1. 07/21/13

2. 07/21/13
Computational Aided Drug
designing
Group Members
Ayesha Aftab Malik
Zahra Hanif
Khadija Ijaz
Department of Bioinformatics and Technology
International Islamic University Islamabad

3. Drug
A chemical substance that affects the
processes of the mind or body which is used
in
 diagnosis
 Treatment
 prevention
of disease or other abnormal condition.

4. DRUG DESIGN
Drug design, is the inventive process of
finding new medications based on the
knowledge of a biological target.

5. Drug designing…..
Selected/designed molecule
should be:
 organic small molecule.
 complementary in shape
to the target.
 Oppositely charge to the
biomolecular target .

6. Drug designing…..
This molecule will:
 interact with target
 bind to the target
 activates or inhibits the function of a
biomolecule such as a protein

7. 7
Cont……..
• Drug design frequently but not necessarily
relies on computer modeling techniques.

8. Types of drug design
1. Ligand based drug design
2. Structure based drug design

9. Ligand based drug design
• Ligand-based drug design
relies on knowledge of other
molecules that bind to the
biological target of interest
• used to derive a
pharmacophore

10. Structure based drug design
Structure-based drug design
relies on knowledge of the
three dimensional structure
of the biological target
obtained through methods
such as
 x-ray crystallography
 NMR spectroscopy.
 homology modeling

11. Structure based drug
design…..
• Using the structure of the biological target,
drugs that are predicted to bind with to the
target may be designed using
 interactive graphics
 the intuition of a medicinal chemist.
 automated computational procedures

12. Techniques of drug design

13. X-ray crystallography
 starting point for gathering information from
mechanistic drug design.
 determine structural information about a
molecule.
 provides the critically important coordinates
needed for the handling of data by computer
modeling system.

14. NuclearMagnetic Resonance (NMR)
 NMR uses much softer radiation
 examine molecules in the more
mobile liquid phase
 three-dimensional information will
be obtained.
 examine small molecule-
macromolecule complexes, such as
an enzyme inhibitor in the active site
of the enzyme.

15. HOMOLOGY MODELING:
 Homology modeling, also known as
comparative modeling of protein, refers to
constructing an atomic-resolution model of
the "target" and an experimental three-
dimensional structure of a related
homologous protein (the "template").

16. Computer Aided Drug design
(CADD)

17. Computer Aided Drug design
• CADD represents computational methods and
resources that are used to facilitate the
design and discovery of new therapeutic
solutions.

18. History of Drug development

19. Screening for new drugs
Plants or Natural Product
 Plant and Natural products were source for medical
substance
 Example: foxglove used to treat heart failure
Accidental Observations
 Penicillin is one good example
 Alexander Fleming observed the effect of mold.

20. Modifications for improvement
• Modifications to improve performance are
often carried out using chemical or bio
fermentative means to make changes in the
lead structure or its intermediates.
• for some natural products, the gene itself
may be engineered so that the producer
organism synthesizes the modified compound
directly.

21. Mechanism based drug design
• When the disease process is understood at
the molecular level and the target
molecule(s) are defined, drugs can be
designed specifically to interact with the
target molecule in such a way as to disrupt
the disease.

22. Basic Mechanism of CADD

23. 1. Selection of disease
• The first step in the design of drugs to treat diseases is to
 determine the biochemical basis of the disease process.
• Ideally, one would know the various steps involved in the
physiological pathway that carries out the normal function. In
addition, one would know the exact step(s) in the pathway
that are altered in the diseased state.
• Knowledge about the regulation of the pathway is also
important. Finally, one would know the three- dimensional
structures of the molecules involved in the process.

24. Target selection
• There are potentially many ways in which
biochemical
pathways could become abnormal and result in
disease.
• Therefore, knowledge of the molecular basis
of the disease is
important in order to select a target at which
to disrupt the
process.

25. Target selection
Categories of targets:
Target for mechanistic drug design usually fall
into three:
 enzymes,
 receptors
 nucleic acids.

26. STRUTURE DETERMINATION
• Crystal structure of target protein can be
taken from PDB database

27. PDB database

28. Determination of active site of
target protein
 Only a small part of a lead compounds may
be involved in the appropriate interaction.
The relevant groups on a molecule that
interact with the receptor and are
responsible for activity are collectively
known as pharmacophore.

29. Selection of ligands/drugs

30. Molecular docking
 • Docking is a method which predicts the
preferred orientation of one molecule to a
second when bound to each other to form a
stable complex.

31. • Flexible docking programs like DOCK,
AutoDock and Molecular Operating
Environment (MOE) enable user to predict
favorable biological target–ligand complex
structures with reasonable accuracy and
speed.

32. AutoDock
 AutoDock is a suite of automated docking
tools. It is designed to predict how small
molecules, such as substrates or drug
candidates, bind to a receptor of known 3D
structure.

33. Visualization of docked
complex
 The docked complex is then visualized and
studied using a software like VMD (Visual
Molecular Dynamics).

34. VMD

35. 35
Retrieving 3D structures
• first step for protein visualization is to extract the protein
structure from a structure database in specific file
formats like PDB format or Cn3D format,which would
serve as input for the 3D visualization programs.

36. Retrieving from PDB database
• protein data bank(PDB)
• -http://www.rcsb.org/pdb/home/home.do

37. Retrieving from PDB database

41. What isVMD?
• VMD (Visual Molecular Dynamics) is a molecular visualization program for
displaying,
• animating, and analyzing large biomolecular systems such as proteins, nucleic
acids, lipid bilayer
• assemblies, etc. using 3-D graphics and built-in scripting. VMD supports computers
running
• MacOS X, Unix, or Windows, is distributed free of charge, and includes source
code. It may be
• used to view more general molecules, as VMD can read standard Protein Data
Bank (PDB) files
• and display the contained structure. VMD provides a wide variety of methods for
rendering and
• coloring a molecule. VMD can be used to animate and analyze the trajectory of a
molecular
• dynamics (MD) simulation. In particular, VMD can act as a graphical front end for
an external
• MD program by displaying and animating a molecule undergoing simulationon a
remote
• computer.

42. Key Features of VMD
• General 3-D molecular visualization with extensive drawing and coloring
methods
• Extensive atom selection syntax for choosing subsets of atoms for display
• Visualization of dynamic molecular data
• Visualization of volumetric data
• Supports all major molecular data file formats
• No limits on the number of molecules or trajectory frames, except available
memory
• Molecular analysis commands
• Rendering high-resolution, publication-quality molecule images
• Movie making capability
• Building and preparing systems for molecular dynamics simulations
• Interactive molecular dynamics simulations
• Extensions to the Tcl/Python scripting languages
• Extensible source code written in C and C++

51. BENEFITS OF CADD

52.  DRUG DISCOVERY:
Use of computing power to streamline drug
discovery and development process.

53. Elimination of compounds with
undesirable properties
Design of in silico filters to eliminate
compounds with undesirable properties (poor
activity and/or poor Absorption
Distribution, Metabolism, Excretion and
Toxicity, ADMET) and select the most
promising candidates

54. Identify and optimize new
drugs
 Leverage of chemical and biological
information about ligands and/or targets to
identify and optimize new drugs

55. Benefits
• TIME SAVING:
The process of drug discovery and
development is a long and difficult one, and
the costs of developing are increasing
rapidly. Today it takes appropriately 10years
and $100million to bring a new drug to
market.

56. REDUCED COST:
The use of new computer-based drug design
techniques has the ability to accomplish both
of these goals and to improve the efficiency
of the process as well, thus reducing costs.

57. • IMPROVE QUALITY OF LIFE:
The emphasis now is not just on finding new
ways to treat human disease, but also on
improving the quality of life of people in
general.