Natural Product
• Plant and Natural products were source for medical substance
• Example: foxglove used to treat congestive heart failure
• Foxglove contain digitalis and cardiotonic glycoside
• Identification of active component
– Accidental Observations
• Penicillin is one good example
• Alexander Fleming observed the effect of mold
• Mold(Penicillium) produce substance penicillin
• Discovery of penicillin lead to large scale screening
• Soil micoorganism were grown and tested
• Streptomycin, neomycin, gentamicin, tetracyclines etc.
http://www.geocities.com/bioinformaticsweb/drugdiscovery.html
Important Points in Drug Design based
on Bioinformatics Tools
• Chemical Modification of Known Drugs
– Drug improvement by chemical modification
– Pencillin G -> Methicillin; morphine->nalorphine
• Receptor Based drug design
– Receptor is the target (usually a protein)
– Drug molecule binds to cause biological effects
– It is also called lock and key system
– Structure determination of receptor is important
• Ligand-based drug design
– Search a lead ocompound or active ligand
– Structure of ligand guide the drug design process
Important Points in Drug Design based
on Bioinformatics Tools
• Identify Target Disease
– Identify and study the lead compounds
– Marginally useful and may have severe side effects
• Refinement of the chemical structures
– Detect the Molecular Bases for Disease
– Detection of drug binding site
– Tailor drug to bind at that site
– Protein modeling techniques
– Traditional Method (brute force testing)
Genetics Review
TACGCTTCCGGATTCAA
transcription
AUGCGAAGGCCUAAGUU
DNA:
RNA:
translation
PIRLMQTS
Protein
Amino Acids:
Overview Continued –
A simple example
Protein
Small molecule
drug
Overview Continued –
A simple example
Protein
Small molecule
drug
Protein
Protein
disabled …
disease
cured
Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases •Large databases
Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases
•Not all can be drugs
•Large databases
•Not all can be drug targets
Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases
•Not all can be drugs
•Opportunity for data
mining techniques
•Large databases
•Not all can be drug targets
•Opportunity for data
mining techniques
Important Points in Drug Design based
on Bioinformatics Tools
• Application of Genome
– 3 billion bases pair
– 30,000 unique genes
– Any gene may be a potential drug target
– ~500 unique target
– Their may be 10 to 100 variants at each target gene
– 1.4 million SNP
– 10200
potential small molecules
Important Points in Drug Design based
on Bioinformatics Tools
• Detect the Molecular Bases for Disease
– Detection of drug binding site
– Tailor drug to bind at that site
– Protein modeling techniques
– Traditional Method (brute force testing)
• Rational drug design techniques
– Screen likely compounds built
– Modeling large number of compounds (automated)
– Application of Artificial intelligence
– Limitation of known structures
Important Points in Drug Design based
on Bioinformatics Tools
• Refinement of compounds
– Refine lead compounds using laboratory techniques
– Greater drug activity and fewer side effects
– Compute change required to design better drug
• Quantitative Structure Activity Relationships (QSAR)
– Compute functional group in compound
– QSAR compute every possible number
– Enormous curve fitting to identify drug activity
– chemical modifications for synthesis and testing.
• Solubility of Molecule
• Drug Testing
Drug Discovery & Development
Identify disease
Isolate protein
involved in
disease (2-5 years)
Find a drug effective
against disease protein
(2-5 years)
Preclinical testing
(1-3 years)
Formulation
Human clinical trials
(2-10 years)
Scale-up
FDA approval
(2-3 years)
FileIND
File
N
DA
Techology is impacting this process
Identify disease
Isolate protein
Find drug
Preclinical testing
GENOMICS, PROTEOMICS & BIOPHARM.
HIGH THROUGHPUT SCREENING
MOLECULAR MODELING
VIRTUAL SCREENING
COMBINATORIAL CHEMISTRY
IN VITRO & IN SILICO ADME MODELS
Potentially producing many more targets
and “personalized” targets
Screening up to 100,000 compounds a
day for activity against a target protein
Using a computer to
predict activity
Rapidly producing vast numbers
of compounds
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing
1. Gene Chips
• “Gene chips” allow us
to look for changes in
protein expression for
different people with a
variety of conditions,
and to see if the
presence of drugs
changes that expression
• Makes possible the
design of drugs to
target different
phenotypes
compounds administered
people / conditions
e.g. obese, cancer,
caucasian
expression profile
(screen for 35,000 genes)
Biopharmaceuticals
• Drugs based on proteins, peptides or natural
products instead of small molecules (chemistry)
• Pioneered by biotechnology companies
• Biopharmaceuticals can be quicker to discover
than traditional small-molecule therapies
• Biotechs now paring up with major
pharmaceutical companies
2. High-Throughput Screening
Screening perhaps millions of compounds in a corporate
collection to see if any show activity against a certain disease
protein
High-Throughput Screening
• Drug companies now have millions of samples of
chemical compounds
• High-throughput screening can test 100,000
compounds a day for activity against a protein target
• Maybe tens of thousands of these compounds will
show some activity for the protei
• The chemist needs to intelligently select the 2 - 3
classes of compounds that show the most promise for
being drugs to follow-up
Informatics Implications
• Need to be able to store chemical structure and biological data for
millions of datapoints
– Computational representation of 2D structure
• Need to be able to organize thousands of active compounds into
meaningful groups
– Group similar structures together and relate to activity
• Need to learn as much information as possible from the data (data
mining)
– Apply statistical methods to the structures and related information
3. Computational Models of Activity
• Machine Learning Methods
– E.g. Neural nets, Bayesian nets, SVMs, Kahonen nets
– Train with compounds of known activity
– Predict activity of “unknown” compounds
• Scoring methods
– Profile compounds based on properties related to target
• Fast Docking
– Rapidly “dock” 3D representations of molecules into 3D
representations of proteins, and score according to how well
they bind
4. Combinatorial Chemistry
• By combining molecular “building blocks”, we
can create very large numbers of different
molecules very quickly.
• Usually involves a “scaffold” molecule, and sets
of compounds which can be reacted with the
scaffold to place different structures on
“attachment points”.
Combinatorial Chemistry Issues
• Which R-groups to choose
• Which libraries to make
– “Fill out” existing compound collection?
– Targeted to a particular protein?
– As many compounds as possible?
• Computational profiling of libraries can help
– “Virtual libraries” can be assessed on computer
5. Molecular Modeling
• 3D Visualization of interactions between compounds and proteins
• “Docking” compounds into proteins computationally
3D Visualization
• X-ray crystallography and NMR Spectroscopy can
reveal 3D structure of protein and bound
compounds
• Visualization of these “complexes” of proteins and
potential drugs can help scientists understand the
mechanism of action of the drug and to improve
the design of a drug
• Visualization uses computational “ball and stick”
model of atoms and bonds, as well as surfaces
• Stereoscopic visualization available
“Docking” compounds into proteins
computationally
6. In Vitro & In Silico ADME
models
• Traditionally, animals were used for pre-human testing.
However, animal tests are expensive, time consuming and
ethically undesirable
• ADME (Absorbtion, Distribution, Metabolism, Excretion)
techniques help model how the drug will likely act in the
body
• These methods can be experemental (in vitro) using
cellular tissue, or in silico, using computational models
In Silico ADME Models
• Computational methods can predict compound
properties important to ADME, e.g.
– LogP, a liphophilicity measure
– Solubility
– Permeability
– Cytochrome p450 metabolism
• Means estimates can be made for millions of
compouds, helping reduce “atrittion” – the failure
rate of compounds in late stage
Size of databases
• Millions of entries in databases
– CAS : 23 million
– GeneBank : 5 million
• Total number of drugs worldwide: 60,000
• Fewer than 500 characterized molecular
targets
• Potential targets : 5,000-10,000

More Related Content

What's hot

Protein Predictinon
Protein PredictinonProtein Predictinon
Protein PredictinonSHRADHEYA GUPTA
 
Computational predictiction of prrotein structure
Computational predictiction of prrotein structureComputational predictiction of prrotein structure
Computational predictiction of prrotein structureArchita Srivastava
 
The Role of Bioinformatics in The Drug Discovery Process
The Role of Bioinformatics in The Drug Discovery ProcessThe Role of Bioinformatics in The Drug Discovery Process
The Role of Bioinformatics in The Drug Discovery ProcessAdebowale Qazeem
 
methods for protein structure prediction
methods for protein structure predictionmethods for protein structure prediction
methods for protein structure predictionkaramveer prajapat
 
threading and homology modelling methods
threading and homology modelling methodsthreading and homology modelling methods
threading and homology modelling methodsmohammed muzammil
 
Threading modeling methods
Threading modeling methodsThreading modeling methods
Threading modeling methodsratanvishwas
 
InterPro and InterProScan 5.0
InterPro and InterProScan 5.0InterPro and InterProScan 5.0
InterPro and InterProScan 5.0EBI
 
Applications of bioinformatics
Applications of bioinformaticsApplications of bioinformatics
Applications of bioinformaticsSudha Rameshwari
 
Protein Structure Prediction
Protein Structure PredictionProtein Structure Prediction
Protein Structure PredictionBalachandramohan Bcm
 
Protein microarray Preparation of protein microarray Different methods of arr...
Protein microarray Preparation of protein microarray Different methods of arr...Protein microarray Preparation of protein microarray Different methods of arr...
Protein microarray Preparation of protein microarray Different methods of arr...naveed ul mushtaq
 
BLAST (Basic local alignment search Tool)
BLAST (Basic local alignment search Tool)BLAST (Basic local alignment search Tool)
BLAST (Basic local alignment search Tool)Ariful Islam Sagar
 
Bioinformatic in drug designing
Bioinformatic in drug designingBioinformatic in drug designing
Bioinformatic in drug designingSalman Khan
 
Secondary protein structure prediction
Secondary protein structure predictionSecondary protein structure prediction
Secondary protein structure predictionSiva Dharshini R
 

What's hot (20)

Protein Predictinon
Protein PredictinonProtein Predictinon
Protein Predictinon
 
Computational predictiction of prrotein structure
Computational predictiction of prrotein structureComputational predictiction of prrotein structure
Computational predictiction of prrotein structure
 
Protein database
Protein databaseProtein database
Protein database
 
The Role of Bioinformatics in The Drug Discovery Process
The Role of Bioinformatics in The Drug Discovery ProcessThe Role of Bioinformatics in The Drug Discovery Process
The Role of Bioinformatics in The Drug Discovery Process
 
Genomics
GenomicsGenomics
Genomics
 
SEQUENCE ANALYSIS
SEQUENCE ANALYSISSEQUENCE ANALYSIS
SEQUENCE ANALYSIS
 
methods for protein structure prediction
methods for protein structure predictionmethods for protein structure prediction
methods for protein structure prediction
 
threading and homology modelling methods
threading and homology modelling methodsthreading and homology modelling methods
threading and homology modelling methods
 
Threading modeling methods
Threading modeling methodsThreading modeling methods
Threading modeling methods
 
InterPro and InterProScan 5.0
InterPro and InterProScan 5.0InterPro and InterProScan 5.0
InterPro and InterProScan 5.0
 
Applications of bioinformatics
Applications of bioinformaticsApplications of bioinformatics
Applications of bioinformatics
 
Multiple sequence alignment
Multiple sequence alignmentMultiple sequence alignment
Multiple sequence alignment
 
Protein Structure Prediction
Protein Structure PredictionProtein Structure Prediction
Protein Structure Prediction
 
Protein fold recognition and ab_initio modeling
Protein fold recognition and ab_initio modelingProtein fold recognition and ab_initio modeling
Protein fold recognition and ab_initio modeling
 
Protein microarray Preparation of protein microarray Different methods of arr...
Protein microarray Preparation of protein microarray Different methods of arr...Protein microarray Preparation of protein microarray Different methods of arr...
Protein microarray Preparation of protein microarray Different methods of arr...
 
Bioinformatics and Drug Discovery
Bioinformatics and Drug DiscoveryBioinformatics and Drug Discovery
Bioinformatics and Drug Discovery
 
Bioinformatics
BioinformaticsBioinformatics
Bioinformatics
 
BLAST (Basic local alignment search Tool)
BLAST (Basic local alignment search Tool)BLAST (Basic local alignment search Tool)
BLAST (Basic local alignment search Tool)
 
Bioinformatic in drug designing
Bioinformatic in drug designingBioinformatic in drug designing
Bioinformatic in drug designing
 
Secondary protein structure prediction
Secondary protein structure predictionSecondary protein structure prediction
Secondary protein structure prediction
 

Viewers also liked

FRET Microscopy Presentation
FRET Microscopy PresentationFRET Microscopy Presentation
FRET Microscopy PresentationVallery Salomon
 
FRET BIOL 497 Presentation
FRET BIOL 497 PresentationFRET BIOL 497 Presentation
FRET BIOL 497 PresentationSaki Mihori
 
Fish(flourescent in-situ hybridization)
Fish(flourescent in-situ hybridization)Fish(flourescent in-situ hybridization)
Fish(flourescent in-situ hybridization)naren
 
Fluorescence(Forster) Resonance Energy Transfer
Fluorescence(Forster) Resonance Energy TransferFluorescence(Forster) Resonance Energy Transfer
Fluorescence(Forster) Resonance Energy Transfersavvysahana
 
Fluorescence in situ Hybridization FISH #glok92
Fluorescence in situ Hybridization FISH #glok92Fluorescence in situ Hybridization FISH #glok92
Fluorescence in situ Hybridization FISH #glok92glok Productions
 
2 d gel electrophoresis
2 d gel electrophoresis2 d gel electrophoresis
2 d gel electrophoresisAashish Patel
 
Fluorescence spectroscopy
Fluorescence spectroscopyFluorescence spectroscopy
Fluorescence spectroscopyRahul Sharma
 
Fluorescence spectroscopy
Fluorescence spectroscopyFluorescence spectroscopy
Fluorescence spectroscopyNimisha Dutta
 
Fluorescent in-situ Hybridization (FISH)
Fluorescent in-situ Hybridization (FISH)Fluorescent in-situ Hybridization (FISH)
Fluorescent in-situ Hybridization (FISH)BioGenex
 

Viewers also liked (15)

FRET Microscopy Presentation
FRET Microscopy PresentationFRET Microscopy Presentation
FRET Microscopy Presentation
 
FRET BIOL 497 Presentation
FRET BIOL 497 PresentationFRET BIOL 497 Presentation
FRET BIOL 497 Presentation
 
Fish(flourescent in-situ hybridization)
Fish(flourescent in-situ hybridization)Fish(flourescent in-situ hybridization)
Fish(flourescent in-situ hybridization)
 
Fluorescence(Forster) Resonance Energy Transfer
Fluorescence(Forster) Resonance Energy TransferFluorescence(Forster) Resonance Energy Transfer
Fluorescence(Forster) Resonance Energy Transfer
 
Calorimetry
CalorimetryCalorimetry
Calorimetry
 
Fish
FishFish
Fish
 
Fluorescence in situ Hybridization FISH #glok92
Fluorescence in situ Hybridization FISH #glok92Fluorescence in situ Hybridization FISH #glok92
Fluorescence in situ Hybridization FISH #glok92
 
Calorimeter
CalorimeterCalorimeter
Calorimeter
 
2 d gel electrophoresis
2 d gel electrophoresis2 d gel electrophoresis
2 d gel electrophoresis
 
Fluorescence spectroscopy
Fluorescence spectroscopyFluorescence spectroscopy
Fluorescence spectroscopy
 
Drug design
Drug designDrug design
Drug design
 
Fluorescence spectroscopy
Fluorescence spectroscopyFluorescence spectroscopy
Fluorescence spectroscopy
 
Colorimetry
ColorimetryColorimetry
Colorimetry
 
Fluorescent in-situ Hybridization (FISH)
Fluorescent in-situ Hybridization (FISH)Fluorescent in-situ Hybridization (FISH)
Fluorescent in-situ Hybridization (FISH)
 
Calorimetry
CalorimetryCalorimetry
Calorimetry
 

Similar to Bioinformatics Tools Speed Drug Design

Sparsh bioinfo.ppt
Sparsh bioinfo.pptSparsh bioinfo.ppt
Sparsh bioinfo.pptSparshTiwari14
 
Bioinformatics
BioinformaticsBioinformatics
BioinformaticsAfra Fathima
 
Drug Designing
Drug DesigningDrug Designing
Drug DesigningZainabSaif
 
Natural products in drug discovery
Natural products in drug discoveryNatural products in drug discovery
Natural products in drug discoverySAKTHIVEL G
 
Applications Of Bioinformatics In Drug Discovery And Process
Applications Of Bioinformatics In Drug Discovery And ProcessApplications Of Bioinformatics In Drug Discovery And Process
Applications Of Bioinformatics In Drug Discovery And ProcessProf. Dr. Basavaraj Nanjwade
 
introduction to bioinfromatics.pptx
introduction to bioinfromatics.pptxintroduction to bioinfromatics.pptx
introduction to bioinfromatics.pptxAbelPhilipJoseph
 
Drug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsDrug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsKedar Bandekar
 
Drug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsDrug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsKedar Bandekar
 
Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014Lee Larcombe
 
Computer aided drug designing
Computer aided drug designing Computer aided drug designing
Computer aided drug designing Ayesha Aftab
 
drug discovery- history, evolution and stages
drug discovery- history, evolution and stagesdrug discovery- history, evolution and stages
drug discovery- history, evolution and stagesaiswarya thomas
 
In silico drug desigining
In silico drug desiginingIn silico drug desigining
In silico drug desiginingDevesh Shukla
 
Genomics and Bioinformatics
Genomics and BioinformaticsGenomics and Bioinformatics
Genomics and BioinformaticsAmit Garg
 
Drug design based on bioinformatic tools
Drug design based on bioinformatic toolsDrug design based on bioinformatic tools
Drug design based on bioinformatic toolsSujeethKrishnan
 
computer simulations.pptx
computer simulations.pptxcomputer simulations.pptx
computer simulations.pptxDr Pavani A
 
Bioinformatics role in Pharmaceutical industries
Bioinformatics role in Pharmaceutical industriesBioinformatics role in Pharmaceutical industries
Bioinformatics role in Pharmaceutical industriesMuzna Kashaf
 

Similar to Bioinformatics Tools Speed Drug Design (20)

Sparsh bioinfo.ppt
Sparsh bioinfo.pptSparsh bioinfo.ppt
Sparsh bioinfo.ppt
 
Bioinformatics
BioinformaticsBioinformatics
Bioinformatics
 
Basic of bioinformatics
Basic of bioinformaticsBasic of bioinformatics
Basic of bioinformatics
 
Drug Designing
Drug DesigningDrug Designing
Drug Designing
 
Natural products in drug discovery
Natural products in drug discoveryNatural products in drug discovery
Natural products in drug discovery
 
Applications Of Bioinformatics In Drug Discovery And Process
Applications Of Bioinformatics In Drug Discovery And ProcessApplications Of Bioinformatics In Drug Discovery And Process
Applications Of Bioinformatics In Drug Discovery And Process
 
introduction to bioinfromatics.pptx
introduction to bioinfromatics.pptxintroduction to bioinfromatics.pptx
introduction to bioinfromatics.pptx
 
Drug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsDrug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugs
 
Drug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugsDrug discovery clinical evaluation of new drugs
Drug discovery clinical evaluation of new drugs
 
Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014
 
Computer aided drug designing
Computer aided drug designing Computer aided drug designing
Computer aided drug designing
 
Computer aided drug design
Computer aided drug designComputer aided drug design
Computer aided drug design
 
drug discovery- history, evolution and stages
drug discovery- history, evolution and stagesdrug discovery- history, evolution and stages
drug discovery- history, evolution and stages
 
Drug discovery
Drug discoveryDrug discovery
Drug discovery
 
Cadd
CaddCadd
Cadd
 
In silico drug desigining
In silico drug desiginingIn silico drug desigining
In silico drug desigining
 
Genomics and Bioinformatics
Genomics and BioinformaticsGenomics and Bioinformatics
Genomics and Bioinformatics
 
Drug design based on bioinformatic tools
Drug design based on bioinformatic toolsDrug design based on bioinformatic tools
Drug design based on bioinformatic tools
 
computer simulations.pptx
computer simulations.pptxcomputer simulations.pptx
computer simulations.pptx
 
Bioinformatics role in Pharmaceutical industries
Bioinformatics role in Pharmaceutical industriesBioinformatics role in Pharmaceutical industries
Bioinformatics role in Pharmaceutical industries
 

Recently uploaded

Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...Dipal Arora
 
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...tanya dube
 
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Faridabad Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...aartirawatdelhi
 
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...vidya singh
 
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...Genuine Call Girls
 
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...astropune
 
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomLucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomdiscovermytutordmt
 
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋TANUJA PANDEY
 
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Gwalior Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Call Girls in Nagpur High Profile
 
Russian Escorts Girls Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls Delhi
Russian Escorts Girls  Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls DelhiRussian Escorts Girls  Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls Delhi
Russian Escorts Girls Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls DelhiAlinaDevecerski
 
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Haridwar Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Top Rated Bangalore Call Girls Richmond Circle ⟟ 9332606886 ⟟ Call Me For Ge...
Top Rated Bangalore Call Girls Richmond Circle ⟟  9332606886 ⟟ Call Me For Ge...Top Rated Bangalore Call Girls Richmond Circle ⟟  9332606886 ⟟ Call Me For Ge...
Top Rated Bangalore Call Girls Richmond Circle ⟟ 9332606886 ⟟ Call Me For Ge...narwatsonia7
 
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Nagpur Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...perfect solution
 

Recently uploaded (20)

Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Bhubaneswar Just Call 9907093804 Top Class Call Girl Service Avail...
 
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
Premium Bangalore Call Girls Jigani Dail 6378878445 Escort Service For Hot Ma...
 
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Faridabad Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Faridabad Just Call 9907093804 Top Class Call Girl Service Available
 
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...
Night 7k to 12k Navi Mumbai Call Girl Photo 👉 BOOK NOW 9833363713 👈 ♀️ night ...
 
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...
Manyata Tech Park ( Call Girls ) Bangalore ✔ 6297143586 ✔ Hot Model With Sexy...
 
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...
Pondicherry Call Girls Book Now 9630942363 Top Class Pondicherry Escort Servi...
 
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
 
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomLucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
 
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
 
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Gwalior Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 9907093804 Top Class Call Girl Service Available
 
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
 
Russian Escorts Girls Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls Delhi
Russian Escorts Girls  Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls DelhiRussian Escorts Girls  Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls Delhi
Russian Escorts Girls Nehru Place ZINATHI 🔝9711199012 ☪ 24/7 Call Girls Delhi
 
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
 
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
 
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ludhiana Just Call 9907093804 Top Class Call Girl Service Available
 
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Haridwar Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Haridwar Just Call 9907093804 Top Class Call Girl Service Available
 
Top Rated Bangalore Call Girls Richmond Circle ⟟ 9332606886 ⟟ Call Me For Ge...
Top Rated Bangalore Call Girls Richmond Circle ⟟  9332606886 ⟟ Call Me For Ge...Top Rated Bangalore Call Girls Richmond Circle ⟟  9332606886 ⟟ Call Me For Ge...
Top Rated Bangalore Call Girls Richmond Circle ⟟ 9332606886 ⟟ Call Me For Ge...
 
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
 
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Nagpur Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Nagpur Just Call 9907093804 Top Class Call Girl Service Available
 
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...
College Call Girls in Haridwar 9667172968 Short 4000 Night 10000 Best call gi...
 

Bioinformatics Tools Speed Drug Design

  • 1. Important Points in Drug Design based on Bioinformatics Tools History of Drug/Vaccine development – Plants or Natural Product • Plant and Natural products were source for medical substance • Example: foxglove used to treat congestive heart failure • Foxglove contain digitalis and cardiotonic glycoside • Identification of active component – Accidental Observations • Penicillin is one good example • Alexander Fleming observed the effect of mold • Mold(Penicillium) produce substance penicillin • Discovery of penicillin lead to large scale screening • Soil micoorganism were grown and tested • Streptomycin, neomycin, gentamicin, tetracyclines etc. http://www.geocities.com/bioinformaticsweb/drugdiscovery.html
  • 2. Important Points in Drug Design based on Bioinformatics Tools • Chemical Modification of Known Drugs – Drug improvement by chemical modification – Pencillin G -> Methicillin; morphine->nalorphine • Receptor Based drug design – Receptor is the target (usually a protein) – Drug molecule binds to cause biological effects – It is also called lock and key system – Structure determination of receptor is important • Ligand-based drug design – Search a lead ocompound or active ligand – Structure of ligand guide the drug design process
  • 3. Important Points in Drug Design based on Bioinformatics Tools • Identify Target Disease – Identify and study the lead compounds – Marginally useful and may have severe side effects • Refinement of the chemical structures – Detect the Molecular Bases for Disease – Detection of drug binding site – Tailor drug to bind at that site – Protein modeling techniques – Traditional Method (brute force testing)
  • 5. Overview Continued – A simple example Protein Small molecule drug
  • 6. Overview Continued – A simple example Protein Small molecule drug Protein Protein disabled … disease cured
  • 8. Chemoinformatics ProteinSmall molecule drug Bioinformatics •Large databases •Not all can be drugs •Large databases •Not all can be drug targets
  • 9. Chemoinformatics ProteinSmall molecule drug Bioinformatics •Large databases •Not all can be drugs •Opportunity for data mining techniques •Large databases •Not all can be drug targets •Opportunity for data mining techniques
  • 10. Important Points in Drug Design based on Bioinformatics Tools • Application of Genome – 3 billion bases pair – 30,000 unique genes – Any gene may be a potential drug target – ~500 unique target – Their may be 10 to 100 variants at each target gene – 1.4 million SNP – 10200 potential small molecules
  • 11. Important Points in Drug Design based on Bioinformatics Tools • Detect the Molecular Bases for Disease – Detection of drug binding site – Tailor drug to bind at that site – Protein modeling techniques – Traditional Method (brute force testing) • Rational drug design techniques – Screen likely compounds built – Modeling large number of compounds (automated) – Application of Artificial intelligence – Limitation of known structures
  • 12. Important Points in Drug Design based on Bioinformatics Tools • Refinement of compounds – Refine lead compounds using laboratory techniques – Greater drug activity and fewer side effects – Compute change required to design better drug • Quantitative Structure Activity Relationships (QSAR) – Compute functional group in compound – QSAR compute every possible number – Enormous curve fitting to identify drug activity – chemical modifications for synthesis and testing. • Solubility of Molecule • Drug Testing
  • 13. Drug Discovery & Development Identify disease Isolate protein involved in disease (2-5 years) Find a drug effective against disease protein (2-5 years) Preclinical testing (1-3 years) Formulation Human clinical trials (2-10 years) Scale-up FDA approval (2-3 years) FileIND File N DA
  • 14. Techology is impacting this process Identify disease Isolate protein Find drug Preclinical testing GENOMICS, PROTEOMICS & BIOPHARM. HIGH THROUGHPUT SCREENING MOLECULAR MODELING VIRTUAL SCREENING COMBINATORIAL CHEMISTRY IN VITRO & IN SILICO ADME MODELS Potentially producing many more targets and “personalized” targets Screening up to 100,000 compounds a day for activity against a target protein Using a computer to predict activity Rapidly producing vast numbers of compounds Computer graphics & models help improve activity Tissue and computer models begin to replace animal testing
  • 15. 1. Gene Chips • “Gene chips” allow us to look for changes in protein expression for different people with a variety of conditions, and to see if the presence of drugs changes that expression • Makes possible the design of drugs to target different phenotypes compounds administered people / conditions e.g. obese, cancer, caucasian expression profile (screen for 35,000 genes)
  • 16. Biopharmaceuticals • Drugs based on proteins, peptides or natural products instead of small molecules (chemistry) • Pioneered by biotechnology companies • Biopharmaceuticals can be quicker to discover than traditional small-molecule therapies • Biotechs now paring up with major pharmaceutical companies
  • 17. 2. High-Throughput Screening Screening perhaps millions of compounds in a corporate collection to see if any show activity against a certain disease protein
  • 18. High-Throughput Screening • Drug companies now have millions of samples of chemical compounds • High-throughput screening can test 100,000 compounds a day for activity against a protein target • Maybe tens of thousands of these compounds will show some activity for the protei • The chemist needs to intelligently select the 2 - 3 classes of compounds that show the most promise for being drugs to follow-up
  • 19. Informatics Implications • Need to be able to store chemical structure and biological data for millions of datapoints – Computational representation of 2D structure • Need to be able to organize thousands of active compounds into meaningful groups – Group similar structures together and relate to activity • Need to learn as much information as possible from the data (data mining) – Apply statistical methods to the structures and related information
  • 20. 3. Computational Models of Activity • Machine Learning Methods – E.g. Neural nets, Bayesian nets, SVMs, Kahonen nets – Train with compounds of known activity – Predict activity of “unknown” compounds • Scoring methods – Profile compounds based on properties related to target • Fast Docking – Rapidly “dock” 3D representations of molecules into 3D representations of proteins, and score according to how well they bind
  • 21. 4. Combinatorial Chemistry • By combining molecular “building blocks”, we can create very large numbers of different molecules very quickly. • Usually involves a “scaffold” molecule, and sets of compounds which can be reacted with the scaffold to place different structures on “attachment points”.
  • 22. Combinatorial Chemistry Issues • Which R-groups to choose • Which libraries to make – “Fill out” existing compound collection? – Targeted to a particular protein? – As many compounds as possible? • Computational profiling of libraries can help – “Virtual libraries” can be assessed on computer
  • 23. 5. Molecular Modeling • 3D Visualization of interactions between compounds and proteins • “Docking” compounds into proteins computationally
  • 24. 3D Visualization • X-ray crystallography and NMR Spectroscopy can reveal 3D structure of protein and bound compounds • Visualization of these “complexes” of proteins and potential drugs can help scientists understand the mechanism of action of the drug and to improve the design of a drug • Visualization uses computational “ball and stick” model of atoms and bonds, as well as surfaces • Stereoscopic visualization available
  • 25. “Docking” compounds into proteins computationally
  • 26. 6. In Vitro & In Silico ADME models • Traditionally, animals were used for pre-human testing. However, animal tests are expensive, time consuming and ethically undesirable • ADME (Absorbtion, Distribution, Metabolism, Excretion) techniques help model how the drug will likely act in the body • These methods can be experemental (in vitro) using cellular tissue, or in silico, using computational models
  • 27. In Silico ADME Models • Computational methods can predict compound properties important to ADME, e.g. – LogP, a liphophilicity measure – Solubility – Permeability – Cytochrome p450 metabolism • Means estimates can be made for millions of compouds, helping reduce “atrittion” – the failure rate of compounds in late stage
  • 28. Size of databases • Millions of entries in databases – CAS : 23 million – GeneBank : 5 million • Total number of drugs worldwide: 60,000 • Fewer than 500 characterized molecular targets • Potential targets : 5,000-10,000

Editor's Notes

  1. Tropsha compares these. Let’s look at some of the comparisons he makes. Mutual similarity techniques.
  2. Tropsha compares these. Let’s look at some of the comparisons he makes. Mutual similarity techniques.
  3. Tropsha compares these. Let’s look at some of the comparisons he makes. Mutual similarity techniques.