The document discusses the applications of bioinformatics in drug discovery. It describes how bioinformatics supports computer-aided drug design through computational methods to simulate drug-receptor interactions. It also discusses how virtual high-throughput screening can identify compounds that strongly bind to protein targets. The document outlines the key steps in drug design, including identifying the disease target, studying lead compounds, rational drug design techniques, and testing drugs. It emphasizes that bioinformatics can predict important drug characteristics like absorption and toxicity to save costs during development.

1. APPLICATIONS OF BIOINFORMATICS
IN DRUG DISCOVERY
AWAH, JANE IJEOMA
I.M.Sc 2014600327
DEPARTMENT OF BIOTECHNOLOGY

2. INTRODUCTION.
The processes of designing a new drug using bioinformatics tools have
open a new area of research.
Bioinformatics Supports computer-aided drug design Research where
computational methods are used to simulate drug-receptor interactions.
One search method is virtual high-throughput screening. In vHTS,
protein targets are screened against databases of small-molecule
compounds to see which molecules bind strongly to the target.
If there is a “hit” with a particular compound, it can be extracted from
the database for further testing.
ZINC is a good example of a vHTS compound library.

3. Drug Bioavailability and Bioactivity
 Most drug candidates fail in Phase III 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 software to save cost.
 The Tufts Report suggests that the cost of drug discovery and
development has reached $770-800 million for each drug successfully
brought to market.

4. •In order to design a new drug one need to take the following path.
Identify target disease
Study Interesting Compounds
Detection of the Molecular Bases for Disease
Rational Drug Design Techniques
Refinement of Compounds
Quantitative Structure Activity Relationships (QSAR)
Solubility of Molecule
Drug Testing

5. Identify target disease
 One needs to know all about the disease and existing or traditional
remedies. It is also important to look at very similar afflictions and their
known treatments.
 Target identification alone is not sufficient in order to achieve a
successful treatment of a disease. A real drug needs to be developed.
 This drug must influence the target protein in such a way that it does
not interfere with normal metabolism.
 Bioinformatics methods have been developed to virtually screen the
target for compounds that bind and inhibit the protein.

6. Study Interesting Compounds
 One needs to identify and study the lead compounds that have some
activity against the disease.
 These compounds provide a starting point for refinement of the
chemical structures.
Detect the Molecular Bases for the Disease
 If it is known that a drug must bind to a particular spot on a particular
protein or nucleotide then a drug can be tailor-made to bind at that site.
 A second method is the brute force testing of large numbers of
compounds from a database of available structures.

7. Rational drug design techniques
 These techniques attempt to reproduce the researchers'
understanding of how to choose likely compounds built into a
software package that is capable of modeling a very large
number of compounds in an automated way.
 Many different algorithms have been used for this type of
testing, many of which were adapted from artificial
intelligence applications.
 The complexity of biological systems makes it very
difficult to determine the structures of large biomolecules.

8. Refinement of compounds
 Once a number of lead compounds have been found,
computational and laboratory techniques will be successful in
refining the molecular structures to give a greater drug activity
and fewer side effects.
It is done both in the laboratory and computationally by
examining the molecular structures to determine which aspects
are responsible for both the drug activity and the side effects.

9. Quantitative Structure Activity Relationships (QSAR)
 Computational technique should be used to detect the
functional group in the compound in order to refine the drug.
 QSAR is involved in computing every possible number that
can describe a molecule, then doing an enormous curve fit to
find out which aspects of the molecule correlate well with the
drug activity or side effect severity.
 This information can then be used to suggest new chemical
modifications for synthesis and testing.

10. Solubility of Molecule
 One need to check whether the target molecule is water soluble or readily soluble in
fatty tissue , and what part of the body it will affect.
 The ability to get a drug to the correct part of the body is an important factor in its
potency.
Drug Testing
 Once a drug has been shown to be effective by an initial assay technique, much more
testing must be done before it can be given to human patients.
Animal testing is the primary type of testing at this stage. Eventually, the compounds,
which are deemed suitable at this stage, are sent on to clinical trials.
In the clinical trials, additional side effects may be found and human dosages are
determined.

11. Drug Lead Optimization
When a promising lead candidate has been found in a drug
discovery program, the next step (a very long and expensive
step!) is to optimize the structure and properties of the
potential drug.
 This usually involves a series of modifications to the
primary structure (scaffold) and secondary structure (moieties)
of the compound.
This process can be enhanced using software tools that
explore related compounds to the lead candidate, such as
OpenEye’s WABE.

12. SOFTWARE AND BIOINFORMATICS DATABASE DEVELOPED
 SVMProt: Protein function prediction software: http://jing.cz3.nus.edu.sg/cgi-
bin/svmprot.cgi
 MoViES: Molecular vibrations evaluation server : http://ang.cz3.nus.edu.sg/cgi-
bin/prog/norm.pl
Therapeutic target database: http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp
Drug adverse reaction target database:
http://xin.cz3.nus.edu.sg/group/drt/dart.asp
Drug ADME associated protein database:
http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp
Kinetic data of bimolecular interactions database:
http://xin.cz3.nus.edu.sg/group/kdbi.asp
Computed ligand binding energy database:
http://xin.cz3.nus.edu.sg/group/CLiBE/CLiBE.asp

13. CONCLUSION
The application of Bioinformatics in drug discovery helps to find out
the genetic sequence of multiple organisms or the amino acid sequence
of proteins from several species.
It is very useful to determine how similar or dissimilar the organisms
are based on gene or protein sequences.
With this information one can infer the evolutionary relationships of the
organisms, search for similar sequences in bioinformatics databases and
find related species to those under investigation using the various
bioinformatics sequence analysis tools.

14. REFERENCES
• Basavaraj, K. and Nanjwade, M. (2014). Applications of
Bioinformatics in Drug Discovery. Department of Pharmaceutics
JN Medical College KLE University, Belgaum- 590010.
•Hanumant, S. (2012). Swami Ramanand Teerth Marathwada
University Subcenter Latur.