describe about docking based screen on drug discovery .

1. Docking Based screening
Praveen Kumar.S
M.Pharm 2nd semester
Department of pharmacology
PSG college of pharmacy

2. Introduction
• Molecular docking : prediction of the association
between two molecules.
We use computational approach to:
1. Observe how a compound is structurally placed
with its partner(receptor).
2. Understand the recognition process and
establish structure activity/property
relationship.
3. Predict on a database of chemical compounds
which ones are the most able to interact with
the target.

3. • Computational virtual screening works
basically as a filter (prefilter)consisting of the
virtual selection of molecules ,based on
predefined properties of active compounds
against determined pharmacological target.
• Two variant of this method ,
1. Ligand based virtual screening.
2. Structure based virtual screening.

4. Cont…
• An inverse virtual screeening technology
based on molecular docking methods has
been developed and widely used for process
of target identification.
• A molecular docking method is defined as the
prediction of both the binding mode and
binding affinity of a query ligand.

6. Steps
Practical application of molecular docking requires Data bank for the search of target
with proper PDB format and a methodology to prepare ligand as a PDB file.
Molecular docking of small molecules to a target includes a pre-defined sampling of
possible conformation of ligand in the particular groove of target in an order to
establish the optimized conformation of the complex.
The infrared spectroscopy, x-ray crystallography and nuclear magnetic resonance
(NMR) spectroscopy are the techniques for the investigation and establishment of
three dimensional structures of any organic molecule/ biomolecular targets.
Homology modelling makes it possible to determine the tentative structure of
proteins of unknown structure with high sequence homology to known structure.
This can be made possible using scoring functions.

8. Approaches in docking
In molecular docking was performed by two
approaches,
1. Simulation approach.
2. Shape complementarity approach.

9. Simulation approach
• The ligand and target is being separated by physical
distance and then ligand is allowed to bind into
groove of target after “definite times of moves” in its
conformational space .
• The moves involve variations to the structure of
ligand either internally (torsional angle rotations) or
externally (rotations and translations).
• The ligand in every move in the conformational limit
releases energy, as “total energy”

10. A simulation approach shown in docked adducts.
Here the ligand and target are separated by some physical distance and interact by
means of mostly H-bond.

11. Shape complementarity approach
• This approach employs ligand and target as surface
structural feature that provides their molecular
interaction.
• The complementarity between two surfaces based
on shape matching illustration helps in searching the
complementary groove for ligand on target surface.
• For example, in protein target molecules,
hydrophobicity is estimated by employing number of
turns in the main-chain atoms.

12. Here the surface structural feature of ligand
and target that provides their
molecular interaction.
Molecular docking of B-DNA [with
sequence (CGCAAATTTCGC)2]
dodecamer with anticancer heterosteroid

13. • In docking based screening a given small
molecules is docked to the binding site of each
protein in a target database through a docking
engine .
• Then target proteins are ranked according to
the binding scores estimated by a scoring
function.

14. Target databases
• A database consisting of three dimensional
protein structure is required for the docking
based screening.
• An x ray crystallography and nmr spectroscopy
,an increasing number protein crystal structure
has been resolved and deposited in publically
accesiable database .
1. Therapeutic database
2. potential drug target database.
3. Drug adverse reaction database.

16. Database Description URL
PDB A pool of 3D structures of
macromolecules, including
proteins, nucleic acids and
complex assemblies.
http://www.rcsb.org/
Sc-PDB A subset of PDB with the
collection of protein-ligand
complexes.
http://bioinfo-pharma.u-
strasbg.fr/scPDB
TTB Therapeutic target
database (TTD)contains
2360 targets,
including2589
targets.including 397
successful 723clinical trial
1469 research targets.
http://bidd.nus.edu.sg/gro
up/ttd

17. PDTD Potential Drug Target
Database(PDTD) Contains
1207 entries covering 841
known and potential drug
targets further
catagoriezed into subsets
acording to 2 criteria one is
therapeutic another is
biochemical.
http://www.dddc.ac.cn/p
dtd
DART Drug Adverse Reaction
Database (DART) contains
147 ADR target and 89
potential targets.
http://bidd.nus.edu.sg/gro
up/drt
DRUGBANK The latest version 5.0
database contains 8261
drug entries including 2021
FDA approved drugs 233
biotech protein-peptide
drugs .
http://www.drugbank.ca/

18. Docking engines
• Prediction of protein –ligand complex structure plays an
essential role in docking based screening .
• A docking program is designed to predict a complex
structure based on the known 3d structure of its
components .
• In early stages of the development of the docking
methods ,both the ligand and receptor were treated
rigidly.
• A shape matching method was employed to place a ligand
in the binding site of a receptor .only six degrees of
freedom (3translational and 3 rotational )of aligand
conformational are considered.

19. • According to the searching method ,ligand
flexibility algorithms can be divided into three
types:
1. Systematic search
2. Stochastic search
3. Deterministic search

20. Systemic search
 It generates all possible ligand binding
conformation by exploring hole
conformational space .
The completeness of sampling ,the number of
evaluations increases rapidly as the no. Of
degree of freeedom also increased .(i.E-the
no.Of rotatable bond in a ligand).
Software: GLIDE,LUDI,DOCK.

21. Stochastic approach
Stochastic algorithms;
• sample the ligand conformational space by
making random changes, which will be
accepted or rejected.
• According to a probabilistic criterion.
• This type of methods significantly reduces
computational efforts for large systems.
• Software: Monte Carlo,MC dock, GOLD

22. Deterministic search
Deterministic search,
• The final state of the system depends on the
initial state.
• Examples are energy minimization methods
and molecular dynamics (MD) simulations.
• Systems are thus guided to states with lower
energies.

23. Docking methods
• The complexity of computational docking
Increase in the following order:
1. Rigid body docking,
Where both the receptor and small molecule are
treated as rigid.
2. Flexible ligand docking,
Where the receptor is held rigid,but the ligand is
treated as flexible.
3. Flexible docking,
Where both receptor and ligand flexibility is
considered.

26. Scoring function
• One of the most important component of
molecular docking is scoring.
• The aim of scoring is to quantify the free energy
associated with protein and ligand in the
formation of the Protein-ligand interactions.
• Most of the docking softwares are equipped with
scoring functions, which enable computing free
energy associated with protein-ligand
interactions(Docking score)

27. Cont..
• Currently, three main types of scoring
functions are applied.
1. Force field-based.
2. Empirical scoring function
3. Knowledge based scoring functions .

28. Force field-based scoring functions
• This type relies on the molecular mechanics
methods.
• Force field based nethods calculate both the
protein-ligand interaction energy and ligand
interaction energy and ligand internal energy and
sum both the energies.
Etotal= Ebonded+Enonbonded
Ebonded=Ebond+Eangle+Edihedral
Enonbonded=Eelectrostatic+Evan der wals.

29. Knowledge based scoring functions:
• It uses atom pair interaction potentials as in
potential of mean force (PMF).
• Atom pair interaction potentials are usually
derived from structural information stored in
databases(chemBridge structural database and
protein data bank)
• One major limitation of this method is the limited
availability of such structural information in the
intermolecular interaction databases.

30. Empirical scoring functions
• The score in the empirical scoring function is
derived from the individual energy
contributions of each component involved in
intermolecular interactions
∆Gbind =
∆Gdesolvation+∆Gmotion+∆Gconfiguration+
+ ∆Ginteraction

31. Software used in molecular docking
Name Search
algorithm
Evaluation
method
Speed Features and
application
Flex X Fragmentation
algorithm
Semi-empirical
calculation on
free energy
Fast Flexible-rigid
docking.It can
be used for
virtual screening
of small
molecule
database.
Gold GA (genetic
algorithm)
Semi-empirical
calculation on
free energy
Fast Flexible
docking.
It is a GA-based
docking
program. The
accuracy and
reliability of this
software have
been highly
evaluated

32. Name Search
algorithm
Evaluation
method
Speed Features and
application
Glide Exhaustive
systematic
search
Semi-empirical
calculation on
free energy
Medium Flexible
docking.This
software uses
domain
knowledge to
narrow the
searching range
and has
XP(extra
precision),
SP
(standard
precision)
Autodock GA (genetic
algorithm)
LGA
(lamarckian
genetic
algorithm)
Semi-empirical
calculation on
free energy
Medium
Flexible-rigid
docking.This
software is
always used
with Autodock-
tools and it
is free for
academic use

33. Applications
• Target identification.
• Side-effects and toxicity.
• Drug repositioning.
• Multi -target therapy
• Receptor designs.

34. Challenges
• The first challenge is the incompleteness of
available target databases.
• Using the data in DrugPort
(http://www.ebi.ac.uk/thornton
srv/databases/drugport/) as an example,
there are a total of 1664 known druggable
protein targets in the database, but only
about half of them have 3D structures in the
PDB.

35. • Another challenge is from the vantage point of
protein flexibility. protein–ligand binding is a
mutual fitting process.
• The existing docking programs are able to
account for the flexibility of small molecules
very well, but the overall flexibility of the
entire protein remains a great challenge.
• To effectively evaluate a method of docking-
based IVS, a database is desired to contain
both positive and negative results.

36. References
• Docking-based inverse virtual screening:
methods,applications, and challenges
Xianjin Xu1,2,3,4, Marshal Huang1,3, Xiaoqin
Zou1,2,3,4&
• Molecular Docking: Approaches, Types,
Applications and Basic Challenges
Ayaz Mahmood Dar1,2* and Shafia Mir2