INTRODUCTION A PERFECT THERAPEUTIC DRUG DRUG DISCOVERY- HISTORY MODERN DRUG DISCOVERY BIOINFORATICS IN DRUG DISCOVERY DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY ECONOMICS OF DRUG DISCOVERY CONCLUSION REFERENCES

1. BIOINFORMATICS IN
DRUG DISCOVERY
By
KAUSHAL KUMAR SAHU
Assistant Professor (Ad Hoc)
Department of Biotechnology
Govt. Digvijay Autonomous P. G. College
Raj-Nandgaon ( C. G. )

2. SYNOPSIS
 INTRODUCTION
 A PERFECT THERAPEUTIC DRUG
 DRUG DISCOVERY- HISTORY
 MODERN DRUG DISCOVERY
 BIOINFORATICS IN DRUG DISCOVERY
 DRUG DISCOVERY BASED ON
BIOINFORMATIC TOOLS
 BIOINFORMATICS IN COMPUTER-AIDED
DRUG DISCOVERY
 ECONOMICS OF DRUG DISCOVERY
 CONCLUSION
 REFERENCES

3. INTRODUCTION
 A drug can be defined as “a substance
intended for use in the diagnosis, cure,
mitigation, treatment, or prevention of
disease…or as a component of a medication”.
 Drug discovery is the process of discovering
and designing drugs. This process is very
important, involving analyzing the causes of
the diseases and finding ways to tackle them.
 This process is so long and expensive that it
might cost millions of dollars and take a
dozen years; and the accuracy of
identification of targets is not good enough,
which in turn delays the process.

4.  Bioinformatics is generally defined as the
research, development & application of
computational tools and approaches for
expanding the use of biological, medical and
health data, including those to acquire,
store, organize, archive, analyze and
visualize such data.
 It can explore the causes of diseases at the
molecular level, explain the phenomena of
the diseases from the angle of the gene and
make use of computer techniques, and
enhance the accuracy of the results so as to
reduce the cost and time.

5. A PERFECT THERAPEUTIC DRUG
 Drug is defined as all natural and
artificially made chemicals that produce
desired effects in the living organisms
when administered by the most favoured
route.
 What makes a chemical compound acting
as pharmaceutically active agent ?
• High affinity towards the target
• Selectivity with respect to the target
• High bioavailability und low toxicity

6. HISTORY
 The discovery of drugs historically has been
serendipitous (Ratti & Trist, 2001). For most of its
history, drug discovery has been a product of trial and
error.
 Long before the pharmaceutical industry existed, drugs
were discovered by accident and their uses passed
down by verbal and written records (Ratti & Trist,
2001).
 According to Boa (2003), “Throughout history people
have found by trial and error which berries, roots and
barks could be used for medicinal purposes to alleviate
symptoms of illness”. For example, the Willow bark,
which contains salicin, was used as a fever reducer .

8. MODERN DRUG DISCOVERY
 Drug discovery is the process of
discovering and designing drugs,
which includes target identification,
target validation, lead identification,
lead optimization and introduction of
the new drugs to the public.

9. BIOINFORMATICS IN DRUG
DISCOVERY
 Bioinformatics is a booming subject combining biology
with computer science. It can explore the causes of
diseases at the molecular level, explain the phenomena of
the diseases from the angle of the gene and enhance the
accuracy of the results so as to reduce the cost and time.
 In recent years, we have seen an explosion in the amount
of biological information that is available. It appears that
the ability to generate vast quantities of data has
surpassed the ability to use this data meaningfully.
 All marketed drugs today target only about 500 gene
products. The elucidation of the human genome which has
an estimated 30,000 to 40,000 genes, presents immense
new opportunities for drug discovery and simultaneously
creates a potential bottleneck regarding the choice of
targets to support the drug discovery pipeline.

10. DRUG DISCOVERY BASED ON
BIOINFORMATIC TOOLS
 The processes of designing a new drug using
bioinformatics tools have open a new area of
research. In order to design a new drug one need to
follow the following path.
• Identify Target Disease
• Study Interesting Compounds
• Detect the Molecular Bases for Disease
• Refinement of compounds
• Quantitative Structure Activity Relationships
(QSAR)
• Solubility of Molecule
• Drug Testing

11. BIOINFORMATICS IN COPUTER-AIDED
DRUG DISCOVERY
 Homology modeling
Most drug targets are proteins, so it is
important to know their 3-D structure.
Homology modeling relies on the
identification of one or more known protein
structures.
Modeller is a well-known tool in homology
modeling, and the Swiss-Model Repository is
a database of protein structures created
with homology modeling.

12.  Interaction networks
Docking is a method used to identify the fit
between a receptor and a potential ligand. . The
goal of protein-ligand docking is to predict the
position and orientation of a ligand (a small
molecule) when it is bound to a protein receptor
or enzyme.
The following are the protein-ligand docking
software’s:
i) Gold
(http://www.ccdc.cam.ac.uk/products/life_science
s/gold).
ii) AutoDock (http://autodock.scripps.edu/).
iii) Dock (http://dock.compbio.ucsf.edu/).
iv) ZDock (http://zlab.bu.edu/zdock/).
v) Docking server:
http://www.dockingserver.com/web.

13.  Virtual high-throughput screening (vHTS)
Pharmaceutical companies are always
searching for new leads to develop into
drug compounds. One search method is
virtual high-throughput screening
(vHTS). In vHTS, protein targets are
screened against databases of small-
molecule compounds to see which
molecules bind strongly to the target.

14.  Drug lead optimization
When a promising lead candidate has
been found in a drug discovery
program, the next step is to optimize
the structure and properties of the
potential drug. This usually involves a
series of modifications to the primary
structure and secondary structure of
the compound.
Lead optimization tools such as WABE
offer a rational approach to drug
design that can reduce the time and
expense of searching for related
compounds

15.  Drug bioavailability and bioactivity
Most drug candidates fail in clinical trials
after many years of research and millions of
dollars have been spent on them. And most
fail because of toxicity or problems with
metabolism. The key characteristics for
drugs are: absorption, distribution,
metabolism, excretion, toxicity (ADMET)
and efficacy—in other words bioavailability
and bioactivity. Although these properties
are usually measured in the lab, they can
also be predicted in advance with
bioinformatics such as C2-ADME, TOPKAT,
CLOGP, DrugMatrix, AbSolv, Bioprint,
GastroPlus etc.

16. ECONOMICS OF DRUG
DISCOVERY

17. CONCLUSION
 The drug discovery process is a long and
expensive one. It starts from target identification,
after that, validates the targets and identifies the
drug candidates.
 Due to the limitation of throughput, accuracy and
cost, experimental techniques cannot be applied
widely, therefore, in recent times the drug
discovery process has shifted to bioinformatic
approaches such as homology modeling, protein-
ligand interactions, vHTS etc.
 Bioinformatic approach has been of great
importance to develop fast and accurate target
identification and prediction method for the
discovery and enhance the accuracy of the results so
as to reduce the cost and time

18. REFERENCES
1. Bioinformatics and drug discovery- Richard S.
Larson
2. Bioinformatics- R.C. Rastogi
3. Modern drug discovery process: An in silico
approach V. Srinivasa Rao and K. Srinivas*
Department of Computer Science and Engineering,
V.R Siddhartha Engineering College, Kanuru,
Vijayawada-520 007, India.
4. Bioinformatics- SABU M. THAMPI Assistant
Professor Dept. of CSE LBS College of Engineering
Kasaragod, Kerala