This lecture discusses computer aided drug design (CADD). CADD uses computational methods to aid in drug discovery and design. It involves identifying drug targets, generating potential drug molecule "hits" through virtual screening, and optimizing "leads" through modeling protein-ligand interactions and simulating the effects of molecular modifications. The key steps are target identification, validation of targets, lead identification through screening libraries or de novo design, lead optimization through docking simulations, and preclinical/clinical trials. CADD approaches like ligand-based, target-based, and structure-based drug design can speed up the drug development process and reduce costs compared to traditional experimental methods alone.

1. Lecture 7- Computer aided drug design
BTT- 516– Drug Designing and Development

2.  Introduction
 Role of CADD
 Impact of structural Bioinformatics on Drug Discovery
 Drug Designing A ppro a c h e s
 Steps involved in Drug designing
 D o c k ing
Topics to be covered today

3. DRUG
• A drug may be defined as “a chemical entity that when consumed/injected,
results in the control or eradication of a particular disease/infection”.
• Drug discovery is a pipeline process involved in the evolution of drugs and
involves “genes to drugs” strategy.
• Identifying the gene responsible for a particular disease process and finally
evolving a drug to combat the disease-these three forms the main areas in
this strategy.

4. Computer Aided Drug Design
• Drug discovery process usually starts with an analysis of binding sites in
target proteins or an identification of structural features common to active
compounds.
• The process ends with the generation of small molecule “leads” suitable for
further chemical synthetic work.
• It is a recent and emerging discipline that uses several bioinformatics tools
and related fields like chem informatics and combinatorial chemistry.
• CADD uses computational chemistry to discover, enhances or study of drugs
and related biologicallyactive molecules.

5. Role of CADD
• 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
• The parameters expected from a drug are
• Safety
• Efficiency
• Stability
• Solubility
• Synthetic viability
• Novelty

6. Hits Lead and Drugs
• Hits are chemical compounds that produce biological activity through to
represent therapeutic potential.
• Biological screening is carried out to identify those compounds that
possess the biological activity, better than the ‘hits’. such compounds
identified are called ‘leads’.
• Drugs are small molecules that bind, interact, and modulate the
activity of specific biological receptors
•The initial leads are unlikely to be the final drugs. complex evaluations
are necessary and typically the initial hit is modified atom-by-atom to
improve important as a characteristic of the molecule.
•The choice of lead structure is very important for success in drug
development.

7. HITS LEADS
Molecules
Active Molecule

8. Impact of structural
Bioinformatics on Drug Discovery
Speeds up key steps in DD process by
combining aspects of
bioinformatics, structural biology,
and structure-based drug design

9. Identify disease
Isolate protein
GENOMICS, PROTEOMICS &
BIOPHARM
In silico & In Vitro ADME MODELS
Potentially producing many more
targets and “personalized” targets
HIGH THROUGHPUT SCREENING
Screening up to 100,000 compounds a
day for activity against a target protein
VIRTUAL SCREENING
Using a computer to
predict activity
Combinatorial Chemistry
Rapidly producing vast
numbers of compounds
Molecular Modeling
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing
Find drug
Preclinical testing

10. Drug Designing Approaches
There are four basic approaches for drug designing
1. Ligand based approach
2. Target based approaches
3. DE NOVOApproaches
4. SBDD

12. DE NOVO Approaches
• DE NOVO design is the approach to build a customized ligand for a
given receptor.
• This approach involves the ligand optimization
• Ligand optimization can be done by analyzing protein active site
properties that could be probable area of contact by the ligand.
• The analyzed active site properties are described to negative image of
protein such as hydrogen bond, hydrogen bond acceptor and
hydrophobic contact region.

13. Steps involved in Drug designing
1. Targetidentification
2. Target validation
3. Lead identification
4. Lead optimization
5. Docking
6. Pre Clinical Trials
7. Clinical trails

14. Ta r g etIdentification
• A target is a molecule (namely a protein) which is
present within an organism.
• The approaches of identifying targets include expression,
protein biochemistry, structure studies, study of
biochemical pathways.
• There are now several other methods to identify specific
molecular targets like high throughput sequencing analysis,
positional cloning, generation of cDNA libraries with ESTS and
database mining by sequence homology.
• It is important to determine whether the novel targets are
actually relevant to the physiology of the disease.

15. Ta r g etVa lida tion
As there are a pleothora of new potential therapeutic drug
targets that are being discovered, selection and validation
of novel molecular targets has become important.
It needs to be confirmed that the targets identified will affect
an appropriate biological response.
Targeted gene disruption (TGD) is a term that refers to
several different methods of target validation.

16. Lead Identification
•Lead is a compound (usually a small organic molecule) that
demonstrates a desired biological activity on a validated
molecular target.
• To be termed as a lead, the compound must exceed a specific
potency threshold against the target.
• The compounds used as potential leads can be from many
sources. the most important sources of leads is libraries of
molecules like peptide libraries, natural compounds

17. • Once a lead compound is established in the identification
process, we need to optimize the desirable traits of the lead.
• To be considered for further development , lead should be
amenable for chemistry optimization.
Lead Optimization

18. Docking
• Docking refers to the ability to position a ligand in the active or a
designated site of a protein and calculate the specific binding affinities.
• Docking algorithms can be used to find ligands and binding
conformations at a receptor site close to experimentally determined
structures.
• Docking algorithms are also used to identify multiple algorithms
and also used to identify proteins to which a small molecule can
bind. Some of the docking programs are GOLD (genetic optimization
for ligand docking), AUTODOCK, LUDI, HEX etc.

19. Mechanism of DrugAction

20. Active Site Prediction
Rolta et al., 2021

21. Mechanism of Drug Binding

22. Ligand Binding Mechanism

23. Protein-Ligand Docking
Rolta et al., 2021

24. Protein-Ligand Docking
Rolta et al., 2021

25. Protein-Ligand Docking
Rolta et al., 2021

26. Examples of drugs designed by structure-
based methods
• Human Renin Inhibitor
Antihypertension
• Collagenase and Stromelysin Inhibitor
Anticancer andAntiarthritis
• Purine Nucleotide Phosphorylase Inhibitor
• Antidepressant
• Thymidylate Synthase Iinhibitor
Antiproliferation
NATURE 384 SUPPL, 23-26 (1996)

27. Thank you
Er. Rajan Rolta
Faculty of Applied Sciences and Biotechnology
Shoolini University,
Village Bhajol, Solan (H.P)
+91-7018792621 (Mob No.)
rajanrolta@shooliniuniversity.com