Virendra

DRUG DISCOVERY
&
COMPUTER AIDED
DRUG DESIGN
Virendra Nath
B.N College Of Pharmacy
Udaipur
Rajasthan
1
B.N COLLEGE OF PHARMACY
UDAIPUR , RAJASTHAN

DRUG DISCOVERY
 The process of drug discovery
involves-
o Identification of candidate
o Synthesis
o Screening
o Assay for therapeutic efficacy
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UDAIPUR , RAJASTHAN

Identify disease
Isolate protein
Find drug
Preclinical testing
COMBINATORIAL CHEMISTRY
Rapidly producing vast numbers
of compounds
MOLECULAR MODELING
Computer graphics & models help improve activity
IN VITRO & IN SILICO ADME MODELS
Tissue and computer models begin to replace animal testing
BIOINFORMATICS
Potentially producing many more targets
and “personalized” targets
HIGH THROUGHPUT SCREENING
Screening up to 100,000 compounds a
day for activity against a target protein
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UDAIPUR , RAJASTHAN

Drug Discovery Process
New
Drug
Target
Identification
Target
Qualification
Validation
Lead
Identification
Lead
Optimization
Preclinical
Development
Clinical
Development
NDA
Clinical
Trials
&
Clinical
monitori
ng
Drug DesignExploratory Drug Development
CADD
&
QSAR
Bioinformatics
&
Assay
Development
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UDAIPUR , RAJASTHAN

Drug Discovery Process
1. What is an ideal drug?
Given by mouth and has a beneficial effect
{safe & efficacious}
2. What is a promising drug
candidate?
Site specific
Affinity
Bioavailability with lowest toxicity.
3. How is a ‘lead’ drug candidate
screened for ideal
characteristics?
Study of the in vitro ADME/Tox- drug
transport , absorption, metabolism, etc.
[Toxicity & pharmacokinetics: In vivo ] 5
UDAIPUR , RAJASTHAN

Focused Area Of Research
Important
Drug
Targets
Metabolic
Gastrointestinal
Inflammator
y /Immune
Related
Oncology/
Cancer
Respiratory
CVS
&
Blood
Musculoskeletal
Infectious
disease
(Microbial
& Viral)
Neurological
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UDAIPUR , RAJASTHAN

Computer Aided Drug
Design
Computer Aided Drug design is the inventive
approach of finding new medications based on
knowledge of biological targets.
Drug is an organic molecule that activate or
inhibits the function of bio-molecule or protein in
the therapeutic manner
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UDAIPUR , RAJASTHAN

Types of Drug Design:
Structure based
drug design
• Finding new
medication based
on the knowledge
of the target.
• Also known as
Direct drug
design.
Ligand based
drug design
• Knowledge of other
molecules that bind
to the biological
target of interest.
• Also known as
Indirect drug
design.
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UDAIPUR , RAJASTHAN

S.no. Name of the Drugs Category Use
1 Dorzolamide Carbonic
Anhydrase
Inhibitor
Glaucoma
2 Cimetidine H2 Blocker Peptic Ulcer &
Acidity
3 Celecoxib ,
Lumaricoxib ,
Firocoxib , Deracoxib
Selective COX-2
Inhibitor
Analgesic ,
Anti-
inflammatory ,
Antipyretic
4 Enfuvirtide Fusion Inhibitor HIV positive
5 Zolpidem & Zopiclone Nobenzodiazepine
s
Antianxiety ,
Anti-epileptic.
6 Fluoxetine SSRI Antidepressant
7 Probenecid Increase Uric acid
Excretion
Anti-Gout
8 Sumatriptan 5-HT Blocker Migraine
9 Naloxone,Naltrioxone Opoid receptor
antagonist
Opoid
poisioning/with
drawl
S
U
C
C
E
S
S
S
T
O
R
Y
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UDAIPUR , RAJASTHAN

Lead Structure
Identification:
LEAD
STRUCTURE/
S
Literature
, Patents and
other drugs
Screenin
g
Side
effects in
the clinics
Identification of
Biological
targets , Proof of
therapeutic
concept
Natural
products &
Combinatoria
l chemistry
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UDAIPUR , RAJASTHAN

Drug Design:
Optimizing target
interactions Once the lead compound has been discovered it
can be used as the starting point for drug design.
 There are various aims in drug design:
1. The drug should have a good selectivity for its
target
2. The drug should have a good level of activity for its
target
3. The drug should have minimum side effects
4. The drug should be easily synthesized
5. The drug should be chemically stable
6. The drug should have acceptable
pharmacokinetics properties
7. The drug should be non-toxic
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UDAIPUR , RAJASTHAN

3D Structures In Drug Res
 Experimental determination of 3D structures:
X-Ray structure analysis & 2D-NMR.
 Generation of 3D Structures:
Concord, CORINA(rule based system)
Force field & QC method.
 Multiple 3D-Structures:
Systematic & Mote-Carlo search, Molecular dyanamics
simulation and Rule-based system.
 Superposition of molecules:
“Rigid fit” & “Field fit” (SEAL)
 Pharmacophore hypothesis:
CATALYST & Active analog approach.
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UDAIPUR , RAJASTHAN

PHARMACOPHORE
 The spatial arrangement of chemical groups
that determines its activity.
 With the model in hand, search databases for
molecules that fit this spatial environment.
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UDAIPUR , RAJASTHAN

PHARMACOPHORE
DESCRIPTOR
 Number of acidic atoms.
 Number of basic atoms.
 Number of hydrogen bond donor
atoms.
 Number of hydrophobic atoms.
 Sum of VDW surface areas of
hydrophobic atoms.
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UDAIPUR , RAJASTHAN

QSAR
Quantitative
Structure
Activity
Relationship
An established mathematical
relationship between
biological activity and
physicochemical
parameters.
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UDAIPUR , RAJASTHAN

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Basic Requirements In
QSAR Studies
 All analogs belong to same group of series.
 All analogs exert same mechanism of action.
 All analogs bind in the comparable manner.
 The effects of isosteric replacement can be predicted.
 Examples:
 Binding affinity is correlated to the interaction energies.
 Biological activity are correlated to biological affinity.
 Three more requirements for QSAR : Dataset
, Descriptors & Statistical methods.
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Group Isosteric Replacement
Xanthine Alloxanthine
Hydrogen Fluorine
Carbon Silicone
Procainamide Procaine
UDAIPUR , RAJASTHAN

Molecular Descriptors
In QSAR1. Constitutional
◦ Total number of atoms, atoms of a certain
type, number of bonds, number of rings
2. Topological
◦ Molecular shape, degree of branching
3. Electronic
◦ Partial atomic charges, dipole moments
4. Geometrical
◦ Van der Waals volume, molecular surface
5. Quantum Mechanical
◦ Total energy, interaction energy between two atoms, nuclear
repulsion between atoms
6. Physicochemical
◦ Liquid solubility, log P, boiling point 19
UDAIPUR , RAJASTHAN

Lipinski’s “Rule of Five”
Compounds are likely to have a good absorption
and permeation in biological systems and are thus
more likely to be successful drug candidates if they
meet the following criteria:
 H donors ≤ 5
 H acceptors ≤ 10
 MW ≤ 500 Dalton
 Calculated Log P ≤ 5
Exceptions: Statins , AT-2 antagonist , Taxanes ,
Leukotriene antagonist and Natural products also.
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UDAIPUR , RAJASTHAN

HANSCH’S
APPROACH:
 The first application of QSAR is considered to
Hansch (1969), who developed an equation that
related biological activity to certain electronic
characteristics and the hydrophobicity of a set of
structures.
log (1/C) = k1log P - k2(log P)2 + k3s + k4
for: C = minimum effective dose
P = Octanol - Water partition coefficient
s = Hammett substituent constant
kx= constants derived from regression analysis
 Biological activity normally expressed as
1/C, where C = [drug] required to achieve a defined
level of biological activity. The more active drugs 21
UDAIPUR , RAJASTHAN

Partition Coffecient
(Log P)
 Log P is a measure of the drug’s
hydrophobicity (ability to pass through the
cell membrane).
 The log P (or log Po/w) value reflects the
relative solubility of the drug in octanol
(representing the lipid bilayer of a cell
membrane) and water (the fluid within the
cell and in blood).
 Log P values may be measured
experimentally or, more commonly,
calculated.
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UDAIPUR , RAJASTHAN

Calculating Log P
Log P = Log K (o/w) = Log ([X]octanol/[X]water)
 Higher value of Log P: Poor solubility in aq.
phase.
Log P values of anesthetics:
ether chloroform halothane
0.98 1.97 2.3
(Halothane enters in CNS more efficiently than others.
)
 Some use more complicated algorithms, including
factors such as the dipole moment, molecular size 23
UDAIPUR , RAJASTHAN

Substitution Constant
(π)
 Calculation of substituent
hydrophobicity constant (p) that
measure of how hydrophobic relative
to H.
px = log Px - log PH
 Positive p = substituent more
hydrophobic than H.
 Negative p = less hydrophobic than H.
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UDAIPUR , RAJASTHAN

Electronic Effects: Hammett
Constants
 Measure e-withdrawing or e-donating effects
(compared to benzoic acid & how affected its
ionization).
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UDAIPUR , RAJASTHAN

 Electron Withdrawing Groups:
Equilibrium shifts Right & Kx > Kbenzoic
Since sx = log Kx – log Kbenzoic, then s will be
positive .
sx = log (Kx/Kbenzoic)
 Value of Hammett constant depends on the
position of substituent
ie; ortho , para or meta
due to both Resonance and Inductive effect.
* Ortho not measurable due to steric
effects. 26
UDAIPUR , RAJASTHAN

Steric Effects:
 Examples are:
• Denoted by Es
• Exp. value based on rate constant
Taft’s steric
factor
• Denoted by MR
• Measure of volume occupied by an
atom or a group.
• Equation includes MW, Density &
Refractive index
Molar
refractivity
• Includes bond angle , bond length &
van der walls radii.
Verloopsteric
parameter
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UDAIPUR , RAJASTHAN

FREE WILSON
APPROACH
 The biological activity of parent structure is
measured and compare with the activity of
analogs having different substituents.
Activity = k1X1 + k2X2 +.…knXn + Z
Xn : Indicator variable (no. of substituents)
 The contribution of each substituent to activity is
determined by the value of kn.
Z: constant representing overall activity of
structure.
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UDAIPUR , RAJASTHAN

• No need for
Physicochemical
properties.
• Useful for structure with
unusual substituent
Advantages
Of
Free Wilson
approach
• Large no. of analogues
need to be synthesized to
represent each different
substituent for each
different position.
• Difficult to rationalize why
specific substituent is good
or bad.
Disadvantages
Of
Free Wilson
approach
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UDAIPUR , RAJASTHAN

3D QSAR
 CoMFA (Comparative Molecular field
Analysis)
 Molecules are described by the values of molecular
field calculated in a point at a 3D grid.
 The molecular field are usually steric and
electrostatic.
 Partial least square(PLS) used to correlate the field
values with biological activity.
 A common pharmacophore is required.
 Biological activity is largely explained by enthalpic
process.
 Pharmacokinetics: Solvent
effects, diffusion, transport are not included.
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UDAIPUR , RAJASTHAN

Calculate property fields for every
molecule in each grid point by using
probe atom(s) or groups
(Property fields : Electrostatic & Steric
effects)
In addition, hydrophobic effect as well
as hydrogen bond donor and acceptor
may be considered.
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UDAIPUR , RAJASTHAN

List of small molecule
databases:S.no. Name of the Database URL
1 PubChem http://pubchem.ncbi.nlm.nih.gov/
2 Spectral Database for
Organic
Compound(SDBS)
http://riodb01.ibase.aist.go.jp/sdb
s/c
gi-bin/cre_index.cgi?lang=eng
3 KEGG LIGAND http://www.genome.jp/ligand/
4 ChemIDplus http://www.cas.org/index.html
5 ChemFinder http://www.chemfinder.com/chem
biofinder/Forms/Home/ContentAr
ea/Home.aspx
6 Chemical Identity
Biological Interest(ChEBI)
http://www.ebi.ac.uk/chebi/
7 Ligand Depot http://ligand-depot.rutgers.edu/
8 MSD http://www.ebi.ac.uk/msd-
srv/msdchem/ligand/help.htm
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UDAIPUR , RAJASTHAN

Softwares for Drug
Design:S.no. Name of the software URL
1 Insight II, Discovery
Studio
http://accelrys.com/products/insight/
2 Sybyl http://www.tripos.com/
3 Bio-Suite http://tcsinnovations.com/
4 Glide https://www.schrodinger.com/produc
ts/14/5/
5 Autodock http://autodock.scripps.edu/
6 Ligplot http://www.biochem.ucl.ac.uk/bsm/li
gplot/ligplot.html
7 OSDD http://www.osdd.net/
8 Sanjeevini http://www.scfbio-
iitd.res.in/sanjeevini/sanjeevini.jsp
9 Molecular Operating
Environment (MOE)
http://www.chemcomp.com/
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UDAIPUR , RAJASTHAN

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UDAIPUR , RAJASTHAN

ABOUT THE PRESENTEE :
UDAIPUR , RAJASTHAN 36
• College Of Pharmacy-IILM-AHL Greater
NOIDA (U.P)
B.PHARMACY
• B.N College Of Pharmacy Udaipur
(RAJASTHAN)
M.PHARMACY
• CSIR-IIIM Discovery Informatics Divison
(JAMMU)
TRAINING

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