Computer aided drug dsign

2. Presented by…..
0 Hafiz Hammad
0 Hassan Ali
0 Haroon Mir
0 Husham Ali
0 Ali Ahsan

3. Drug design and drug
discovery
0 Drug design, often referred to as rational drug
design or simply rational design, is the inventive
process of finding new medications based on the
knowledge of a biological target.

4. How drugs are discovered?
0 Mainly by accident
0 Can be discovered by………..
0 screening of new drugs
0 modification for improvement-by modifying existing
drugs
0 mechanistic based drug design
0 combining techniques- by combining different drugs

5. Introduction to CADD
0 CADD stands for Computer Aided drug design
0 lies In the hand of computational scientists, who are
able to manipulate molecule on the screen
0 Rather it is a complex process involving many
scientist from various stream working together.

6. CONT….
0 Drug design with the help of computers using:
0 Molecular docking
0 virtual screening (structure- or ligand-based design)
0 QSAR

7. Role of CADD
0 The target of Computer Assisted Drug Design (CADD)
is not to find the ideal drug but to identify and
optimize lead compounds and save some experiments
0 The parameters expected from a drug are…….
0 Safety
0 Efficiency
0 Stability
0 Solubility

8. What is Molecular Docking?
0 To place a ligand (small molecule) into the binding
site of a receptor in the manners appropriate for
optimal interactions with a receptor.

9. More serious definition…..
0 It predicts the preferred orientation of one molecule
to a second when bound to each other to form a stable
complex.
“Docking is a term used for computational schemes that
attempt to find the “best” matching between two
molecules a receptor and a ligand”

10. LOCK AND KEY
0 Finding the correct relative
orientation of the “key” which
will open up the “lock”.
0 On the surface of the lock is
the key hole…
0 In which direction to turn the
key after it is inserted.

11. 0 The protein can be thought of as the “lock” and the
ligand can be thought of as a “key”.

12. Docking can be between….
0 Protein - Ligand
0 Protein – Protein
0 Protein – Nucleotide

13. Basic principle
Docking involves two separate molecules.
0 It initiates from folded protein chains and ligand
conformations.
0 In contrast, protein folding initiates from some non-
native protein conformations. Hence, docking is often
viewed as distinct from folding.

14. Three Components of Docking
• Representation of the (system)
receptor binding site and ligandPre-docking
• Conformational space search of
the ligand-receptor complex
During
docking
• Evaluation of ligand-receptor
interactions
During
docking and
scoring

15. Types of Docking
0 Rigid Docking (Protein- Protein Docking)
It relates to the molecules as rigid objects that cannot
change their spatial shape during the docking process.
0 Flexible (soft) Docking (Protein – Ligand Studies)
Docking procedures that consider possible
conformational changes are termed flexible docking

16. Mechanics of docking

18. Why We Do Docking?
0 To Reduce cost of formulating new drug
0 Structure based drug design (SBDD) for lead
generation and optimization.

19. Problems of Docking studies
0 Protein-Protein Docking
0 This problem involves two proteins that are approximately
the same size.
0 Both molecules are rigid
0 Interaction produces no change in conformation
0 Similar to lock-and key model
0 Protein-Ligand Docking
0 Ligand is flexible but the receptor protein is rigid.
0 Interaction produces conformational changes in ligand

20. Why is docking important?
0 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.
0 In addition to new drug discovery, it is of extreme
relevance in cellular biology

21. Factors affecting docking
Intramolecular forces. . . .
0 bond length
0 bond angle
0 dihedral angle
Intermolecular forces. . . .
0 electrostatic
0 dipolar
0 H-bonding
0 hydrophobicity
0 Vander waals forces

22. APPLICATIONS OF
MOLECULAR DOCKING
Virtual screening (hit identification)
0 docking with a scoring function can be used to
quickly screen large databases of potential drugs in
silico to identify molecules that are likely to bind to
protein target of interest.
Bioremediation
 Protein ligand docking can also be used to predict
pollutants that can be degraded by enzymes.

23. 0 To study the geometry of a particular
complex.(Rational Design Of Drugs)
0 Identification of the ligand’s correct binding geometry
in the binding site
0 Prediction of the binding affinity
0 For predicting protein-protein interaction

24. Softwares
0 SANJEEVINI – IIT Delhi (www.scfbio-iitd.res.in/sanjeevini/sanjeevini.jsp)
0 GOLD – University of Cambridge ,UK
(www.ccdc.cam.ac.uk/Solutions/GoldSuite/Pages/GOLD.aspx)
0 AUTODOCK - Scripps Research Institute,USA (autodock.scripps.edu/)
0 GemDock(Generic Evolutionary Method for Molecular Docking) - A tool,
developed by Jinn-Moon Yang, a professor of the Institute of Bioinformatics,
National Chiao Tung University, Taiwan (gemdock.life.nctu.edu.tw/dock/)
0 Hex Protein Docking - University of Aberdeen, UK (hex.loria.fr/)
0 GRAMM (Global Range Molecular Matching) Protein docking - A Center for
Bioinformatics, University of Kansas, USA
(www.bioinformatics.ku.edu/files/vakser/gramm/)

25. QSAR
0 Quantitative structure-activity relationships (QSAR)
have been applied for decades in the development of
relationships between physicochemical properties of
chemical substances and their biological activities to
obtain a reliable statistical model for prediction of the
activities of new chemical entities.

27. Principle
0 The difference in structural properties is responsible
for the variations in biological activities of the
compounds

28. Hansch analysis
0 In Hansch analysis, physicochemical properties are
correlated with biological activity values.
0 affinities of ligands to their binding sites,
0 inhibition constants,
0 rate constants, and
0 other biological end points,
0 with atomic, group or molecular properties such as
lipophilicity, polarizability, electronic and steric
properties.

29. Free Wilson analysis
0 The Free Wilson model is a simple and efficient
method for the quantitative description of structure
activity relationships. It is the only numerical method
which directly relates structural features with
biological properties

30. Limitations of QSAR
0 This approach has only a limited utility for designing a
new molecule due to the lack of consideration of the
3D structure of the molecules.

31. Why 3D QSAR?
0 3D-QSAR has emerged as a natural extension to the
classical Hansch and Free-Wilson approaches, which
exploits the three-dimensional properties of the
ligands to predict their biological activities using
robust chemometric techniques. It has served as a
valuable predictive tool in the design of
pharmaceuticals and agrochemicals.

32. 3 D QSAR
0 In 3 D QSAR, 3D properties of a molecule are
considered.
0 3D-QSAR involve the analysis of the quantitative
relationship between the biological activity of a set of
compounds and their three-dimensional properties
using statistical correlation methods.
0 3 D QSAR revolves around the important features of a
molecule, its overall size and shape, and its electronic
properties.

33. 3D QSAR
0 Although the trial and error factor involved in the
development of a new drug cannot be ignored
completely, QSAR certainly decreases the number of
compounds to be synthesized by facilitating the
selection of the most promising candidates. Several
success stories of QSAR have attracted the medicinal
chemists to investigate the relationships of structural
properties with biological activity.

34. 3D QSAR -APPROACHES
0 ACTIVE SITE INTERACTION –how active site interact
with different molecule
0 COMPARITIVE MOLECULAR FIELD ANALYSIS
(CoMFA)-new approach to structure/ activity
correlation.
0 Representation of ligand molecule by their steric and
electrostatic field.

35. 3D QSAR- ADVANTAGES
0 Useful in the design of new drugs.
0 The necessary software and hardware are readily
affordable and relatively easy to use.
0 Favorable and unfavorable interaction are represented by 3
D contours around a representative molecule.
0 Graphical representation of beneficial and non beneficial
interactions help to define a new structure.
0 In 3 D QSAR, the properties of test molecule are calculated
individually by computer program.

36. 3D-QSAR Assumptions
The effect is produced by modeled compound and not
it’s metabolites.
The binding site is the same for all modeled compounds.
The biological activity is largely explained by enthalpic
processes.
The system is considered to be at equilibrium, and
kinetics aspects are usually not considered.

37. Advantages over QSAR
0 No reliance on experimental values
0 Not restricted to molecules of same structural class
0 Predictive capability