CADD is modern technique of drug design and use of this technique reduce drug screening time and discover new drugs with specific therapeutic activity.

1. 1

2. Computer assisted drug design involves all
computer assisted techniques used to discover,
design and optimize biologically active
compounds with that use as a drugs.
2

3.  In 1909 Atoxyl as first rational drug design by Paul
Erhlich. which is safer used in treatment of Syphilis.
 1970s: Quantitative structure-activity relationships
(QSAR).
 1990s: Human genome Bioinformatics, NMR
Molecular Modeling, High throughput
screening(HTS).
3

4.  The Computer-Assisted Drug Design (CADD) Center
was created to research between biologists,
biophysicists, structural biologists and computational
scientists.
 The major goal of the CADD is to discover novel
chemical entities with the potential to be developed
into novel therapeutic agents.
4

5. CADD is usually used for three major purposes:
(1)Filter large compound libraries into smaller sets of predicted
active compounds that can be tested experimentally.
(2)Guide the optimization of lead compounds, whether to
increase its affinity or optimize drug metabolism and
pharmacokinetics (DMPK) properties including absorption,
distribution, metabolism, excretion, and the potential for toxicity
(ADMET).
(3) Design novel compounds.
5

6.  CADD can be classified into two general categories
1. Structure based CADD
2. Ligand based CADD
 Structure based CADD
 Structure-based drug design (SBDD, also known as rational drug
design) is a technique that accelerates the drug discovery process
by utilizing structural information to improve the lead optimization
process.
 The technique requires high resolution 3-D structure of the inhibitor
bound to the target obtained using X-ray crystallography.
 The central goal of structure based CADD is to design compounds
that bind tightly to the target and improved ADMET properties.
6

7.  Ligand based CADD is generally preferred when no or little
structural information is available, often for membrane protein
targets.
 Ligand based approaches try to identify characteristics
common to known ligands to use in screening for new or
improved drugs.
7

8. 8

9.  The objective of drug design is to find a chemical compound
that can fit to a specific cavity on a protein target both
geometrically and chemically.
 To discover, design, and optimize new, effective, and safe
drugs.
 Random screening against disease assays.
 Speed-up screening process.
 To facilitate hit identification, hit-to-lead selection, optimize
the absorption, distribution, metabolism, excretion and
toxicity profile and avoid safety issues.
 De novo design. 9

10.  Priniciples of CADD based upon two different mechanism
1. Molecular mechanism
2. Quantum mechanism
1.Molecular mechanism
 Molecular mechanics refers to the use of geometry and motions of
molecules.
 Molecular mechanics methods are based on the following principles:
 Nuclei and electrons are lumped into atom-like particles.
 Atom-like particles are spherical and have a net charge.
 Interactions are based on classical potentials.
 Interactions must be pre assigned to specific sets of atoms.
 Interactions determine the distribution of atom-like particles and their
energies.
 The object of molecular mechanics is to predict the energy associated with
a given conformation of a molecule. 10

11.  Energy= Stretching Energy + Bending Energy + Torsion Energy
+ Non-Bonded Energy
11

12.  Quantum theory uses known physical constants, such as velocity of light&
charges of nuclear particles to calculate molecular properties.
 Quantum mechanism methods are based on the following principles:
 Nuclei and electrons are distinguished from each other.
 Electron-electron and electron-nuclear interactions are specific.
 Interactions are governed by nuclear and electron charges (i.e. potential
energy) and electron motions.
 Interactions determine the nuclei and electrons and their energies.
 Equation for calculate molecular properties which derived from
Schrodinger equation
HΨ=EΨ
E- energy of the system relative to all atomic particles are separated to
infinite distances .
H- is both kinetic and potential energy. 12

13.  Docking refers to place a ligand (small molecule) into the binding
site of a receptor in the manners suitable for optimal interactions with
a receptor.
 List of docking softwares
(1)Flexx (5) Ligand Fit
(2)Flexi Dock (6) Fred
(3)IcmDock (7) Glide
(4)Dock (8) Gold 13

14.  Protein-Ligand docking
 Protein-Protein docking
 Local and global docking
 Rigid vs flexible docking
 Bound and unbound docking
 Application of Docking :
 Determine the lowest free energy structures for the receptor-ligand
complex.
 Calculate the differential binding of a ligand to two different
macromolecular receptors.
 Study the geometry of a particular complex.
 Propose modification of a lead molecules to optimize potency or other
properties. 14

15.  CADD provides a deep insight to the drug-receptor
interactions acquired by the researchers.
 It focuses drug research on specific lead candidates and
avoids potential “dead-end” compounds.
 Information about toxicity and its relationship to structure.
 Leverage of chemical and biological information about
ligands and targets to identify and optimize new drugs.
15

16.  Successful applications of CADD in the development of
novel and potent drug candidates in drug discovery.
Such as HIV inhibitor Ritonavir , Relenza (which treats
influenza), Captopril
16

17.  Computer-Assisted Drug Design is a natural outgrowth of
theoretical chemistry, Computer- Assisted Drug Design is central
to rational drug design, it contributes to the selection and
synthesis of new materials, and it guides the design of catalysts.
The search for new molecular entities has led to the construction
of high quality datasets and design that may be optimized for
molecular similarity.
17

18.  PranitaKore,MadhaviM.Mutha,RishikeshV.Antre,RajeshJ.Oswal,San
dipS.Kshirsagar"Computer-Aided Drug Design: An Innovative Tool
for Modeling" Open Journal of Medicinal Chemistry, 2012, 2, page no
;139-145
 Gregory Sliwoski, Sandeep kumar Kothiwale, Jens Meiler, and
Edward W. Lowe "Computational Methods in Drug
Discovery",January 2014, page no ;337
 Lewis RA (2011),"The Development Of Molecular Modelling
programs: The use and Limitations of Physical models", In
Gramatica P, Livingstone DJ, Davis AM, Drug Design Strategies:
Quantitative Approach . Royal Society of chemistry. Pg. 88-107
 Journal of Molecular Graphics and Modelling, “Combining structure-
based drug design and pharmacophores”, Renate Griffith, 23, 439–
446, 2005.
 Bahl and Tuli, "Textbook of Physical Chemistry" , S. Chand
publications page no : 1048.
18

19. 19