1) Docking attempts to predict how biological molecules, such as proteins and ligands, interact and bind to each other. It involves finding the optimal orientation that maximizes molecular interaction and minimizes total energy. 2) Rational drug design uses docking to identify potential drug candidates in ligand databases that may bind to a target protein or receptor. The highest scoring candidates then undergo further testing and optimization. 3) Accurate docking is challenging due to the high degrees of flexibility in both molecules as they interact and conformational changes that can occur upon binding. Improving scoring functions and algorithms to model flexibility remains an important area of research.

1. Drug Design(DOCKING)
By:
JAIDEEP SARKAR
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2. Drug Design
High Throughput Screening→104 ligands per day
But: Hit Rate 10-6 per ligand


3. RATIONAL DRUG DESIGN
Compound
databases,
Microbial broths,
Plants extracts,
Combinatorial
Libraries
Random
screening
synthesis
3-D ligand
Databases
Docking
Linking or
Binding
Receptor-Ligand
Complex
Lead molecule
3-D QSAR
Target Enzyme
OR Receptor
3-D structure by
Crystallography,
NMR, electron
microscopy OR
Homology Modeling
Testing
Redesign
to improve
affinity,
specificity etc.

4. MECHANISM OF DRUG ACTION
Structure specific drugs –
Act at specific sites (receptor or enzyme)- Activity/potency susceptible to small changes in
structure
Ex.- It took Pfizer about 18 years to develop the anti-inflammatory drug Piroxicam, which
was launched in 1980 during the “golden age of rational drug discovery

5. BINDING
Substrate
Ligand
Protein
REACTION
STRUCTURAL
CHANGE
FUNCTION

6. What is Docking?
•Docking attempts to find the “best” matching between two molecules
•It includes finding the Right Key for the Lock
•Given two biological molecules determine:
- Whether the two molecules “interact”
- If so, what is the orientation that maximizes the “interaction”
while minimizing the total “energy” of the complex
Goal: To be able to search a database of molecular structures
and retrieve all molecules that can interact with the query
structure

7. The Process
Identify disease
protein
Determine structure
of Protein
Identify active site
Pharmacological
Testing
Synthesis of Lead
Compounds
Virtual Screening of
Drug Candidates
Optimisation
Clinical Trials
Drug

8. Docking Protocol

9. contd...
RANDOM START POSITION:
• Creation of a decoy begins with a random orientation of
each partner and a translation of one partner along the line
of protein centers to create a glancing contact between the
proteins

10. Lead Optimization
Express proteins
with changes in
amino acid
sequences
Identify amino
acids involved in
function
Active site
Lead Lead Optimization

11. How DOCK works…….
Generate molecular surface of protein
Cavities in the receptor are used to
define spheres (blue); the centres
are potential locations for ligand atoms.
Sphere centres are matched to ligand
atoms, to determine possible orientations
for the ligand. 104 orientations generated

12. Virtual screening, to
•
•
•
•
•
•
identify potential lead
compounds from a large
dataset
Known structures of organic
compounds
Libraries of Virtual Compounds
Programs calculate affinity for
protein
Narrow down to small number of
possiblities
Surface representation that
efficiently represents the docking
surface and identifies the regions of
interest (cavities and protrusions)
Surface matching that matches
surfaces to optimize a binding score

13. Pose prediction
• If we know exactly
where and how a
known ligand binds...
– We can see which
parts are important
for binding
– We can suggest
changes to improve
affinity
– Avoid changes that
will ‘clash’ with the
protein

14. Introducing flexibility:
Whole molecule docking programs
•
•
•
•
Monte Carlo methods (MC)
Molecular Dynamics (MD)
Simulated Annealing (SA)
Genetic Algorithms (GA)
Available in packages:
 Auto Dock (MC,GA,SA)
 GOLD (GA)
 Sybyl (MD)
 Glide (Schrodinger)
Rosetta DOCK (Baker ,
Washington Univ., Gray,
Johns Hopkins Univ.)

15. Why is docking important?
• It is the key to rational drug design: The results of
docking can be used to find inhibitors for specific
target proteins and thus to design new drugs. It is
gaining importance as the number of proteins
whose structure is known increases
• In addition to new drug discovery, it is of extreme
relevance in cellular biology, where function is
accomplished by proteins interacting with
themselves and with other molecular components

16. Modified Simple Algorithm and 3D Superposition and
Alignment

17. Drug Discovery by Drug Designing
Case Study: Tuberculosis
Combinatorial chemistry
Enzyme assay
AccD5-NCI65828
7
6
5
1/Vo (min-1)
Crystals &
Crystal structure
[I] = 0.00
[I] = 2.50
[I] = 5.00
[I] =10.00
4
3
2
1
0
-1
-0.006
-0.004
-0.002
0
0.002
0.004
0.006
0.008
0.010
0.012
0.014
1/[Malonyl-CoA]um-1
Virtual Screening
TB ACCase, AccD5
Lead compound

18. The Computational Loop Similarity Search
Docking

19. Structure-Based Drug Design
Identified AccD5 Inhibitors
NH2
HO3S
N

N
OH
New TB drug lead

20. Why is this difficult?
• Both molecules are flexible and may alter each other’s
structure as they interact:
• Hundreds to thousands of degrees of freedom (DOF)
• Total possible conformations are astronomical

21. Trypsinogen
Trypsin
Chymotrypsinogen
Chymotrypsin
Enterokinase
Duodenal Cell

22. USES OF DOCKING
 Drug targets
 Protein- ligand interactions that otherwise may be
overlooked
 Better understand the Machinery of Life
 Enzyme-inhibitor class
 Antibody-antigen class
 Others
 Protein Therapies
 Engineered Protein Enzymes
 Although the reliability of docking methods is not so
high, they can provide new suggestions
 False positives rates can be reduced using several scoring
functions in a consensus-scoring strategy

23. ADVANCE USE…….
Cancer cell growth appears to be related to
evolutionary development of plump fruits and
vegetables
Large tomatoes can evolve from wild,
blueberry-size tomatoes. The genetic
mechanism responsible for this is
similar to the one that proliferates
cancer cells in mammalians. That's a
connection nobody could have made
in the past.

24. Future Challenges For Docking
• Better Scoring Functions
• High-Throughput Screening
• Tractable Models of Flexibility
• The so-called computational molecular docking problem is far
from being solved. There are two major bottle-necks:
1. The algorithms can handle only a limited extent of
backbone flexibility
2. The availability of selective and efficient scoring
functions